A method and device for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs

Abstract

The present invention provides a method and device for identifying high permeability bands in marine carbonate bioclastic limestone reservoirs, the method comprising: determining a single-layer dynamic permeability and a single-layer specific liquid production index of a single-well flow unit according to well test data and production logging data; analyzing the interlayer interference of multi-layer combined production according to production logging data, comprehensively utilizing the single-layer production and the single-layer dynamic permeability and single-layer specific liquid production index of a single-well flow unit in the production logging data to establish a high permeability band dynamic standard and extract the single-well high permeability band; dividing the high permeability reservoir genesis type in the coring well according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, and determining the distribution law of the high permeability band in the rock phase, sedimentary phase and sequence interface; establishing a high permeability band logging identification mode, identifying the high permeability band well by well in the entire reservoir according to the high permeability band logging identification mode, and realizing the logging interpretation of the entire reservoir.

Description

Technical Field

[0001] The invention relates to a method and a device for identifying high-permeability bands in marine carbonate bioclastic limestone reservoirs, belonging to the technical field of reservoir heterogeneity evaluation in the field of oil and gas field exploration and development. Background Art

[0002] High permeability strips are also called high permeability strips, and their English name is abbreviated as HPS (High Permeability Streak). According to OMA Deoye (SPE-177824), it is a manifestation of reservoir heterogeneity caused by relatively high permeability reservoirs, and it is also the reason why some wells lose control due to increased water content due to early and uneven advance of water drive front. Therefore, in the development of highly heterogeneous marine carbonate reservoirs, it is very important to understand the cause, type and distribution of high permeability strips for deploying high-yield development wells, designing injection and production well networks, improving the efficiency of injected water drive, extending the water-free or low-water production period, and improving the well opening rate.

[0003] At present, there are a lot of research contents related to hypertonic strips. The differences of the present invention include:

[0004] First, the research objects are different. Most of the published literature uses the widely used “thief layer” The high permeability zones are mainly "super-high permeability zone" and "super-high permeability zone (Super-K)", both of which are thin layers with abnormally high permeability, usually formed by erosion of leaching surface and high-energy deposition of coarse-grained rock phase (such as oolite limestone) and fracture corridors, and are the most conductive channels that lead to early water breakthrough, rapid water content rise, low oil displacement efficiency and low recovery rate in oil fields; the high permeability zones proposed in the present invention include both "thief zone" and "super-high permeability zone", as well as high-energy bioclastic limestone sedimentary high permeability zones different from typical oolite limestone. Actual research has shown that in porous carbonate reservoirs, "thief zone" and "super-high permeability zone" are controlled by stratigraphic sequence, mostly developed near the third-order sequence interface or local exposure surface and abnormal high-energy sedimentary zones that are significantly different from normal deposition, with strong distribution regularity, easy to identify and manage, and less impact on water injection development management, while the high-energy sedimentary high permeability zones developed in large quantities inside bioclastic limestone are controlled by sedimentation, with poor distribution regularity, great difficulty in identification, and great impact on water injection effect and development management.

[0005] Second, the research contents are different. In the published literature, there have been relatively in-depth studies on the geological causes, identification, characterization and application of thief layers and ultra-high permeability layers (such as SPE-64989, IPTC-16632, SEG-2008-3184, WPC-30164 and Chinese patent CN106121641A, etc.). Among them, the identification of thief layers or ultra-high permeability layers mainly focuses on single-discipline identification such as geology, well logging, seismicity and dynamics. The identification results have a certain coincidence rate but are limited in application due to the influence of the methods. In the literature related to high permeability zones (HPS), the research content of some of the literature mainly focuses on establishing geological models based on field outcrops, coring, well logging and geological analysis, revealing and characterizing the HPS. The spatial distribution of high permeability bands (such as IPTC-13385). The research content of some literatures is mainly focused on analyzing the dynamic characteristics of high permeability bands, tracking the direction of bands with tracers, and realizing the overall management and application of horizontal well water injection development technology (such as SPE-31149, SPE-176110, etc.). The currently disclosed patent literature involving high permeability bands involves high permeability band core experiments (such as Chinese patent CN108535161A), dynamic identification and monitoring (such as Chinese patent CN110821485A), and calculation of physical property parameters of dominant channels (such as Chinese patent CN110821486A). However, there are currently no relevant reports on static and dynamic integrated identification.

[0006] In view of the current status of research on high-permeability zones and the difficulties faced in the development of bioclastic limestone reservoirs, an innovative method and device for identifying high-permeability zones in marine carbonate bioclastic limestone reservoirs based on static and dynamic integration is not only an urgent need for production, but also the key to improving the connotation of high-permeability zone research and the level of water injection development management.

[0007] Description of the references cited in the background technology section:

[0008] 1) Abbreviation of journal title:

[0009] SPE is the abbreviation of Society of Petroleum Engineers;

[0010] IPTC is the abbreviation of International Petroleum Technology Conference;

[0011] SEG is the abbreviation of Society of Exploration Geophysicists International Exhibition and Annual Meeting;

[0012] WPC is the abbreviation of World Petroleum Council;

[0013] 2) Detailed description of references:

[0014] SPE-177824: O.M. Adeoye, etc. Integrated Evaluation Approach and Implications of High Permeability Streaks in Giant Carbonate Oil Field. 2015.11;

[0015] SPE-64989: M.H. Alqam, etc. Treatment of Super-K Zones Using Gelling Polymers. 2001.02;

[0016] IPTC-16632: Diah Agustina, etc. Drilling with Casing Technique Successfully Overcome Massive Thief Zone. 2013.03;

[0017] SEG-2008-3184: Alexandre W. Araman, etc. Thief Zone Identification Through Seismic Monitoring of a CO2 Flood, Weyburn Field, Saskatchewan. 2008;

[0018] WPC-30164: C. Ravenne, etc. Characterisation of Reservoir Heterogeneities and Super Permeability Thief Zones in a Major Oilfield in The Middle East. 2000;

[0019] IPTC-13385: Agus Sudarsana, etc. High Permeability Streaks Characterisations in Middle East Carbonate. 2009.12;

[0020] SPE-31149:P.valko.Performance of Fractured Horizontal Wells in High-Permeability Reservoirs.1996.01;

[0021] SPE-176110: Hu Dandan,etc.Integrated management and Application ofHorizontal Well Water Flooding Technology in a Large-scale ComplicatedCarbonate Oilfield Containing High permeability Streaks.2015.08. Summary of the invention

[0022] In order to solve the above-mentioned shortcomings and deficiencies, an object of the present invention is to provide a method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs.

[0023] Another object of the present invention is to provide a device for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs.

[0024] In yet another aspect, the present invention further provides a computer device.

[0025] In another aspect, the present invention also provides a computer-readable storage medium. The present invention solves the problem of water breakthrough sequence and injection-production management in injection-production well groups in highly heterogeneous bioclastic limestone reservoirs, and provides technical support for efficient development and balanced utilization of oil reservoirs and improving ultimate recovery.

[0026] In order to achieve the above objectives, on the one hand, the present invention provides a method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs, wherein the method comprises:

[0027] Determine the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit based on well test data and production logging data;

[0028] Analyze the interlayer interference of multi-layer commingled production according to production logging data, comprehensively utilize the single-layer production and the single-layer dynamic permeability and single-layer specific production liquid index of the single-well flow unit in the production logging data to establish the dynamic standard of the high-permeability band and extract the single-well high-permeability band;

[0029] In the coring well, based on the results obtained from the study of sequence stratigraphy, lithofacies, sedimentary facies and rock physical facies, the genesis type of high permeability reservoir (high permeability layer) is classified, and the distribution pattern of the high permeability band in the lithofacies, sedimentary facies and sequence interface is determined;

[0030] A high permeability band logging identification mode is established, and high permeability bands are identified well by well in the entire reservoir according to the high permeability band logging identification mode, so as to realize logging interpretation of the entire reservoir.

[0031] In the present invention, the single well flow unit refers to a reservoir with similar seepage characteristics formed along a certain path under certain production conditions (production pressure difference), which is manifested as a certain liquid production in the vertical direction of the single well.

[0032] As a specific implementation of the above method of the present invention, the well testing data is PBU data, and the production logging data is PLT test data.

[0033] As a specific implementation of the above method of the present invention, the single layer specific liquid production index (SPI) is determined according to the well test data and production logging data according to the following formula (1):

[0034]

[0035] In formula (1), SPI is the specific liquid index, unit is bbl / (d·psi·m); q o is the daily liquid production, in bbl / d; ΔP is the bottom hole pressure difference (production pressure difference), in psi; h is the thickness of the liquid producing layer, in m.

[0036] In formula (1) of the present invention, it is necessary to use well test data to determine the bottom hole pressure difference (production pressure difference) ΔP.

[0037] In the present invention, the specific liquid production index (SPI), also known as meter liquid production index, is an important parameter reflecting the production capacity of a flow unit and is defined as the daily liquid production under unit thickness and unit production pressure difference.

[0038] As a specific implementation of the above method of the present invention, in the case of a single-layer well test, when the well test data is PBU data, determining the single-layer dynamic permeability (K_PBU) of the single-well flow unit according to the PBU data includes:

[0039] 1) Determine the formation coefficient of the single well according to the following formula (2) based on the PBU data interpretation;

[0040]

[0041] In formula (2), kh is the formation coefficient of the single well interpreted by PBU data, in mD·m; q is the PBU test production, in m 3 / ks; μ is the fluid viscosity, in mPa·s; m is the slope of the Horner curve used in PBU data interpretation, dimensionless; h is the flow unit thickness (usually the effective reservoir thickness with seepage capacity in the well test perforation section), in m; k is the single-layer dynamic permeability of the single well flow unit, in mD;

[0042] 2) Determine the thickness of the flow unit on the well logging curve, and then divide the formation coefficient of the single well by the thickness of the flow unit to obtain the single-layer dynamic permeability of the flow unit of the single well;

[0043] In the case of a combined well test, when the well test data is PBU data and the production logging data is PLT test data, the single-layer dynamic permeability (K_PBU) of a single well flow unit is determined based on the PBU data and the PLT test data, including:

[0044] 1) Determine the comprehensive formation coefficient of the single well (i.e., the sum of the formation coefficients of all flow units) according to the above formula (2) based on the PBU data interpretation;

[0045] 2) using the layered liquid production in the PLT test data, the comprehensive formation coefficient of the single well is batched into each flow unit according to the following formula (3) to formula (5), so as to obtain the single-layer formation coefficient of each flow unit;

[0046] q t =q1+q2+q3+…+q l Formula (3);

[0047]

[0048] (kh) l =(kh)×ration l Formula (5);

[0049] Formula (3)-In formula (5), q t It is the cumulative liquid production in the PLT test data, in bbl / d; q1, q2, q3, ... q l They are the actual liquid production of different production sections in the PLT test data, both in bbl / d; l is the ratio of the actual liquid production of different liquid production sections in the PLT test data to the cumulative liquid production in the PLT test data, and the unit is dimensionless; kh is the formation coefficient interpreted by PBU data, that is, the comprehensive formation coefficient of the single well, and the unit is mD·m; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m;

[0050] 3) Then, the single-layer dynamic permeability of each flow unit in the single well is determined according to the single-layer formation coefficient of each flow unit and the thickness of each flow unit according to the following formula (6);

[0051]

[0052] In formula (6), k l is the single layer dynamic permeability of the flow unit, in mD; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m; h l is the actual thickness of the liquid-producing section of the flow unit in the PLT test data, in m; l is the number of actual liquid-producing sections in the PLT test data, a positive integer.

[0053] In general, the object tested by the present invention is an oil layer, so the fluid viscosity μ in formula (2) is generally the viscosity of the oil under underground conditions.

[0054] As a specific implementation of the method described above in the present invention, in the case of a single-layer well test, when the well test data is PBU data, when determining the single-layer dynamic permeability of a single-well flow unit based on the PBU data, the flow unit thickness is determined on the logging curve by using a single-layer PBU test to determine the flow unit thickness h, specifically: based on the perforation section thickness h1, after deducting the interlayer h2 from the logging curve, the flow unit thickness h is determined after correction by well inclination.

[0055] It can be seen that for a single-layer well test (single-layer PBU test), the PBU data obtained through the PBU test can be interpreted to obtain the formation coefficient kh of the layer, and combined with the flow unit thickness (usually the relatively good effective reservoir thickness in the perforation section) h, the dynamic permeability of the layer can be determined; among them, the acquisition of kh depends on the Horner curve used in the interpretation of PBU data, Figure 4 This is the Horner curve of the pressure recovery test of Well X in a certain oil field in the Middle East in the embodiment of the present invention. Figure 4 Medium p is the oil well production time before the pressure recovery test, in ks; dt is the oil well pressure recovery time, in ks;

[0056] However, for wells with combined production, the kh obtained from the interpretation of PBU data is the comprehensive formation coefficient of all flow units in the well. Only by combining the PLT test data and batching kh into each flow unit can the dynamic permeability of different flow units be determined. Therefore, having both well test data and production logging data is a necessary condition for interpreting reservoir parameters for combined production wells.

[0057] According to the oil and gas industry standard of the People's Republic of China, "Oilfield Well Testing Technical Specifications" (SY / T 6172-2006), the well testing data described in the present invention is a special test data for oil and water wells to determine the formation pressure, formation temperature, flow pressure and production capacity of a single well, study reservoir parameters, detect oil, gas, water layers and their connectivity, and monitor reservoir dynamics. Among them, PBU, also known as pressure recovery well testing, is an unstable well testing, and the data obtained from the pressure recovery well testing is called PBU data.

[0058] In the present invention, the production logging data refers to the data of fluid density, water holdup, temperature, pressure, production, etc. of the production layer measured in the casing, which can directly determine the difference in production capacity of different layers under the same production conditions. Among them, PLT is a logging instrument produced by Schlumberger, which is mainly used to measure the actual fluid output of different perforated layers and identify and distinguish the oil production, water production and gas production, and quantify the fluid supply capacity of different perforated layers under certain working conditions. The production logging data obtained by PLT is called PLT test data.

[0059] As a specific implementation of the above method of the present invention, determining the thickness of the flow unit includes:

[0060] Inside the flow unit shown in the PLT test data, the internal partitions and interlayers of the unit are deducted using the logging curve; the thickness of the flow unit is then corrected to the vertical depth through well trajectory calculation, thus obtaining the thickness of the flow unit.

