Method, device, equipment and medium for predicting lower limit of porosity depth of sandstone reservoir

Abstract

The invention relates to a sandstone reservoir porosity depth lower limit prediction method, device, equipment and medium, and relates to the field of oil and gas exploration and development, and the method comprises the steps: determining the tectonic uplift denudation amount of a main reservoir forming period of oil and gas reservoir forming in a target research area; obtaining the lower limit of the porosity depth of the sandstone reservoir by utilizing the constructed uplift denudation amount and by means of a coupling model of uplift denudation amount x-sandstone porosity critical burial depth y; wherein the coupling model of the uplift denudation amount x-sandstone porosity critical burial depth y is as follows: y = ax < 2 > + bx + c, in the formula, a is a denudation cumulative effect strength coefficient, b is a denudation dominant pore reduction effect coefficient, and c is a constant term. According to the prediction method provided by the invention, the specific main reservoir forming period is selected in the research area, and the coupling model of the denudation amount x-sandstone porosity critical burial depth y is combined, so that the critical depth corresponding to the economic exploitation lower limit of which the porosity is greater than or equal to 8% can be accurately determined, and efficient and accurate prediction of the reservoir porosity physical property depth lower limit is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of oil and gas exploration and development, in particular to a method, device, equipment and medium for predicting the lower limit of porosity depth of a sandstone reservoir, and more particularly to a method, device, equipment and medium for predicting the lower limit of physical property depth of a sandstone reservoir with a porosity of 8%. BACKGROUND

[0002] Currently, the cut-off value of reservoir properties refers to the minimum physical property standard in an oil and gas reservoir that can achieve industrial oil and gas flow, which is usually characterized by the threshold values of key parameters such as porosity, permeability and oil saturation.

[0003] In the field of oil and gas exploration and development, accurately determining the cut-off value of reservoir properties has three core significances: from an economic perspective, the cut-off value of reservoir properties directly determines the recoverability and development economy of the reservoir; from a geological evaluation perspective, the cut-off value of reservoir properties is a scientific boundary for dividing effective reservoirs and non-reservoirs, and directly affects the accuracy of reserve calculation; from the perspective of exploration and development practice, the prediction of the cut-off value of reservoir properties provides a key basis for the optimization of drilling target areas, the development of development plans and the design of stimulation measures.

[0004] The prediction technology of the cut-off value of reservoir properties has undergone an evolution process from experience analogy to quantitative prediction. The traditional method mainly relies on core experiments and logging interpretation, and determines the lower limit value through static methods such as porosity-permeability crossplot and oil occurrence method. This method is simple to operate but has obvious limitations: core analysis is costly and the sampling is not representative; logging interpretation is significantly affected by the wellbore environment; and empirical formula is difficult to extrapolate to new areas.

[0005] With the development of geophysical technology and artificial intelligence, the prediction of the cut-off value of reservoir properties has entered the stage of dynamic, three-dimensional and intelligent. Seismic inversion and attribute analysis realize the spatial prediction of reservoir parameters, but are limited by resolution, deep-ultra-deep density, and the prediction results have multiple solutions. Machine learning algorithms establish nonlinear prediction models, which require large data support, high algorithm complexity, and are still in the stage of "auxiliary tools". In complex scenes such as strong heterogeneity and multi-stage structure, the algorithm results still need to be calibrated and reinterpreted.

[0006] Currently, porosity is one of the key parameters for evaluating reservoir properties. Existing methods (such as porosity-depth trend line method and diagenetic numerical simulation) can only predict the porosity value at a specific depth, and cannot accurately determine the critical depth corresponding to the economic exploitation lower limit of porosity ≥ 8% (i.e. the depth threshold at which the reservoir property changes from "effective reservoir" to "non-economic reservoir").

[0007] The conventional model does not involve the denudation amount as an independent variable in inversion, and ignores the control effect of the denudation amount on the critical depth, and the error of the conventional inversion method (such as the method based on seismic attributes or logging statistics) is often more than ±10% in the strong denudation reconstruction area, which leads to a deviation of more than 200m in the prediction of the critical depth, and cannot meet the requirement of target area optimization in exploration and development.

[0008] In conclusion, the prediction of the lower limit of the porosity depth of the sandstone reservoir still has the defects of poor prediction accuracy and is not conducive to the exploration and development of the oil reservoir. SUMMARY

[0009] In view of the problems in the prior art, the purpose of the present application is to provide a prediction method, device, equipment and medium for the lower limit of the porosity depth of a sandstone reservoir, so as to solve the defects of the prediction of the lower limit of the porosity depth of the sandstone reservoir, such as poor prediction accuracy and being not conducive to the exploration and development of the oil reservoir.

[0010] To achieve this purpose, the present application adopts the following technical solutions:

[0011] In a first aspect, the present application provides a prediction method for the lower limit of the porosity depth of a sandstone reservoir, which comprises:

[0012] determining the main accumulation period of oil and gas accumulation in the target research area;

[0013] obtaining the tectonic uplift denudation amount of the main accumulation period;

[0014] obtaining the lower limit of the porosity depth of the sandstone reservoir by using the tectonic uplift denudation amount and the coupling model of the uplift denudation amount x-the critical burial depth of sandstone porosity y;

[0015] wherein the coupling model of the uplift denudation amount x-the critical burial depth of sandstone porosity y is as follows: y=ax 2 +bx+c, wherein a is the cumulative effect intensity coefficient of denudation, b is the dominant porosity reduction effect coefficient of denudation, and c is a constant term.

