A qualitative evaluation method and system for oil-bearing property of a heterogeneous reservoir

Abstract

This invention relates to the technical field of reservoir oil-bearing evaluation methods, and discloses a qualitative evaluation method and system for the oil-bearing properties of heterogeneous reservoirs. The qualitative evaluation method for the oil-bearing properties of heterogeneous reservoirs introduces the natural gamma coefficient of variation V. GR This method characterizes the heterogeneity of reservoirs caused by mudstone interlayers. By combining arrayed induced resistivity (RT) and natural gamma (GR) to establish cross plots, the impact of reservoir heterogeneity on oil-bearing evaluation is reduced to some extent, thereby improving the reliability of oil-bearing evaluation for heterogeneous reservoirs. In addition, through actual data statistics and cross plot analysis, combined with well types and sand body structure models, this method establishes an oil-bearing evaluation standard table, making the method highly operable and practical in actual applications. This improves the reliability of oil-bearing evaluation for heterogeneous reservoirs and provides methodological support for reservoir development and reserve upgrading.

Description

Technical Field

[0001] This invention belongs to the technical field of reservoir oil-bearing evaluation methods, specifically relating to a qualitative evaluation method and system for the oil-bearing properties of heterogeneous reservoirs. Background Technology

[0002] Reservoir oil content indicates the amount of oil in a reservoir and is an important indicator of the degree of oil enrichment. The degree of oil and gas enrichment directly affects the exploration and development results of an oilfield.

[0003] Currently, reservoir oil-bearing evaluation methods are divided into qualitative and quantitative analysis methods. Qualitative analysis methods include overlay plots and cross-plots, while quantitative analysis methods mainly use the calculation of oil saturation as the primary parameter. Methods include mercury intrusion porosimetry, quantitative logging data analysis (Archie's formula method), nuclear magnetic resonance (NMR), and direct core analysis. Compared to quantitative methods, quantitative analysis methods can directly obtain accurate values ​​for oil-bearing assessment. However, in reservoirs with complex lithology and high heterogeneity, the influence of multiple factors can reduce the reliability of oil-bearing evaluation. While qualitative evaluation methods do not directly calculate relevant parameter values, they are simple and easy to implement, offering advantages for analyzing complex lithology and highly heterogeneous reservoirs. They allow for faster selection of relevant parameters for identification. Cross-plots, in particular, can analyze multi-well logging data and summarize relevant information from multiple wells in a graph, intuitively and conveniently reflecting the range of oil-bearing characteristic parameters. However, reservoirs are often affected by sedimentary hydrodynamics. The inclusion of mudstone in the reservoir results in significant differences in oil and gas accumulation, which in turn affects the oil-bearing properties of the reservoir. This leads to increased heterogeneity in oil-bearing properties, making it difficult to increase development and reserves.

[0004] Therefore, in highly heterogeneous reservoirs, how to characterize the degree of variation of mudstone interlayers and evaluate the oil-bearing properties of heterogeneous reservoirs has become a problem that needs to be solved. Summary of the Invention

[0005] The purpose of this invention is to overcome the above-mentioned problems and provide a qualitative evaluation method and system for the oil-bearing properties of heterogeneous reservoirs. This method can reduce the impact of reservoir heterogeneity on oil-bearing property evaluation, improve the reliability of oil-bearing property evaluation of heterogeneous reservoirs, and provide methodological support for reservoir development and reserve upgrading.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for qualitative evaluation of the oil-bearing capacity of heterogeneous reservoirs, comprising the following steps: Select the study area; The selected study area will be classified into different types of test wells based on the oil production volume of the test wells. Select natural gamma GR and natural gamma coefficient of variation VGR The array induced resistivity RT is used as the core logging parameter to characterize the oil-bearing capacity of the reservoir and the oil production of the test production. The core logging parameters are statistically analyzed to obtain the statistical core logging parameters. A cross plot was created by combining the types of test wells and the core logging parameters obtained from the statistics, and the parameter range for the cross plot was selected. Based on the selected cross plot parameter range, the identification rate between the test well category and the cross plot parameter range is obtained, and the parameters with high identification rates are selected as evaluation parameters. Within the parameters of the cross plot, representative sand body structures are selected based on the type of test well, and a sand body structure model is established. An oil-bearing evaluation standard table was established by combining the types of test wells, core logging parameters, cross plot parameter ranges, evaluation parameters, and sand body structure models.