[0061] As a specific implementation of the method described above in the present invention, the inter-layer interference of multi-layer combined production is analyzed based on production logging data, including: analyzing the production capacity suppression and interference of possible high-yield layers on relatively poor reservoirs based on production logging data (such as PLT test data).

[0062] In the present invention, interlayer interference is defined as the phenomenon that the interlayer fluid flow interferes with each other due to the differences in permeability, fluid properties and pressure between small layers in the oil and gas production layer. Usually, the flow unit with the best production capacity interferes with the flow unit with relatively poor capacity, which is mostly determined by unstable well testing and dynamic logging.

[0063] For multi-layer commingled wells, the PLT test liquid production of reservoirs with better physical properties and higher pressure contributes more. When the overall liquid production is large, the liquid production capacity of reservoirs with poorer physical properties and lower pressure cannot be fully released, and the PLT test liquid production is lower than the actual production capacity. Therefore, by comprehensively comparing the matching degree of reservoir physical properties, formation pressure and PLT production of different perforated layers, obvious interlayer interference phenomena can be determined.

[0064] In the present invention, when it is determined that a flow unit has interlayer interference, it indicates that its production data and calculated dynamic permeability fail to reflect its actual production capacity. If other wells have layers (referred to as layer B) with the same reservoir characteristics as the layers (referred to as layer A) with interlayer interference, and layer B is not affected by the interlayer interference under the same production conditions, then the dynamic permeability of layer B can be calibrated as representing the dynamic permeability of a single layer with similar reservoir characteristics, and the dynamic permeability data of layer A is regarded as unreliable data and will not enter the database used in the next operation.

[0065] As a specific implementation of the above method of the present invention, the high permeability zone dynamic standard is established by comprehensively utilizing the single-layer production in the production logging data and the single-layer dynamic permeability and single-layer specific liquid production index of the single-well flow unit, including:

[0066] A scatter plot of single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit was established to analyze the production capacity of the flow unit, that is, the changing trend of the specific liquid production index with dynamic permeability and determine the inflection point. The dynamic permeability and liquid production index corresponding to the inflection point were determined as the dynamic identification criteria for high permeability zones in marine carbonate bioclastic limestone reservoirs.

[0067] As a specific embodiment of the method described above in the present invention, extracting the single well hypertonic band includes: extracting the hypertonic band in layers in the single well according to the dynamic identification standard, specifically including:

[0068] On the basis of deducting the internal partitions and interlayers of the flow unit, the dynamic permeability and liquid production index rectangular curves are drawn respectively using the single-layer dynamic permeability and liquid production index data of the single-well flow unit determined by segmentation, and the single-layer dynamic permeability and liquid production index in the high permeability strip dynamic standard are set as the baseline of the rectangular curve and filled to the right of the rectangular curve. When the dynamic permeability and liquid production index of the single layer are greater than the dynamic permeability and liquid production index corresponding to the baseline of the rectangular curve, the single layer is determined to be a high permeability strip.

[0069] In the present invention, extracting high permeability bands in layers in the single well according to the dynamic identification standard can provide samples for establishing an identification model that is extended to the entire reservoir.

[0070] In the present invention, the sequence stratigraphic research includes: based on the sequence stratigraphic theory that sea level changes control the formation and development of sequences, a hierarchical sub-marine stratigraphic division scheme is established according to lithofacies cycles and seismic sequence structures, and extended to the entire reservoir through single well logging curves and three-dimensional seismic.

[0071] In the present invention, the rock phase research includes: classifying the rock phase types according to the Dunham scheme based on the carbonate rock grain structure; classifying the rock phases and calibrating the well logging and establishing the identification standard based on the core observation and thin section analysis in the coring well; identifying the rock phase by using the well logging curve in the non-coring well, and then extending it to the entire oil reservoir.

[0072] In the present invention, the sedimentary facies study includes: determining the reservoir sedimentary environment according to the regional geological background and establishing a sedimentary model; in coring wells, using cores and thin sections to analyze sedimentary characteristics, divide sedimentary microfacies, calibrate logging and establish a sedimentary microfacies logging identification model; in non-coring wells, using logging curve morphology, combination and longitudinal rhythmic changes and other characteristics to identify sedimentary microfacies, thereby extending to the entire reservoir.

[0073] In the present invention, the petrophysical phase research includes: in accordance with the provisions of the oil and gas industry standard "Oil and Gas Reservoir Evaluation Method" (SY / T 6285-1997) of the People's Republic of China, the carbonate reservoir is divided into four levels according to the core porosity, namely high porosity (≥20%), medium porosity (12%-20%), low porosity (4%-12%) and ultra-low porosity (<4%), and the core permeability is divided into four levels, namely high permeability (≥100mD), medium permeability (10-100mD), low permeability (1-10mD) and ultra-low permeability (<1mD);

[0074] Taking into account that the porosity and permeability classification standards of different oil fields may not be completely consistent with the national standards due to differences in the genesis of oil reservoirs and reservoirs, in the present invention, the porosity and permeability grade classification standards can be determined based on the physical property experiments of standard cores in coring wells and the porosity and permeability scatter plot constrained by the main controlling factors of the reservoir (such as sedimentary microfacies).

[0075] As a specific implementation of the above method of the present invention, according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, the genetic type of high permeability reservoir is divided, and the distribution law of the high permeability band in the rock phase, sedimentary phase and sequence interface is determined, including:

[0076] The high permeability reservoir or the single well high permeability belt data divided by the rock physical phase of the core well is used to analyze the rock phase and sedimentary phase type of the high permeability reservoir or the high permeability belt by using the scatter cross plot or frequency histogram method; at the same time, combined with the results of sedimentary microfacies and sequence stratigraphic division, the position of the high permeability belt in the sedimentary phase and stratigraphic sequence is analyzed to provide regular constraints for identifying the high permeability belt using logging data.

[0077] In the present invention, the high permeability reservoir or the single well high permeability strip data divided by the coring well rock physical phase is used to analyze the rock phase and sedimentary phase type of the high permeability reservoir or high permeability strip by using the method of scatter cross plot or frequency histogram; two acquisition routes, static and dynamic, are involved here, specifically: the porosity and permeability of the 1 cm small rock sample obtained by core testing and the seepage capacity and dynamic permeability of the PBU and PLT test wells up to tens to hundreds of meters, the two trends are consistent but the specific values ​​are quite different. The most reliable method is to carry out this work in a well with coring, PBU and PLT testing at the same time, but generally there are few coring wells (high cost), many PBU and PLT testing wells, and very few wells with both coring and PBU and PLT testing. Therefore, using the consistency of the two, two paths are taken: one is to use the core experimental data to divide high, medium and low permeability reservoirs according to the industry standard (SY / T 6285-1997), and then find the law based on the sequence stratigraphy, rock phase and sedimentary phase results established by the core. The advantage is that the data are all from the core, the matching is good, and the high permeability is good with the medium and low permeability. The second is to establish a corresponding relationship using the high permeability bands determined by PBU and PLT and the sequence stratigraphy, rock phase and sedimentary phase identified by the logging curve. Since the data comes from the logging interpretation, the data reliability and consistency of different attributes are slightly insufficient. In the present invention, it is preferred to use the first route to determine the distribution law of the high permeability bands in the rock phase, sedimentary phase and sequence interface, wherein the high permeability reservoir comes from the core analysis data, which is consistent with the trend of the dynamic data.

[0078] As a specific implementation of the above method of the present invention, according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, the genetic type of high permeability reservoir is divided, and the distribution law of the high permeability band in the rock phase, sedimentary phase and sequence interface is determined, which specifically includes:

[0079] Using the geological research results of core wells, the results of single well stratigraphic sequence, sedimentary phase and rock phase division are extracted;

[0080] Using the experimental data of rock properties in coring wells and combining the results of geological phase research, a rock physical phase classification standard is established and rock physical phases are extracted in coring wells;

[0081] The genetic types of high permeability zones are divided by sedimentary phase, rock phase and rock physical phase, laying a foundation for revealing the distribution law of high permeability zones.

[0082] Comprehensively analyze the distribution patterns of high permeability zones in rock phases, sedimentary phases and sequence interfaces.

[0083] As a specific implementation of the above method of the present invention, wherein the establishment of a high permeability zone logging identification mode includes:

[0084] Taking the production logging test section of a single well (if PLT test is carried out, the test section here is the test section of the PLT test) as a sample, and taking the single-layer dynamic permeability and single-layer liquid production index ratio corresponding to the dynamic standard of the high-permeability zone as the boundary, analyze the logging response characteristics of the high-permeability zone and the non-high-permeability zone, and establish a qualitative identification model for the logging facies of the high-permeability zone and a conventional logging quantitative identification model for the sedimentary high-permeability zone.

[0085] Among them, if the single-layer dynamic permeability corresponding to the dynamic standard of the high-permeability zone is a, then the high-permeability zone corresponds to the dynamic permeability ≥ a, and the non-high-permeability zone corresponds to the dynamic permeability < a.

[0086] As a specific embodiment of the above method of the present invention, wherein, the establishment of the qualitative identification model for the logging facies of the high-permeability zone includes:

[0087] Analyze the differences between the high-permeability zone and the non-high-permeability zone on the conventional logging curves, FMI imaging logging maps, and nuclear magnetic logging T2 spectra, and establish a qualitative identification model for the logging facies of the high-permeability zone in sedimentary reservoirs and karst reservoirs respectively according to the analysis results.

[0088] As a specific embodiment of the above method of the present invention, in sedimentary reservoirs, high-permeability zones are mostly developed in high-energy sedimentary environments, and mostly belong to pore-type high-permeability zones with pure lithology, coarse grain size, high porosity, and high permeability; the conventional logging curves show low gamma, high porosity, and high resistivity; the FMI imaging map shows light color, regularly or irregularly distributed black patches, indicating the development of intergranular pores or large dissolution pores; the nuclear magnetic logging T2 spectrum shows a bimodal or multimodal feature, and both the T2 time and the energy spectrum peak show high values;

[0089] In karst reservoirs, the high-permeability zones are thin in thickness, the conventional logging characteristics are not obvious but the productivity is high, and mostly show the characteristics of "thief layers"; the FMI imaging map shows the development of sinusoidal through-well fractures or irregular microfractures, and some wells show karst caves or large dissolution pores; the nuclear magnetic logging T2 spectrum shows a bimodal or multimodal feature, the T2 time and the energy spectrum peak value are medium or low, and the T2 value of the high-permeability zone with karst caves or large dissolution pores is large.

[0090] Among them, those skilled in the art can reasonably determine the degree corresponding to a certain parameter according to the actual situation of the target oilfield and in combination with the normal distribution of a certain parameter in this oilfield, such as the fineness or coarseness of the grain size, low gamma or high gamma, high resistivity or low resistivity, high porosity or low porosity, etc.

[0091] As a specific embodiment of the above method of the present invention, wherein, the establishment of the conventional logging quantitative identification model for the sedimentary high-permeability zone includes:

[0092] In the production logging test section (if a PLT test is conducted, the test section here is the test section of the PLT test), according to the principle of seepage dominant channel, the obvious non-permeable interlayers and low permeability reservoirs (high gamma, high density, low resistivity and low Am layers in the oil layer) are deducted, and the curve values ​​of the logging curve are obtained in sections according to the conventional logging curve sampling interval. Then, according to the dynamic permeability distribution interval, a dual logging curve classification scatter point intersection diagram is made, and the distribution law and identification limit (including upper or lower limit) of the logging curve value of the high permeability strip are analyzed in combination with the geological law, and the conventional logging quantitative identification mode of sedimentary high permeability strip is established accordingly.

[0093] The dual logging curve classification scatter cross plot includes a scatter cross plot of any two curves in all logging curves, such as a porosity curve value-resistivity curve value scatter cross plot and a natural gamma curve value-pore structure index curve value scatter cross plot.

[0094] As a specific implementation of the above method of the present invention, in the process of establishing the conventional logging quantitative identification mode of sedimentary high permeability strips, the logging curve includes: natural gamma curve (GR), porosity curve (RHOB), resistivity curve (Rt) and pore structure index curve (Am). Correspondingly, the curve values ​​of the logging curve include natural gamma curve value, porosity curve value, resistivity curve value and pore structure index curve value.

[0095] In a specific embodiment of the present invention, a conventional well logging quantitative identification mode for sedimentary high permeability zones is established, which specifically includes the following steps:

[0096] In the production logging test section, according to the principle of seepage dominant channel, the obvious non-permeable interlayers and low permeability reservoirs are deducted, and the curve values ​​of natural gamma curve (GR), porosity curve (RHOB), resistivity curve (Rt) and pore structure index curve (Am) are obtained in sections according to the conventional logging curve sampling interval. Then, the double logging curve classification scatter intersection diagram is made according to the dynamic permeability distribution interval, and the logging curve value distribution law and identification boundary of the high permeability strip are analyzed in combination with the geological law, and the conventional logging quantitative identification mode of sedimentary high permeability strip is established accordingly;

[0097] Wherein, the curve values ​​include natural gamma curve values, porosity curve values, resistivity curve values ​​and pore structure index curve values;

[0098] The dual logging curve classification scatter point intersection diagram includes a porosity curve value-resistivity curve value scatter point intersection diagram and a natural gamma curve value-pore structure index curve value scatter point intersection diagram.

[0099] Since the dynamic permeability represents the test result and is affected by interlayer interference, it does not necessarily fully reflect the formation seepage characteristics. Therefore, the present invention determines the dynamic permeability distribution range according to the following specific principles:

[0100] 0mD represents no liquid production during the test; other dynamic permeability distribution intervals are determined according to the maximum value and the normal distribution interval, according to the logarithmic partition principle, and considering the lower limit of the possible hypertonic band. For example, in a specific embodiment of the present invention, a permeability greater than 100mD may be a hypertonic band, and greater than 500mD may be related to hypertonic or thief layers. Therefore, in a specific embodiment of the present invention, the determined dynamic permeability distribution intervals are: 0mD, 0-1mD, 1-10mD, 10-50mD, 50-100mD, 100-200mD, 200-500mD, 500-1000 and >1000mD.