[0016] The prediction method provided by the present application can accurately determine the critical depth corresponding to the economic exploitation lower limit of porosity ≥8% by selecting a specific main accumulation period in the research area and combining the coupling model of the uplift denudation amount x-the critical burial depth of sandstone porosity y, and realizes efficient and accurate prediction of the lower limit of the porosity depth of the sandstone reservoir.

[0017] As a preferred technical solution of the present application, the determination of the main accumulation period of oil and gas accumulation in the target research area comprises: cross-verification analysis of the source rock hydrocarbon generation and expulsion history, trap formation period and oil and gas charging age of the research area to obtain the main accumulation period of oil and gas accumulation.

[0018] As a preferred technical scheme of the present application, the obtaining of the hydrocarbon source rock generation and expulsion history comprises: performing basin inversion thermal evolution history to realize vitrinite reflectance Ro simulation.

[0019] As a preferred technical scheme of the present application, the obtaining method of the trap formation period comprises: one or a combination of at least two of growth fault analysis, stratum back-stripping technology or fission track thermal history inversion.

[0020] As a preferred technical scheme of the present application, the oil and gas charging age is obtained by means of reservoir oil and gas inclusion homogenization temperature.

[0021] As a preferred technical scheme of the present application, the cross-validation analysis comprises: data verification analysis, time sequence coupling quantification and reservoir forming intensity analysis.

[0022] Preferably, the data verification analysis comprises: time window overlap verification or non-overlapping contradictory data analysis.

[0023] Preferably, the judgment of the cross-validation analysis comprises: meeting I-level criteria, II-level criteria or III-level criteria.

[0024] Preferably, the I-level criteria comprise: simultaneously meeting the following two: three-element time window overlap and high-intensity reservoir forming, which is inclusion abundance > 15 / section and gas-bearing oil saturation > 60%.

[0025] Preferably, the II-level criteria comprise: meeting (1) only two-element overlap + high-intensity reservoir forming evidence or (2) three-element overlap but medium-intensity reservoir forming, which is oil-bearing saturation 40-50%.

[0026] Preferably, the III-level criteria comprise: meeting no time window overlap and low-intensity reservoir forming, which is inclusion abundance < 5 / section.

[0027] As a preferred technical scheme of the present application, the manner of recovering the tectonic uplift denudation amount of the main reservoir forming period in the research area comprises: one or a combination of at least two of stratum trend extrapolation method, vitrinite reflectance Ro method, apatite fission track AFT method or acoustic wave time difference Delta logt method.

[0028] In a second aspect, the present application provides a device for predicting the lower limit of sandstone reservoir porosity depth, which comprises:

[0029] A main reservoir forming period obtaining module is configured to determine the main reservoir forming period of oil and gas reservoir forming in a target research area.

[0030] A denudation amount obtaining module is configured to obtain the tectonic uplift denudation amount of the main reservoir forming period.

[0031] A prediction module is configured to obtain a lower limit of sandstone reservoir porosity depth by using a coupling model of structural uplift denudation amount and a critical buried depth y of sandstone porosity under the condition of the coupling of the structural uplift denudation amount x and the critical buried depth y of sandstone porosity.

[0032] The coupling model of the structural uplift denudation amount x and the critical buried depth y of sandstone porosity is as follows: y=ax 2 +bx+c, wherein a is a denudation cumulative effect intensity coefficient, b is a denudation dominant porosity reduction effect coefficient, and c is a constant term.

[0033] In a third aspect, the present application provides an electronic device, which comprises:

[0034] at least one processor; and a memory connected to the at least one processor in communication;

[0035] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the prediction method of the lower limit of sandstone reservoir porosity depth.

[0036] In a fourth aspect, the present application provides a computer storage medium, which stores computer executable instructions, and the computer executable instructions are executed by a processor to implement the prediction method of the lower limit of sandstone reservoir porosity depth.

[0037] Compared with the prior art, the present application has the following beneficial effects:

[0038] (1) The prediction method provided by the present application quantifies the control effect of multi-episode uplift denudation amount on the lower limit of reservoir porosity, overcomes the prediction deficiency of the conventional static model, and realizes efficient prediction of the lower limit of sandstone reservoir porosity physical depth.

[0039] (2) The model innovatively constructs a quantitative mapping relationship between the structural uplift-denudation history and the lower limit of reservoir porosity preservation depth, and through analysis of the dual-path coupling mechanism of the denudation cumulative effect (ax 2 ) and the denudation dominant porosity reduction effect (bx), the dynamic structural process is converted into a key indicator for predicting the critical depth of porosity physical properties, thereby providing a scientific decision-making tool for economic evaluation and quantitative prediction of exploration risks of deep-ultra-deep oil and gas reservoirs. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 is a flowchart of the prediction method of the lower limit of sandstone reservoir porosity depth provided by the present application;

[0041] Figure 2 is a schematic diagram of the prediction device of the lower limit of sandstone reservoir porosity depth provided by the present application;

[0042] Figure 3 is a schematic diagram of an electronic device provided by an embodiment of the present application;

[0043] Figure 4 is a structural uplift denudation amount plane distribution diagram of a main reservoir forming period in Embodiment 1 of the present application;

[0044] Figure 5 is a chart diagram of a coupling model of uplift denudation amount x-critical burial depth y of sandstone porosity in Embodiment 1 of the present application.

