Sea area ultra-shallow non-diagenesis reservoir fluid saturation classification interpretation evaluation method and system

Abstract

The invention belongs to the technical field of oil exploration and development, and relates to a sea area ultra-shallow non-diagenesis reservoir fluid saturation classification interpretation evaluation method and system, and the method comprises the steps: obtaining an artificial core rock physical experiment result and target reservoir logging curve data which accord with sea area ultra-shallow non-diagenesis target reservoir characteristics; classifying the rock core based on the nuclear magnetic resonance distribution spectrum; calculating a fluid index according to the porosity and permeability of the artificial core, and establishing a core type division standard based on the fluid index; based on the core classification result, re-establishing the fitting relationship between the resistivity increase coefficient of the different types of cores and the water saturation, the fitting relationship between the formation factor and the porosity of the target stratum to obtain the rock electricity parameters corresponding to the different types of cores, and determining the type of the target reservoir based on the core type division standard so as to determine the rock electricity parameters of the target reservoir; and calculating the water saturation of the target reservoir according to the rock electrical parameters of the target reservoir. The method can be used for finely evaluating the fluid saturation of the ultra-shallow non-diagenesis reservoir in the sea area.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas exploration and development, and relates to a classification interpretation and evaluation technology for reservoir fluid saturation, and specifically relates to a classification interpretation and evaluation method and system for fluid saturation in ultra-shallow undiagenetic reservoirs in marine areas. Background Art

[0002] In the field of oil and gas exploration and development, the interpretation and evaluation of fluid saturation is a key technology used to quantitatively describe the filling degree of various fluids (such as water, oil, and gas) in the pores of reservoir rocks. It is one of the core parameters for predicting reservoir production capacity and reserves. Traditional fluid saturation calculation methods usually rely on formed and pressure-bearing plunger cores to conduct rock physics experiments, obtain rock electrical parameters, and build saturation interpretation models (such as Archie's formula or its variants) based on this.

[0003] However, for ultra-shallow gas-bearing reservoirs in the sea, most of the rocks are in an undiagenetic and uncemented state, the rock structure is loose, the coring operation is difficult, and there is a lack of supporting rock physics experimental data support. In this case, the existing fluid saturation calculation method has low saturation accuracy, which seriously restricts the accurate assessment of shallow natural gas reserves in the sea. In order to improve the calculation accuracy, preparing artificial cores that match the characteristics of the target layer has become an important way to obtain the rock electrical parameters of the target layer. Even so, there is still a practical problem of insufficient calculation accuracy for the saturation evaluation of ultra-shallow gas-bearing reservoirs in the sea.

[0004] At present, the fine evaluation of fluid saturation mostly adopts the phase control concept, that is, the saturation is calculated separately according to different reservoir types to achieve fine evaluation. Common saturated fluid calculation methods include fluid unit index method, plate method and machine learning method, etc. These methods are mainly applicable to low-porosity and low-permeability reservoirs (such as shale, tight sandstone oil and gas reservoirs), fracture-cavity carbonate reservoirs and volcanic rock reservoirs. For ultra-shallow undiagenetic natural gas reservoirs in the sea, fluid saturation evaluation mostly adopts unified rock electrical parameters to substitute into Archie formula, or considers the influence of additional conductivity of mud for overall calculation by Simendan formula (for example, the rock electrical parameters are usually set to a = b = 1, m = n = 2). However, actual applications have shown that the Archie formula will seriously underestimate the gas saturation in high-quality reservoirs with extremely high porosity and permeability; although the Simonds formula takes into account the additional conductivity of mud, it fails to fully consider the impact of the mineralization of ultra-shallow formation water on the macroscopic conductivity in the sea, resulting in the calculated gas saturation being higher than the actual value due to the superposition of the additional conductivity of mud during the calculation process. The above problems directly lead to the fact that the existing methods are unable to meet the actual exploration and development needs in the calculation of fluid saturation in ultra-shallow undiagenerated natural gas reservoirs in the sea. Therefore, how to achieve a refined assessment of the fluid saturation of ultra-shallow undiagenerated natural gas reservoirs in the sea has become a key technical problem that needs to be overcome urgently. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a method and system for classifying, interpreting and evaluating the fluid saturation of ultra-shallow undiagenetic reservoirs in marine areas, which can realize the fine evaluation of the fluid saturation of ultra-shallow undiagenetic reservoirs in marine areas.

[0006] In a first aspect, the present invention provides a method for classifying, interpreting and evaluating fluid saturation in ultra-shallow undiagenetic reservoirs in the sea, the steps of which are as follows: Data acquisition steps: Obtaining artificial core rock physics experimental results and target reservoir logging curve data that meet the characteristics of ultra-shallow undiagenetic target reservoirs in the sea area; the experimental results include nuclear magnetic resonance Distribution spectrum, porosity, permeability, water saturation, resistivity increase coefficient, formation factor; Core classification steps: Based on NMR The cores are classified according to the different intervals of the distribution spectrum; Steps for constructing the classification standard: select cores of the same type according to the core classification results, calculate the fluid index of each core according to the porosity and permeability of each core, and establish the core type classification standard according to the fluid index; Steps for determining rock electrical parameters: for the same type of cores, establish the fitting relationship between the resistivity increase coefficient and water saturation, the formation factor and the porosity of the target layer, and obtain the rock electrical parameters corresponding to the same type of cores based on the fitting relationship; Reservoir type determination steps: calculating the porosity of the target reservoir according to the target reservoir logging curve data, calculating the permeability of the target reservoir according to the porosity of the target reservoir, calculating the fluid index of the target reservoir according to the porosity and permeability of the target reservoir, and determining the target reservoir type based on the core type classification standard according to the fluid index; Saturation calculation steps: determine the rock electrical parameters corresponding to the target reservoir according to the reservoir type to which the target reservoir belongs, and calculate the water saturation of the target reservoir according to the rock electrical parameters of the target reservoir.

