Porosity 3D modeling method, system, medium and equipment for carbonate reservoirs

Abstract

The invention discloses a three-dimensional porosity modeling method, system, medium and equipment for carbonate reservoirs, and relates to the technical field of oil and gas exploration and development. The method comprises: using multi-source information of geological exploration data, well logging data and seismic exploration data, and constructing an initial three-dimensional porosity model by interpolation method; analyzing the influence of different diagenesis on porosity of carbonate reservoirs, and determining the diagenetic transformation coefficients corresponding to different diagenesis, wherein the diagenetic transformation coefficient is the ratio of the porosity of carbonate rock after diagenesis to the porosity without diagenesis; introducing the diagenetic transformation coefficient as a key parameter into the initial porosity model to obtain an optimized three-dimensional porosity model; and adjusting the optimized three-dimensional porosity model by stratification and partition according to the type, intensity and distribution characteristics of formation diagenesis to obtain a final three-dimensional porosity model. The invention can accurately describe the heterogeneity of carbonate reservoirs and improve the accuracy of the model.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration and development, and in particular to a three-dimensional porosity modeling method, system, medium and equipment for carbonate reservoirs. Background Art

[0002] Carbonate reservoirs are a very important type of reservoir in oil and gas exploration and development. They usually have large reserves and high single-well production, and are easy to form large oil and gas fields. The storage space of carbonate reservoirs can be divided into porous reservoirs, fracture reservoirs, fracture-porous reservoirs, fracture-cavern reservoirs, etc. These reservoir types have their own characteristics. For example, porous reservoirs are mainly composed of various types of pores. In geology, the study of carbonate reservoirs not only includes its rock characteristics, but also involves rock physical characteristics, stratigraphic principles, diagenesis, fracture-type reservoirs and other aspects. These studies help to better identify, describe and characterize carbonate reservoirs, thereby improving the success rate of oil and gas exploration.

[0003] The geological modeling technology of carbonate reservoirs is one of the key technologies in the field of oil and gas exploration and development. With the development of technology, the existing geological modeling technology has made significant progress. Patent application CN201510458235.X discloses a three-dimensional geological modeling method for fracture-cavity carbonate oil and gas reservoirs. A. Modeling block division: first divide the fracture-cavity system; then divide the oil and gas reservoir; then divide the flow unit, and finally establish a three-dimensional geological model according to the flow unit block; B. Modeling category division: at least divide into two categories of matrix and fracture, and model step by step; C. Matrix modeling phase separation: divide the matrix into multiple reservoir types, and then divide the reservoir phase according to the reservoir type, and establish a three-dimensional geological model of each reservoir phase respectively; D. Fracture classification: classify according to different scales of fractures, and establish fracture models of different scales step by step; E. Model merging: equivalently merge the established matrix and fracture three-dimensional geological models to establish a three-dimensional geological model of fracture-cavity carbonate oil and gas reservoirs. The three-dimensional geological model established by this method can meet the needs of development plan design, development plan implementation, development dynamic analysis, etc.

[0004] Patent application CN201610152180.4 discloses a three-dimensional reservoir geological modeling method. By implementing three-dimensional seismic exploration on the surface, N exploration wells with representative significance in the same block are selected, and intensive sand dredging, conventional logging, imaging logging, VSP logging, and inter-well seismic are carried out on each exploration well to make a complete and comprehensive logging interpretation. Then, the reservoir obtained from the logging interpretation is cored on the well wall, and the cores are scanned by electron microscope, porosity is measured, and rock strain experiments are performed on the cores. Combined with the logging interpretation, a three-dimensional reservoir geological model is finally established using modeling software to achieve a comprehensive and accurate establishment of a three-dimensional reservoir geological model, thereby facilitating a detailed exploration of the basic geological information of the reservoir.