[0101] As a specific implementation of the above method of the present invention, when the well logging curve includes a pore structure index curve, the curve value of the pore structure index curve used to reflect the reservoir storage and permeability characteristics is calculated according to the following formula (7):

[0102]

[0103] In formula (7), R w is the formation water resistivity, in ohm·m; R t is the original formation resistivity, and the resistivity corresponding to the deep detection resistivity curve on the logging curve is in ohm·m; POR is the reservoir porosity, in dimensionless decimal; S w is the formation water saturation, and its unit is a dimensionless decimal; n is the saturation index, and its unit is a dimensionless decimal.

[0104] In a specific embodiment of the method described above, the high permeability bands are identified well by well in the whole reservoir according to the high permeability band logging identification mode, so as to realize the logging interpretation of the whole reservoir, including: performing the logging quantitative identification of high-energy sedimentary high permeability bands according to the conventional logging quantitative identification mode of sedimentary high permeability bands, performing the logging phase qualitative identification according to the logging phase qualitative identification mode of high permeability bands, and the constraints and mutual verification of geological laws;

[0105] Among them, the quantitative identification of high-energy sedimentary high-permeability strips is carried out according to the conventional logging quantitative identification mode of sedimentary high-permeability strips, including: in the four curves of natural gamma curve, porosity curve, resistivity curve and pore structure index curve, GR represents lithology and sedimentary environment, and its low value represents pure lithology, coarse particles, and relatively high sedimentary energy; RHOB represents total rock porosity, and its low value represents high porosity and good physical properties; Rt represents oil content and permeability, and its high value in pure oil layer represents good oil content, indicating that the degree of oil and gas filling is high during accumulation, which can indirectly reflect that its permeability is relatively good; Am represents pore structure, and its high value represents complex conductive path, which belongs to typical large-pore small-throat coarse-grained sedimentary reservoir. Therefore, as a high-permeability strip that can form a dominant seepage channel, it must meet all the above conditions, and the high-energy sedimentary high-permeability strips are screened point by point by using the logging curve that simultaneously meets the high-permeability strip standard;

[0106] Among them, the qualitative identification of logging phases is carried out according to the qualitative identification mode of logging phases of high permeability strips, including: further identifying and determining the high-energy sedimentary high-permeability strips according to the display characteristics of "double-peak or multi-peak characteristics of T2 spectrum and high values ​​of T2 time and energy spectrum peaks" in nuclear magnetic logging and "large-scale and strong dissolution holes" in imaging logging;

[0107] Karst reservoirs often have "thief layer" characteristics, which can be qualitatively identified based on the "development of sinusoidal cross-well fractures or irregular micro-fractures, black patchy caves or large dissolution pores" on the FMI imaging map and the "double-peak or multi-peak characteristics" of the nuclear magnetic logging T2 spectrum;

[0108] The constraints and mutual confirmation of geological laws include: sedimentary high-permeability belts are controlled by sedimentary facies and developed in relatively fixed sedimentary positions, and karst high-permeability belts are constrained by sequence stratigraphy and paleostructures and developed in areas near sequence interfaces. In the above identification process, the high-permeability belts are confirmed or picked up again according to the geological laws that "tidal channel-type high-permeability belts are mostly developed in the lower part of tidal channels, bioclastic beach-type high-permeability belts are mostly developed in the upper part of beach bodies, beach-wing high-permeability belts are mostly developed near beach bodies, and karst-type high-permeability belts are mostly developed near sequence interfaces".

[0109] As a specific implementation of the method described above in the present invention, the method also includes: using core test results of coring wells, production logging data (such as PLT test data) and dynamic permeability data, as well as the water-bearing layers of water-bearing wells in the injection-production well group and the development of high permeability zones in the water-bearing layers to verify the identification results of high permeability zones in marine carbonate bioclastic limestone reservoirs.

[0110] As a specific implementation of the method described above in the present invention, the core experiment results are used to verify the high permeability zone identification results of the marine carbonate bioclastic limestone reservoir, including: among the identified high permeability zones, analyzing whether the high-energy sedimentary high permeability zones (sedimentary high permeability zones) have a good correspondence with the high permeability part in the core permeability. Generally, the correlation between the karst high permeability zones and the core permeability is unstable, while the correlation between the sedimentary high permeability zones and the core permeability is relatively stable.

[0111] As a specific implementation of the method described above in the present invention, production logging data (such as PLT test data) and dynamic permeability data are used to verify the identification results of high permeability zones in marine carbonate bioclastic limestone reservoirs, including: analyzing whether the K_PBU in the identified high permeability zone is higher than the lower limit value (i.e., the single-layer dynamic permeability corresponding to the dynamic standard of the high permeability zone), whether there is high production in the PLT test data, and whether there is a statistical relationship between the high permeability zone and the high K_PBU and high PLT production, so as to verify the reliability of the method.

[0112] As a specific implementation of the above-mentioned method of the present invention, the identification results of high permeability zones in marine carbonate bioclastic limestone reservoirs are verified by utilizing the water-bearing layers of water-bearing wells in the injection-production well group and the development of high permeability zones in the water-bearing layers, including: in the established injection-production well group, analyzing the correspondence and statistical relationship between the identified high permeability zones and the currently seen water wells (early water-bearing wells) to verify the reliability of the method.

[0113] On the other hand, the present invention also provides a device for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs, wherein the device comprises:

[0114] A reservoir dynamic parameter determination module is used to determine the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit based on well test data and production logging data;

[0115] A high permeability band extraction module is used to analyze the interlayer interference of multi-layer commingled production according to production logging data, comprehensively utilize the single-layer production and the single-layer dynamic permeability and single-layer specific production liquid index of the single-well flow unit in the production logging data to establish a high permeability band dynamic standard and extract the single-well high permeability band;

[0116] The high permeability zone genetic type classification module is used to classify the high permeability reservoir genetic type in the coring well according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, and determine the distribution law of the high permeability zone in the rock phase, sedimentary phase and sequence interface;

[0117] The high permeability band logging identification module is used to establish a high permeability band logging identification mode, and identify the high permeability bands well by well in the entire reservoir according to the high permeability band logging identification mode to achieve full reservoir logging interpretation.

[0118] The present invention also provides a device for identifying high permeability bands in marine carbonate bioclastic limestone reservoirs, wherein the device comprises: a processor, wherein the processor is used to execute the following program modules stored in a memory:

[0119] A reservoir dynamic parameter determination module is used to determine the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit based on well test data and production logging data;

[0120] A high permeability band extraction module is used to analyze the interlayer interference of multi-layer commingled production according to production logging data, comprehensively utilize the single-layer production and the single-layer dynamic permeability and single-layer specific production liquid index of the single-well flow unit in the production logging data to establish a high permeability band dynamic standard and extract the single-well high permeability band;

[0121] The high permeability zone genetic type classification module is used to classify the high permeability reservoir genetic type in the coring well according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, and determine the distribution law of the high permeability zone in the rock phase, sedimentary phase and sequence interface;

[0122] The high permeability band logging identification module is used to establish a high permeability band logging identification mode, and identify the high permeability bands well by well in the entire reservoir according to the high permeability band logging identification mode to achieve full reservoir logging interpretation.

[0123] As a specific implementation of the above-mentioned device of the present invention, the well testing data is PBU data, and the production logging data is PLT test data.

[0124] As a specific embodiment of the above-mentioned device of the present invention, the reservoir dynamic parameter determination module includes a single-layer specific liquid production index determination unit, and the single-layer specific liquid production index determination unit is used to determine the single-layer specific liquid production index according to the well test data and production logging data according to the following formula (1):

[0125]

[0126] In formula (1), SPI is the specific liquid index, unit is bbl / (d·psi·m); q o is the daily liquid production, in bbl / d; ΔP is the bottom hole pressure difference, in psi; h is the thickness of the liquid producing layer, in m.

[0127] As a specific embodiment of the above device of the present invention, the reservoir dynamic parameter determination module further includes a single-layer dynamic permeability determination unit. For a single-layer well test, when the well test data is PBU data, the single-layer dynamic permeability determination unit is used to determine the single-layer dynamic permeability of the single-well flow unit according to the PBU data, including:

[0128] 1) Determine the formation coefficient of the single well according to the following formula (2) based on the PBU data interpretation;

[0129]

[0130] In formula (2), kh is the formation coefficient of the single well interpreted by PBU data, in mD·m; q is the PBU test production, in m 3 / ks; μ is the fluid viscosity, in mPa·s; m is the slope of the Horner curve used in PBU data interpretation, dimensionless; h is the flow unit thickness, in m; k is the single-layer dynamic permeability of a single well flow unit, in mD;

[0131] 2) Determine the thickness of the flow unit on the well logging curve, and then divide the formation coefficient of the single well by the thickness of the flow unit to obtain the single-layer dynamic permeability of the flow unit of the single well;

[0132] In the case of combined well testing, when the well testing data is PBU data and the production logging data is PLT test data, the single-layer dynamic permeability determination unit is used to determine the single-layer dynamic permeability of the single-well flow unit according to the PBU data and the PLT test data, including:

[0133] 1) Determine the comprehensive formation coefficient of the single well according to the above formula (2) based on the PBU data interpretation;

[0134] 2) using the layered liquid production in the PLT test data, the comprehensive formation coefficient of the single well is batched into each flow unit according to the following formula (3) to formula (5), so as to obtain the single-layer formation coefficient of each flow unit;

[0135] q t =q1+q2+q3+…+q l Formula (3);

[0136]

[0137] (kh) l =(kh)×ration l Formula (5);

[0138] Formula (3)-In formula (5), q t is the cumulative liquid production in the PLT test data, in bbl / d; q1, q2, q3, ... q l They are the actual liquid production of different production sections in the PLT test data, both in bbl / d; lis the ratio of the actual liquid production of different liquid production sections in the PLT test data to the cumulative liquid production in the PLT test data, and the unit is dimensionless; kh is the formation coefficient interpreted by PBU data, that is, the comprehensive formation coefficient of the single well, and the unit is mD·m; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m;

[0139] 3) Then, the single-layer dynamic permeability of each flow unit in the single well is determined according to the single-layer formation coefficient of each flow unit and the thickness of each flow unit according to the following formula (6);

[0140]

[0141] In formula (6), k l is the single layer dynamic permeability of the flow unit, in mD; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m; h l is the actual thickness of the liquid-producing section of the flow unit in the PLT test data, in m; l is the number of actual liquid-producing sections in the PLT test data, a positive integer.

[0142] As a specific embodiment of the above device of the present invention, the reservoir dynamic parameter determination module further includes a flow unit thickness determination unit, which is used to determine the thickness of the flow unit, including:

[0143] Inside the flow unit shown in the PLT test data, the internal partitions and interlayers of the unit are deducted using the logging curve; the thickness of the flow unit is then corrected to the vertical depth through well trajectory calculation, thus obtaining the thickness of the flow unit.

[0144] As a specific embodiment of the above device of the present invention, the hypertonic strip extraction module is specifically used for:

[0145] A scatter plot of single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit was established to analyze the production capacity of the flow unit, that is, the changing trend of the specific liquid production index with dynamic permeability and determine the inflection point. The dynamic permeability and liquid production index corresponding to the inflection point were determined as the dynamic identification criteria for high permeability zones in marine carbonate bioclastic limestone reservoirs.

[0146] As a specific embodiment of the above device of the present invention, the hypertonic band extraction module further includes a single well hypertonic band extraction unit, and the single well hypertonic band extraction unit is used to extract the hypertonic band in layers in the single well according to the dynamic identification standard, specifically for:

[0147] On the basis of deducting the internal partitions and interlayers of the flow unit, the dynamic permeability and liquid production index rectangular curves are drawn respectively using the single-layer dynamic permeability and liquid production index data of the single-well flow unit determined by segmentation, and the single-layer dynamic permeability and liquid production index in the high permeability strip dynamic standard are set as the baseline of the rectangular curve and filled to the right of the rectangular curve. When the dynamic permeability and liquid production index of the single layer are greater than the dynamic permeability and liquid production index corresponding to the baseline of the rectangular curve, the single layer is determined to be a high permeability strip.

[0148] As a specific embodiment of the above device of the present invention, the hypertonic band genesis type classification module is specifically used for:

[0149] The high permeability reservoir or the single well high permeability belt data divided by the rock physical phase of the core well is used to analyze the rock phase and sedimentary phase type of the high permeability reservoir or the high permeability belt by using the scatter cross plot or frequency histogram method; at the same time, the position of the high permeability belt in the sedimentary phase and stratigraphic sequence is analyzed in combination with the results of sedimentary microfacies and sequence stratigraphic division.

[0150] As a specific embodiment of the above device of the present invention, the high permeability band logging identification module is specifically used for:

[0151] Taking the single-well production logging test section as the sample and the single-layer dynamic permeability and single-layer specific liquid production index corresponding to the dynamic standard of the high-permeability zone as the boundary, the logging response characteristics of the high-permeability zone and the non-high-permeability zone are analyzed, and the qualitative identification mode of the high-permeability zone logging phase and the conventional logging quantitative identification mode of the sedimentary high-permeability zone are established.

[0152] As a specific embodiment of the above device of the present invention, the high permeability band logging identification module includes a high permeability band logging phase qualitative identification mode establishment unit, and the high permeability band logging phase qualitative identification mode establishment unit is used to:

[0153] The differences between high-permeability bands and non-high-permeability bands in conventional logging curves, FMI imaging logging diagrams, and nuclear magnetic resonance logging T2 spectra were analyzed. Based on the analysis results, qualitative identification modes of high-permeability band logging phases were established in sedimentary reservoirs and karst reservoirs, respectively.

[0154] As a specific embodiment of the above device of the present invention, the high permeability band logging identification module further includes a sedimentary high permeability band conventional logging quantitative identification mode establishment unit, and the sedimentary high permeability band conventional logging quantitative identification mode establishment unit is used to:

[0155] In the production logging test section, according to the principle of dominant seepage channels, obvious non-permeable interlayers and low permeability reservoirs are deducted, and the curve values ​​of the logging curves are obtained in sections according to the conventional logging curve sampling intervals. Then, a dual logging curve classification scatter intersection diagram is made according to the dynamic permeability distribution interval. The distribution law and identification boundary of the logging curve values ​​of the high permeability strips are analyzed in combination with geological laws, and a conventional logging quantitative identification mode for sedimentary high permeability strips is established accordingly.