[0007] In some embodiments, in the data acquisition step, the method for obtaining the artificial core rock physics experiment results of the ultra-shallow undiagenetic target reservoir characteristics in the sea area is: Produce artificial cores that meet the reservoir characteristics of ultra-shallow undiagenetic targets in the sea area; Measure the porosity and permeability of artificial cores under set temperature conditions; Artificial core saturation is performed using brine with a set salinity; The saturated artificial core was placed in the nuclear magnetic resonance imaging system, and the echo interval, waiting time, number of echo trains collected and scanning times were set to measure the magnetic resonance. Distribution spectrum; Under formation conditions, the core resistivity and water saturation under different water saturation conditions are measured through displacement experiments, and the resistivity increase coefficient and formation factor are calculated based on the core resistivity.

[0008] In some embodiments, the resistivity increase coefficient is calculated according to the core resistivity by using a resistivity increase coefficient calculation formula;

[0009] In the formula, is the core resistivity enhancement factor, is the core resistivity after displacement, is the core resistivity at saturation.

[0010] In some embodiments, the formation factor is calculated based on the core resistivity using a formation factor calculation formula;

[0011] In the formula, is the formation factor of the core, is the core resistivity at saturation, is the resistivity of the saturated solution.

[0012] In some embodiments, in the step of constructing the classification criteria, the fluid index of the core is calculated according to the porosity and permeability of the core by a fluid index calculation formula;

[0013] In the formula, is the fluid index of the core, is the permeability of the core, is the porosity of the core.

[0014] In some embodiments, in the rock electrical parameter determination step, the fitting relationship between the resistivity increase coefficient and the water saturation is expressed as:

[0015] In the formula, is the core resistivity enhancement factor, is the lithology parameter, The water saturation of the core, is the saturation index; Fitting relationship between formation factor and porosity:

[0016] In the formula, is the formation factor of the core, is the lithology parameter, is the porosity of the core, Is the cementation index.

[0017] In some embodiments, in the reservoir type determination step, the method for calculating the porosity of the target reservoir according to the target reservoir logging curve data is: Calculate the relative value of natural gamma;

[0018] In the formula, is the relative value of natural gamma; is the natural gamma logging value of the target layer, unit: API; It is the natural gamma logging value of pure lithologic formation, unit: API; is the natural gamma logging value of pure mudstone formation, unit: API; Calculate reservoir mud content based on relative value of natural gamma;

[0019] In the formula, is the reservoir mud content, is the empirical coefficient related to the stratigraphic age; According to the reservoir shale content, the density porosity corrected by shale and the neutron porosity corrected by shale are calculated respectively;

[0020]

[0021] In the formula, It is the density porosity after mud correction, unit: decimal; is the neutron porosity after shale correction, unit: decimal; is the density of the rock skeleton, unit: g / cm 3 ; is the density of the formation fluid, unit: g / cm 3 ; is the density of mudstone, unit: g / cm 3 ; is the target layer density logging value, unit: g / cm 3 ; is the neutron value of the rock skeleton, unit: %; is the neutron value of the formation fluid, unit: %; is the neutron value of mudstone, unit: %; is the neutron logging value of the target layer, unit: %; is the reservoir mud content, unit: decimal; Calculate the target reservoir porosity based on the density porosity corrected by shale and the neutron porosity corrected by shale;

[0022] In the formula, is the target reservoir porosity.

[0023] In some embodiments, in the reservoir type determination step, the method for calculating the target reservoir permeability according to the target reservoir porosity is: According to the porosity and permeability of the artificial core in the data acquisition step, a porosity-permeability fitting relationship is established; The permeability of the target reservoir is calculated based on the porosity of the target reservoir through the porosity-permeability fitting relationship.

[0024] In some embodiments, in the saturation calculation step, the water saturation of the target reservoir is calculated by Archie's formula according to the determined rock electrical parameters;

[0025] In the formula, is the water saturation of the target reservoir, is the lithology parameter, is the cementation index, is the saturation index, is the target reservoir porosity, is the formation water resistivity, is the target reservoir resistivity logging value.

[0026] In a second aspect, the present invention provides a system for classifying, interpreting and evaluating fluid saturation in ultra-shallow undiagenetic reservoirs in marine areas, which is used to implement the method for classifying, interpreting and evaluating fluid saturation in ultra-shallow undiagenetic reservoirs in marine areas described in the first aspect of the present invention, comprising: The data acquisition module is used to obtain the rock physics experimental results of artificial cores and the logging curve data of the target reservoir that are consistent with the characteristics of the ultra-shallow undiagenetic target reservoir in the sea area; Core classification module, based on NMR The cores are classified according to the different intervals of the distribution spectrum; The classification standard construction module selects cores of the same type according to the core classification results, calculates the fluid index of each core according to the porosity and permeability of each core, and establishes the core type classification standard based on the fluid index; The rock electrical parameter determination module establishes the fitting relationship between the resistivity increase coefficient and water saturation, the formation factor and the porosity of the target layer for the same type of cores, and obtains the rock electrical parameters corresponding to the same type of cores based on the fitting relationship; A reservoir type determination module calculates the porosity of the target reservoir according to the target reservoir logging curve data, calculates the permeability of the target reservoir according to the porosity of the target reservoir, calculates the fluid index of the target reservoir according to the porosity and permeability of the target reservoir, and determines the target reservoir type based on the core type classification standard according to the fluid index; The saturation calculation module determines the rock electrical parameters corresponding to the target reservoir according to the reservoir type to which the target reservoir belongs, and calculates the water saturation of the target reservoir according to the rock electrical parameters of the target reservoir.