[0005] Patent application CN201810705617.1 discloses a fracture-cavity carbonate reservoir uncertainty modeling method and device thereof, which adopts a modeling method controlled by genesis, selects at least one uncertain geological parameter to perform uncertainty modeling on the first discrete distribution model of different types of reservoirs, and obtains a second discrete distribution model; the second discrete distribution model is merged to form a third discrete distribution model, and the third discrete distribution model includes a plurality of fracture-cavity reservoir three-dimensional discrete distribution models; the fracture-cavity reservoir three-dimensional discrete distribution models in the third discrete distribution model are screened to obtain a fourth discrete distribution model that retains at least one of the fracture-cavity reservoir three-dimensional discrete distribution models. This scheme takes into account the differences in reservoir scale, the influence of uncertainty, and the constraints of geological laws and genesis on the modeling process, and also avoids the problems of only establishing one model in the past, which are inconsistent with the production dynamics and connectivity, and inaccurate reserves.

[0006] Patent application CN201910138421.3 discloses a geological modeling method for carbonate fracture-cavity reservoirs, which fully considers the karst genesis type of fracture-cavity reservoirs, determines the reservoir type and distribution law according to the different karst genesis types, uses different modeling algorithms for simulation for different types of reservoirs, constructs classified reservoir models under different karst genesis backgrounds, uses different fusion methods to fuse the classified reservoirs under different genesis backgrounds, and optimizes the geological model based on a variety of production dynamic data. This method can be used to obtain a three-dimensional geological model that is more consistent with both static and dynamic data, can improve the characterization accuracy of the strong heterogeneity characteristics of fracture-cavity reservoirs, and provide a reliable geological basis for reservoir development.

[0007] Patent application CN202010277876.6 invented a method and device for dividing the internal structure of a carbonate strike-slip fault zone, which includes obtaining the characteristics of a carbonate strike-slip fault zone; the characteristics include cracks, holes and caves; and dividing the carbonate strike-slip fault zone into a first type, a second type and a third type according to the characteristics. The method and device for dividing the internal structure of a carbonate strike-slip fault zone provided by the present invention can be used to guide drilling trajectory design and adjustment and optimization during drilling, while optimizing drilling fluid, realizing early prediction of complex working conditions, and ensuring well control safety by dividing the carbonate strike-slip fault zone into a first type, a second type and a third type.

[0008] The above methods have contributed to the 3D modeling of underground reservoir porosity of carbonate reservoirs to a certain extent. However, due to the strong heterogeneity of carbonate reservoirs, there is a great deal of uncertainty in the prediction of inter-well porosity. This uncertainty not only affects the formulation of reservoir evaluation and development plans, but also increases the risk in the development process. Therefore, how to establish a relatively correct geological model in carbonate reservoirs with strong heterogeneity is a research difficulty that needs to be solved urgently. Summary of the invention

[0009] The purpose of the present invention is to solve the geological modeling problem of carbonate reservoirs with strong heterogeneity and propose a three-dimensional porosity modeling method for carbonate reservoirs, comprising the following steps:

[0010] S1. Obtain multi-source information of geological exploration, use the multi-source information of geological exploration, describe and characterize the porosity of underground reservoir in three-dimensional space through interpolation method, and construct an initial porosity three-dimensional model;

[0011] S2. Analyze the influence of different diagenesis on the porosity of carbonate reservoirs and determine the diagenetic transformation coefficients corresponding to different diagenesis, where the diagenetic transformation coefficient is the ratio of the porosity of carbonate rock after diagenesis to the porosity before diagenesis;

[0012] S3. The diagenetic transformation coefficient is introduced as a key parameter into the initial porosity model to obtain an optimized three-dimensional porosity model; according to the type, intensity and distribution characteristics of diagenetic action in the formation, the optimized three-dimensional porosity model is adjusted in layers and zones to obtain the final three-dimensional porosity model.