[0156] As a specific embodiment of the above device of the present invention, the high permeability band logging identification module further includes a curve value calculation unit of the pore structure index curve, and the curve value calculation unit of the pore structure index curve is used to:

[0157] When the logging curve includes a pore structure index curve, the curve value of the pore structure index curve is calculated according to the following formula (7):

[0158]

[0159] In formula (7), R w is the formation water resistivity, in ohm·m; R t is the original formation resistivity, and the resistivity corresponding to the deep detection resistivity curve on the logging curve is in ohm·m; POR is the reservoir porosity, in dimensionless decimal; S w is the formation water saturation, and its unit is a dimensionless decimal; n is the saturation index, and its unit is a dimensionless decimal.

[0160] As a specific embodiment of the above-mentioned device of the present invention, the device also includes: an identification result verification module, which is used to use core test results, production logging data and dynamic permeability data, as well as the water-bearing layers of the water-bearing wells in the injection and production well group and the development of high permeability bands in the water-bearing layers to verify the identification results of high permeability bands in marine carbonate bioclastic limestone reservoirs.

[0161] On the other hand, the present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs when executing the computer program.

[0162] On the other hand, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs described above are implemented.

[0163] The present invention takes dynamics as its key point and provides a method and device for identifying high-permeability zones in marine carbonate bioclastic limestone reservoirs that integrates dynamics and statics under the constraints of geological laws. The theoretical basis and technical logic of the method and device provided by the present invention are solid and reliable, and the method is simple and easy to operate. The identification objects of the method and device provided by the present invention include thief layers but are not limited to thief layers, which effectively solves the problem of identifying high-energy sedimentary high-permeability zones in marine carbonate bioclastic limestone reservoirs that have the greatest impact on water injection development. After the method and device provided by the present invention are promoted and applied in oil fields, a set of reliable high-permeability zone data that effectively covers the entire reservoir can be provided, which verifies that the current early water-seeking wells in the injection-production well group are related to the high-permeability zones identified by the method and device of the present invention, and can provide technical support for the optimal design of new injection-production well groups. BRIEF DESCRIPTION OF THE DRAWINGS

[0164] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0165] Figure 1 A flow chart of a method for identifying high permeability zones in a marine carbonate bioclastic limestone reservoir provided in an embodiment of the present invention.

[0166] Figure 2 It is a schematic diagram of the PBU test results of Well X in a certain oil field in a specific embodiment of the present invention.

[0167] Figure 3 It is a schematic diagram of the dynamic test and high permeability band picking results of a Y data well in an oil field in a specific embodiment of the present invention.

[0168] Figure 4 Schematic diagram of Horner curve of pressure recovery test of well X in a specific embodiment of the present invention.

[0169] Figure 5 Schematic diagram of Z-well inter-layer interference identification in a specific embodiment of the present invention.

[0170] Figure 6 This is a schematic diagram of determining the dynamic identification standard of the hypertonic band in a specific embodiment of the present invention.

[0171] Figure 7 It is a schematic diagram of the research results of single well sequence stratigraphy, rock phase and sedimentary phase in a specific embodiment of the present invention.

[0172] Figure 8 It is a schematic diagram of the physical classification of effective reservoir rocks in a specific embodiment of the present invention.

[0173] Fig. 9 It is a schematic diagram of rock phase analysis of high permeability reservoir development in a specific embodiment of the present invention.

[0174] Fig.10a It is a statistical histogram of rock phase types developed in high permeability reservoirs in a specific embodiment of the present invention.

[0175] Fig.10b It is a statistical histogram of sedimentary facies types developed in high-permeability reservoirs in a specific embodiment of the present invention.

[0176] Fig.11a It is a schematic diagram of the electrical characteristics and longitudinal distribution of tidal channel type sedimentary high permeability strips in a specific embodiment of the present invention.

[0177] Fig.11b It is a schematic diagram of the electrical characteristics and longitudinal distribution of bioclast beach type sedimentary high permeability strips in a specific embodiment of the present invention.

[0178] Fig.11c It is a schematic diagram of the electrical characteristics and longitudinal distribution of beach-wing type sedimentary high-permeability strips in a specific embodiment of the present invention.

[0179] Fig.12a It is a schematic diagram of the electrical characteristics and longitudinal distribution of the karst high-permeability strip in Well D in a specific embodiment of the present invention.

[0180] Figure 12b It is a schematic diagram of the electrical characteristics and longitudinal distribution of the karst high-permeability strip in Well E in a specific embodiment of the present invention.

[0181] Fig.13a It is a schematic diagram of the FMI and CMR logging characteristics of a sedimentary high permeability strip in a specific embodiment of the present invention.

[0182] Fig.13b It is a schematic diagram of FMI and CMR logging characteristics of karst high permeability zones in a specific embodiment of the present invention.

[0183] Fig.14 A schematic diagram of sample extraction for establishing a well logging interpretation model for a high permeability zone in a specific embodiment of the present invention.

[0184] Fig.15a It is a scatter cross plot of the dual logging curve RHOB-Rt based on K_PBU classification in a specific embodiment of the present invention.

[0185] Fig.15b It is a scatter cross plot of the dual logging curve GR-Am based on K_PBU classification in a specific embodiment of the present invention.

[0186] Fig.16a This is a schematic diagram of the single well identification results of the hypertonic band in a specific embodiment of the present invention.

[0187] Fig.16bfor Fig.16a FMI imaging and CMR logging T2 energy spectrum of the karst high permeability zone corresponding to Zhong76.

[0188] Fig.16c for Fig.16a FMI imaging and CMR logging T2 energy spectrum of the karst high permeability zone corresponding to Zhong77.

[0189] Fig.17a Figure 79 is the well location distribution map of the injection and production well group.

[0190] Fig.17b This is a comparison diagram of the connection between two water injection wells (INJ1 and INJ2) and one oil production well (PROD1).

[0191] Fig.17c for Fig.17b Legend of the sedimentary microfacies corresponding to No. 84.

[0192] Fig.18 A schematic diagram of the structure of a high permeability zone identification device for a marine carbonate bioclastic limestone reservoir provided by an embodiment of the present invention.

[0193] Fig.19 A schematic structural diagram of a device for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs provided in another embodiment of the present invention. DETAILED DESCRIPTION

[0194] In order to have a clearer understanding of the technical features, purposes and beneficial effects of the present invention, the technical scheme of the present invention is now described in detail in conjunction with the following specific embodiments, but it should not be understood as limiting the applicable scope of the present invention.

[0195] Figure 1 A flow chart of a method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs provided by an embodiment of the present invention, from Figure 1 It can be seen that the method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs includes the following specific steps:

[0196] S101: Determine the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit based on well test data and production logging data;

[0197] S102: Analyze the interlayer interference of multi-layer commingled production according to the production logging data, comprehensively utilize the single-layer production and the single-layer dynamic permeability and single-layer specific production liquid index of the single-well flow unit in the production logging data to establish a dynamic standard for the high-permeability band and extract the single-well high-permeability band;

[0198] S103: in the coring well, according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, the high permeability reservoir genetic type is classified, and the distribution law of the high permeability band in the rock phase, sedimentary phase and sequence interface is determined;

[0199] S104: establishing a high permeability band logging identification mode, and identifying high permeability bands well by well in the entire reservoir according to the high permeability band logging identification mode, so as to realize logging interpretation of the entire reservoir.

[0200] In one embodiment, the well testing data is PBU data, and the production logging data is PLT test data.

[0201] In one embodiment, the single-layer specific liquid production index is determined according to the following formula (1) based on the well test data and the production logging data:

[0202]

[0203] In formula (1), SPI is the specific liquid index, unit is bbl / (d·psi·m); q o is the daily liquid production, in bbl / d; ΔP is the bottom hole pressure difference, in psi; h is the thickness of the liquid producing layer, in m.

[0204] In one embodiment, for a single-layer well test, when the well test data is PBU data, determining the single-layer dynamic permeability of a single-well flow unit according to the PBU data includes:

[0205] 1) Determine the formation coefficient of the single well according to the following formula (2) based on the PBU data interpretation;

[0206]

[0207] In formula (2), kh is the formation coefficient of the single well interpreted by PBU data, in mD·m; q is the PBU test production, in m 3 / ks; μ is the fluid viscosity, in mPa·s; m is the slope of the Horner curve used in PBU data interpretation, dimensionless; h is the flow unit thickness, in m; k is the single-layer dynamic permeability of a single well flow unit, in mD;

[0208] 2) Determine the thickness of the flow unit on the well logging curve, and then divide the formation coefficient of the single well by the thickness of the flow unit to obtain the single-layer dynamic permeability of the flow unit of the single well;

[0209] In the case of combined layer well testing, when the well testing data is PBU data and the production logging data is PLT test data, the single layer dynamic permeability of the single well flow unit is determined based on the PBU data and the PLT test data, including:

[0210] 1) Determine the comprehensive formation coefficient of the single well according to the above formula (2) based on the PBU data interpretation;

[0211] 2) using the layered liquid production in the PLT test data, the comprehensive formation coefficient of the single well is batched into each flow unit according to the following formula (3) to formula (5), so as to obtain the single-layer formation coefficient of each flow unit;

[0212] q t =q1+q2+q3+…+q l Formula (3);

[0213]

[0214] (kh) l =(kh)×ration l Formula (5);

[0215] Formula (3)-In formula (5), q t It is the cumulative liquid production in the PLT test data, in bbl / d; q1, q2, q3, ... q l They are the actual liquid production of different production sections in the PLT test data, both in bbl / d; l is the ratio of the actual liquid production of different liquid production sections in the PLT test data to the cumulative liquid production in the PLT test data, and the unit is dimensionless; kh is the formation coefficient interpreted by PBU data, that is, the comprehensive formation coefficient of the single well, and the unit is mD·m; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m;

[0216] 3) Then, the single-layer dynamic permeability of each flow unit in the single well is determined according to the single-layer formation coefficient of each flow unit and the thickness of each flow unit according to the following formula (6);

[0217]

[0218] In formula (6), h l is the single layer dynamic permeability of the flow unit, in mD; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m; h l is the actual thickness of the liquid-producing section of the flow unit in the PLT test data, in m; l is the number of actual liquid-producing sections in the PLT test data, a positive integer.

[0219] In one embodiment, determining the thickness of the flow unit includes:

[0220] Inside the flow unit shown in the PLT test data, the internal partitions and interlayers of the unit are deducted using the logging curve; the thickness of the flow unit is then corrected to the vertical depth through well trajectory calculation, thus obtaining the thickness of the flow unit.

[0221] In one embodiment, the high permeability zone dynamic standard is established by comprehensively utilizing the single-layer production in the production logging data and the single-layer dynamic permeability and single-layer specific liquid production index of the single-well flow unit, including:

[0222] A scatter plot of single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit was established to analyze the production capacity of the flow unit, that is, the changing trend of the specific liquid production index with dynamic permeability and determine the inflection point. The dynamic permeability and liquid production index corresponding to the inflection point were determined as the dynamic identification criteria for high permeability zones in marine carbonate bioclastic limestone reservoirs.

[0223] In one embodiment, extracting the single well hypertonic band includes: extracting the hypertonic band in layers in the single well according to the dynamic identification standard, specifically including:

[0224] On the basis of deducting the internal partitions and interlayers of the flow unit, the dynamic permeability and liquid production index rectangular curves are drawn respectively using the single-layer dynamic permeability and liquid production index data of the single-well flow unit determined by segmentation, and the single-layer dynamic permeability and liquid production index in the high permeability strip dynamic standard are set as the baseline of the rectangular curve and filled to the right of the rectangular curve. When the dynamic permeability and liquid production index of the single layer are greater than the dynamic permeability and liquid production index corresponding to the baseline of the rectangular curve, the single layer is determined to be a high permeability strip.

[0225] In one embodiment, based on the research results of sequence stratigraphy, lithofacies, sedimentary facies and rock physical facies, the genetic type of high permeability reservoir is classified, and the distribution law of the high permeability band in the lithofacies, sedimentary facies and sequence interface is determined, including:

[0226] The high permeability reservoir or the single well high permeability belt data divided by the rock physical phase of the core well is used to analyze the rock phase and sedimentary phase type of the high permeability reservoir or the high permeability belt by using the scatter cross plot or frequency histogram method; at the same time, the position of the high permeability belt in the sedimentary phase and stratigraphic sequence is analyzed in combination with the results of sedimentary microfacies and sequence stratigraphic division.

[0227] In one embodiment, the establishment of a high permeability zone logging identification mode includes:

[0228] Taking the single-well production logging test section as the sample and the single-layer dynamic permeability and single-layer specific liquid production index corresponding to the dynamic standard of the high-permeability zone as the boundary, the logging response characteristics of the high-permeability zone and the non-high-permeability zone are analyzed, and the qualitative identification mode of the high-permeability zone logging phase and the conventional logging quantitative identification mode of the sedimentary high-permeability zone are established.

[0229] In one embodiment, the establishment of a high permeability zone logging phase qualitative identification mode includes:

[0230] The differences between high-permeability bands and non-high-permeability bands in conventional logging curves, FMI imaging logging diagrams, and nuclear magnetic resonance logging T2 spectra were analyzed. Based on the analysis results, qualitative identification modes of high-permeability band logging phases were established in sedimentary reservoirs and karst reservoirs, respectively.

[0231] In one embodiment, in a sedimentary reservoir, high-permeability bands are mostly developed in a high-energy sedimentary environment, and are mostly porous high-permeability bands with pure lithology, coarse grain size, high porosity, and high permeability; conventional logging curves show low gamma, high porosity, and high resistivity; FMI imaging images have light-colored, regularly or irregularly distributed black patches, indicating the development of intergranular pores or larger dissolution pores; nuclear magnetic logging T2 spectrum shows that the T2 value is bimodal or multi-modal, and both the T2 time and energy spectrum peaks show high values;

[0232] In karst reservoirs, the high-permeability zones are thin, with no obvious conventional logging features but high productivity, and often display “thief layer” features; FMI imaging shows the development of sinusoidal cross-well fractures or irregular microcracks, with caves or large dissolution pores in some wells; the nuclear magnetic resonance logging T2 spectrum shows bimodal or multi-peak features, with medium or low T2 time and energy spectrum peaks, and high-permeability zones with developed caves or large dissolution pores have large T2 values.

