Method, device, electronic equipment and medium for establishing natural fracture model of shale gas reservoir

Abstract

The present application discloses a method, device, electronic device and medium for establishing a natural fracture model of a shale gas reservoir. The method may include: determining the nature and direction of stresses in different regions of shale, and then establishing a geostress intensity model of shale; dividing the fracture phases of shale, performing discrete data marking on the fracture phases, and establishing a spatial distribution model of the fracture phases of shale; judging the relationship between the geostress and the fractures of each fracture phase, and determining the distribution state of parameters characterizing the fracture development characteristics; determining the seismic fracture detection attributes, establishing a fracture development probability model, and determining a spatial distribution model of the fracture development intensity; establishing a discrete fracture network model and repeatedly verifying it, and then establishing a natural fracture model of a shale gas reservoir. The present invention takes into account the spatial distribution of fractures in different tectonic stress units, ensures that the distribution relationship of different stress field parameters matches the geological laws of the generation of natural fractures in shale, and more accurately reflects the spatial distribution of shale fracture attribute parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration and development, and more specifically, to a method, device, electronic equipment and medium for establishing a natural fracture model of a shale gas reservoir. Background Art

[0002] Shale gas is a replacement energy source for conventional oil and gas. Through in-depth analysis of the geological characteristics of this type of gas reservoir, the establishment of a high-precision geological model, and the formation of a geological modeling method for shale gas reservoirs, it can truly serve as a "bridge" between shale gas exploration and development. In the field of modeling, natural fracture modeling is a very important and critical research part. A high-quality fracture model needs to be able to accurately reflect the distribution characteristics of fractures in the study area and characterize the spatial distribution of fracture parameters. At present, the characterization and modeling of shale gas reservoir fractures are still in the preliminary stage, and the research focus is on the description and prediction of fractures based on outcrops, drilling and seismic methods. A reliable fracture model is not only a comprehensive display of fracture characterization results, but also a means of quantitative fracture characterization. So far, there are few studies that can effectively integrate tectonic stress fields and geophysical data to predict the spatial distribution of natural fractures in shale gas reservoirs through three-dimensional geological modeling.

[0003] Fracture geological modeling is a three-dimensional quantitative model that reflects the characterization parameters and spatial distribution of fractures in oil and gas reservoirs. It can not only reflect the distribution law of fractures, but also meet the needs of reservoir engineering research. Since shale gas is a self-generating and self-storing gas reservoir, and the permeability of shale reservoirs is extremely low, shale gas is difficult to flow between different wellbores. Therefore, most of the current shale gas geological modeling is to establish a single well (or well group) geological model. In fact, the establishment of a regional geological model is still necessary because: (1) More drilling and seismic data can help us better analyze the spatial distribution law of natural fractures in shale gas reservoirs; (2) Regional geological models can predict the reserve distribution and production capacity of shale gas reservoirs.

[0004] Due to the complexity of unconventional gas reservoirs, there are relatively few research results in fracture modeling. How to comprehensively use the research results of various fractures such as core, logging interpretation, seismic, dynamic, and numerical simulation to establish a reasonable three-dimensional geological model of fractures is the key to the characterization of fractures in shale gas reservoirs. The current technology for modeling natural fractures in shale reservoirs can be generally divided into two categories: one is the equivalent continuous fracture modeling method, which uses seismic attribute analysis and other means to detect fractures and deterministic modeling; the other is the discrete network fracture modeling method, which randomly simulates the distribution of fractures through simulation methods such as indicator points.

[0005] The existing technology for modeling natural fractures in shale gas reservoirs basically adopts the modeling ideas of general fracture reservoirs. However, in fact, there are still many things to note when establishing a shale reservoir fracture model:

[0006] (1) Due to the influence of seismic quality and processing and interpretation, some fractures are difficult to distinguish based on seismic data alone, and the accuracy of seismic fracture detection has yet to be improved;

[0007] (2) The occurrence, density, and opening of natural fractures in shale reservoirs are mostly obtained from limited imaging logging interpretation, and the fracture parameters in unimaging logging and between wells are still difficult to determine;

[0008] (3) The most important point is that the tectonic geological background of shale gas producing areas is relatively complex. The stratigraphic distribution, geostress state and shale gas production capacity of different tectonic units are quite different. Natural fractures are the direct result of tectonic stress. However, the current use of geostress analysis to predict fractures is mostly analyzed through numerical methods, and the results have never effectively integrated the actual well-seismic fracture interpretation data.