[0013] Furthermore, the multi-source information of geological exploration includes: geological exploration data, well logging data and seismic exploration data, specifically including: coordinate data, stratification data, sedimentary phase data, physical property data, and structural data; coordinate data include well point coordinates, well inclination data, and seismic line coordinates; stratification data include the division and comparison of strata and oil and gas layers, and the well sections and thickness of single layers and interlayers of each well within the oil and gas field; sedimentary phase data include core observations and well logging phase interpretations, core observations and description data; physical property data include mud content, porosity, permeability, oil and gas saturation, and bound water saturation; structural data include top and bottom surface structure and other depth data of the modeled layer.

[0014] Furthermore, the initial porosity 3D model includes: 3D structural modeling, 3D sedimentary phase modeling, and 3D reservoir attribute modeling;

[0015] Among them, 3D structural modeling includes: fault model, stratigraphic model, and geological grid model;

[0016] And the three-dimensional structural modeling, three-dimensional sedimentary phase modeling and three-dimensional reservoir attribute modeling are coarsened.

[0017] Furthermore, the diagenetic transformation coefficient is expressed as:

[0018]

[0019] in, is the rock porosity before diagenesis; is the rock porosity after diagenesis; is the diagenetic transformation coefficient;

[0020] when When , it is destructive diagenesis; when When , it is constructive diagenesis;

[0021] Destructive diagenesis includes: compaction and pressure solution, cementation, and silicification; constructive diagenesis includes: dissolution.

[0022] Furthermore, the diagenetic transformation coefficient corresponding to the compaction effect is calculated as follows:

[0023]

[0024]

[0025] in, is the porosity after compaction; C is the mass fraction of cement, is the inter-particle surface ratio, is the intercrystalline face ratio, represents the average measured porosity; represents the total face rate.

[0026] Furthermore, the diagenetic transformation coefficient corresponding to cementation is calculated as follows:

[0027]

[0028]

[0029] in, is the porosity after cementation, is the inter-particle surface ratio; is the intercrystalline face ratio; represents the average measured porosity; is the total face rate.

[0030] Furthermore, the diagenetic transformation coefficient corresponding to dissolution is calculated as follows:

[0031]

[0032]

[0033] in, is the porosity after dissolution, is the surface ratio of the dissolution pores; represents the average measured porosity; is the total face rate.

[0034] The present invention also provides a carbonate reservoir porosity three-dimensional modeling system, comprising:

[0035] Initial model building module: It is used to describe and characterize the porosity of underground reservoirs in three-dimensional space by interpolation method using multi-source information of geological exploration data, well logging data and seismic exploration data, and to build an initial porosity three-dimensional model;

[0036] Data analysis module: used to analyze the impact of different diagenesis on the porosity of carbonate reservoirs and determine the diagenetic transformation coefficients corresponding to different diagenesis, where the diagenetic transformation coefficient is the ratio of the porosity of carbonate rock after diagenesis to the porosity before diagenesis;

[0037] Final model building module: The diagenetic transformation coefficient is introduced into the initial porosity model as a key parameter to obtain an optimized three-dimensional porosity model; according to the type, intensity and distribution characteristics of diagenetic action in the formation, the optimized three-dimensional porosity model is layered and partitioned to obtain the final three-dimensional porosity model.

[0038] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned three-dimensional porosity modeling method of carbonate reservoirs is implemented.

[0039] The present invention also proposes an electronic device, comprising a processor and a memory, wherein the processor and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises computer-readable instructions, and the processor is configured to call the computer-readable instructions to execute the above-mentioned three-dimensional porosity modeling method of carbonate reservoirs.