[0045] In the figure: 100-main reservoir forming period acquisition module, 200-denudation amount acquisition module, 300-prediction module;

[0046] 10-electronic device, 11-processor, 12-ROM, 13-RAM, 14-bus, 15-I / O interface, 16-input unit, 17-output unit, 18-storage unit, 19-communication unit.

[0047] The present application is further described in detail below. However, the following examples are merely simple examples of the present application and do not represent or limit the protection scope of the present application, and the protection scope of the present application is subject to the claims. DETAILED DESCRIPTION

[0048] To better illustrate the present application and facilitate understanding of the technical solutions of the present application, the typical but non-limiting embodiments of the present application are as follows:

[0049] I. The present embodiment provides a prediction method for the lower limit of the porosity depth of a sandstone reservoir, and the flow is as shown in Figure 1 The prediction method comprises:

[0050] determining the main reservoir forming period of oil and gas accumulation in a target study area;

[0051] acquiring the structural uplift denudation amount of the main reservoir forming period;

[0052] using the structural uplift denudation amount to obtain the lower limit of the porosity depth of the sandstone reservoir by means of a coupling model of uplift denudation amount x-critical burial depth y of sandstone porosity;

[0053] The coupling model of uplift denudation amount x-critical burial depth y of sandstone porosity is as follows: y=ax 2 +bx+c, wherein a is a denudation cumulative effect intensity coefficient, b is a denudation dominant porosity reduction effect coefficient, and c is a constant term.

[0054] In the present application, the denudation cumulative effect intensity coefficient a and the denudation dominant pore reduction effect coefficient b can be obtained according to the conventional requirements in the field, and exemplarily, the denudation amount sequence of multiple stages of uplift events can be selected by simulating the thermal history of the apatite fission track (AFT) of the drilling core in the denudation area; the critical buried depth reference value corresponding to the porosity of 8% is determined by combining core slice identification and logging interval transit time-density crossplot analysis; the denudation amount sequence and the critical buried depth reference value corresponding to the porosity of 8% are subjected to nonlinear regression fitting, and the quadratic term coefficient is taken as the a value, and the linear term coefficient is taken as the b value, exemplarily, a = 4 x 10 -4 , b = -2.0313.

[0055] In the present application, the constant c representing the theoretical critical depth without denudation (x = 0) can be obtained according to the conventional requirements in the field, and exemplarily, the buried depth corresponding to the porosity of 8% can be selected in the tectonic stable area (the denudation amount is in the range of -5 m to 5 m), and then the buried depth corresponding to the porosity of 8% is determined by drilling core slice identification and logging interval transit time-density crossplot analysis, exemplarily, the fine sandstone c = 5502.3, and the medium sandstone c = 5682.3.

[0056] The method further includes: determining a main hydrocarbon accumulation period of the target research area, including: cross-verification analysis of the source rock hydrocarbon generation and expulsion history, trap formation period and oil and gas charging age of the research area to obtain the main hydrocarbon accumulation period.

[0057] The method further includes: obtaining the source rock hydrocarbon generation and expulsion history, including: performing basin inversion thermal evolution history to simulate vitrinite reflectance Ro.

[0058] Exemplarily, the basin simulation software is used to invert the thermal evolution history to simulate the vitrinite reflectance Ro.

[0059] The method further includes: obtaining the trap formation period, including: one or a combination of at least two of the growth fault analysis method, the stratum back-stripping technique or the fission track thermal history inversion.

[0060] In the present application, the growth fault analysis method refers to that the growth fault (synsedimentary fault) continuously acts in the deposition process, resulting in that the thickness of the downthrown side is significantly greater than that of the upthrown side (downthrown side thickness / upthrown side thickness = growth index GI, GI > 1 indicates the fault activity period; GI = 1 indicates the fault is in the dormant period; and GI < 1 indicates that the fault may be in the dormant period or the property is reversed). The displacement difference caused by the fault activity forms structural traps such as fault nose and fault block, so that the trap formation period can be determined by analyzing the fault activity period.

[0061] In the present application, the stratum back-stripping technique refers to that the trap burial history and the paleo-structural form are reconstructed by gradually stripping the sedimentary layer and correcting the compaction effect, and the trap formation time is determined.

[0062] In the present application, the fission track thermal history inversion refers to that the trap formation is usually accompanied by tectonic uplift, resulting in cooling of the stratum and being recorded by the fission track system. By inverting the cooling time-temperature node in the thermal history curve, the key period of trap setting can be identified.

[0063] Wherein, the oil and gas charging age is obtained by means of reservoir oil and gas inclusion homogenization temperature.

[0064] In the present application, the oil and gas charging age is obtained by means of reservoir oil and gas inclusion homogenization temperature, which refers to that the oil and gas charging age is obtained by means of reservoir oil and gas inclusion homogenization temperature (Th), and specifically, the inclusion trapping temperature is coupled with the burial thermal history curve to realize projection of the measured homogenization temperature (representing the minimum temperature of oil and gas charging) of the inclusion onto the thermal history curve of the target reservoir. The principle is that in the burial history of the reservoir, only when the temperature of the reservoir reaches or exceeds the homogenization temperature of the inclusion, the inclusion at the temperature can be formed. After the formation of the inclusion, the temperature information captured by the inclusion is frozen and saved. Specifically, in the thermal history curve, the time period corresponding to the homogenization temperature value of the inclusion is the time of the oil and gas charging event represented by the oil and gas inclusion of the period.

[0065] Wherein, the cross-validation analysis includes data verification analysis, time sequence coupling quantification and reservoir forming intensity analysis.