[0009] Establishing a natural fracture distribution model for shale gas reservoirs helps to identify shale layers with different degrees of natural fracture development in different regions. Therefore, before artificial fracturing, the development characteristics of natural fractures in shale formations must be systematically characterized, and the ground stress conditions must be clarified to reasonably optimize the fracturing storage and improvement measures and enhance the effectiveness of fracturing treatment. At present, the establishment of a natural fracture model for shale gas reservoirs is still relatively simple. The entire modeling area often has only one or two groups of fractures, and the stress differences of different structural units and the differences in fractures under their control are not reflected.

[0010] The quality and production of shale gas reservoirs are directly dependent on the degree of development of natural fractures. The existing technology for modeling natural fractures in shale gas reservoirs basically adopts the modeling ideas of general fracture reservoirs, and does not consider the differences in stress effects of different structural units. The results only reproduce the simple spatial distribution of fractures in the entire region, while the fracture distribution status and shale gas production capacity of different structural units are difficult to match the actual geological conditions. On the other hand, traditional natural modeling of shale gas reservoirs is more of a direct use of seismic fracture detection results, and rarely comprehensively considers the relationship between shale stress and fracture development, resulting in an inaccurate understanding of the distribution law of fractures in shale gas reservoirs.

[0011] Therefore, it is necessary to develop a method, device, electronic equipment and medium for establishing a natural fracture model of shale gas reservoirs based on fracture phase characterization.

[0012] The information disclosed in the background technology section of the present invention is only intended to deepen the understanding of the general background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0013] The present invention proposes a method, device, electronic device and medium for establishing a natural fracture model of a shale gas reservoir. The fracture model of a shale gas reservoir is established with the goal of characterizing the spatial distribution of natural fractures in the shale gas reservoir. The information such as drilling, earthquake and ground stress parameters is comprehensively utilized. The fracture phases are divided by tectonic stress unit partitions, and the fracture parameters are characterized from the fracture genesis mechanism. The spatial distribution state of parameters such as fracture occurrence and strength is obtained, and a discrete fracture network model of each fracture phase area is established by adopting a phase-controlled modeling idea. The formation mechanism of natural fractures in different tectonic units, the differences in cluster occurrence and development degree, and the spatial distribution state of each parameter data of natural fractures are fully considered, and a more reliable geological model foundation is provided for the establishment of a post-compression model of a shale gas reservoir and the prediction of production capacity.

[0014] In a first aspect, an embodiment of the present disclosure provides a method for establishing a natural fracture model of a shale gas reservoir, comprising:

[0015] Determine the nature and direction of stress in different areas of shale, and then establish a shale ground stress intensity model;

[0016] Dividing the fracture phases of shale, marking the fracture phases with discrete data, and establishing a spatial distribution model of the fracture phases of shale;

[0017] Determine the relationship between the ground stress and the cracks in each fracture phase, and determine the distribution state of the parameters that characterize the fracture development characteristics;

[0018] Determine the seismic fracture detection attributes, establish a fracture development probability model, constrain and correct the fracture development probability model through the in-situ stress intensity model, and determine the spatial distribution model of fracture development intensity;

[0019] A discrete fracture network model was established and calibrated repeatedly to establish a natural fracture model of shale gas reservoirs.

[0020] Preferably, determining the nature and direction of stresses in different regions of shale includes:

[0021] Based on the three-dimensional seismic data, the structure of the shale formation is interpreted in detail, the key shale layers and fault distribution data are obtained, the structural undulation characteristics of the shale formation are analyzed, the shale structural deformation is geologically analyzed, and the nature and direction of the stress in different shale areas are determined.

[0022] Preferably, establishing a shale in-situ stress intensity model includes:

[0023] Based on geological data, fault distribution, structural deformation characteristics, and logging information data, three-dimensional geostress prediction is carried out under the constraint control of structural stress characteristics based on seismic analysis and single well stress sensitivity parameters to establish a shale geostress intensity model.