[0040] The beneficial effects brought by the technical solution provided by the present invention are:

[0041] The present invention first constructs an initial porosity three-dimensional model by interpolation, proposes the concept of diagenetic transformation coefficient by using the ratio of the porosity of carbonate rocks after diagenesis to the porosity without diagenesis, optimizes the initial porosity three-dimensional model by using the diagenetic transformation coefficient, and adjusts the optimized model by layers and zones to obtain the final porosity three-dimensional model. The present invention divides the diagenetic transformation area, optimizes the model by using the diagenetic transformation coefficient, reflects the transformation effect of diagenesis on porosity, accurately describes the heterogeneity of carbonate reservoirs, and improves the accuracy of the model. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of a method for three-dimensional porosity modeling of a carbonate reservoir according to an embodiment of the present invention;

[0043] Figure 2 is an initial porosity three-dimensional model of an embodiment of the present invention;

[0044] Figure 3 Porosity models constructed for interpolation-based deterministic modeling;

[0045] Figure 4 is a diagram of the action area of ​​diagenesis according to an embodiment of the present invention;

[0046] Figure 5 is the final three-dimensional porosity model of the embodiment of the present invention;

[0047] Figure 6 It is a block diagram of an electronic device in an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0049] The flowchart of the method for three-dimensional porosity modeling of carbonate reservoirs according to an embodiment of the present invention is as follows: Figure 1 , specifically including the following steps:

[0050] S1. Acquire multi-source information of geological exploration, use the multi-source information of geological exploration, and describe and characterize the porosity of underground reservoirs in three-dimensional space by interpolation method, and construct an initial porosity three-dimensional model. The initial porosity three-dimensional model is a geological model constructed by interpolation method. The initial porosity three-dimensional model of the embodiment of the present invention refers to Figure 2 The porosity model constructed by the traditional modeling method (deterministic modeling based on interpolation method) is referenced Figure 3 .

[0051] In a further embodiment, the multi-source information of geological exploration includes: geological exploration data, well logging data and seismic exploration data, specifically including: coordinate data, layering data, sedimentary phase data, physical property data, and structural data. Coordinate data include well point coordinates, well inclination data, and seismic line coordinates; layering data include the division and comparison of strata and oil and gas layers, and the well sections and thickness of single layers and interlayers of each well within the oil and gas field; sedimentary phase data include core observation and well logging phase interpretation, core observation and description data; physical property data is the result of core analysis and testing data and well logging continuous interpretation, including mud content, porosity, permeability, oil and gas saturation and bound water saturation; structural data comes from the structural map compiled from the seismic structural interpretation results and well data, including top and bottom surface structural and other depth data of the modeling layer segment, and isobath data refers to the data of a surface formed by connecting points of the same depth into a closed curve.

[0052] Constructing the initial porosity 3D model includes: 3D structural modeling, 3D sedimentary phase modeling, and 3D reservoir attribute modeling.

[0053] Among them, three-dimensional structural modeling includes: fault model, stratigraphic model, and geological grid model.

[0054] The fault model must first determine the structural skeleton, establish a preliminary framework of the fault in three-dimensional space, determine the geometric shape and spatial position of the fault, and refine the fault model based on the well logging data to fit the fault surface and estimate the fault thickness. Then adjust and optimize the fault model based on actual data to improve the accuracy and reliability of the model.

[0055] The stratigraphic model constructs a three-dimensional model of the stratigraphic interface based on drilling data and geological profile data. The stratigraphic interface is characterized using the interpolation method, and the three-dimensional models of multiple geological bodies are integrated to form a complete stratigraphic model.

[0056] The geological grid model is often used to describe any three-dimensional model. It can also describe the detailed internal structure of oil and gas reservoirs. The internal structure depends largely on the distribution of reservoir sedimentary phases, which is determined based on the sedimentary conceptual model, geological knowledge and simulation algorithms. The geological grid model is eventually filled with sedimentary phases and rock properties. Three-dimensional sedimentary phase modeling requires the combination of geological survey data and exploration data to establish a geological conceptual model and clarify the approximate distribution of underground lithofacies, fluid phases or other geological attributes.

[0057] Three-dimensional sedimentary phase modeling requires the combination of geological survey data and exploration data to establish a geological conceptual model and clarify the approximate distribution of underground lithofacies, fluid phases or other geological attributes. The purpose of the sedimentary phase model is mainly to reflect the heterogeneity of the reservoir, which is mainly determined by well data and seismic attribute data. Sedimentary phase is the main factor controlling the distribution of reservoir physical properties, which has led to the formation of phase-constrained physical property simulation technology.