[0066] Wherein, the data verification analysis includes time window overlap verification or non-overlap contradictory data analysis.

[0067] Wherein, the determination of the cross-validation analysis includes meeting the I-level standard, the II-level standard or the III-level standard.

[0068] Wherein, the I-level standard includes meeting the following two conditions simultaneously: three-element time window overlap and high-intensity reservoir forming (inclusion abundance > 15 per slice and gas-bearing oil saturation > 60%).

[0069] In the present application, the three-element time window overlap refers to the determination formula: main reservoir forming period = {t | t element of T hydrocarbon expulsion intersection t element of T trap intersection t element of T charging}, such as the hydrocarbon source rock expulsion time window 16-6Ma, trap formation 14-5.3Ma, oil and gas charging 7.2±0.8Ma, and the overlap window 7.2-6Ma, that is, the intersection of the three, and two-element overlap is used in the same way.

[0070] Wherein, the II-level standard includes meeting (1) only two-element overlap + high-intensity reservoir forming evidence or (2) three-element overlap but medium-intensity reservoir forming (oil saturation 40-50%).

[0071] Wherein, the III-level standard includes meeting no time window overlap (even if the single-element evidence is strong) and low-intensity reservoir forming (inclusion abundance < 5 per slice).

[0072] The method for recovering the tectonic uplift and denudation amount in the main reservoir period in the research area comprises one of a stratigraphic trend extrapolation method, a vitrinite reflectance Ro method, an apatite fission track AFT method, or a sonic traveltime difference Delta logt method, or a combination of at least two of them.

[0073] In the present application, the tectonic uplift and denudation amount in the main reservoir period in the research area can also be selected from other optimized methods in the art to ensure that the tectonic uplift and denudation amount in the main reservoir period can be accurately obtained, thereby ensuring the prediction accuracy of the lower limit of physical properties, for example:

[0074] A reference well is selected in the research area, the uplift and denudation amount Delta H0 of the target layer of the reference well is obtained, and a time-depth conversion relationship is obtained; a standard layer is selected, and the depth T of the three-dimensional tectonic top surface of the marker layer is reconstructed according to the time-depth conversion relationship of the reference well n ; the uplift and denudation amount X of the target stratum is calculated based on the uplift and denudation amount Delta H0 of the reference well and the paleostructure surface of the marker layer n .

[0075] The reference well is located at the axial part of the structural anticline and the key part of the hanging wall of the fault, and can control the main tectonic unit of the research area.

[0076] The reference well has full-well-section cutting / core logging, systematic logging, and accurate stratification data.

[0077] The reference well drills the late Miocene target stratum, and is not strongly reformed by a later fault.

[0078] The drilling samples of the reference well can meet the apatite fission track AFT and (U-Th) / He thermochronology analysis requirements.

[0079] The uplift and denudation amount Delta H0 is obtained by selecting samples below the late Miocene unconformity of the reference well for apatite and zircon fission track testing and (U-Th) / He age testing, then performing thermal history inversion simulation to obtain simulation results, and calculating the uplift and denudation amount Delta H0 based on the simulation results.

[0080] In the present application, the samples below the late Miocene unconformity of the reference well are obtained by continuous sampling, and the sampling interval can be selected as 50-100m.

[0081] In the present application, the uplift and denudation amount Delta H0 is calculated by constraining the uplift and cooling time by fission tracks.

[0082] The simulation results include a cooling amplitude Delta T and a paleogeothermal gradient G.

[0083] The simulation result also includes a temperature-time (T-t) track, a rapid cooling event (7.2+0.8Ma), a vitrinite reflectance Ro, etc.

[0084] In the application, the palaeogeothermal gradient G is obtained through fluid inclusion inversion.

[0085] The calculation formula of the uplift denudation amount Delta H0 includes Delta H0=cooling amplitude Delta T / palaeogeothermal gradient G.

[0086] The time-depth conversion relationship is obtained by selecting a wavelet extracted from seismic data and performing a convolution operation on the reflection coefficient sequence to generate a simulated seismic trace, comparing the time domain of the seismic trace with the actual seismic trace beside the well, and making the main reflection peak / trough on the synthetic record and the key phase axis of the seismic trace best match in time, phase and amplitude characteristics.

[0087] In the application, the time, phase and amplitude characteristics are best matched, the time matching refers to accurately aligning the geological interface, and specifically, the main peak / trough time difference is less than or equal to 1 / 8 of the main wavelength (usually less than 5ms), the key horizon (such as an unconformity surface and a reservoir top) time difference is less than or equal to 3ms, and the synthetic record time domain and the seismic trace time domain velocity model error is less than 3%; the phase matching refers to eliminating waveform distortion, and specifically, the polarity is consistent, the main peak / trough corresponds to the same geological interface property (such as a sandstone top), the synthetic record wavelet phase spectrum and the seismic trace phase spectrum residual error is less than 10°, and the phase stability is that the phase rotation angle change in a time window is less than 5° (20-80Hz frequency band); the amplitude matching refers to reflecting the lithology change, and specifically, the relative amplitude is maintained, the reservoir / non-reservoir amplitude ratio error is less than 15%, the frequency band energy is balanced, and the main frequency band (20-50Hz) energy difference is less than 10%; and the wave impedance trend matching is that the synthetic record and the seismic trace envelope form correlation coefficient is greater than 0.8.