[0027] Compared with the prior art, the advantages and positive effects of the present invention are: The method and system for classifying, interpreting and evaluating the fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area provided by the present invention is based on the core experiment results, by finding the distribution law of core physical properties and rock electrical parameters of different pore structure types, and according to nuclear magnetic resonance Cores are classified into different categories according to the distribution spectrum distribution intervals, and the fluid index is calculated according to the qualitative relationship between porosity-permeability-fluid index. The core type classification standard is established according to the fluid index, and the rock electrical parameters of different types of cores are determined according to the re-established fitting relationship between the resistivity increase coefficient and water saturation, and the formation factor and the porosity of the target layer; the target reservoir type is determined based on the core type classification standard, and then the rock electrical parameters of the target reservoir are determined, and the fluid saturation of the target reservoir is calculated according to the rock electrical parameters of the target reservoir. On the basis of clarifying that the differences in porosity and permeability types of different reservoirs lead to complex rock electrical relationships, the present invention constructs a core type classification standard according to the core type classification results, and reconstructs the fitting relationship between the resistivity increase coefficient and water saturation, the formation factor and the porosity of the target layer, and obtains the rock electrical parameters corresponding to different core types according to the fitting relationship, quantifies the classification indicators, unifies the standards, and realizes the fine evaluation of the fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area, which has important guiding significance for the fine calculation of saturation and subsequent reserve generalization of ultra-shallow undiagenetic reservoirs in the sea area. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic flow chart of the method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area according to an embodiment of the present invention; Figure 2 A schematic flow chart of a method for obtaining rock physics experimental results of artificial cores for obtaining ultra-shallow undiagenetic target reservoir characteristics in the sea area according to an embodiment of the present invention; Figure 3 This is a schematic flow chart of a method for calculating the porosity of a target reservoir according to well logging curve data of the target reservoir according to an embodiment of the present invention; Figure 4 The method for calculating the permeability of a target reservoir according to the porosity of the target reservoir according to the embodiment of the present invention is Figure 5This is a structural block diagram of the system for classifying, interpreting and evaluating the fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the porosity and permeability measurement results of an artificial core that meets the characteristics of an ultra-shallow undiagenerated natural gas reservoir in the sea area according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the measurement results of water saturation and resistivity increase coefficient of an artificial core that meets the characteristics of an ultra-shallow undiagenerated natural gas reservoir in the sea area according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the measurement results of porosity and formation factors of artificial cores that meet the characteristics of ultra-shallow undiagenerated natural gas reservoirs in the sea area according to an embodiment of the present invention; Fig. 9 The core nuclear magnetic resonance of the embodiment of the present invention Distribution spectrum diagram; Fig.10 The core nuclear magnetic resonance of the embodiment of the present invention Schematic diagram of the results after distribution spectrum classification; Fig.11 The relationship between the resistivity increase coefficient and the water saturation and the parameter diagram re-established after classification of the embodiment of the present invention; Fig.12 The relationship between porosity and formation factor and the parameter diagram re-established after classification in the embodiment of the present invention; Fig.13 This is a schematic diagram of the X1 well parameters and classification results according to an embodiment of the present invention; Fig.14 This is a schematic diagram of the saturation result calculated using unified parameters for the X1 well according to an embodiment of the present invention; Fig.15 This is a schematic diagram of the saturation results of the X1 well calculated by classification according to the embodiment of the present invention.

[0029] In the figure, 1. data acquisition module, 2. core classification module, 3. classification standard construction module, 4. rock electrical parameter determination module, 5. reservoir type determination module, 6. saturation calculation module. DETAILED DESCRIPTION

[0030] The present invention will be described in detail below by way of exemplary embodiments in conjunction with the accompanying drawings. However, it should be understood that, without further description, elements, structures and features in one embodiment may also be beneficially combined in other embodiments.

[0031] The present invention provides a method and system for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenerated reservoirs in the sea area. The method and system are based on nuclear magnetic resonance (NMR) and artificial core experimental results that meet the characteristics of ultra-shallow undiagenerated natural gas reservoirs in the sea area. The cores are classified by distribution spectrum; the fluid index is calculated according to the porosity and permeability of the artificial cores, and the core type classification standard is established based on the fluid index; based on the core classification results, the fitting relationship between the resistivity increase coefficient and water saturation of different types of cores, the formation factor and the porosity of the target layer is re-established to obtain the rock electrical parameters corresponding to different types of cores, and the target reservoir type is determined based on the core type classification standard, and then the rock electrical parameters of the target reservoir are determined; the water saturation of the target reservoir is calculated according to the rock electrical parameters of the target reservoir, and a detailed evaluation of the fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area is realized. The following is a detailed description of the above-mentioned ultra-shallow undiagenetic reservoir fluid saturation classification interpretation evaluation method and system in combination with the attached drawings.

[0032] See also Figure 1 The first embodiment of the present invention provides a method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area, the steps of which are: S1. Data acquisition step: Obtain the rock physics experimental results of artificial cores and the logging curve data of the target reservoir that meet the characteristics of the ultra-shallow undiagenetic target reservoir in the sea area. The experimental results include nuclear magnetic resonance Distribution spectrum, porosity, permeability, water saturation, resistivity increase coefficient, and formation factor.

[0033] In one embodiment of the present application, see Figure 2 The method for obtaining the results of artificial core rock physics experiments on the characteristics of ultra-shallow undiagenetic target reservoirs in the sea area is: S11. Produce artificial cores that meet the characteristics of ultra-shallow undiagenetic reservoirs in the sea area.