[0024] Preferably, the three-dimensional geostress prediction includes:

[0025] Analyze the pilot well pressure curve and determine the stress sensitive parameters;

[0026] Using the pilot well stress parameter data, the stress parameter distribution of the horizontal well section is established;

[0027] According to the geological, fault, fold deformation and well logging information, a stress field simulation material library for the modeling area is established;

[0028] The attribute bodies that are sensitive to the direction and intensity of the stress field are determined, the attribute correction is performed through the drilling stress parameter data, and the three-dimensional ground stress prediction is achieved by fusing multiple attribute bodies.

[0029] Preferably, determining the seismic fracture detection attribute comprises:

[0030] Extracting multiple seismic fracture detection attribute volumes;

[0031] Calculate the inter-layer average value of each seismic fracture detection attribute volume;

[0032] Extract the interlayer average value of the attribute body at the well point with imaging logging, and make intersection statistics with the fracture interpretation density value of imaging logging;

[0033] The correlation between each seismic fracture detection attribute body and the imaging logging fracture interpretation density value is obtained to determine the seismic fracture detection attribute with the best correlation.

[0034] Preferably, constraining and correcting the fracture development probability model by using the in-situ stress intensity model comprises:

[0035] Performing normalization calculation on the in-situ stress intensity model to convert the model value into distribution data in the interval [0,1];

[0036] Performing normalization calculation on the fracture development probability model to convert the model value into distribution data in the interval [0,1];

[0037] Based on the normalized ground stress model and fracture development probability model, the percentage coefficients are multiplied respectively, and the sum of the coefficients is 100%;

[0038] The calculated ground stress model is added to the calculated crack probability model to obtain a three-dimensional distribution model of crack development intensity.

[0039] Preferably, establishing a discrete fracture network model and repeatedly performing verification to further establish a natural fracture model of a shale gas reservoir includes:

[0040] Based on the fracture phase spatial distribution model, taking the parameters characterizing fracture development characteristics as conditional data, performing random simulation for each fracture phase, and sequentially establishing discrete fracture network models;

[0041] By adjusting the fracture parameter input, the discrete fracture network model is repeatedly verified until the geometry of the discrete fracture network model is consistent with the fracture parameters interpreted by the imaging logging;

[0042] A natural fracture model of shale gas reservoir is established based on the discrete fracture network model.

[0043] As a specific implementation method of the embodiment of the present disclosure,

[0044] In a second aspect, the present disclosure also provides a device for establishing a natural fracture model of a shale gas reservoir, comprising:

[0045] The module for establishing the in-situ stress intensity model determines the nature and direction of stress in different areas of shale, and then establishes the in-situ stress intensity model of shale;

[0046] A fracture phase spatial distribution model establishment module is used to divide the fracture phases of shale, to perform discrete data marking on the fracture phases, and to establish a fracture phase spatial distribution model of shale;

[0047] The fracture parameter determination module determines the relationship between the ground stress and the fracture of each fracture phase and determines the distribution state of the parameters that characterize the fracture development characteristics;

[0048] A module for establishing a spatial distribution model of fracture development intensity, determining seismic fracture detection attributes, establishing a fracture development probability model, constraining and correcting the fracture development probability model through the in-situ stress intensity model, and determining a spatial distribution model of fracture development intensity;

[0049] The fracture attribute parameter distribution model establishment module establishes a discrete fracture network model and repeatedly verifies it, and then establishes a natural fracture model of shale gas reservoirs.

[0050] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0051] A memory storing executable instructions;

[0052] A processor runs the executable instructions in the memory to implement the method for establishing a natural fracture model of a shale gas reservoir.

[0053] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the method for establishing a natural fracture model of a shale gas reservoir is implemented.

[0054] Its beneficial effects are:

[0055] ① Taking fracture phase as the target, the fracture model is established by phase-controlled zoning, which reflects the differences in fracture development in different tectonic units and has higher model accuracy;

[0056] ② Comprehensively consider the relationship between shale geostress and fracture development, solve the problem of geostress-driven fracture modeling, and effectively and comprehensively utilize the calibration information of drilling, seismic, and geostress on fractures, so that the fracture model is more in line with the actual work area;

[0057] ③ Provide a basis for quantitative research on shale gas geology-engineering integration, provide more reliable analysis and prediction for subsequent compressibility evaluation and artificial fracturing fracture modeling, and provide a more reliable model guarantee for the effective development of shale gas.

[0058] The methods and apparatus of the present invention have other features and advantages that will be apparent from, or will be described in detail in, the accompanying drawings and subsequent detailed descriptions incorporated herein, which together serve to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.