[0088] In the application, the time-depth conversion relationship is obtained by using acoustic logging integral calculation to calculate the cumulative propagation time or using a regional velocity empirical formula.

[0089] In the application, the time-depth conversion relationship is obtained by checking the depth reference surface consistency (such as logging depth, drilling stratification depth and seismic processing reference surface) of data (such as acoustic logging, density logging and seismic data (nearby trace)).

[0090] The standard layer is close to the unconformity surface and below the unconformity surface, is not denuded and can record the original tectonic shape of tectonic movement.

[0091] In the application, the selected marker layer has the characteristics of strong amplitude, high continuity and consistent polarity.

[0092] In the present invention, strong amplitude means that the energy of seismic reflection wave is significantly higher than the background noise and the reflection of adjacent strata, and the relative amplitude ratio is ≥3 times the average amplitude of the background strata.

[0093] In the present invention, high continuity refers to the reflection event having stable lateral extension, consistent waveform, few fractures or lithologic discontinuities, a continuity index of 0.85, and a fault cut of <5%.

[0094] In the present invention, the polarity is consistent, which means that the top interface of the marker layer shows a uniform phase (peak / trough) in the entire working area.

[0095] Among them, the top interface depth of the three-dimensional structure of the marker layer is T n The reconstruction process includes: performing grid fine structural interpretation on the top surface of the marker layer and reconstructing the top interface depth T of the marker layer based on the time-depth conversion relationship of the benchmark well. n .

[0096] In the present invention, the grid spacing in the grid fine structure interpretation can be selected as (20-30m)×(20-30m), which can be selected according to actual requirements.

[0097] Wherein, the uplift erosion amount X n The calculation process includes: based on the top surface depth value T0 of the marker layer of the benchmark well and the top interface depth T of the marker layer three-dimensional structure n The relative uplift ΔH is calculated n , then according to the relative uplift ΔH n Draw the contour map of the uplift erosion amount ΔH0, based on the relative uplift amount ΔH n The uplift and erosion amount X of the target formation is calculated by adding the uplift and erosion amount ΔH0 n .

[0098] In the present invention, the contour map of the uplift and erosion amount ΔH0 can intuitively display the relative fluctuation of the marker layer in three dimensions and judge the relative uplift / subsidence trend of the stratum. In the map, if ΔH n >0, the top boundary of the marker layer is uplifted relative to the reference well; if ΔH n <0, the top boundary of the marker layer is subsided relative to the reference well; if ΔH n =0, the benchmark well point and the top boundary of the marker layer are at the same structural height.

[0099] Wherein, the relative uplift ΔH n The calculation formula is as follows:

[0100] ΔH n =T0-T n

[0101] Where, T0 is the top depth of the marker layer of the benchmark well, m; T nFor the mark layer three-dimensional structure top interface depth, m.

[0102] In the present application, the uplift denudation amount X of the target formation n The calculation of the spatial continuous denudation amount model is generated by combining the seismic sequence framework and the compaction correction coefficient.

[0103] The calculation formula of the uplift denudation amount X of the target formation n is as follows:

[0104] X n =(ΔH0+ΔH n )×C

[0105] In the formula, ΔH0 is the uplift denudation amount, m; ΔH n is the relative uplift amount, m; and C is the compaction correction coefficient.

[0106] In the present application, the compaction correction coefficient can be obtained according to the conventional method in the art, and an example is as follows: During the burial of sediments, the overlying strata pressure causes the porosity to decrease and the thickness to thin. The decompaction correction reversely restores the paleo-thickness at the end of strata deposition through a porosity-depth relationship model: C=(1-φ paleo ) / (1-φ now ), wherein φ now is the average present porosity of the strata, which is obtained by logging data statistics or laboratory core analysis method; φ paleo is the average paleo-porosity at the end of strata deposition, φ paleo =φ0*e -Cc*Xn , Xn is the uplift denudation amount of the target formation; φ0(sandstone=0.42, mudstone=0.68); and Cc(sandstone=0.35km -1 , mudstone=0.48km -1 ).

[0107] Secondly, the embodiment provides a device for predicting the lower limit of the porosity-depth of a sandstone reservoir, as shown in FIG. Figure 2 The device for predicting the lower limit of the porosity-depth of a sandstone reservoir comprises:

[0108] A main accumulation period acquisition module 100 is configured to determine the main accumulation period of oil and gas accumulation in a target research area.

[0109] An erosion amount acquisition module 200 is configured to acquire the structural uplift denudation amount in the main accumulation period.

[0110] A prediction module 300 is configured to acquire the lower limit of the porosity-depth of a sandstone reservoir by using the structural uplift denudation amount and a coupling model of the uplift denudation amount X-sandstone porosity critical burial depth Y.

[0111] The coupling model of the uplift erosion amount x and the critical buried depth y of sandstone porosity is as follows: y=ax+bx+c, wherein a is a cumulative erosion effect intensity coefficient, b is a dominant porosity reduction effect coefficient of erosion, and c is a constant term. 2 +bx+c, wherein a is a cumulative erosion effect intensity coefficient, b is a dominant porosity reduction effect coefficient of erosion, and c is a constant term.

[0112] With regard to the apparatus in the above-described embodiments, the specific manner in which each of the modules performs operations has been described in detail in the embodiments related to the method, and will not be described in detail here.

[0113] Third, the present embodiment provides an electronic device, which is intended to represent a variety of forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent a variety of forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections, and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the applications described and / or claimed in this document.

[0114] As shown in Figure 3 The electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An I / O interface 15 is also connected to the bus 14.