[0233] In one embodiment, a conventional well logging quantitative identification mode for sedimentary high permeability zones is established, including:

[0234] In the production logging test section, according to the principle of dominant seepage channels, obvious non-permeable interlayers and low permeability reservoirs are deducted, and the curve values ​​of the logging curves are obtained in sections according to the conventional logging curve sampling intervals. Then, a dual logging curve classification scatter intersection diagram is made according to the dynamic permeability distribution interval. The distribution law and identification boundary of the logging curve values ​​of the high permeability strips are analyzed in combination with geological laws, and a conventional logging quantitative identification mode for sedimentary high permeability strips is established accordingly.

[0235] In one embodiment, when the logging curve includes a pore structure index curve, the curve value of the pore structure index curve is calculated according to the following formula (7):

[0236]

[0237] In formula (7), R w is the formation water resistivity, in ohm·m; R t is the original formation resistivity, and the resistivity corresponding to the deep detection resistivity curve on the logging curve is in ohm·m; POR is the reservoir porosity, in dimensionless decimal; S wis the formation water saturation, and its unit is a dimensionless decimal; n is the saturation index, and its unit is a dimensionless decimal.

[0238] In one embodiment, the method also includes: using core test results of coring wells, production logging data and dynamic permeability data, as well as the water-bearing layers of water-bearing wells in the injection and production well group and the development of high permeability zones in the water-bearing layers to verify the high permeability zone identification results of marine carbonate bioclastic limestone reservoirs.

[0239] The following will take a marine carbonate bioclastic limestone reservoir in an oil field as an example to specifically illustrate the method for identifying high permeability zones in a marine carbonate bioclastic limestone reservoir provided by the present invention, which includes:

[0240] Determine the single-layer dynamic permeability and single-layer specific liquid production index of the single-well flow unit according to the well test data and the production logging data: wherein the well test data is PBU data, and the production logging data is PLT test data;

[0241] In a specific embodiment, Figure 2 This is a schematic diagram of the PBU well test results of Well X in the oil field. Figure 2 It can be seen that the well has reached the quasi-stable flow stage during the well test. The reservoir parameters interpreted by the double logarithmic curve of the well test can more realistically reflect the reservoir characteristics of the flow unit encountered by the single well. The formation coefficient interpreted by it can better reveal the production capacity of the flow unit.

[0242] In a specific embodiment, Figure 3 This is a schematic diagram of the dynamic test and high permeability band picking results of Well Y in the oil field. Figure 3 1 is the well logging depth channel, 2 is the vertical depth channel after the correction of the core height, 3 is the overlapped channel of the natural gamma (GR) and rock density (RHOB) curve, 4 is the overlapped channel of the natural gamma (GR) and deep detection resistivity (LLD) curve, 5 is the PLT test channel, 6 is the K_PBU calculation result channel, 7 is the SPI calculation result channel, 8 is the perforation section indicator channel, 9 is the K_PBU baseline, 10 is the K_PBU rectangular curve, 11 is the SPI baseline, 12 is the SPI rectangular curve, 13 is the SPI baseline rightward and the SPI rectangular curve filling ( Figure 3 The black area represented by 13 in the figure can be filled only when the SPI value is greater than the SPI baseline value. 14-15 are perforated interlayers. Figure 3 As shown in Figure 5, within the perforation section, the PLT test fluid flow section is intermittently distributed, with the strongest at the top of MB1-2C, that is, the PLT test fluid flow section within the perforation section shows the flow unit through the test well under the current production conditions;

[0243] In a specific embodiment, determining the thickness of the flow unit includes:

[0244] First, within the flow unit revealed by PLT, the internal partitions and interlayers of the unit were deducted using the logging curve. Figure 3 14, 15); then, through the calculation of the well trajectory, the flow unit thickness is corrected to the vertical depth after the core height correction ( Figure 3 2), that is, the thickness of the flow unit is obtained;

[0245] In a specific embodiment, the single-layer specific liquid production index of well Y is determined according to the above formula (1): Figure 3 7 and Table 1, the production pressure difference (bottom hole pressure difference) of the five PLT test liquid sections of the well is 453.7 psi, the daily oil production is 196.93-1015.70 bbl / d, and the flow unit thickness (vertical depth thickness of the PLT liquid production section) is 1.30-7.23 m. Based on this, the SPI value calculated according to formula (1) ranges from 0.064 to 0.525 bbl / (d·psi·m);

[0246] Table 1 Calculation table of specific production fluid index of Y well

[0247]

[0248]

[0249] In the specific embodiment, since Well Y is a combined well test, the dynamic permeability is calculated according to Formula (4) to Formula (6) as described above. The intermediate parameters involved in the calculation process and the calculated result data are shown in Figure 3 As shown in Figure 6 and Table 2, it can be seen that the K_PBU values ​​of different flow units obtained by comprehensive interpretation of PBU data and PLT test data range from 26.00 to 328.54 mD, with the highest values ​​in the flow units at the top of MB1-2A and the upper part of MB1-2C. The calculation results of the upper part of MB1-2C have a good correlation with the reservoir geological characteristics and logging response characteristics. The logging response characteristics of the extremely thin layer at the top of MB1-2A are not obvious, but because it is near the third-order sequence interface and is related to dissolution exposure, it is difficult to identify except for imaging logging, and has typical "thief layer" characteristics.

[0250] Table 2 Dynamic permeability calculation table of Y well

[0251]

[0252] According to the production logging data, the interlayer interference of multi-layer commingled production is analyzed, and the single-layer production, single-layer dynamic permeability and single-layer specific production liquid index of the single-layer production logging data are comprehensively used to establish the dynamic standard of the high-permeability band and extract the single-well high-permeability band:

[0253] In a specific embodiment, the interlayer interference of multi-layer commingled production is analyzed based on production logging data, including: analyzing the production capacity suppression and interference of the possible high-yield layer on the relatively poor reservoir based on production logging data (such as PLT test data);

[0254] Figure 5 This is a schematic diagram of inter-layer interference identification of the Z well in a specific embodiment. Figure 5 16 is the single well stratum division information, 17-19 are conventional logging natural gamma, rock density, deep detection resistivity curves, 20 is the PLT test curve, 21 is the MDT test data, 22 is the perforation profile, 23-25 ​​are the production data of PLT tests at different layers, 26-27 are PLT non-production layers, from Figure 5 It can be seen that due to the influence of the high-yield layer of MA2 (23) and the high-yield layer of MB1-2C (25), the reservoirs of MB1-2A and MB1-2B in the middle, which have similar reservoir characteristics to the MB1-2C production layer, show low production (24) or even no production (26-27), indicating that there is obvious production suppression and interlayer interference.

[0255] In a specific embodiment, the high permeability zone dynamic standard is established by comprehensively utilizing the single-layer production in the production logging data and the single-layer dynamic permeability and single-layer specific liquid production index of the single-well flow unit, including:

[0256] The scatter cross-plot of the single-layer dynamic permeability and the single-layer specific liquid production index of the single-well flow unit is established. The obtained cross-plot (i.e., the schematic diagram for determining the dynamic identification standard of the high permeability band) is shown as follows: Figure 6 As shown, from Figure 6 It can be seen that SPI increases monotonically with K_PBU and has a good correlation. At K_PBU=100mD, SPI obviously bifurcates. The inflection point is set as K_PBU=100mD(28) and SPI=0.3bbl / (d·psi·m)(29). Above the inflection point, the production capacity of the flow unit increases rapidly with the increase of permeability. Therefore, K_PBU=100mD and SPI=0.3bbl / (d·psi·m) are defined as the dynamic identification criteria for the high permeability zone of the bioclastic limestone reservoir in the specific embodiment.

[0257] Then, according to the dynamic identification standard of high permeability zones in bioclastic limestone reservoirs, high permeability zones are extracted in layers in wells with both PBU data and PLT test data, providing samples for establishing an identification model that can be extended to the entire reservoir. Figure 3 As shown in the figure, after deducting the internal partitions and interlayers of the flow unit, the dynamic permeability rectangular curve is drawn using the segmented determined K_PBU and SPI data, and the lower limit of the dynamic permeability of the high permeability strip (K_PBU = 100mD, SPI = 0.3bbl / (d·psi·m)) is set as the baseline of the rectangular curve. Figure 36, 7, 9 and 11) and fill the right side of the rectangular curve. When K_PBU and SPI are greater than the dynamic permeability and specific production index corresponding to the baseline, it indicates that the layer is a high permeability band. In this specific embodiment, a total of 200 flow units from 31 wells were analyzed, and a total of 62 layers of high permeability bands were extracted, effectively covering all sweet spot sedimentary phases of the reservoir. The sample quantity is large and representative, which lays a good foundation for establishing geological and well logging identification models.

[0258] In the coring well, the high permeability reservoir genesis type is classified according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, and the distribution law of the high permeability band in the rock phase, sedimentary phase and sequence interface is determined;

[0259] In a specific embodiment, the study of sequence stratigraphy includes: based on the sequence stratigraphy theory that sea level changes control the formation and development of sequences, a hierarchical sub-marine stratigraphic division scheme is established according to the lithofacies cycle and seismic sequence structure, and extended to the entire reservoir through single well logging curves and three-dimensional seismic. The third and fourth order sequences divided into target reservoirs in the specific embodiment have the characteristics of rapid transgression and slow regression, and the top is exposed, which is highly comparable. Tidal channels and incised valleys are developed at the top of some sequences (such as Figure 7 (30).

[0260] In a specific embodiment, the study of rock phases includes: classifying rock phase types according to the Dunham scheme based on the carbonate rock grain structure; classifying rock phases and calibrating well logging based on core observation and thin section analysis in coring wells and establishing identification standards; identifying rock phases using logging curves in non-coring wells, thereby extending to the entire oil reservoir. In a specific embodiment, the oil reservoir is developed on a gentle slope platform, and the carbonate rock grain structure is mainly composed of bioclastic particles, mud matrix, and bright crystal cement. Due to the weak cementation of the effective reservoir, five rock phases are divided: grain limestone (grain content>75%), grain-dominated mud limestone (grain content of 50%-75%), mud-dominated mud limestone (grain content of 25%-50%), grain marl (grain content of 10%-25%), and micrite (grain content of <10%). Figure 7 As shown in Figure 31, as the particle content decreases, the logging curve under the same conditions has the characteristics of increasing gamma (especially deuranium gamma) value and decreasing resistivity value.

[0261] In a specific embodiment, the study of sedimentary facies includes: determining the reservoir sedimentary environment according to the regional geological background and establishing a sedimentary model; using cores and thin sections to analyze sedimentary characteristics, divide sedimentary microfacies, calibrate logging and establish a sedimentary microfacies logging identification model in coring wells; using the morphology, combination and longitudinal rhythmic changes of logging curves in non-coring wells to identify sedimentary microfacies, and then extending it to the entire reservoir. The reservoir in the specific embodiment is a weakly edged gentle slope carbonate platform environment, and a total of eight sedimentary microfacies are divided, including tidal channels, incised valleys, intra-platform bioclastic beaches, front bioclastic beaches, beach wings, lagoons, swamps and subtidal zones. Figure 7 It can be seen from Figure 32 that in high-energy environment sedimentary microfacies such as tidal channels and bioclastic beaches, granular limestone and particle-dominated mudstone are mostly developed, while in low-energy environment sedimentary microfacies such as subtidal zones and lagoons, micrite, granular marl and mudstone dominated by limestone are mainly developed.

[0262] In a specific embodiment, the study of rock physical phases includes: in accordance with the Petroleum and Natural Gas Industry Standard of the People's Republic of China "Oil and Gas Reservoir Evaluation Method" (SY / T 6285-1997), the carbonate reservoir porosity is divided into four levels: high porosity (≥20%), medium porosity (12%-20%), low porosity (4%-12%) and ultra-low porosity (<4%), and the permeability is divided into four levels: high permeability (≥100mD), medium permeability (10-100mD), low permeability (1-10mD) and ultra-low permeability (<1mD); in a specific embodiment, considering that the porosity and permeability classification standards of different oil fields may not be completely consistent with the national standards due to differences in the genesis of oil reservoirs and reservoirs, the porosity and permeability classification standards are determined by using the physical property experiment of the standard core of the coring well and the porosity and permeability scatter plot constrained by the main controlling factors of the reservoir (such as sedimentary microfacies). Figure 8 As shown in the figure, considering the genesis of effective reservoirs and the clustering characteristics of pore and permeability points, the limits of porosity classification are adjusted to 22% ( Figure 8 33), 15%( Figure 8 34), 8%( Figure 8 35), adjust the permeability classification standard limit to 30mD ( Figure 8 36), 3mD( Figure 8 37) and 0.3mD( Figure 8 38), which is slightly different from the industry standard.

[0263] In a specific embodiment, the high permeability reservoir layer divided by the rock physical phase of the core well or the single well high permeability strip data picked up by the PBU data and PLT test data of the data well is used to analyze the rock phase and sedimentary phase type of the high permeability reservoir layer or high permeability strip development by using the scatter cross plot or frequency histogram method; Fig. 9As shown in Figure 39, the high permeability reservoirs in the rock physical phase (core permeability>30mD, porosity>0.15) are mainly developed in grain limestone and grain-dominated mudstone; at the same time, combined with the results of sedimentary microfacies and sequence stratigraphic division, the position of the high permeability belt in the sedimentary facies and stratigraphic sequence is analyzed to provide regular constraints for identifying high permeability belts using logging data. Fig.10a is a statistical histogram of rock phase types developed in high permeability reservoirs in a specific embodiment, Fig.10b is a statistical histogram of sedimentary facies types of high permeability reservoirs in a specific embodiment, from Fig.10a It can be seen that the rock phases developed in the high permeability reservoirs are mainly grain limestone and grain-dominated mudstone. Fig.10b It can be seen that the sedimentary facies where high-permeability reservoirs are developed are mainly tidal channels and front bioclastic beaches, a small amount of beach wings and lagoons. Among them, the sweet spot sedimentary facies of tidal channels, bioclastic beaches and some beach wings are the main bodies of sedimentary high-permeability belts, and other non-sweet spot phases such as lagoons, swamps and beach wings are mostly formed by karst transformation, and karst-type high-permeability belts are developed (see Table 3 below).