[0058] Three-dimensional reservoir property modeling mainly uses phase constraints to simulate the distribution of three-dimensional reservoir physical property parameters to characterize the heterogeneity of the reservoir, so that the fluid flow dynamics can be accurately simulated. Generally, the two-dimensional distribution of reservoir physical properties is the result of smooth interpolation of well data, while the distribution of underground reservoir physical properties is not smooth. Simple geostatistical methods can simulate the changes in reservoir physical properties between wells, and at the same time superimpose other trend changes on the model, so that the three-dimensional reservoir physical property simulation can reflect the planar and vertical changes of reservoir physical properties.

[0059] The 3D structural modeling and 3D reservoir attribute modeling are coarsened. It is not feasible to use the fine geological model directly as the input for oil and gas reservoir simulation, so the model must be coarsened. The size of the model must meet the requirements of fast numerical simulation, and the reservoir structure and effective pore volume retained by the coarsening must be consistent with the development effect predicted by the numerical simulation.

[0060] S2. Analyze the influence of different diagenesis on the porosity of carbonate reservoirs and determine the diagenetic transformation coefficients corresponding to different diagenesis, where the diagenetic transformation coefficient is the ratio of the porosity of carbonate rock after diagenesis to the porosity before diagenesis.

[0061] The diagenetic transformation coefficient is expressed as:

[0062]

[0063] in, is the rock porosity before diagenesis; is the rock porosity after diagenesis; is the diagenetic transformation coefficient;

[0064] when When the diagenetic system is continuously supplied with dolomitizing fluid, over-dolomitization will occur, and the newly generated dolomite will fill the pores. Therefore, dolomitization can also be a destructive diagenesis.

[0065] when When the calcite is not completely replaced, dolomitization is constructive diagenesis, and the pore volume increases continuously. After the calcite is completely replaced, the pore volume reaches the maximum.

[0066] First, the specific range of the diagenetic transformation coefficient under different diagenesis is obtained. Experimental determination: By collecting representative rock samples, conducting diagenetic simulation experiments or comparing the porosity data of rocks in different diagenetic stages, the diagenetic transformation coefficient can be directly determined. Secondly, geostatistical methods can be used to estimate the distribution range of the diagenetic transformation coefficient in combination with factors such as regional geological background, sedimentary facies, diagenetic type and intensity.

[0067] According to the influence of different diagenesis on porosity, the diagenetic transformation coefficient corresponding to different diagenesis is determined. In a specific embodiment, compaction reduces the reservoir porosity, and the corresponding diagenetic transformation coefficient is calculated as follows:

[0068]

[0069]

[0070] in, is the porosity after compaction; C is the mass fraction of cement, is the inter-particle surface ratio, is the intercrystalline face ratio, represents the average measured porosity; represents the total face rate.

[0071] Cementation reduces the reservoir porosity, and the corresponding diagenetic transformation coefficient is calculated as follows:

[0072]

[0073]

[0074] in, is the porosity after cementation, is the inter-particle surface ratio; is the intercrystalline face ratio; represents the average measured porosity; is the total face rate.

[0075] Dissolution increases the reservoir porosity, and the corresponding diagenetic transformation coefficient is calculated as follows:

[0076]

[0077]

[0078] in, is the porosity after dissolution, is the surface ratio of the dissolution pores; represents the average measured porosity; is the total face rate.

[0079] S3. The diagenetic transformation coefficient is introduced into the initial porosity model as a key parameter. The porosity calculation formula or parameter weight in the model is adjusted to reflect the transformation effect of diagenesis on porosity, and an optimized porosity three-dimensional model is obtained.