[0007] A further improvement of the present invention is that, in the step of selecting the study area, reservoirs with reservoir heterogeneity greater than a preset value, without proven reserves and without development or utilization are selected as the study area.

[0008] A further improvement of the present invention is that, in the step of classifying the selected study area into test well categories based on the test production, the test well categories are divided into three categories: Category I wells are wells with an initial daily production of more than 1 t, Category II wells are wells with an initial daily production of less than 1 t, and Category III wells are wells that produce water or no liquid during the test production.

[0009] A further improvement of the present invention is that the natural gamma variation coefficient V GR The formula is:

[0010] Among them, GR i For each depth point, the natural gamma GR value, Let represent the average GR at a certain depth, where N is the total number of samples and n is the number of points within a certain segment.

[0011] A further improvement of this invention is that, in the step of establishing a cross-plot by combining the type of test well and the core logging parameters, it specifically includes the use of natural gamma ray GR and natural gamma ray coefficient of variation V. GR A cross-plot is established by combining the array induced resistivity RT with each other.

[0012] A further improvement of this invention is that the step of selecting the cross-plot parameter range specifically includes combining the cross-plot and the type of test well, based on the natural gamma ray GR and the natural gamma ray coefficient of variation V. GR The distribution of standard data points of the array induced resistivity RT on the cross plot is analyzed, intervals are divided, and interval parameters are recorded.

[0013] A further improvement of this invention is that the identification rate of the test well category and the cross-plot parameter range is:

[0014] Among them, K i N represents the degree to which each type of test well is identified within the parameter range. i n represents the total number of test wells of a certain type. i This refers to the number of parameters for a certain type of pilot well within its parameter value range.

[0015] Secondly, the present invention provides a qualitative evaluation system for the oil-bearing properties of heterogeneous reservoirs, comprising the following modules: The study area selection module is used to select a study area. The classification module is used to classify the selected study area into different categories of test wells based on the oil production of the test wells. The well logging parameter selection module is used to select natural gamma ray (GR) and natural gamma ray coefficient of variation (V). GR The array induced resistivity RT is used as the core logging parameter to characterize the oil-bearing capacity of the reservoir and the oil production of the test production. The core logging parameters are statistically analyzed to obtain the statistical core logging parameters. The cross plot creation module is used to create cross plots by combining the type of test well and the core logging parameters, and to select the range of cross plot parameters; The identification rate determination module is used to obtain the identification rate of the test well category and the cross plot parameter range based on the selected cross plot parameter range, and select the parameters with high identification rates as evaluation parameters. The model building module is used to select representative sand body structures within the cross plot parameter range and in combination with the type of test well to build a sand body structure model; The standard table creation module is used to create an oil-bearing evaluation standard table by combining the type of test well, core logging parameters, cross plot parameter range, evaluation parameters, and sand body structure model.

[0016] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a qualitative evaluation method for the oil content of heterogeneous reservoirs.

[0017] Fourthly, the present invention provides a storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of a qualitative evaluation method for the oil content of heterogeneous reservoirs.

[0018] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a qualitative evaluation method for the oil-bearing properties of heterogeneous reservoirs, by introducing the natural gamma variability coefficient V. GRThis method characterizes the heterogeneity of reservoirs caused by mudstone interlayers. By combining arrayed induced resistivity (RT) and natural gamma (GR) to establish cross plots, the impact of reservoir heterogeneity on oil-bearing evaluation is reduced to some extent, thereby improving the reliability of oil-bearing evaluation for heterogeneous reservoirs. In addition, through actual data statistics and cross plot analysis, combined with well types and sand body structure models, this method establishes an oil-bearing evaluation standard table, making the method highly operable and practical in actual applications. This improves the reliability of oil-bearing evaluation for heterogeneous reservoirs and provides methodological support for reservoir development and reserve upgrading. Attached Figure Description

[0019] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of the invention in any way. Furthermore, the shapes and proportions of the components in the drawings are merely illustrative to aid in understanding the invention and do not specifically limit the shapes and proportions of the components of the invention.