[0264] Figure 11a-Figure 11c Figure 2 is a schematic diagram of the logging response characteristics and vertical distribution of three types of sedimentary high permeability zones in a specific embodiment. Fig.11a In the figure, channel 40 represents the stratigraphic layering data, channel 41 represents the drilling depth, channel 42 represents the natural gamma curve and porosity curve, channel 43 represents the deep detection resistivity and natural gamma curve, and channel 44 represents the HPS identification result; Figure 11b-Figure 11c have the same drawing structure. Figure 11a-Figure 11c As can be seen from Table 3, the tidal channel has the characteristics of weakening sedimentation energy upward, finer and less grains, mostly positive grain sequence structure, and high permeability bands are mostly developed in the lower part ( Fig.11a The bioclastic beaches are the opposite, showing mostly inverse grain sequence structures, with high permeability zones mostly developed in the upper part ( Fig.11b Well B in the figure is taken as an example); the high permeability zones of the beach wing are mostly developed near the beach body ( Fig.11c Take Well C in Figure 1 as an example).

[0265] Figure 12a-12b It is a schematic diagram of the logging response characteristics and vertical distribution of the karst high permeability zone in a specific embodiment. Figure 12a-12b Channel 45 is the sequence stratigraphic division channel, channel 46 is the FMI static imaging channel, channel 47 is the FMI dynamic imaging channel, channel 48 is the nuclear magnetic logging T2 spectrum channel, channel 49 is the PLT test data channel, and channel 50 is the dynamic permeability calculation result channel. Figure 12a-12bIt can be seen that karst high-permeability zones are mostly controlled by sequence structure and sedimentary exposure, and are mostly developed near sequence interfaces (see Table 3 below). The FMI imaging logging of Well D shows that dissolution-type microfractures are developed near the sequence interface. Although the reservoir matrix physical properties are poor near the sequence interface of Well E, the PLT test obtains higher production capacity and higher dynamic permeability (328mD).

[0266] Table 3 Genesis types and characteristics of high permeability bands

[0267]

[0268] A high permeability band logging identification mode is established, and high permeability bands are identified well by well in the entire reservoir according to the high permeability band logging identification mode, so as to realize the logging interpretation of the entire reservoir:

[0269] Taking the PLT test section of the data well as the sample and K_PBU=100mD as the boundary, the logging response characteristics of high permeability zones (K_PBU≥100mD) and non-high permeability zones (K_PBU<100mD) were analyzed, and the qualitative identification mode of high permeability zones logging phase and the quantitative identification mode of sedimentary high permeability zones conventional logging were established.

[0270] The establishment of a qualitative identification model of high-permeability band logging phase includes: analyzing the differences between high-permeability bands and non-high-permeability bands in conventional logging curves, FMI imaging logging diagrams, and nuclear magnetic logging T2 spectra, and establishing two types of qualitative identification models of high-permeability band logging phases. In sedimentary reservoirs, high-permeability bands are controlled by sedimentary phases and are mostly developed in high-energy sedimentary environments. They are mostly porous high-permeability bands with pure lithology, coarse grain size, high porosity, and high permeability. Conventional logging curves show low gamma, high porosity, and high resistivity, such as Figure 11a-Figure 11c As shown in Well A, Well B, and Well C in the figure; the FMI imaging image has light-colored, regularly or irregularly distributed black patches, indicating the development of intergranular pores or larger dissolution pores; the nuclear magnetic logging T2 spectrum shows that the T2 value is bimodal or multi-modal, and the T2 time and energy spectrum peaks both show high values, such as Fig.13a As shown, in Fig.13a In the figure, 51 is the FMI static imaging channel, 52 is the FMI dynamic imaging channel, and 53 is the nuclear magnetic logging T2 spectrum channel. Fig.13a It can be seen that the D well has regular dissolution pores (black patches) in the illustrated layer, and the CMR logging T2 spectrum shows bimodal or multimodal characteristics. In karst reservoirs, the high permeability zone is thin, the conventional logging characteristics are not obvious, but the production capacity is high, and it often shows the characteristics of "thief layer" (see Figure 12b Well E in Figure 1); FMI imaging shows the development of sinusoidal cross-well fractures or irregular micro fractures (see Fig.12a Well D in the figure), some wells have caves or large dissolution holes (see Fig.13b); The T2 spectrum of nuclear magnetic logging shows double or multi-peak characteristics, and the T2 time and energy spectrum seam peaks are medium or low (see Fig.13b Well D in the figure), the high permeability zone with developed caves or large karst pores has a large T2 value (see Fig.13b ).

[0271] The establishment of a conventional well logging quantitative identification mode for sedimentary high permeability zones includes:

[0272] First, according to the above formula (7), the pore structure index curve reflecting the reservoir storage and permeability characteristics is introduced, and the formation water salinity, capillary pressure curve, phase permeability curve, displacement resistivity experiment, etc. are comprehensively analyzed. In the specific embodiment, R in formula (7) is determined. w The value is 0.05ohm·m, n is 2.05, the Sw value of the pure oil layer is 0.1-0.3, which increases with the deterioration of physical properties, the Sw value of the pure water layer is 1, and the oil and water layers are interpolated according to the oil column height and physical properties. Therefore, the pore structure index curve (Am) is calculated using the porosity curve and the deep detection logging resistivity curve. Fig.14 This is a schematic diagram of sample extraction for establishing a logging identification mode for a high permeability zone in a specific embodiment of the present invention. Fig.14 In the figure, 54 is the natural gamma curve, 55 is three porosity curves (density RHOB, neutron NPHI, acoustic wave DT), 56 is the deep detection resistivity curve, 57 is the calculated pore structure index curve Am, 58 is the PLT test data, 59 is the dynamic permeability calculation result, and 60-61 are the dynamic permeability rectangular curves of the PLT test liquid production section after deducting the interlayer. Fig.14 As shown in Figure 57, in a pure oil layer, the Am value increases as the reservoir permeability improves.

[0273] Secondly, in the PLT test section ( Fig.14 57), according to the principle of seepage dominant channel, the obvious impermeable interlayers and low permeability reservoirs (high gamma, high density, low resistivity and low Am layers in oil layers, such as Fig.14 61), and obtain the natural gamma curve (GR, Fig.14 54), representative porosity curves (RHOB, Fig.14 55), representative resistivity curve (Rt, Fig.14 56) and the pore structure index curve (Am, Fig.14 Zhong57) and other logging curve values ​​( Fig.1460-61); then according to the K_PBU value distribution interval (in the specific embodiment, the K_PBU value is divided into 9 intervals of 0mD, 0-1mD, 1-10mD, 10-50mD, 50-100mD, 100-200mD, 200-500mD, 500-1000, >1000mD), a double logging curve classification scatter intersection diagram is made, and the logging curve value distribution law and identification boundary of the high permeability strip (K_PBU ≥ 100mD) are analyzed in combination with geological laws, and a conventional logging quantitative identification model for sedimentary high permeability strips is established accordingly. Figure 15a-Figure 15b The figure shows a scatter cross plot of dual logging curves based on K_PBU classification in this specific embodiment. Figure 15a-Figure 15b In the figure, 62 is the lower limit of resistivity of the high permeability zone, 63 is the upper limit of the porosity curve RHOB of the high permeability zone, 64 is the lower limit of the pore structure index curve of the high permeability zone, and 65 is the upper limit of the natural gamma curve of the high permeability zone. Figure 15a-Figure 15b It can be seen that the reservoirs with K_PBU greater than 100mD are concentrated in the low density / porosity (<2.4g / cm 3 ), high resistivity (≥20ohm·m), low gamma (<20API), and high Am (≥2.5) areas, which are consistent with the electrical characteristics of high-energy sedimentary high-permeability reservoirs. Based on this, a conventional logging quantitative identification model for sedimentary high-permeability zones is established, and the identification criteria are shown in Table 4.

[0274] Table 4 Well logging identification standard table for high energy sedimentary high permeability zones

[0275] GR / (API) <![CDATA[RHOB / (g / cm 3 )]]> Rt / (Ω.m) Am <20 <2.4 ≥20 ≥2.5

[0276] In a specific embodiment, according to the high permeability band logging identification mode, high permeability bands are identified well by well in the entire reservoir to implement logging interpretation of the entire reservoir, including:

[0277] Quantitative identification of high-energy sedimentary high-permeability strip logging. Among the four curves, GR represents lithology and sedimentary environment. Its low value means pure lithology, coarse particles, and relatively high sedimentary energy; RHOB represents total rock porosity. Its low value means high porosity and good physical properties; Rt represents oil content and permeability. In pure oil layers, its high value means good oil content, indicating a high degree of oil and gas filling during accumulation, which can indirectly reflect that its permeability is relatively good; Am represents pore structure. Its high value means complex conductive paths, which is a typical large-pore, small-throat coarse-grained sedimentary reservoir. Therefore, as a high-permeability strip that can form a dominant seepage channel, it must meet all the above conditions, so that the logging curve can simultaneously meet "GR<20API, RHOB<2.4g / cm 3 , Rt≥20ohm·m, Am≥2.5” to screen high-energy sedimentation type high-permeability strips point by point;

[0278] Qualitative identification of logging phases: further identify and determine high-energy sedimentary high-permeability zones based on the display characteristics of "double-peak or multi-peak characteristics of T2 spectrum and T2 time and spectrum peak height" of nuclear magnetic logging and "large-scale and strong dissolution holes" of imaging logging; karst reservoirs often have "thief layer" characteristics, which are qualitatively identified based on "sinusoidal cross-well fractures or irregular micro-fractures, black patchy caves or large dissolution holes" on FMI imaging images and "double-peak or multi-peak characteristics" of nuclear magnetic logging T2 spectrum;

[0279] Constrained by geological laws and mutually confirmed, sedimentary high-permeability belts are controlled by sedimentary facies and developed in relatively fixed sedimentary positions, and karst high-permeability belts are constrained by sequence stratigraphy and paleostructures and developed in areas near sequence interfaces. In the above identification process, according to the geological laws that "tidal channel high-permeability belts are mostly developed in the lower part of tidal channels, bioclastic beach high-permeability belts are mostly developed in the upper part of beach bodies, beach wing high-permeability belts are mostly developed near beach bodies, and karst high-permeability belts are mostly developed near sequence interfaces", high-permeability belts are confirmed or picked up again;

[0280] Fig.16a This is a schematic diagram of the single well identification result of the high permeability band in this specific embodiment. Fig.16a 66 is the conventional logging GR curve, 67 is the RHOB curve and core porosity, 68 is the Rt curve and core permeability, 69 is the calculated Am curve, 70 is the PLT test result, 71 is the K_PBU calculation result, 72-74 are the evaluation results of rock phase, sedimentary phase and sequence stratigraphy, 75 is the high permeability band identification result, 76-77 are karst type high permeability bands (shown by black bands fully filled in the logging channel), 78 is high energy sedimentary type high permeability band (shown by gray bands not fully filled in the logging channel); Fig.16b for Fig.16a The FMI image and CMR logging T2 spectrum of the karst high permeability zone corresponding to 76, 761 is the FMI static image, 762 is the FMI dynamic image, and 763 is the CMR logging T2 spectrum. Fig.16b It can be seen that microcracks and larger dissolution holes can be seen in this karst high permeability zone, and the CMR logging T2 energy spectrum shows multiple peaks and high-value characteristics of T2 time spectrum peaks; Fig.16c for Fig.16a The FMI image and CMR logging T2 spectrum of the karst high permeability zone corresponding to 77, 771 is the FMI static image, 772 is the FMI dynamic image, and 773 is the CMR logging T2 spectrum. Fig.16c It can be seen from the figure that the karst high permeability zone is mainly composed of relatively small-scale dissolution holes, and the CMR logging T2 energy spectrum shows double peaks and high-value characteristics of T2 time spectrum peaks; in addition, Fig.16cIt can also be seen that the high-energy sedimentary high-permeability belt strictly meets the logging identification conditions of low gamma, low density, high resistivity and high Am. The karst high-permeability belt does not strictly meet the above conditions, but its development is controlled by the sequence interface and can be effectively identified by using FMI imaging logging combined with CMR logging T2 energy spectrum.

[0281] In a specific embodiment, the method further includes: using the core test results of the coring well, production logging data and dynamic permeability data, as well as the water-bearing layers of the water-bearing wells in the injection-production well group and the development of high-permeability bands in the water-bearing layers to test the high-permeability band identification results of the marine carbonate bioclastic limestone reservoir, specifically as follows Figure 16a-Figure 16c and Figure 17a-Figure 17c As shown:

[0282] Among them, the core test results of the coring well were used to verify the identification results of high permeability zones in marine carbonate bioclastic limestone reservoirs, including: Fig.16a 75), the high-energy sedimentary high-permeability band has a good correspondence with the high-permeability part of the core permeability, while the karst high-permeability band has a poor correlation with the core permeability. For details, see Fig.16a As shown in 68;

[0283] Among them, the production logging data and dynamic permeability data were used to verify the identification results of high permeability zones in marine carbonate bioclastic limestone reservoirs, including: Fig.16a 75) with high K_PBU (>100mD) ( Fig.16a 71) and PLT high yield ( Fig.16a 70) in has a good corresponding relationship, such as Figure 16a-Figure 16c As shown; Based on the comparative analysis of 60 PLT test wells and 24 PBU test wells, the dynamic coincidence rate of HPS identification results is about 89%;

[0284] Among them, the water-bearing layers of the water-bearing wells in the injection-production well group and the development of high-permeability belts in the water-bearing layers are used to verify the identification results of high-permeability belts in marine carbonate bioclastic limestone reservoirs, including: high-permeability belts form dominant water injection channels, which are usually the first to achieve water injection breakthrough in the injection-production well group, thus causing the main reason for the injection of water in the production wells. Figure 17a-Figure 17c This is a schematic diagram of water well analysis for the PROD1 water injection well group in a specific embodiment, wherein: Fig.17a Figure 79 is the well location distribution map of the injection and production well group; Fig.17b This is a comparison chart of two water injection wells (INJ1, INJ2) and one oil production well (PROD1). Fig.17b Figures 80-81 are respectively the conventional three-porosity curve, natural gamma curve and resistivity curve, 82 is the oil and water production profile of PLT test, 83 is the water injection well water absorption profile, 84 is the sedimentary microfacies profile, and 85 is the HPS identification result; Fig.17c for Fig.17b 84 Sedimentary Microfacies Legend; Figure 17a-Figure 17c It can be seen that there are two water injection wells around the production well PROD1, and the water injection layers include MB1-2A to MB1-2C. The current water-seeping layer is located in the upper part of MB1-2B. This layer and the water injection well INJ1 develop tidal channel-type high permeability belts at the same time, which are interconnected to form a dominant seepage channel, resulting in the earliest water seepage. Currently, the production wells that have seen water injection involve 16 wells in 9 well groups, and the proportion of water injection wells related to high permeability belts has reached 85%. On the one hand, it shows that the current water seepage in the injection-production well group is mainly related to the high permeability belt. On the other hand, it shows that the compliance rate of the injection-production relationship of the high permeability belt identified this time is as high as more than 85%, which is basically consistent with the results of PLT and PBU test verification.