[0115] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunications networks.

[0116] The processor 11 can be various general and / or special purpose processing components having processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the prediction method of the lower porosity depth limit of sandstone reservoirs.

[0117] In some embodiments, the prediction method of the lower porosity depth limit of sandstone reservoirs can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded onto the RAM 13 and executed by the processor 11, one or more steps of the prediction method of the lower porosity depth limit of sandstone reservoirs described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the prediction method of the lower porosity depth limit of sandstone reservoirs by any other suitable means, such as by means of firmware.

[0118] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0119] Computer programs used to implement the methods of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0120] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0121] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0122] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), blockchain network, and the Internet.

[0123] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server is one of communication and distribution, with the client requesting a service that is accessible via the server. The server provides the service in response to the request from client. A cloud server, also known as a cloud computing server or cloud host, is a host product in the cloud computing service system, which solves the defects of great management difficulty and weak business scalability in traditional physical host and VPS service.

[0124] The server provided by the embodiment comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and the processor implements the prediction method for the lower limit of the porosity depth of the sandstone reservoir when executing the program.

[0125] Unless specifically stated otherwise, terms such as processing, computing, calculating, determining, displaying, and the like, can refer to an action and / or process of one or more processing or computing systems, or similar devices, that manipulate and / or transform data represented as physical (e.g., electronic) quantities within the processing system's registers and / or memories into other data similarly represented as physical quantities within the processing system's memories, registers or other such information storage, transmission or display devices. Information and signals can be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that can be referenced throughout the above description can be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0126] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0127] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor and the storage medium can reside as discrete components in a user terminal.

[0128] For a software implementation, the techniques described in this disclosure can be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes can be stored in memory units and executed by processors. The memory unit can be implemented within the processor or external to the processor, in which case it can be communicatively coupled to the processor via various means as is known in the art.

[0129] Four, in order to illustrate the prediction effect of the prediction method of the lower limit of the porosity depth of sandstone reservoir provided by the present application, an actual example is used for illustration, which is as follows:

[0130] Embodiment 1

[0131] The embodiment provides a prediction process of the lower limit of the porosity depth of a sandstone reservoir, which is as follows:

[0132] 1) First, determine the main accumulation period of the study area oil and gas accumulation, the process is as follows:

[0133] Determination of the main accumulation period of oil and gas accumulation needs to comprehensively analyze the hydrocarbon source rock generation and expulsion history, trap formation period, and oil and gas charging age, combined with geological-geochemical multi-method cross verification. The following is the main accumulation period identification method system of Xihu Sag in the East China Sea Basin

[0134] ① Hydrocarbon source rock generation and expulsion history analysis:

[0135] Vitrinite reflectance (Ro) simulation: Inversion of thermal evolution history by using basin simulation software (PetroMod)

[0136] T max = 10 0.018×Ro+1.52 (Sweeney) formula

[0137] Hydrocarbon generation threshold: Ro=0.6%(oil generation onset), Ro=1.3%(gas generation peak). Hydrocarbon generation peak of Pinghu Formation: oil generation 16-12Ma(Ro=0.8-1.0%), gas generation 10-6Ma(Ro=1.3-2.0%).

[0138] ②The timing of trap formation is constrained, as shown in Table 1 below:

[0139] Table 1

[0140]

[0141] ③Direct dating of oil and gas charging: reservoir oil and gas inclusion homogenization temperature, main reservoir 5-7Ma.

[0142] The main reservoir period of the study area is determined to be 5.5±0.3Ma(late Miocene Longjing movement II phase).

[0143] 2) Secondly, restore the tectonic uplift and denudation in the main reservoir period of the study area.

[0144] A three-dimensional quantitative restoration method of tectonic uplift and denudation thickness in oil and gas bearing basins based on chronology constraints is used to restore the paleostructure of the target area, as follows:

[0145] Firstly, select a reference well in the main reservoir period to establish the uplift and denudation amount of the reference well.

[0146] Selection criteria for reference well:

[0147] ① Located in the key part of the fault hanging wall with relatively stable structure, which can control the main tectonic unit of the study area.

[0148] ② With full well section cuttings / core logging, systematic logging(sonic, density, gamma), and accurate stratification data.

[0149] ③ Drilling the target strata of late Miocene(e.g., refer to the Miocene Yuguang Formation of East China Shelf Basin), and not strongly modified by later faults.

[0150] ④ The well has sufficient core or cutting samples to meet the requirements of apatite fission track AFT and(U-Th) / He thermal chronology analysis.

[0151] Key steps for uplift and denudation amount of reference well point:

[0152] ① Sample collection and mineral separation: continuous sampling(between 80m) below the late Miocene unconformity, with sandstone lithology. Screen and water-washed cutting samples, and separate apatite and zircon using international standard heavy liquid and magnetic separation technology.

[0153] ② Apatite and zircon fission track testing and(U-Th) / He age testing.

[0154] ③ Thermal history modeling and inversion: the temperature-time (T-t) path, the rapid cooling event (7.2±0.8Ma), the cooling amplitude ΔΤ (18±1℃), the Ro, the fluid inclusion, the inversion of the paleo-geothermal gradient G (34±2℃ / km) of the sample from the key well in the main accumulation period.

[0155] ④ Calculation principle of the denudation amount: ΔΗ0=ΔΤ / G, thus the denudation amount of the target formation of the key well is 559m.