[0020] Figure 1 This is a schematic diagram of the qualitative evaluation method for oil-bearing properties of heterogeneous reservoirs according to the present invention; Figure 2 This is a schematic diagram of the process of the qualitative evaluation system for the oil-bearing properties of heterogeneous reservoirs according to the present invention; Figure 3 Map showing the results of oil exploration in the W area, Chang 81. Figure 4 Interpretation diagrams of well logging results and oil-bearing evaluation parameters for wells X1, X2, and X3 with a length of 81; Figure 5(a) shows the variation coefficient of natural gamma in the Chang 81 oil layer in area W. GR Cross plot of oil content evaluation parameters in cross plot with array induced resistivity RT; Figure 5(b) is a cross-plot of oil content evaluation parameters for the Chang 81 oil layer in area W, plotted between natural gamma GR and array induced resistivity RT. Figure 6(a) shows the variation coefficient of natural gamma ray in the Chang 81 oil layer in area W. GR Oil-bearing evaluation parameters and well identification rate of test wells in the cross-plot of array induced resistivity RT; Figure 6(b) shows the oil-bearing evaluation parameters and well identification rate of the Chang 81 oil layer in the W area in the cross plot of natural gamma GR and array inductive resistivity RT. Figure 7 A typical structural feature diagram of the 81-long sand body in region W; Figure 8 The evaluation standard for the oil-bearing properties of the Chang 81 oil reservoir in the W area; Figure 9 This is a system diagram for Example 4. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0022] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0023] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0024] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper," "lower," "horizontal," or "inner" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, terms such as "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0025] Furthermore, the use of the term "horizontal" does not imply that the component must be absolutely horizontal, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0026] In the description of the embodiments of the present invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention according to the specific circumstances.

[0027] The present invention will now be described in further detail with reference to the accompanying drawings: Example 1: like Figure 1 As shown, a qualitative evaluation method for the oil-bearing properties of heterogeneous reservoirs includes the following steps: S1, Select the study area. The study area should be selected from areas with many well locations, complete logging data, and oil reservoirs that are difficult to upgrade or difficult to exploit. S2. Based on the oil production of the trial production, the selected trial production exploration wells are divided into three categories: Category I wells (initial daily production greater than 1t), Category II wells (initial daily production less than 1t), and Category III wells (trial production with water or no liquid). S3, Select core logging parameters and compile statistics; To reduce potential errors in interpreting logging parameters for reservoirs with different lithologies, array resistivity RT, which is more sensitive to fluid properties, was selected as the primary parameter. Natural gamma ray spectroscopy (GR) was used as the primary parameter for clay content, and the coefficient of variation (V) of natural gamma ray spectroscopy was used for clay interlayers within the oil reservoir. GR As a key parameter, it reflects the heterogeneity of the oil reservoir. Natural gamma variation coefficient V GR The formula is:

[0028] Among them, GR i For each depth point, the natural gamma GR value, GR is the average value of GR at a certain depth segment, N is the total number of samples, and n is the number of points in a certain segment; The core logging parameters of the oil-bearing sections of the test production wells were statistically analyzed to obtain the statistical core logging parameters. S4, combining the test well category and the core logging parameters, constructs a cross plot by combining them in pairs, and selects the parameter range for the cross plot. Specifically, this includes combining the cross plot and the test well category, based on the natural gamma ray GR and the natural gamma ray coefficient of variation V. GR The distribution of standard data points of array induced resistivity RT on the cross plot is analyzed, intervals are divided, and interval parameters are recorded. S5. Based on the selected cross-plot parameter range, the identification rate between the test well category and the cross-plot parameter range is obtained, and the parameters with high identification rates are selected as evaluation parameters. The identification rate of the verification test well category and the cross-plot parameter range is:

[0029] Among them, K i N represents the degree to which each type of test well is identified within the parameter range. i n represents the total number of test wells of a certain type. i For a certain type of pilot well, the number of parameters within the range of values; S6. Within the range of cross plot parameters, select representative sand body structures based on the type of test wells and establish a sand body structure model, which mainly includes lithological sand body structures. S7. An oil-bearing evaluation standard table is established by combining the type of test well, core logging parameters, cross plot parameter range, evaluation parameters, and sand body structure model.