[0080] In the preferred embodiment, the diagenetic area is first divided according to the specific situation, and the reference Figure 4 , Figure 4 The diagenesis action area map of the embodiment of the present invention is then used to identify the impact of the diagenesis, determine whether it is destructive diagenesis or constructive diagenesis, and obtain the area where the diagenesis transformation coefficient acts. After analyzing the diagenesis, it is found that the diagenesis transformation coefficient of cementation is approximately 0.305~0.480; the diagenesis transformation coefficient of dissolution is approximately 1.318~1.746; and the diagenesis transformation coefficient of compaction is approximately 0.502~0.563. After manual identification, the destructive diagenesis in the area is dominant, and the diagenesis transformation coefficient is obtained based on comprehensive geological analysis and statistical principles. =0.523. In other embodiments, the diagenetic action area can be divided more accurately, and the diagenetic transformation coefficient The value division is more accurate, so as to further optimize the geological model obtained by the traditional modeling method.

[0081] According to the type, intensity and distribution characteristics of diagenesis, the optimized porosity 3D model is layered and zoned to ensure that the application of diagenetic transformation coefficient is more accurate and reasonable. The optimized porosity model is verified and corrected using actual drilling, coring, testing and other data to ensure that the model prediction results are consistent with the actual geological conditions, and the final porosity 3D model is obtained. Figure 5 , Figure 5 It is the final three-dimensional porosity model of the embodiment of the present invention.

[0082] The embodiment of the present invention further provides a carbonate reservoir porosity three-dimensional modeling system, comprising:

[0083] Initial model building module: It is used to describe and characterize the porosity of underground reservoirs in three-dimensional space by interpolation method using multi-source information of geological exploration data, well logging data and seismic exploration data, and to build an initial porosity three-dimensional model;

[0084] Data analysis module: used to analyze the impact of different diagenesis on the porosity of carbonate reservoirs and determine the diagenetic transformation coefficients corresponding to different diagenesis, where the diagenetic transformation coefficient is the ratio of the porosity of carbonate rock after diagenesis to the porosity before diagenesis;

[0085] Final model building module: The diagenetic transformation coefficient is introduced into the initial porosity model as a key parameter to obtain an optimized three-dimensional porosity model; according to the type, intensity and distribution characteristics of diagenetic action in the formation, the optimized three-dimensional porosity model is layered and partitioned to obtain the final three-dimensional porosity model.

[0086] In an exemplary embodiment, a computer-readable storage medium is included, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned three-dimensional porosity modeling method of carbonate reservoir is implemented.

[0087] See also Figure 6 In an exemplary embodiment, an electronic device is also included, including at least one processor, at least one memory, and at least one communication bus.

[0088] Wherein, a computer program is stored in the memory, and the computer program includes computer-readable instructions. The processor calls the computer-readable instructions stored in the memory through a communication bus to execute the above-mentioned carbonate reservoir porosity three-dimensional modeling method.

[0089] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A three-dimensional porosity modeling method for carbonate reservoirs, characterized in that: The following steps are involved: S1. Obtain multi-source information of geological exploration, use the multi-source information of geological exploration, describe and characterize the porosity of underground reservoir in three-dimensional space through interpolation method, and construct an initial porosity three-dimensional model; S2. Analyze the influence of different diagenesis on the porosity of carbonate reservoirs and determine the diagenetic transformation coefficients corresponding to different diagenesis, where the diagenetic transformation coefficient is the ratio of the porosity of carbonate rock after diagenesis to the porosity before diagenesis; The diagenetic transformation coefficient corresponding to the compaction effect is calculated as follows: ； in, is the porosity after compaction; C is the mass fraction of cement, is the inter-particle surface ratio, is the intercrystalline face ratio, represents the average measured porosity; It represents the diagenetic transformation coefficient after compaction; The diagenetic transformation coefficient corresponding to cementation is calculated as follows: ； in, is the porosity after cementation, It represents the diagenetic transformation coefficient after cementation; The diagenetic transformation coefficient corresponding to dissolution is calculated as follows: ； in, is the porosity after dissolution, is the surface ratio of the dissolved pores; It represents the diagenetic transformation coefficient after dissolution; S3. The diagenetic transformation coefficient is introduced as a key parameter into the initial porosity model to obtain an optimized three-dimensional porosity model; according to the type, intensity and distribution characteristics of diagenetic action in the formation, the optimized three-dimensional porosity model is adjusted in layers and zones to obtain the final three-dimensional porosity model.