[0034] It should be noted that when making artificial cores, the parameters such as the porosity distribution range and permeability distribution range of the artificial cores need to be suppressed with the original formation and consistent with the characteristics of the ultra-shallow undiagenetic target reservoir in the sea.

[0035] S12. Under set temperature conditions, measure the porosity and permeability of the artificial core.

[0036] S13. Saturating the artificial core with brine of set mineralization.

[0037] S14, put the saturated artificial core into the nuclear magnetic resonance imaging system, set the echo interval time, waiting time, number of echo strings collected and number of scans, and measure the magnetic resonance Distribution spectrum.

[0038] S15. Under formation conditions, the core resistivity and water saturation under different water saturation conditions are measured through displacement experiments, and the resistivity increase coefficient and formation factor are calculated based on the core resistivity.

[0039] It should be noted that during experimental testing and analysis, the measurement conditions must be consistent with the original formation, including formation temperature, formation pressure, formation water mineralization, etc.

[0040] Specifically, in one embodiment of the present application, the resistivity increase coefficient is calculated according to the core resistivity by using the resistivity increase coefficient calculation formula;

[0041] In the formula, is the core resistivity enhancement factor, is the core resistivity after displacement, is the core resistivity at saturation.

[0042] Specifically, in one embodiment of the present application, the formation factor is calculated according to the core resistivity using a formation factor calculation formula;

[0043] In the formula, is the formation factor of the core, is the core resistivity at saturation, is the resistivity of the saturated solution.

[0044] S2. Core classification steps: According to nuclear magnetic resonance The cores are classified according to the different distribution ranges of the distribution spectrum.

[0045] It should be noted that nuclear magnetic resonance The size of the distribution spectrum can characterize the pore size. The distribution spectrum morphology is obviously different, and the nuclear magnetic resonance The overall distribution spectrum is consistent. It is mainly single-peaked. The NMR of different types of cores Distribution spectrum is all about peak size and NMR There are differences in the distribution spectrum. Therefore, according to the nuclear magnetic resonance The different distribution ranges of the distribution spectrum can effectively classify the cores.

[0046] S3. Steps for constructing the classification standard: select cores of the same type according to the core classification results, calculate the fluid index of each core according to the porosity and permeability of each core, and establish the core type classification standard according to the fluid index.

[0047] Specifically, in one embodiment of the present application, the fluid index of the core is calculated by a fluid index calculation formula according to the porosity and permeability of the core;

[0048] In the formula, is the fluid index of the core, is the permeability of the core, is the porosity of the core.

[0049] By calculating the fluid index by combining porosity and permeability, a multi-parameter coupled classification standard is constructed, which solves the classification bias problem caused by traditional methods that only rely on porosity or permeability.

[0050] It should be noted that for the same type of core, The values ​​are concentrated in a certain range. The larger the value, the better the reservoir porosity structure, the larger the proportion of large interconnected pores, and the better the pore-throat relationship. Upper and lower limits of values, different types of cores The cores can be divided into different types by the interval distribution of the values. For example, type I cores, type II cores, and type III cores. Type I cores correspond to higher Value, high permeability, good core permeability, good porosity structure; Type II core corresponds to medium The value is between that of type I core and type III core, and the core physical properties are medium; type III core corresponds to a lower value, low permeability, generally high mud content, and poor pore connectivity.

[0051] S4. Rock electrical parameter determination steps: For the same type of cores, establish the fitting relationship between the resistivity increase coefficient and water saturation, formation factor and porosity, and obtain the corresponding rock electrical parameters of the same type of cores based on the fitting relationship.

[0052] Specifically, in one embodiment of the present application, the fitting relationship between the resistivity increase coefficient and the water saturation is expressed as:

[0053] In the formula, is the core resistivity enhancement factor, is the lithology parameter, The water saturation of the core, is the saturation index; Specifically, in one embodiment of the present application, the fitting relationship between the formation factor and the porosity is:

[0054] In the formula, is the formation factor of the core, is the lithology parameter, is the porosity of the core, Is the cementation index.

[0055] It should be noted that based on the core experiment results, the fitting relationship between the resistivity increase coefficient and water saturation, formation factor and porosity of different types of cores was established, and the correlation coefficient was significantly improved, which can better reflect the saturation of reservoirs with different porosity-permeability relationships.

[0056] S5. Reservoir type determination steps: calculate the porosity of the target reservoir based on the target reservoir logging curve data, calculate the permeability of the target reservoir based on the porosity of the target reservoir, calculate the fluid index of the target reservoir based on the porosity and permeability of the target reservoir, and determine the target reservoir type based on the core type classification standard according to the fluid index.

[0057] Specifically, in one embodiment of the present application, see Figure 3 The method for calculating the porosity of the target reservoir based on the target reservoir logging curve data is: S511, calculating the relative value of natural gamma;

[0058] In the formula, is the relative value of natural gamma; is the natural gamma logging value of the target layer, unit: API; It is the natural gamma logging value of pure lithologic formation, unit: API; It is the natural gamma logging value of pure mudstone formation, unit: API.

[0059] S512, calculating the reservoir mud content according to the relative value of natural gamma;

[0060] In the formula, is the reservoir mud content, is an empirical coefficient related to the stratigraphic age. When the target reservoir is a new stratum (i.e., Paleogene or Neogene), =3.7, when the target reservoir is an old stratum, take =2.0.