[0030] Example 2: like Figure 2 As shown, a qualitative evaluation system for the oil-bearing properties of heterogeneous reservoirs includes the following modules: The study area selection module is used to select a study area. The classification module is used to classify the selected study area into different categories of test wells based on the oil production of the test wells. The well logging parameter selection module is used to select natural gamma ray (GR) and natural gamma ray coefficient of variation (V). GR The array induced resistivity RT is used as the core logging parameter to characterize the oil-bearing capacity of the reservoir and the oil production of the test production. The core logging parameters are statistically analyzed to obtain the statistical core logging parameters. The cross plot creation module is used to create cross plots by combining the type of test well and the core logging parameters, and to select the range of cross plot parameters; The identification rate determination module is used to obtain the identification rate of the test well category and the cross plot parameter range based on the selected cross plot parameter range, and select the parameters with high identification rates as evaluation parameters. The model building module is used to select representative sand body structures within the cross plot parameter range and in combination with the type of test well to build a sand body structure model; The standard table creation module is used to create an oil-bearing evaluation standard table by combining the type of test well, core logging parameters, cross plot parameter range, evaluation parameters, and sand body structure model.

[0031] Example 3: S1, selecting reservoirs with simple sedimentary structures, strong reservoir heterogeneity, numerous exploration, assessment, development, and testing wells, and no submitted proven reserves that have not yet been developed or utilized as the study area, such as... Figure 3 The map shown is a map of the oil exploration results in area W, section 81. S2 classifies the same production layer of exploration, evaluation, development and production wells into three categories based on the statistics of initial oil production (the average oil production in the first three months after production): Category I (initial daily oil production > 1t), Category II (initial daily oil production < 1t), and Category III (test production with water or no liquid).

[0032] S3, by comparing the production output and logging parameters of the development well, selected natural gamma ray GR and natural gamma ray coefficient of variation V. GRThe natural gamma ray GR and the array induction resistivity RT are the core logging parameters for characterizing the oil-bearing property of the reservoir and the oil production during the test production. Among them, the natural gamma ray GR characterizes the shale content, and the coefficient of variation of natural gamma ray V GR characterizes the intensity of heterogeneity in the reservoir, and the array induction resistivity RT characterizes the fluid property in the oil layer. The coefficient of variation of natural gamma ray V GR The formula is:

[0033] Where, GR i is the natural gamma ray GR value at each depth point, is the average value of GR in a certain depth interval, N is the total number of samples, and n is the number of points in a certain segment.

[0034] From Figure 4 it can be seen that in the presence of shale interlayers, the oil-bearing property of pure sandstone is better. Well X1 has no sediment interlayers, and the initial daily oil production is 2.1 t. The coefficient of variation of natural gamma ray V GR is 0.08. Well X2 has fewer sediment interlayers, and the initial daily oil production is 1.38 t. The coefficient of variation of natural gamma ray V GR is 0.118. Well X3 has more sediment interlayers, with stronger heterogeneity and overall non-uniformity. The initial daily oil production is 0 t. The coefficient of variation of natural gamma ray V GR is 0.18. From this, it can be seen that the coefficient of variation of natural gamma ray V GR has a linear relationship with the sediment interlayers.

[0035] S4. By pairwise plotting crossplots of the natural gamma ray GR, the coefficient of variation of natural gamma ray V GR and the array induction resistivity RT, and using different colors to represent the three types of development test production wells divided in S2 in the plotted crossplots, determine the parameter crossplot intervals according to the scatter distribution. As shown in Figures 5(a) and 5(b), taking the W1 study area as an example, through pairwise crossplotting of logging parameters and combining with the categories of development test production wells, it is obtained that for Type I, RT > 32 Ωm, V GR < 0.115, GR < 86; for Type II, 28 Ωm < RT < 32 Ωm, 0.115 < V GR < 0.13, 86 < GR < 94; for Type III, RT < 28 Ωm, V GR > 0.13, GR > 94.

[0036] S5. Verify the recognition rate Ki of the test production well categories in the parameter crossplot intervals. The recognition rate Ki indicates whether the three types of test production wells in S2 can be recognized within the value ranges obtained in S4. The formula for verifying the recognition rate of the test production well categories and the parameter ranges of the crossplot is:

[0037] Among them, K i N represents the degree to which each type of test well is identified within the parameter range. i n represents the total number of test wells of a certain type. i This refers to the number of parameters for a certain type of pilot well within its parameter value range.