2. The method for three-dimensional porosity modeling of a carbonate reservoir according to claim 1, characterized in that: The multi-source information of geological exploration includes: geological exploration data, well logging data and seismic exploration data, specifically including: coordinate data, stratification data, sedimentary phase data, physical property data, and structural data; coordinate data include well point coordinates, well inclination data, and seismic line coordinates; stratification data include the division and comparison of strata and oil and gas layers, and the well sections and thickness of single layers and interlayers of each well within the oil and gas field; sedimentary phase data include core observations and well logging phase interpretations, core observations and descriptions; physical property data include mud content, porosity, permeability, oil and gas saturation, and bound water saturation; structural data include top and bottom surface structure and other depth data of the modeled layer.

3. The method for three-dimensional porosity modeling of a carbonate reservoir according to claim 1, characterized in that: The initial porosity 3D model includes: 3D structural modeling, 3D sedimentary phase modeling, and 3D reservoir attribute modeling; Among them, 3D structural modeling includes: fault model, stratigraphic model, and geological grid model; And the three-dimensional structural modeling, three-dimensional sedimentary phase modeling and three-dimensional reservoir attribute modeling are coarsened.

4. The method for three-dimensional porosity modeling of a carbonate reservoir according to claim 1, characterized in that: Diagenetic transformation coefficient When , it is destructive diagenesis; when the diagenetic transformation coefficient When , it is constructive diagenesis; Destructive diagenesis includes: compaction and pressure solution, cementation, and silicification; constructive diagenesis includes: dissolution.

5. A three-dimensional porosity modeling system for carbonate reservoirs, characterized in that: include: Initial model building module: It is used to describe and characterize the porosity of underground reservoirs in three-dimensional space by interpolation method using multi-source information of geological exploration data, well logging data and seismic exploration data, and to build an initial porosity three-dimensional model; Data analysis module: used to analyze the impact of different diagenesis on the porosity of carbonate reservoirs and determine the diagenetic transformation coefficients corresponding to different diagenesis, where the diagenetic transformation coefficient is the ratio of the porosity of carbonate rock after diagenesis to the porosity before diagenesis; The diagenetic transformation coefficient corresponding to the compaction effect is calculated as follows: ； in, is the porosity after compaction; C is the mass fraction of cement, is the inter-particle surface ratio, is the intercrystalline face ratio, represents the average measured porosity; represents the total face rate; It represents the diagenetic transformation coefficient after compaction; The diagenetic transformation coefficient corresponding to cementation is calculated as follows: ； in, is the porosity after cementation, is the inter-particle surface ratio; is the intercrystalline face ratio; represents the average measured porosity; is the total face rate; It represents the diagenetic transformation coefficient after cementation; The diagenetic transformation coefficient corresponding to dissolution is calculated as follows: ； in, is the porosity after dissolution, is the surface ratio of the dissolved pores; represents the average measured porosity; is the total face rate; It represents the diagenetic transformation coefficient after dissolution; Final model building module: The diagenetic transformation coefficient is introduced into the initial porosity model as a key parameter to obtain an optimized three-dimensional porosity model; according to the type, intensity and distribution characteristics of diagenetic action in the formation, the optimized three-dimensional porosity model is layered and partitioned to obtain the final three-dimensional porosity model.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

7. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the processor and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises computer-readable instructions, and the processor is configured to call the computer-readable instructions to execute the method according to any one of claims 1 to 4.

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