[0061] S513, respectively calculating density porosity corrected by shale and neutron porosity corrected by shale according to the shale content of the reservoir;

[0062]

[0063] In the formula, It is the density porosity after mud correction, unit: decimal; is the neutron porosity after shale correction, unit: decimal; is the density of the rock skeleton, unit: g / cm 3 ; is the density of the formation fluid, unit: g / cm 3 ; is the density of mudstone, unit: g / cm 3 ; is the target layer density logging value, unit: g / cm 3 ; is the neutron value of the rock skeleton, unit: %; is the neutron value of the formation fluid, unit: %; is the neutron value of mudstone, unit: %; is the neutron logging value of the target layer, unit: %; is the reservoir mud content, unit: decimal; S514, calculating the porosity of the target reservoir according to the density porosity corrected by the shale and the neutron porosity corrected by the shale;

[0064] In the formula, is the target reservoir porosity.

[0065] It should be noted that, due to the characteristics of high formation water mineralization, high mud content, and sandstone heterogeneity in ultra-shallow undiagenetic reservoirs in the sea, neutron and density logging are not affected by mud distribution and compaction, but are sensitive to the influence of mud. Therefore, the neutron-density intersection method is used to calculate the porosity of the target reservoir. During the calculation of the porosity of the target reservoir, mud correction is performed at the same time, and the calculated porosity of the target reservoir is highly accurate.

[0066] Specifically, in one embodiment of the present application, see Figure 4 , the method for calculating the permeability of the target reservoir based on the porosity of the target reservoir is: S521, establishing a porosity-permeability fitting relationship according to the porosity and permeability of the artificial core in the data acquisition step; S522. Calculate the target reservoir permeability according to the target reservoir porosity through the porosity-permeability fitting relationship.

[0067] S6. Saturation calculation step: determine the rock electrical parameters corresponding to the target reservoir according to the reservoir type to which the target reservoir belongs, and calculate the water saturation of the target reservoir according to the rock electrical parameters of the target reservoir.

[0068] Specifically, in one embodiment of the present application, the water saturation of the target reservoir is calculated by using the Archie formula according to the determined rock electrical parameters;

[0069] In the formula, is the water saturation of the target reservoir, is the lithology parameter, is the cementation index, is the saturation index, is the target reservoir porosity, is the formation water resistivity, is the target reservoir resistivity logging value.

[0070] The above-mentioned classification, interpretation and evaluation method for fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area of ​​the present invention, on the basis of clarifying that the differences in porosity and permeability types of different reservoirs lead to complex rock-electricity relationships, constructs a core type classification standard according to the core type classification results, and reconstructs the fitting relationship between the resistivity increase coefficient and water saturation, the formation factor and the porosity of the target layer, obtains the rock-electricity parameters corresponding to different core types according to the fitting relationship, quantifies the classification indicators, unifies the standards, and realizes the fine evaluation of fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area, which has important guiding significance for the fine calculation of saturation and subsequent reserve generalization of ultra-shallow undiagenetic reservoirs in the sea area.

[0071] See also Figure 5 The second embodiment of the present invention provides a classification, interpretation and evaluation system for fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area, which is used to implement the classification, interpretation and evaluation method for fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area described in the first aspect of the present invention, including: Data acquisition module 1, used to obtain artificial core rock physics experimental results and target reservoir logging curve data that meet the characteristics of ultra-shallow undiagenerated target reservoirs in the sea area; Core classification module 2, based on NMR The cores are classified according to the different intervals of the distribution spectrum; Classification standard construction module 3, according to the core classification results, select the cores that meet the same type, calculate the fluid index of each core according to the porosity and permeability of each core, and establish the core type classification standard according to the fluid index; The rock electrical parameter determination module 4 establishes a fitting relationship between the resistivity increase coefficient and the water saturation, the formation factor and the porosity of the target layer for the same type of cores, and obtains the rock electrical parameters corresponding to the same type of cores according to the fitting relationship; The reservoir type determination module 5 calculates the porosity of the target reservoir according to the well logging curve data of the target reservoir, calculates the permeability of the target reservoir according to the porosity of the target reservoir, calculates the fluid index of the target reservoir according to the porosity and permeability of the target reservoir, and determines the type of the target reservoir based on the core type classification standard according to the fluid index; The saturation calculation module 6 calculates the water saturation of the target reservoir according to the determined rock electrical parameters.

[0072] The above-mentioned ultra-shallow undiagenetic reservoir fluid saturation classification, interpretation and evaluation system of the present invention, on the basis of clarifying that the differences in porosity and permeability types of different reservoirs lead to complex rock-electricity relationships, constructs a core type classification standard according to the core type classification results, and reconstructs the fitting relationship between the resistivity increase coefficient and water saturation, the formation factor and the porosity of the target layer. According to the fitting relationship, the rock-electricity parameters corresponding to different core types are obtained, the classification indicators are quantified, the standards are unified, and a fine evaluation of the fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area is achieved, which has important guiding significance for the fine calculation of the saturation of ultra-shallow undiagenetic reservoirs in the sea area and the subsequent reserve generalization.

[0073] In order to verify the effectiveness of the method and system for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in marine areas described in the above embodiments of the present invention, the following specific embodiments are used for illustration.

[0074] Embodiment: The target reservoir is the Ledong Formation in the ultra-deepwater and ultra-shallow Lingshui 36-1 block in the Qiongdongnan Basin.