[0038] As shown in Figure 6(a), the natural gamma coefficient of variation V GR In the cross plot of natural gamma ray (GR) and array induced resistivity (RT), the identification rate of Class I wells is 74%, that of Class II wells is 73%, and that of Class III wells is 100%. As shown in Figure 6(b), in the cross plot of natural gamma ray (GR) and array induced resistivity (RT), the identification rate of Class I wells is 69%, that of Class II wells is 67%, and that of Class III wells is 80%. From Figures 6(a) and 6(b), it can be seen that the natural gamma ray coefficient of variation V... GR The cross plots of array induced resistivity RT and natural gamma ray GR and array induced resistivity RT show a high identification rate for Class I and Class II wells. Therefore, the parameter ranges in these two cross plots are selected as the values ​​for oil-bearing evaluation parameters.

[0039] S6, through statistical analysis of the data in S2 and S4, establishes a sand body structure model, such as... Figure 7 As shown, representative sand body structures were selected, and sand body structure models were established. Based on reservoir combination type and oil-bearing logging parameter range, they were divided into three categories. Among them, Category I sand bodies are thick oil layers with the best oil-bearing properties and the highest oil production; Category II sand bodies are a combination of thick oil layers and thin dry layers, with poorer oil-bearing properties and moderate oil production compared to Category I; Category III is a combination of thin oil layers, medium-thickness oil layers, and dry layers, with the worst oil-bearing properties and the lowest oil production.

[0040] S7, combining the types of test wells, core logging parameters, cross-plot parameter ranges, evaluation parameters, and parameter value ranges in the sand body structure model, establishes an oil-bearing evaluation standard table for the reservoir, such as... Figure 8 As shown, the oil-bearing evaluation parameters are divided into three categories: Category I reservoirs have weak heterogeneity and good oil production; Category II reservoirs have moderate heterogeneity and moderate oil production; and Category III reservoirs have strong heterogeneity and poor oil production.

[0041] Example 4: Please see Figure 9 As shown, the present invention also provides an electronic device 100 for a qualitative evaluation method of oil-bearing properties in heterogeneous reservoirs; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0042] The memory 101 can be used to store the computer program 103. The processor 102 implements the steps of the qualitative evaluation method for the oil content of heterogeneous reservoirs described in Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0043] The at least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor. The processor 102 is the control center of the electronic device 100, connecting various parts of the electronic device 100 via various interfaces and lines.

[0044] The memory 101 in the electronic device 100 stores multiple instructions to implement a qualitative evaluation method for the oil-bearing properties of heterogeneous reservoirs, and the processor 102 can execute the multiple instructions to achieve the following: Select the study area; The selected study area will be classified into different types of test wells based on the oil production volume of the test wells. Select natural gamma GR and natural gamma coefficient of variation V GR The array induced resistivity RT is used as the core logging parameter to characterize the oil-bearing capacity of the reservoir and the oil production of the test production. The core logging parameters are statistically analyzed to obtain the statistical core logging parameters. A cross plot was created by combining the types of test wells and the core logging parameters obtained from the statistics, and the parameter range for the cross plot was selected. Based on the selected cross plot parameter range, verify the recognition rate between the test well category and the cross plot parameter range, and select the parameters with high recognition rate as evaluation parameters; Within the parameters of the cross plot, representative sand body structures are selected based on the type of test well, and a sand body structure model is established. An oil-bearing evaluation standard table was established by combining the types of test wells, core logging parameters, cross plot parameter ranges, evaluation parameters, and sand body structure models.

[0045] Example 5: If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0046] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0047] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0048] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0049] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

[0051] Many embodiments and applications beyond the examples provided will be apparent to those skilled in the art upon reading the foregoing description. Therefore, the scope of this teaching should not be determined by reference to the foregoing description, but rather by reference to the foregoing claims and the full scope of their equivalents. For purposes of completeness, all articles and references, including patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the foregoing claims is not intended as a waiver of that subject matter, nor should it be construed as an indication that the applicant has not considered that subject matter as part of the disclosed inventive subject matter.

[0052] The above content provides a further detailed description of the present invention. It should not be construed that the specific embodiments of the present invention are limited to this. For those skilled in the art, several simple deductions or substitutions can be made without departing from the concept of the present invention, and all such deductions or substitutions should be considered to fall within the scope of protection of the present invention as defined by the submitted claims.