[0060] Figure 1 A flow chart showing the steps of a method for establishing a natural fracture model of a shale gas reservoir according to an embodiment of the present invention.

[0061] Figure 2 A schematic diagram of a shale formation seismic interpretation plane and its structural and stress characteristics according to an embodiment of the present invention is shown.

[0062] Figure 3 A schematic diagram of shale structure and fault distribution according to an embodiment of the present invention is shown.

[0063] Figure 4 A schematic diagram of fracture phase division based on stress difference according to an embodiment of the present invention is shown.

[0064] Figure 5 A schematic diagram of a fracture development probability model according to an embodiment of the present invention is shown.

[0065] Figure 6 A schematic diagram of a discrete fracture network model based on fracture phase control according to an embodiment of the present invention is shown.

[0066] Figure 7 A statistical diagram of the number of fractures in a shale gas reservoir fracture model at a drilling site according to an embodiment of the present invention is shown.

[0067] Figure 8 A block diagram of a device for establishing a natural fracture model of a shale gas reservoir according to an embodiment of the present invention is shown.

[0068] Description of reference numerals:

[0069] 201. A module for establishing a model of ground stress intensity; 202. A module for establishing a model of spatial distribution of fracture phase; 203. A module for determining fracture parameters; 204. A module for establishing a model of spatial distribution of fracture development intensity; 205. A module for establishing a model of fracture attribute parameter distribution. DETAILED DESCRIPTION

[0070] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0071] The present invention provides a method for establishing a natural fracture model of a shale gas reservoir, comprising:

[0072] Determine the nature and direction of stress in different regions of shale, and then establish a shale ground stress intensity model; in one example, determine the nature and direction of stress in different regions of shale including:

[0073] Based on the three-dimensional seismic data, the structure of the shale formation is interpreted in detail, the key shale layers and fault distribution data are obtained, the structural undulation characteristics of the shale formation are analyzed, the shale structural deformation is geologically analyzed, and the nature and direction of the stress in different shale areas are determined.

[0074] In one example, establishing a geostress intensity model for shale includes:

[0075] Based on geological data, fault distribution, structural deformation characteristics, and logging information data, three-dimensional geostress prediction is carried out under the constraint control of structural stress characteristics based on seismic analysis and single well stress sensitivity parameters to establish a shale geostress intensity model.

[0076] In one example, three-dimensional geostress prediction includes:

[0077] Analyze the pilot well pressure curve and determine the stress sensitive parameters;

[0078] Using the pilot well stress parameter data, the stress parameter distribution of the horizontal well section is established through fitting calculation formulas, deep learning and other methods;

[0079] According to the geological, fault, fold deformation and well logging information, a stress field simulation material library for the modeling area is established;

[0080] Determine the attribute bodies that are sensitive to the direction and intensity of the stress field, perform attribute correction through drilling stress parameter data, and achieve three-dimensional geostress prediction by fusing multiple attribute bodies.

[0081] Specifically, the structure of the shale formation is interpreted in detail based on three-dimensional seismic data, the key shale layers and fault distribution data are obtained, the structural undulation characteristics of the shale formation are analyzed, the shale structural deformation is geologically analyzed, and the nature and direction of the stress in different shale areas are obtained.

[0082] The structural undulation characteristics mainly refer to the fold morphology. The specific implementation steps are: use seismic interpretation to obtain the structural layers and fault distribution data of shale strata; determine the nature of the faults by analyzing the layer folds and the relationship between the layers and faults; use the fault properties to determine the regional stress background, such as reverse faults indicate compressive stress, and the direction of maximum stress is perpendicular to the fault direction.

[0083] According to geological data, fault distribution, structural deformation characteristics, and logging information data, three-dimensional geostress prediction is carried out under the control of structural stress characteristics analysis based on seismic analysis and single well stress sensitivity parameters, and a shale geostress strength model is established. Among them, single well stress sensitivity parameters include: horizontal maximum (minimum) principal stress direction, horizontal maximum (minimum) principal stress magnitude, pore fluid pressure, rock mechanics parameters, such as Poisson's ratio, Young's modulus, etc.