[0285] Based on the same inventive concept, an embodiment of the present invention also provides a device for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs. Since the principle of solving the problem by the device is similar to the method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. The device described in the following embodiments is preferably implemented in hardware, but the implementation of software or a combination of software and hardware is also possible and conceived.

[0286] Fig.18 A schematic diagram of the structure of a device for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs provided by an embodiment of the present invention, Fig.18 As can be seen, the device comprises:

[0287] The reservoir dynamic parameter determination module 101 is used to determine the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit according to the well test data and production logging data;

[0288] The high permeability band extraction module 102 is used to analyze the interlayer interference of multi-layer commingled production according to the production logging data, comprehensively utilize the single-layer production and the single-layer dynamic permeability and single-layer specific production liquid index of the single-well flow unit in the production logging data to establish the high permeability band dynamic standard and extract the single-well high permeability band;

[0289] The high permeability zone genetic type classification module 103 is used to classify the high permeability reservoir genetic type according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase in the coring well, and determine the distribution law of the high permeability zone in the rock phase, sedimentary phase and sequence interface;

[0290] The high permeability band logging identification module 104 is used to establish a high permeability band logging identification mode, and identify high permeability bands well by well in the entire reservoir according to the high permeability band logging identification mode to achieve full reservoir logging interpretation.

[0291] In one embodiment, the well testing data is PBU data, and the production logging data is PLT test data.

[0292] In one embodiment, the reservoir dynamic parameter determination module includes a single-layer specific liquid production index determination unit, which is used to determine the single-layer specific liquid production index according to the well test data and production logging data according to the following formula (1):

[0293]

[0294] In formula (1), SPI is the specific liquid index, unit is bbl / (d·psi·m); q o is the daily liquid production, in bbl / d; ΔP is the bottom hole pressure difference, in psi; h is the thickness of the liquid producing layer, in m.

[0295] In one embodiment, the reservoir dynamic parameter determination module further includes a single-layer dynamic permeability determination unit. For a single-layer well test, when the well test data is PBU data, the single-layer dynamic permeability determination unit is used to determine the single-layer dynamic permeability of the single-well flow unit according to the PBU data, including:

[0296] 1) Determine the formation coefficient of the single well according to the following formula (2) based on the PBU data interpretation;

[0297]

[0298] In formula (2), kh is the formation coefficient of the single well interpreted by PBU data, in mD·m; q is the PBU test production, in m 3 / ks; μ is the fluid viscosity, in mPa·s; m is the slope of the Horner curve used in PBU data interpretation, dimensionless; h is the flow unit thickness, in m; k is the single-layer dynamic permeability of a single well flow unit, in mD;

[0299] 2) Determine the thickness of the flow unit on the well logging curve, and then divide the formation coefficient of the single well by the thickness of the flow unit to obtain the single-layer dynamic permeability of the flow unit of the single well;

[0300] In the case of combined well testing, when the well testing data is PBU data and the production logging data is PLT test data, the single-layer dynamic permeability determination unit is used to determine the single-layer dynamic permeability of the single-well flow unit according to the PBU data and the PLT test data, including:

[0301] 1) Determine the comprehensive formation coefficient of the single well according to the above formula (2) based on the PBU data interpretation;

[0302] 2) using the layered liquid production in the PLT test data, the comprehensive formation coefficient of the single well is batched into each flow unit according to the following formula (3) to formula (5), so as to obtain the single-layer formation coefficient of each flow unit;

[0303] q t =q1+q2+q3+…+q l Formula (3);

[0304]

[0305] (kh) l =(kh)×ration l Formula (5);

[0306] Formula (3)-In formula (5), q t It is the cumulative liquid production in the PLT test data, in bbl / d; q1, q2, q3, ... q l They are the actual liquid production of different production sections in the PLT test data, both in bbl / d; l is the ratio of the actual liquid production of different liquid production sections in the PLT test data to the cumulative liquid production in the PLT test data, and the unit is dimensionless; kh is the formation coefficient interpreted by PBU data, that is, the comprehensive formation coefficient of the single well, and the unit is mD·m; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m;

[0307] 3) Then, the single-layer dynamic permeability of each flow unit in the single well is determined according to the single-layer formation coefficient of each flow unit and the thickness of each flow unit according to the following formula (6);

[0308]

[0309] In formula (6), k l is the single layer dynamic permeability of the flow unit, in mD; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m; h l is the actual thickness of the liquid-producing section of the flow unit in the PLT test data, in m; l is the number of actual liquid-producing sections in the PLT test data, a positive integer.

[0310] In one embodiment, the reservoir dynamic parameter determination module further includes a flow unit thickness determination unit, which is used to determine the thickness of the flow unit, including:

[0311] Inside the flow unit shown in the PLT test data, the internal partitions and interlayers of the unit are deducted using the logging curve; the thickness of the flow unit is then corrected to the vertical depth through well trajectory calculation, thus obtaining the thickness of the flow unit.

[0312] In one embodiment, the hypertonic band extraction module is specifically used for:

[0313] A scatter plot of single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit was established to analyze the production capacity of the flow unit, that is, the changing trend of the specific liquid production index with dynamic permeability and determine the inflection point. The dynamic permeability and liquid production index corresponding to the inflection point were determined as the dynamic identification criteria for high permeability zones in marine carbonate bioclastic limestone reservoirs.

[0314] In one embodiment, the hypertonic band extraction module further includes a single well hypertonic band extraction unit, and the single well hypertonic band extraction unit is used to extract the hypertonic bands in layers in the single well according to the dynamic identification standard, specifically for:

[0315] On the basis of deducting the internal partitions and interlayers of the flow unit, the dynamic permeability and liquid production index rectangular curves are drawn respectively using the single-layer dynamic permeability and liquid production index data of the single-well flow unit determined by segmentation, and the single-layer dynamic permeability and liquid production index in the high permeability strip dynamic standard are set as the baseline of the rectangular curve and filled to the right of the rectangular curve. When the dynamic permeability and liquid production index of the single layer are greater than the dynamic permeability and liquid production index corresponding to the baseline of the rectangular curve, the single layer is determined to be a high permeability strip.

[0316] In one embodiment, the hypertonic band genesis type classification module is specifically used to:

[0317] The high permeability reservoir or the single well high permeability belt data divided by the rock physical phase of the core well is used to analyze the rock phase and sedimentary phase type of the high permeability reservoir or the high permeability belt by using the scatter cross plot or frequency histogram method; at the same time, the position of the high permeability belt in the sedimentary phase and stratigraphic sequence is analyzed in combination with the results of sedimentary microfacies and sequence stratigraphic division.

[0318] In one embodiment, the high permeability band logging identification module is specifically used for:

[0319] Taking the single-well production logging test section as the sample and the single-layer dynamic permeability and single-layer specific liquid production index corresponding to the dynamic standard of the high-permeability zone as the boundary, the logging response characteristics of the high-permeability zone and the non-high-permeability zone are analyzed, and the qualitative identification mode of the high-permeability zone logging phase and the conventional logging quantitative identification mode of the sedimentary high-permeability zone are established.

[0320] In one embodiment, the high permeability band logging identification module includes a high permeability band logging phase qualitative identification mode establishment unit, and the high permeability band logging phase qualitative identification mode establishment unit is used to:

[0321] The differences between high-permeability bands and non-high-permeability bands in conventional logging curves, FMI imaging logging diagrams, and nuclear magnetic resonance logging T2 spectra were analyzed. Based on the analysis results, qualitative identification modes of high-permeability band logging phases were established in sedimentary reservoirs and karst reservoirs, respectively.

[0322] In one embodiment, the high permeability band logging identification module further includes a sedimentary high permeability band conventional logging quantitative identification mode establishment unit, and the sedimentary high permeability band conventional logging quantitative identification mode establishment unit is used to:

[0323] In the production logging test section, according to the principle of dominant seepage channels, obvious non-permeable interlayers and low permeability reservoirs are deducted, and the curve values ​​of the logging curves are obtained in sections according to the conventional logging curve sampling intervals. Then, a dual logging curve classification scatter intersection diagram is made according to the dynamic permeability distribution interval. The distribution law and identification boundary of the logging curve values ​​of the high permeability strips are analyzed in combination with geological laws, and a conventional logging quantitative identification mode for sedimentary high permeability strips is established accordingly.

[0324] In one embodiment, the high permeability zone logging identification module further includes a curve value calculation unit for a pore structure index curve, and the curve value calculation unit for the pore structure index curve is used to:

[0325] When the logging curve includes a pore structure index curve, the curve value of the pore structure index curve is calculated according to the following formula (7):

[0326]

[0327] In formula (7), R w is the formation water resistivity, in ohm·m; R t is the original formation resistivity, and the resistivity corresponding to the deep detection resistivity curve on the logging curve is in ohm·m; POR is the reservoir porosity, in dimensionless decimal; S w is the formation water saturation, and its unit is a dimensionless decimal; n is the saturation index, and its unit is a dimensionless decimal.

[0328] In one embodiment, the device (eg Fig.19 The method also includes: an identification result verification module 105, which is used to verify the identification result of the high permeability zone of the marine carbonate bioclastic limestone reservoir by using the core test results, production logging data and dynamic permeability data, as well as the water-bearing layers of the water-bearing wells in the injection and production well group and the development of high permeability zones in the water-bearing layers.

[0329] An embodiment of the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs when executing the computer program.

[0330] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs described above are implemented.

[0331] In summary, the embodiments of the present invention take dynamics as the guideline and provide a dynamic and static integrated high-permeability band identification method and device for marine carbonate bioclastic limestone reservoirs under the constraints of geological laws. The theoretical basis and technical logic of the method and device provided by the embodiments of the present invention are solid and reliable, and the method is simple and easy to operate; the identification objects of the method and device provided by the embodiments of the present invention include thief layers but are not limited to thief layers, which effectively solves the problem of identifying high-energy sedimentary high-permeability bands in marine carbonate bioclastic limestone reservoirs that have the greatest impact on water injection development; after the method and device provided by the embodiments of the present invention are promoted and applied in oil fields, a set of reliable high-permeability band data that effectively covers the entire reservoir can be provided, which verifies that the current early water-seeking wells in the injection-production well group are related to the high-permeability bands identified by the method and device of the present invention, and can provide technical support for the optimal design of new injection-production well groups.

[0332] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0333] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0334] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0335] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0336] The above is only a specific embodiment of the present invention, and cannot be used to limit the scope of the invention. Therefore, the replacement of equivalent components, or equivalent changes and modifications made according to the protection scope of the patent of the present invention, should still fall within the scope of this patent. In addition, the technical features of the present invention can be freely combined with each other, with each other and with each other, and with each other.

Claims

1. A method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs, wherein: The method comprises: Determine the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit based on well test data and production logging data; Analyze the interlayer interference of multi-layer commingled production according to production logging data, comprehensively utilize the single-layer production and the single-layer dynamic permeability and single-layer specific production liquid index of the single-well flow unit in the production logging data to establish the dynamic standard of the high-permeability band and extract the single-well high-permeability band; In the coring well, the high permeability reservoir genesis type is classified according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, and the distribution law of the high permeability band in the rock phase, sedimentary phase and sequence interface is determined; Establishing a high permeability band logging identification mode, identifying high permeability bands well by well in the entire reservoir according to the high permeability band logging identification mode, and realizing logging interpretation of the entire reservoir; Wherein, the well test data is PBU data, and the production logging data is PLT test data; The single-layer specific production liquid index is determined according to the following formula (1) based on the well test data and production logging data: In formula (1), SPI is the specific liquid index, unit is bbl / (d·psi·m); q o is the daily liquid production, in bbl / d; ΔP is the bottom hole pressure difference, in psi; h is the thickness of the liquid producing layer, in m; Wherein, for the case of a single-layer well test, when the well test data is PBU data, determining the single-layer dynamic permeability of the single-well flow unit according to the PBU data includes: 1) Determine the formation coefficient of the single well according to the following formula (2) based on the PBU data interpretation; In formula (2), kh is the formation coefficient of the single well interpreted by PBU data, in mD·m; q is the PBU test production, in m 3 / ks; μ is the fluid viscosity, in mPa·s; m is the slope of the Horner curve used in PBU data interpretation, dimensionless; h is the flow unit thickness, in m; k is the single-layer dynamic permeability of a single well flow unit, in mD; 2) Determine the thickness of the flow unit on the well logging curve, and then divide the formation coefficient of the single well by the thickness of the flow unit to obtain the single-layer dynamic permeability of the flow unit of the single well; In the case of combined layer well testing, when the well testing data is PBU data and the production logging data is PLT test data, the single layer dynamic permeability of the single well flow unit is determined based on the PBU data and the PLT test data, including: 1) Determine the comprehensive formation coefficient of the single well according to the above formula (2) based on the PBU data interpretation; 2) using the layered liquid production in the PLT test data, the comprehensive formation coefficient of the single well is batched into each flow unit according to the following formula (3) to formula (5), so as to obtain the single-layer formation coefficient of each flow unit; q t = q1 + q2 + q3 + ... + q l Formula (3): (kh) l =(kh)×ration l Formula (5); Formula (3)-In formula (5), q t is the cumulative liquid production in the PLT test data, in bbl / d; q1, q2, q3, ... q l They are the actual liquid production of different production sections in the PLT test data, both in bbl / d; l is the ratio of the actual liquid production of different liquid production sections in the PLT test data to the cumulative liquid production in the PLT test data, and the unit is dimensionless; kh is the formation coefficient interpreted by PBU data, that is, the comprehensive formation coefficient of the single well, and the unit is mD·m; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m; 3) Then, the single-layer dynamic permeability of each flow unit in the single well is determined according to the single-layer formation coefficient of each flow unit and the thickness of each flow unit according to the following formula (6); In formula (6), k l is the single layer dynamic permeability of the flow unit, in mD; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m; h l is the actual thickness of the liquid-producing section of the flow unit in the PLT test data, in m; l is the number of actual liquid-producing sections in the PLT test data, a positive integer; Wherein, determining the thickness of the flow unit comprises: Inside the flow unit shown in the PLT test data, the internal partitions and interlayers of the unit are deducted using the well logging curve; the thickness of the flow unit is then corrected to the vertical depth through well trajectory calculation, that is, the thickness of the flow unit is obtained; Among them, the dynamic standard of high permeability zone is established by comprehensively utilizing the single-layer production in production logging data, the single-layer dynamic permeability of the single-well flow unit and the single-layer specific liquid production index, including: Establish a scatter plot of the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit, analyze the flow unit production capacity, that is, the change trend of the specific liquid production index with the dynamic permeability and determine the inflection point, and determine the dynamic permeability and liquid production index corresponding to the inflection point as the dynamic identification standard of the high permeability zone of marine carbonate bioclastic limestone reservoir; Wherein, extracting the single well hypertonic band comprises: extracting the hypertonic band in layers in the single well according to the dynamic identification standard, specifically comprising: On the basis of deducting the internal partitions and interlayers of the flow unit, the dynamic permeability and liquid production index rectangular curves are drawn respectively using the single-layer dynamic permeability and liquid production index data of the single-well flow unit determined by segmentation, and the single-layer dynamic permeability and liquid production index in the high permeability strip dynamic standard are set as the baseline of the rectangular curve and filled to the right of the rectangular curve. When the dynamic permeability and liquid production index of the single layer are greater than the dynamic permeability and liquid production index corresponding to the baseline of the rectangular curve, the single layer is determined to be a high permeability strip.