Claims

1. A method for qualitative evaluation of the oil-bearing properties of heterogeneous reservoirs, characterized in that, Includes the following steps: Select the study area; The selected study area will be classified into different types of test wells based on the oil production volume of the test wells. Select natural gamma GR and natural gamma coefficient of variation V GR The array induced resistivity RT is used as the core logging parameter to characterize the oil-bearing capacity of the reservoir and the oil production of the test production. The core logging parameters are statistically analyzed to obtain the statistical core logging parameters. A cross plot was created by combining the types of test wells and the core logging parameters obtained from the statistics, and the parameter range for the cross plot was selected. Based on the selected cross plot parameter range, verify the recognition rate between the test well category and the cross plot parameter range, and select the parameters with high recognition rate as evaluation parameters; Within the parameters of the cross plot, representative sand body structures are selected based on the type of test well, and a sand body structure model is established. An oil-bearing evaluation standard table was established by combining the types of test wells, core logging parameters, cross plot parameter ranges, evaluation parameters, and sand body structure models.

2. The method for qualitative evaluation of oil-bearing properties in heterogeneous reservoirs according to claim 1, characterized in that, In the step of selecting the study area, reservoirs with reservoir heterogeneity greater than a preset value, without proven reserves, and without development or utilization are selected as the study area.

3. The method for qualitative evaluation of oil-bearing properties in heterogeneous reservoirs according to claim 1, characterized in that, In the step of classifying the selected study area into test well categories based on the test production, the test wells are divided into three categories: Category I wells are those with an initial daily production of more than 1 t, Category II wells are those with an initial daily production of less than 1 t, and Category III wells are those with water or no liquid produced during the test.

4. The method for qualitative evaluation of oil-bearing properties in heterogeneous reservoirs according to claim 1, characterized in that, The natural gamma variation coefficient V GR The formula is: Among them, GR i For each depth point, the natural gamma GR value, Let represent the average GR value at a certain depth, where N is the total number of samples and n is the number of points within a certain segment.

5. The method for qualitative evaluation of oil-bearing properties in heterogeneous reservoirs according to claim 1, characterized in that, The step of establishing a cross-plot by combining the type of test well and the core logging parameters statistically includes, in particular, the analysis of natural gamma ray GR and natural gamma ray coefficient of variation V. GR A cross-plot is established by combining the array induced resistivity RT with each other.

6. The method for qualitative evaluation of oil-bearing properties in heterogeneous reservoirs according to claim 1, characterized in that, The step of selecting the cross plot parameter range specifically includes combining the cross plot and the type of test well, based on the natural gamma ray GR and the natural gamma ray coefficient of variation V. GR The distribution of standard data points of the array induced resistivity RT on the cross plot is analyzed, intervals are divided, and interval parameters are recorded.

7. The method for qualitative evaluation of oil-bearing properties in heterogeneous reservoirs according to claim 1, characterized in that, The identification rate of the verification test well category and the cross-plot parameter range is: Among them, K i N represents the degree to which each type of test well is identified within the parameter range. i n represents the total number of test wells of a certain type. i This refers to the number of parameters for a certain type of pilot well within its parameter value range.

8. A qualitative evaluation system for the oil-bearing properties of heterogeneous reservoirs, characterized in that, Includes the following modules: The study area selection module is used to select a study area. The classification module is used to classify the selected study area into different categories of test wells based on the oil production of the test wells. The well logging parameter selection module is used to select natural gamma ray (GR) and natural gamma ray coefficient of variation (V). GR The array induced resistivity RT is used as the core logging parameter to characterize the oil-bearing capacity of the reservoir and the oil production of the test production. The core logging parameters are statistically analyzed to obtain the statistical core logging parameters. The cross plot creation module is used to create cross plots by combining the type of test well and the core logging parameters, and to select the range of cross plot parameters; The identification rate determination module is used to obtain the identification rate of the test well category and the cross plot parameter range based on the selected cross plot parameter range, and select the parameters with high identification rates as evaluation parameters. The model building module is used to select representative sand body structures within the cross plot parameter range and in combination with the type of test well to build a sand body structure model; The standard table creation module is used to create an oil-bearing evaluation standard table by combining the type of test well, core logging parameters, cross plot parameter range, evaluation parameters, and sand body structure model.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the qualitative evaluation method for the oil-bearing properties of heterogeneous reservoirs as described in any one of claims 1 to 7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the qualitative evaluation method for the oil-bearing properties of heterogeneous reservoirs as described in any one of claims 1 to 7.

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