[0075] S1. According to the statistical analysis results of the Ledong Formation in the ultra-deep and ultra-shallow Lingshui 36-1 block in the Qiongdongnan Basin, a batch of plunger rock samples with ultra-high porosity and permeability were prepared to simulate the physical characteristics of shallow offshore undiagenerated and unconsolidated ultra-fine-grained sediments. The characteristic parameters are consistent with the characteristics of high formation water mineralization, high mud content, and sandstone and mudstone heterogeneity of ultra-shallow undiagenerated natural gas reservoirs in the sea. According to the national standard SY / T6385-2016 of the People's Republic of China "Methods for Determination of Porosity and Permeability of Rocks under Overburden Pressure" and the national standard SY / T 5385-2007 "Laboratory Measurement and Calculation Methods of Rock Resistivity Parameters", experimental research was carried out. Under the design temperature of 18°C, the porosity and permeability of 120 artificial cores were measured, such as Figure 6 A saturated solution with a salinity of 35,000 ppm was used to saturate the core using a vacuum pressurized saturation device. Under formation conditions, an array-type gross pressure resistivity joint measurement system was used to measure the core resistivity under different water saturation conditions, and the water saturation, resistivity increase coefficient, and formation factor were obtained. The porosity-formation factor and water saturation-resistivity increase coefficient were fitted, and a power function relationship was established to determine the rock electrical parameters. , , , ,like Figure 7 and Figure 8 As shown. Relationship between resistivity increase coefficient and water saturation:

[0076] Relationship between formation factors and porosity:

[0077] The rock NMR experiment measures the NMR signal of the hydrogen nuclei in the pore fluid in the plug rock sample and determines the transverse relaxation time which is closely related to the change of signal intensity and pore structure. The distribution of the core is important for evaluating the pore structure of the rock. Due to the high porosity of the core, the size of the void space in the rock sample is widely distributed. In order to prevent signal loss and keep the instrument stable during the test, the MicroMR02-040V nuclear magnetic resonance imaging system is used to set the echo interval time. 0.3ms, the number of collected echo strings NECH is 15000, and the waiting time The scanning time is 5000ms and the number of scans is 16. 120 cores NMR Distribution spectrum distribution Fig. 9 shown.

[0078] S2. Based on the core test results of step S1, Distribution spectrum, according to NMR The cores are classified according to the different distribution ranges of the distribution spectrum. From the distribution spectrum, type I samples are mainly distributed in the range of 100-300ms, with the peak concentrated around 150ms; type II samples are mainly distributed in the range of 30-100ms, with the peak concentrated around 50ms; type III samples are mainly distributed in the range of 6-30ms, with the peak concentrated around 20ms. Fig.10 shown.

[0079] S3. Select cores of the same type based on the core classification results, calculate the fluid index of each core based on the porosity and permeability of each core, and establish a core type classification standard based on the fluid index.

[0080] Corresponding to the same type of core, The values ​​are concentrated in a certain range, and the same type of cores are statistically determined Upper and lower limits of values, different types of cores The core of type I corresponds to the higher value, ≥15, the permeability is high, the core seepage capacity is good, and the porosity structure is good; Type II core corresponds to medium Value, 15> >12, between Class I and Class III, the core physical properties are medium; Class III core corresponds to a lower FI value, 12≤ , low permeability, generally high mud content, and poor pore connectivity.

[0081] S4. According to Based on the three-category classification results, all 120 cores were classified into corresponding categories Ⅰ, Ⅱ, and Ⅲ, and the resistivity increase coefficient was re-established. and water saturation The correlation coefficient has obviously improved, which can better reflect the resistivity increase coefficient. and water saturation relationship, such as Fig.11 As shown, the classification is as follows: Category I:

[0082] Category II:

[0083] Category III:

[0084] Re-establishing the stratigraphic factors and porosity The correlation coefficient has improved significantly, which can better reflect the formation factors. and porosity relationship, such as Fig.12 As shown, the classification is as follows: Category I:

[0085] Category II:

[0086] Category III:

[0087] After the cores were classified, the correlation between resistivity, saturation and porosity became better. Based on the above analysis results, the classification criteria for different types and the selected rock electrical parameters were determined as shown in Table 1.

[0088] Table 1

[0089] S5. Calculate the porosity of the target reservoir based on the target reservoir logging curve data, calculate the permeability of the target reservoir based on the porosity of the target reservoir, calculate the fluid index of the target reservoir based on the porosity and permeability of the target reservoir, and determine the type of the target reservoir based on the core type classification standard according to the fluid index.

[0090] The ultra-shallow undiagenesized natural gas reservoir in the Lingshui 36-1 block in this embodiment is characterized by high formation water mineralization, high mud content, and sandstone and mudstone heterogeneity. Neutron and density logging are not affected by mud distribution and compaction degree, but are sensitive to the influence of mud. Therefore, the neutron-density intersection method is used to calculate the porosity of the target reservoir, and corresponding mud content correction is performed at the same time.

[0091] When calculating the porosity of the target reservoir, since the ultra-shallow undiagenesized natural gas reservoir in the Lingshui 36-1 block in this embodiment is a new reservoir, =3.7.

[0092] The reservoir permeability is calculated using the core pore-permeability fitting formula. According to the porosity and permeability parameters of the artificial core measured in step S1 that meet the characteristics of the ultra-shallow undiagenerated natural gas reservoir in the sea area, a porosity-permeability relationship curve is established, and the formation permeability is calculated based on the fitting curve. The permeability is obtained based on the porosity-permeability relationship fitting formula.

[0093]

[0094] Specifically, the porosity, permeability and other parameters of the X1 well in the Lingshui 36-1 block and the classification results are shown in Figure 13. The first track in the figure is the depth track. The ultra-shallow undiagenetic natural gas reservoir in the sea area is usually within 500m of the seabed. The depth in the figure is the sea level depth; the second track is the natural GR curve; the third track is the deep and shallow resistivity curves; the fourth track is the neutron porosity logging curve and the density porosity logging curve; the fifth track is the permeability curve calculated based on the porosity-permeability relationship fitting formula; the sixth track is the porosity curve and lithology profile curve calculated based on the porosity calculation formula of the target reservoir; the seventh track is the different reservoir types calculated and classified.