2. The method according to claim 1, wherein: Based on the research results of sequence stratigraphy, lithofacies, sedimentary facies and rock physical facies, the genetic types of high permeability reservoirs are divided, and the distribution patterns of the high permeability zones in lithofacies, sedimentary facies and sequence interfaces are determined, including: The high permeability reservoir or the single well high permeability belt data divided by the rock physical phase of the core well is used to analyze the rock phase and sedimentary phase type of the high permeability reservoir or the high permeability belt by using the scatter cross plot or frequency histogram method; at the same time, the position of the high permeability belt in the sedimentary phase and stratigraphic sequence is analyzed in combination with the results of sedimentary microfacies and sequence stratigraphic division.

3. The method according to claim 1, wherein: The method of establishing a high permeability zone logging identification mode comprises: Taking the single-well production logging test section as the sample and the single-layer dynamic permeability and single-layer specific liquid production index corresponding to the dynamic standard of the high-permeability zone as the boundary, the logging response characteristics of the high-permeability zone and the non-high-permeability zone are analyzed, and the qualitative identification mode of the high-permeability zone logging phase and the conventional logging quantitative identification mode of the sedimentary high-permeability zone are established.

4. The method according to claim 3, wherein: The method of establishing a high permeability zone logging phase qualitative identification mode comprises: The differences between high-permeability bands and non-high-permeability bands in conventional logging curves, FMI imaging logging diagrams, and nuclear magnetic resonance logging T2 spectra were analyzed. Based on the analysis results, qualitative identification modes of high-permeability band logging phases were established in sedimentary reservoirs and karst reservoirs, respectively.

5. The method according to claim 3, wherein: Establish a conventional logging quantitative identification model for sedimentary high permeability zones, including: In the production logging test section, according to the principle of dominant seepage channels, obvious non-permeable interlayers and low permeability reservoirs are deducted, and the curve values ​​of the logging curves are obtained in sections according to the conventional logging curve sampling intervals. Then, a dual logging curve classification scatter intersection diagram is made according to the dynamic permeability distribution interval. The distribution law and identification boundary of the logging curve values ​​of the high permeability strips are analyzed in combination with geological laws, and a conventional logging quantitative identification mode for sedimentary high permeability strips is established accordingly.

6. The method according to claim 5, wherein: When the logging curve includes a pore structure index curve, the curve value of the pore structure index curve is calculated according to the following formula (7): In formula (7), R w is the formation water resistivity, in ohm·m; R t is the original formation resistivity, and the resistivity corresponding to the deep detection resistivity curve on the logging curve is in ohm·m; POR is the reservoir porosity, in dimensionless decimal; S w is the formation water saturation, and its unit is a dimensionless decimal; n is the saturation index, and its unit is a dimensionless decimal.

7. The method according to any one of claims 1 to 6, wherein: The method also includes: using core test results of coring wells, production logging data and dynamic permeability data, as well as the water-bearing layers of water-bearing wells in the injection-production well group and the development of high-permeability zones in the water-bearing layers to verify the high-permeability zone identification results of marine carbonate bioclastic limestone reservoirs.

8. A device for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs, wherein: The device comprises: A reservoir dynamic parameter determination module is used to determine the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit based on well test data and production logging data; A high permeability band extraction module is used to analyze the interlayer interference of multi-layer commingled production according to production logging data, comprehensively utilize the single-layer production and the single-layer dynamic permeability and single-layer specific production liquid index of the single-well flow unit in the production logging data to establish a high permeability band dynamic standard and extract the single-well high permeability band; The high permeability zone genetic type classification module is used to classify the high permeability reservoir genetic type in the coring well according to the research results of sequence stratigraphy, rock phase, sedimentary phase and rock physical phase, and determine the distribution law of the high permeability zone in the rock phase, sedimentary phase and sequence interface; A high permeability band logging identification module is used to establish a high permeability band logging identification mode, and identify high permeability bands well by well in the entire reservoir according to the high permeability band logging identification mode to achieve full reservoir logging interpretation; Wherein, the well test data is PBU data, and the production logging data is PLT test data; The reservoir dynamic parameter determination module includes a single-layer specific liquid production index determination unit, which is used to determine the single-layer specific liquid production index according to the well test data and production logging data according to the following formula (1): In formula (1), SPI is the specific liquid index, unit is bbl / (d·psi·m); q o is the daily liquid production, in bbl / d; ΔP is the bottom hole pressure difference, in psi; h is the thickness of the liquid producing layer, in m; The reservoir dynamic parameter determination module further includes a single-layer dynamic permeability determination unit. For a single-layer well test, when the well test data is PBU data, the single-layer dynamic permeability determination unit is used to determine the single-layer dynamic permeability of the single-well flow unit according to the PBU data, including: 1) Determine the formation coefficient of the single well according to the following formula (2) based on the PBU data interpretation; In formula (2), kh is the formation coefficient of the single well interpreted by PBU data, in mD·m; q is the PBU test production, in m 3 / ks; μ is the fluid viscosity, in mPa·s; m is the slope of the Horner curve used in PBU data interpretation, dimensionless; h is the flow unit thickness, in m; k is the single-layer dynamic permeability of a single well flow unit, in mD; 2) Determine the thickness of the flow unit on the well logging curve, and then divide the formation coefficient of the single well by the thickness of the flow unit to obtain the single-layer dynamic permeability of the flow unit of the single well; In the case of combined well testing, when the well testing data is PBU data and the production logging data is PLT test data, the single-layer dynamic permeability determination unit is used to determine the single-layer dynamic permeability of the single-well flow unit according to the PBU data and the PLT test data, including: 1) Determine the comprehensive formation coefficient of the single well according to the above formula (2) based on the PBU data interpretation; 2) using the layered liquid production in the PLT test data, the comprehensive formation coefficient of the single well is batched into each flow unit according to the following formula (3) to formula (5), so as to obtain the single-layer formation coefficient of each flow unit; q t = q1 + q2 + q3 + ... + q l Formula (3): (kh) l =(kh)×ration l Formula (5); Formula (3)-In formula (5), q t is the cumulative liquid production in the PLT test data, in bbl / d; q1, q2, q3, ... q l They are the actual liquid production of different production sections in the PLT test data, both in bbl / d; l is the ratio of the actual liquid production of different liquid production sections in the PLT test data to the cumulative liquid production in the PLT test data, and the unit is dimensionless; kh is the formation coefficient interpreted by PBU data, that is, the comprehensive formation coefficient of the single well, and the unit is mD·m; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m; 3) Then, the single-layer dynamic permeability of each flow unit in the single well is determined according to the single-layer formation coefficient of each flow unit and the thickness of each flow unit according to the following formula (6); In formula (6), k l is the single layer dynamic permeability of the flow unit, in mD; (kh) l is the single-layer formation coefficient of each flow unit, in mD·m; h l is the actual thickness of the liquid-producing section of the flow unit in the PLT test data, in m; l is the number of actual liquid-producing sections in the PLT test data, a positive integer; The reservoir dynamic parameter determination module further includes a flow unit thickness determination unit, which is used to determine the thickness of the flow unit, including: Inside the flow unit shown in the PLT test data, the internal partitions and interlayers of the unit are deducted using the well logging curve; the thickness of the flow unit is then corrected to the vertical depth through well trajectory calculation, that is, the thickness of the flow unit is obtained; Wherein, the hypertonic band extraction module is specifically used for: Establish a scatter plot of the single-layer dynamic permeability and single-layer specific liquid production index of a single well flow unit, analyze the flow unit production capacity, that is, the change trend of the specific liquid production index with the dynamic permeability and determine the inflection point, and determine the dynamic permeability and liquid production index corresponding to the inflection point as the dynamic identification standard of the high permeability zone of marine carbonate bioclastic limestone reservoir; Wherein, the hypertonic band extraction module further includes a single well hypertonic band extraction unit, and the single well hypertonic band extraction unit is used to extract the hypertonic bands in layers in the single well according to the dynamic identification standard, specifically for: On the basis of deducting the internal partitions and interlayers of the flow unit, the dynamic permeability and liquid production index rectangular curves are drawn respectively using the single-layer dynamic permeability and liquid production index data of the single-well flow unit determined by segmentation, and the single-layer dynamic permeability and liquid production index in the high permeability strip dynamic standard are set as the baseline of the rectangular curve and filled to the right of the rectangular curve. When the dynamic permeability and liquid production index of the single layer are greater than the dynamic permeability and liquid production index corresponding to the baseline of the rectangular curve, the single layer is determined to be a high permeability strip.

9. The device according to claim 8, wherein: The hypertonic zone genesis type classification module is specifically used for: The high permeability reservoir or the single well high permeability belt data divided by the rock physical phase of the core well is used to analyze the rock phase and sedimentary phase type of the high permeability reservoir or the high permeability belt by using the scatter cross plot or frequency histogram method; at the same time, the position of the high permeability belt in the sedimentary phase and stratigraphic sequence is analyzed in combination with the results of sedimentary microfacies and sequence stratigraphic division.

10. The device according to claim 8, wherein: The high permeability band logging identification module is specifically used for: Taking the single-well production logging test section as the sample and the single-layer dynamic permeability and single-layer specific liquid production index corresponding to the dynamic standard of the high-permeability zone as the boundary, the logging response characteristics of the high-permeability zone and the non-high-permeability zone are analyzed, and the qualitative identification mode of the high-permeability zone logging phase and the conventional logging quantitative identification mode of the sedimentary high-permeability zone are established.

11. The device according to claim 10, wherein: The high permeability band logging identification module includes a high permeability band logging phase qualitative identification mode establishment unit, and the high permeability band logging phase qualitative identification mode establishment unit is used to: The differences between high-permeability bands and non-high-permeability bands in conventional logging curves, FMI imaging logging diagrams, and nuclear magnetic resonance logging T2 spectra were analyzed. Based on the analysis results, qualitative identification modes of high-permeability band logging phases were established in sedimentary reservoirs and karst reservoirs, respectively.

12. The device according to claim 10, wherein: The high permeability band logging identification module further includes a sedimentary high permeability band conventional logging quantitative identification mode establishment unit, and the sedimentary high permeability band conventional logging quantitative identification mode establishment unit is used to: In the production logging test section, according to the principle of dominant seepage channels, obvious non-permeable interlayers and low permeability reservoirs are deducted, and the curve values ​​of the logging curves are obtained in sections according to the conventional logging curve sampling intervals. Then, a dual logging curve classification scatter intersection diagram is made according to the dynamic permeability distribution interval. The distribution law and identification boundary of the logging curve values ​​of the high permeability strips are analyzed in combination with geological laws, and a conventional logging quantitative identification mode for sedimentary high permeability strips is established accordingly.

13. The device according to claim 12, wherein: The high permeability zone logging identification module further includes a curve value calculation unit for a pore structure index curve, and the curve value calculation unit for the pore structure index curve is used to: When the logging curve includes a pore structure index curve, the curve value of the pore structure index curve is calculated according to the following formula (7): In formula (7), R w is the formation water resistivity, in ohm·m; R t is the original formation resistivity, and the resistivity corresponding to the deep detection resistivity curve on the logging curve is in ohm·m; POR is the reservoir porosity, in dimensionless decimal; S w is the formation water saturation, and its unit is a dimensionless decimal; n is the saturation index, and its unit is a dimensionless decimal.

14. The device according to any one of claims 8 to 13, wherein: The device also includes: an identification result verification module, which is used to verify the identification result of the high permeability zone of the marine carbonate bioclastic limestone reservoir by using core test results, production logging data and dynamic permeability data, as well as the water-bearing layers of the water-bearing wells in the injection and production well group and the development of high permeability zones in the water-bearing layers.

15. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs according to any one of claims 1 to 7 are implemented.

16. A computer-readable storage medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the steps of the method for identifying high permeability zones in marine carbonate bioclastic limestone reservoirs according to any one of claims 1 to 7 are implemented.

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