[0156] Secondly, the uplift amount calculation of the key well to the 3D seismic interpretation interface. The key steps are as follows:

[0157] ① Time-depth calibration of the key well and the seismic data volume:

[0158] i. Data preparation and quality control: high-quality sonic logging, density logging, seismic data (nearby well), accurate drilling stratification data (geological marker layer depth), check the consistency of the depth datum (logging depth, drilling stratification depth, seismic processing datum) of the data.

[0159] ii. Establishing the initial time-depth relationship: usually using the sonic logging integral to calculate the cumulative travel time or using the regional velocity empirical formula.

[0160] iii. Synthetic record making and calibration: selecting the appropriate wavelet (extracted from seismic data) and reflection coefficient sequence to perform convolution operation, generating a simulated seismic trace-synthetic seismic record. Comparing the synthetic seismic trace (time domain) with the actual seismic trace (time domain) near the well. Adjust the time-depth relationship repeatedly by stretching, compressing or moving the record, so that the main reflection peaks / troughs on the synthetic record and the key events on the seismic trace are best matched in time, phase and amplitude characteristics. Finally, the time-depth pairs and the time-depth conversion relationship of the key well position are obtained.

[0161] Again, the marker layer selection and 3D structural interface reconstruction are carried out.

[0162] ① Select a marker layer that has not been denuded closely below the unconformity surface, to ensure that the original tectonic form is recorded. The top interface of the marker layer has strong amplitude, high continuity, consistent polarity, and continuous tracking throughout the region.

[0163] ② Fine structural interpretation of the marker layer top surface with a grid spacing of 25m x 25m, based on the time-depth conversion relationship of the key well, to reconstruct the 3D structural top interface depth T n .

[0164] Finally, the uplift amount is calculated by the denudation amount of the quasi-well and the paleo-structural surface of the marker layer.

[0165] ① Refer to the benchmark well and calculate the relative uplift of the top interface of the marker layer ΔH n , the formula is as follows:

[0166] ΔH n =T0-T n

[0167] Where, T0 is the top depth of the marker layer of the benchmark well, m; T n is the depth of the top interface of the three-dimensional structure of the marker layer, m;

[0168] Calculation steps:

[0169] i. Determine the base well data. Obtain the top depth value T0 of the marker layer of the base well (reference well).

[0170] ii. Extract the top interface depth T of the marker layer 3D structure n data.

[0171] iii. Substitute ΔH into the formula n =T0-T n , calculate the relative uplift amount, draw the ΔH0 contour map, intuitively display the relative ups and downs of the marker layer in three dimensions, and judge the relative uplift / subsidence trend of the stratum.

[0172] Geological significance:

[0173] ΔH n >0: The uplift of the top boundary of the marker layer relative to the reference well.

[0174] ΔH n <0: Subsidence of the top boundary of the marker layer relative to the reference well.

[0175] ΔH n =0: The benchmark well point and the top boundary of the marker layer are at the same structural height.

[0176] ② Based on the relative uplift of the top interface of the marker layer ΔH n , calculate the target stratum uplift and erosion amount X n , the formula is as follows:

[0177] X n =(ΔH0+ΔH n )×C

[0178] Where ΔH0 is the uplift erosion amount, m; ΔH n is the relative uplift, m; C is the compaction correction coefficient.

[0179] X n The calculation results of the uplift and erosion amount of the target formation during the main reservoir formation period are shown in Figure 4The result shows that the planar structure uplift denudation amount of the research area is between 500-1750m. The denudation amount has significant spatial difference in planar distribution, showing regular zonation characteristics: the denudation intensity is the largest in the core area of the structure, and the denudation amount generally reaches 1200-1800m; and the denudation intensity is obviously weakened in the transition to the wing of the structure, and the denudation amount decreases to 500-1200m.

[0180] Finally, according to the coupling model of the denudation amount and the critical buried depth of the sandstone porosity (8%), the lower limit of the reservoir property is predicted, and the process is as follows:

[0181] The quantitative dynamic correlation model of the denudation amount (x) and the critical depth of the porosity (8%) used in the application is mathematically expressed as follows:

[0182] Fine sandstone: y = 4x10 -4 x 2 -2.0313x + 5502.3

[0183] In the formula, the symbols are defined as follows:

[0184] y: the lower limit of the depth corresponding to the porosity of 8% (unit: m);

[0185] x: the structural uplift denudation amount (i.e. the denudation amount, unit: m);

[0186] 4x10 -4 : binomial coefficient, representing the cumulative effect strength of denudation, indicating the critical depth recovery;

[0187] -2.0313: the first term coefficient, reflecting the dominant denudation effect of reducing porosity, and the critical depth is lifted by 2.0313m on average for every 1m of denudation amount;

[0188] 5502.3: constant term, representing the theoretical critical depth (unit: m) without denudation (x = 0).

[0189] Further, the quantitative dynamic correlation model of the denudation amount (x) and the critical depth of the porosity (8%) can be used by being converted into a sandstone reservoir porosity critical buried depth prediction chart (Fig. 2). Figure 5 The chart specifically includes the following core features:

[0190] ① Chart structure definition

[0191] A two-dimensional coordinate system is formed by the denudation amount (x-axis) and the buried depth (y-axis); the curve in the figure is the critical buried depth curve, and the mathematical expression is: y = ax 2 +bx+c

[0192] ② Area division rule, as shown in the following table 2

[0193] Table 2

[0194]

[0195] ③Curved geological connotation

[0196] The critical burial depth curve represents: porosity threshold response, each point on the curve corresponds to the critical burial depth of 8% porosity;

[0197] Dynamic coupling mechanism: the curve shape reflects the quadratic function decay relationship between denudation amount (x) and critical burial depth (y).