[0095] S6. Calculate the gas saturation of this type of reservoir based on the reservoir classification result and rock electrical parameters in step S5 in combination with Archie's formula.

[0096] Specifically, according to the Waxman-Smits model, the conductivity of argillaceous sandstone is considered to be the result of the combined effect of the conductivity of free formation water in the rock pores and the conductivity of cation exchange related to clay. Under the condition of low-mineralization equilibrium solution, the formation conductivity will be affected by both mud and formation water at the same time, and the conductivity of argillaceous sandstone is nonlinear. When the solution mineralization exceeds 20200ppm, the cation exchange mobility will reach a constant (maximum value), the conductivity of formation water will increase, the proportion of additional conductivity contribution of mud will decrease, and the conductivity of argillaceous sandstone will be linear and parallel to the pure sandstone line. At this time, Archie's formula is still applicable to argillaceous sandstone reservoirs. According to the results of the target layer water analysis and testing data of Lingshui 36-1 block, the formation water mineralization of the ultra-shallow undiagenetic natural gas reservoir in the South China Sea is 35000ppm. Therefore, Archie's formula can be used for saturation evaluation.

[0097] Specifically, the rock electrical parameters determined according to the porosity-formation factor and water saturation-resistivity increase coefficient relationship obtained in step S1 are: =1.0, =1.0, =1.51, =2.17, Archie formula and Simendan formula with unified parameters were used to calculate the saturation of the entire well section of Well X1. The calculation results are as follows Fig.14 As shown. The first to sixth paths in the figure are Fig. 9 The seventh track is the water saturation curve of the entire well section of Well X1 calculated using the Simen formula, Archie formula, and rock electrical parameters obtained from closed coring; the eighth track is the logging interpretation conclusion.

[0098] The calculation results show that the rock electrical parameters determined based on the experimental results of artificial rock samples are: m=1.511, n=2.17. The sandstone and mudstone heterogeneous reservoirs have a greater impact. For the low-resistance reservoir section, the water saturation calculated by the traditional Archie formula is too high. Although the Simmen formula can eliminate the influence of the additional conductivity of mud on the formation resistivity to a certain extent through mud correction, in actual application, the accuracy of saturation calculation is limited due to model assumptions and parameter selection. On the one hand, the Simmen formula assumes that mud contains oil, gas and water like pure sandstone, and the pore bound water is considered to be free water. After mud correction, this part of water is subtracted, and the calculated water saturation is too low. On the other hand, rock electrical parameters often use empirical values ​​or values ​​directly obtained from rock electrical experiments, rather than rock electrical parameter values ​​that eliminate the influence of mud conductivity.

[0099] Specifically, the saturation results of well X1 are calculated as follows: Fig.15 As shown. The first to seventh tracks in the figure are Fig.14 The eighth track is the water saturation curve calculated by the method and system of the present application, and the saturation curve calculated by the experimental results obtained by closed coring; the ninth track is the difference between the results of the two saturation calculation methods; and the tenth track is the logging interpretation conclusion. By comparing the calculation results of different reservoir sections, it can be obtained that compared with the closed coring results, the water saturation calculated for Class I reservoirs is lower, the water saturation calculated for Class II reservoirs is equivalent to it, and the water saturation calculated for Class III reservoirs is higher. The method and system of the present application improves the gas saturation of Class I high-quality reservoirs and reduces the saturation of Class III relatively low-quality reservoirs. Compared with the actual formation test results, the saturation calculation results show that Class I reservoirs have the best porosity and permeability relationship, good pore connectivity, easy gas filling, and higher gas saturation. The method and system of the present application obtain the rock electrical parameters of different reservoir types through fine classification of reservoirs, and calculate the saturation based on the Archie formula, realizing the fine interpretation and evaluation of the gas saturation of ultra-shallow undiagenetic reservoirs in the sea.

[0100] The above embodiments are used to explain the present invention rather than to limit the present invention. Any modification and change made to the present invention within the spirit of the present invention and the protection scope of the claims shall fall within the protection scope of the present invention.

Claims

1. A classification, interpretation and evaluation method for fluid saturation of ultra-shallow undiagenetic reservoirs in the sea, characterized in that: The steps are: Data acquisition steps: Obtaining artificial core rock physics experimental results and target reservoir logging curve data that meet the characteristics of ultra-shallow undiagenetic target reservoirs in the sea area; the experimental results include nuclear magnetic resonance Distribution spectrum, porosity, permeability, water saturation, resistivity increase coefficient, formation factor; Core classification steps: Based on NMR The cores are classified according to the different intervals of the distribution spectrum; Steps for constructing the classification standard: select cores of the same type according to the core classification results, calculate the fluid index of each core according to the porosity and permeability of each core, and establish the core type classification standard according to the fluid index; The steps of determining rock electrical parameters are as follows: for the same type of cores, the fitting relationship between resistivity increase coefficient and water saturation, formation factor and porosity is established, and the rock electrical parameters corresponding to the same type of cores are obtained according to the fitting relationship; Reservoir type determination steps: calculating the porosity of the target reservoir according to the target reservoir logging curve data, calculating the permeability of the target reservoir according to the porosity of the target reservoir, calculating the fluid index of the target reservoir according to the porosity and permeability of the target reservoir, and determining the target reservoir type based on the core type classification standard according to the fluid index; Saturation calculation steps: determine the rock electrical parameters corresponding to the target reservoir according to the reservoir type to which the target reservoir belongs, and calculate the water saturation of the target reservoir according to the rock electrical parameters of the target reservoir.

2. The method for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area as claimed in claim 1, characterized in that: In the data acquisition step, the method for obtaining the rock physics experimental results of artificial cores of ultra-shallow undiagenetic target reservoir characteristics in the sea area is: Produce artificial cores that meet the reservoir characteristics of ultra-shallow undiagenetic targets in the sea area; Measure the porosity and permeability of artificial cores under set temperature conditions; Artificial core saturation is performed using brine with a set salinity; The saturated artificial core was placed in the nuclear magnetic resonance imaging system, and the echo interval, waiting time, number of echo trains collected and scanning times were set to measure the magnetic resonance. Distribution spectrum; Under formation conditions, the core resistivity and water saturation under different water saturation conditions are measured through displacement experiments, and the resistivity increase coefficient and formation factor are calculated based on the core resistivity.

3. The method for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area as claimed in claim 2, characterized in that: The resistivity increase coefficient is calculated according to the core resistivity by using the resistivity increase coefficient calculation formula; In the formula, is the core resistivity enhancement factor, is the core resistivity after displacement, is the core resistivity at saturation.

4. The method for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area as claimed in claim 2, characterized in that: The formation factor is calculated according to the core resistivity using the formation factor calculation formula; In the formula, is the formation factor of the core, is the core resistivity at saturation, is the resistivity of the saturated solution.

5. The method for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area as claimed in claim 1, characterized in that: In the step of constructing the classification standard, the fluid index of the core is calculated according to the porosity and permeability of the core by using a fluid index calculation formula; In the formula, is the fluid index of the core, is the permeability of the core, is the porosity of the core.

6. The method for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area as claimed in claim 1, characterized in that: In the rock electrical parameter determination step, the fitting relationship between the resistivity increase coefficient and the water saturation is expressed as: In the formula, is the core resistivity enhancement factor, is the lithology parameter, The water saturation of the core, is the saturation index; The fitting relationship between formation factor and porosity is expressed as: In the formula, is the formation factor of the core, is the lithology parameter, is the porosity of the core, is the cementation index.

7. The method for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area as claimed in claim 1, characterized in that: In the reservoir type determination step, the method for calculating the porosity of the target reservoir according to the target reservoir logging curve data is: Calculate the relative value of natural gamma; In the formula, is the relative value of natural gamma; is the natural gamma logging value of the target layer, unit: API; It is the natural gamma logging value of pure lithologic formation, unit: API; is the natural gamma logging value of pure mudstone formation, unit: API; Calculate reservoir mud content based on relative value of natural gamma; In the formula, is the reservoir mud content, is the empirical coefficient related to the stratigraphic age; According to the reservoir shale content, the density porosity corrected by shale and the neutron porosity corrected by shale are calculated respectively; In the formula, It is the density porosity after mud correction, unit: decimal; is the neutron porosity after shale correction, unit: decimal; is the density of the rock skeleton, unit: g / cm 3 ; is the density of the formation fluid, unit: g / cm 3 ; is the density of mudstone, unit: g / cm 3 ; is the target layer density logging value, unit: g / cm 3 ; is the neutron value of the rock skeleton, unit: %; is the neutron value of the formation fluid, unit: %; is the neutron value of mudstone, unit: %; is the neutron logging value of the target layer, unit: %; is the reservoir mud content, unit: decimal; Calculate the target reservoir porosity based on the density porosity corrected by shale and the neutron porosity corrected by shale; In the formula, is the target reservoir porosity.

8. The method for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area as claimed in claim 1, characterized in that: In the reservoir type determination step, the method for calculating the target reservoir permeability according to the target reservoir porosity is: According to the porosity and permeability of the artificial core in the data acquisition step, a porosity-permeability fitting relationship is established; The permeability of the target reservoir is calculated based on the porosity of the target reservoir through the porosity-permeability fitting relationship.

9. The method for classifying, interpreting and evaluating fluid saturation of ultra-shallow undiagenetic reservoirs in the sea area as claimed in claim 1, characterized in that: In the saturation calculation step, the water saturation of the target reservoir is calculated by using the Archie formula according to the determined rock electrical parameters; In the formula, is the water saturation of the target reservoir, is the lithology parameter, is the cementation index, is the saturation index, is the target reservoir porosity, is the formation water resistivity, is the target reservoir resistivity logging value.

10. A classification, interpretation and evaluation system for fluid saturation of ultra-shallow undiagenetic reservoirs in marine areas, used to implement the classification, interpretation and evaluation method for fluid saturation of ultra-shallow undiagenetic reservoirs in marine areas as claimed in any one of claims 1 to 9, characterized in that: include: The data acquisition module is used to obtain the rock physics experimental results of artificial cores and the logging curve data of the target reservoir that are consistent with the characteristics of the ultra-shallow undiagenetic target reservoir in the sea area; Core classification module, based on NMR The cores are classified according to the different intervals of the distribution spectrum; The classification standard construction module selects cores of the same type according to the core classification results, calculates the fluid index of each core according to the porosity and permeability of each core, and establishes the core type classification standard based on the fluid index; The rock electrical parameter determination module establishes the fitting relationship between the resistivity increase coefficient and water saturation, the formation factor and the porosity of the target layer for the same type of cores, and obtains the rock electrical parameters corresponding to the same type of cores based on the fitting relationship; A reservoir type determination module calculates the porosity of the target reservoir according to the target reservoir logging curve data, calculates the permeability of the target reservoir according to the porosity of the target reservoir, calculates the fluid index of the target reservoir according to the porosity and permeability of the target reservoir, and determines the target reservoir type based on the core type classification standard according to the fluid index; The saturation calculation module determines the rock electrical parameters corresponding to the target reservoir according to the reservoir type to which the target reservoir belongs, and calculates the water saturation of the target reservoir according to the rock electrical parameters of the target reservoir.

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