[0198] In summary, the prediction method provided by the present application can accurately determine the critical depth corresponding to the economic exploitation lower limit of porosity ≥8% by selecting a specific main accumulation period in the study area and combining the coupling model of uplift denudation amount x-sandstone porosity critical burial depth y, and realizes efficient and accurate prediction of the lower limit of the depth of sandstone reservoir porosity.

[0199] It is declared that the above embodiments are used to illustrate the detailed structural features of the present application, but the present application is not limited to the above detailed structural features, that is, it does not mean that the present application must rely on the above detailed structural features to be implemented. Those skilled in the art should understand that any improvement of the present application, equivalent replacement of the components selected by the present application, increase of auxiliary components, selection of specific modes, etc. fall within the protection scope and disclosure scope of the present application.

[0200] The preferred embodiments of the present application are described in detail above, but the present application is not limited to the specific details in the above embodiments, and within the technical concept scope of the present application, the technical solutions of the present application can be variously modified, and these simple modifications all belong to the protection scope of the present application.

[0201] In addition, it should be noted that each specific technical feature described in the above specific embodiments can be combined in any appropriate manner without contradiction, and in order to avoid unnecessary repetition, the present application will not further describe various possible combination manners.

[0202] In addition, various different embodiments of the present application can also be combined in any manner, as long as it does not deviate from the idea of the present application, and it should be considered as disclosed content of the present application.

Claims

1. A method for predicting the lower limit of porosity depth in sandstone reservoirs, characterized in that: The prediction method comprises: Determine the main accumulation period of oil and gas in the target study area; Obtain the amount of tectonic uplift and erosion during the main reservoir-forming period; The lower limit of the porosity depth of the sandstone reservoir is obtained by using the coupling model of tectonic uplift and erosion amount x and the critical buried depth y of sandstone porosity. The coupling model of uplift erosion amount x and critical buried depth y of sandstone porosity is as follows: y = ax 2 +bx+c, where a is the intensity coefficient of the cumulative effect of erosion, b is the coefficient of the pore reduction effect dominated by erosion, and c is a constant term.

2. The prediction method according to claim 1, wherein: Determining the main accumulation period of oil and gas accumulation in the target study area includes: conducting a cross-validation analysis on the hydrocarbon generation and expulsion history of the source rocks, the trap formation period and the oil and gas filling age in the study area to obtain the main accumulation period of oil and gas accumulation.

3. The prediction method according to claim 2, wherein: The acquisition of the hydrocarbon generation and expulsion history of the source rock includes: performing basin inversion thermal evolution history to achieve vitrinite reflectance Ro simulation.

4. The prediction method according to claim 2, wherein: The method for obtaining the trap formation period includes: one or a combination of at least two of the following: growth fault analysis, stratum backstripping technology, or fission track thermal history inversion.

5. The prediction method according to claim 2, wherein: The oil and gas charging age is obtained by means of the homogenization temperature of oil and gas inclusions in the reservoir.

6. The prediction method according to claim 2, wherein: The cross-validation analysis includes: data validation analysis, time series coupling quantification and reservoir intensity analysis; Preferably, the data verification analysis includes: time window overlap verification or non-overlapping contradictory data analysis; Preferably, the determination of the cross-validation analysis includes: meeting the Level I standard, Level II standard or Level III standard; Preferably, the Level I standard includes: simultaneously meeting the following two conditions: the three-element time window overlaps and high-intensity accumulation is characterized by inclusion abundance > 15 per thin section and gas-oil saturation > 60%; Preferably, the Level II criteria include: meeting (1) only two elements overlap + high-intensity accumulation evidence or (2) three elements overlap but moderate accumulation intensity with oil saturation of 40-50%; Preferably, the Level III standard includes: satisfying no time window overlap, and low-intensity accumulation with inclusion abundance < 5 per thin section.

7. The prediction method according to any one of claims 1 to 6, wherein: The method of restoring the amount of tectonic uplift and erosion during the main reservoir formation period in the study area includes: one or a combination of at least two of the formation trend extrapolation method, the vitrinite reflectance Ro method, the apatite fission track AFT method or the acoustic wave time difference Δlogt method.

8. A device for predicting the lower limit of porosity depth in sandstone reservoirs, characterized in that: The device for predicting the lower limit of the porosity depth of the sandstone reservoir comprises: The main accumulation period acquisition module is used to determine the main accumulation period of oil and gas accumulation in the target study area; The erosion volume acquisition module is used to obtain the tectonic uplift and erosion volume during the main reservoir formation period; A prediction module is used to obtain the lower limit of the porosity depth of the sandstone reservoir by using the tectonic uplift and erosion amount with the help of a coupling model of uplift and erosion amount x and critical buried depth y of sandstone porosity; The coupling model of uplift erosion amount x and critical buried depth y of sandstone porosity is as follows: y = ax 2 +bx+c, where a is the intensity coefficient of the cumulative effect of erosion, b is the coefficient of the pore reduction effect dominated by erosion, and c is a constant term.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for predicting the lower limit of the porosity depth of a sandstone reservoir according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that The computer storage medium stores computer executable instructions, which, when executed by a processor, implement the method for predicting the lower limit of the porosity depth of a sandstone reservoir as described in any one of claims 1 to 7.

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