[0084] The fracture phases of shale are divided, and the fracture phases are discretely marked, and a spatial distribution model of the fracture phases of shale is established. Specifically, the tectonic stress units are classified according to the three parameters of ground stress properties, maximum stress direction, and stress intensity, and the shale fracture phases are divided accordingly, and the fracture phases are discretely marked, and a deterministic method is used to establish a spatial distribution model of the shale fracture phases.

[0085] Determine the relationship between the geostress and cracks of each fracture phase, and determine the distribution state of parameters characterizing the fracture development characteristics; specifically, based on the geomechanical theory of fracture genesis, analyze and determine the relationship between the geostress and cracks of each fracture phase, and based on the fracture genesis mechanism, obtain the distribution state of parameters characterizing the fracture development characteristics, such as the natural fracture cluster system, fracture inclination and inclination, and fracture opening in each fracture phase area.

[0086] Determine the seismic crack detection attribute, establish a crack development probability model, constrain and correct the crack development probability model through the ground stress intensity model, and determine the spatial distribution model of crack development intensity; in one example, determining the seismic crack detection attribute includes:

[0087] Extracting multiple seismic fracture detection attribute volumes;

[0088] Calculate the inter-layer average value of each seismic fracture detection attribute volume;

[0089] Extract the interlayer average value of the attribute body at the well point with imaging logging, and make intersection statistics with the fracture interpretation density value of imaging logging;

[0090] The correlation between each seismic fracture detection attribute body and the imaging logging fracture interpretation density value is obtained to determine the seismic fracture detection attribute with the best correlation.

[0091] In one example, constraining and correcting the fracture development probability model through the ground stress intensity model includes:

[0092] Perform normalization calculation on the ground stress intensity model and transform the model value into distribution data in the interval [0,1];

[0093] Perform normalization calculation on the fracture development probability model and transform the model value into distribution data in the interval [0,1];

[0094] Based on the normalized ground stress model and fracture development probability model, the percentage coefficients are multiplied respectively, and the sum of the coefficients is 100%;

[0095] The calculated ground stress model is added to the calculated crack probability model to obtain a three-dimensional distribution model of crack development intensity.

[0096] A discrete fracture network model is established and repeatedly verified, thereby establishing a natural fracture model of a shale gas reservoir. In one example, the discrete fracture network model is established and repeatedly verified, thereby establishing a natural fracture model of a shale gas reservoir, including:

[0097] Based on the spatial distribution model of fracture phases, the parameters characterizing fracture development characteristics are used as conditional data, and random simulation is performed for each fracture phase to establish discrete fracture network models in turn.

[0098] By adjusting the fracture parameter input, the discrete fracture network model is repeatedly verified until the geometry of the discrete fracture network model is consistent with the fracture parameters interpreted by the imaging logging;

[0099] Based on the discrete fracture network model, a natural fracture model of shale gas reservoirs is established.

[0100] Specifically, according to the fracture phase space distribution model, different fracture phase discrete data values ​​are set as different regions, and according to the fracture occurrence and strength parameter data distribution of each fracture phase as conditional data, each fracture phase is randomly simulated using the characteristic point method, and discrete fracture network (DFN) models are established in sequence; the partition phase control approach is adopted during modeling, and fracture modeling is performed separately in each fracture phase area, and the fracture modeling parameters of each fracture phase area are controlled by the fracture phase characterization results of the corresponding area; if the tectonic stresses of different shale layers are different, the fracture development conditions are also different. At this time, the fracture phase space distribution model needs to be divided not only in the plane, but also in the vertical direction.

[0101] The established fracture DFN model is verified by using the fracture tendency, dip angle and fracture density parameters interpreted by imaging logging. The fracture parameter input of the fracture phase where the verification target area is located is adjusted until the geometric shape of the generated fracture model is consistent with the fracture parameters interpreted by imaging logging. The modification and verification are repeated until the entire fracture model meets the conditions of all imaging logging fracture interpretation parameters.

[0102] The fracture aperture data interpreted from imaging logging and the stress properties of different fracture phases are integrated to obtain the data distribution characteristics such as the distribution range, mean and variance of the fracture aperture parameters in each fracture phase. Based on the constructed fracture DFN model, the natural fracture model of shale gas reservoirs is calculated and generated.

[0103] The shale gas reservoir natural fracture model of the present invention first establishes a fracture phase distribution model to better understand the parameter difference distribution of fracture development under different tectonic stresses, and then adopts the phase-controlled attribute modeling idea to construct a fracture DFN model in different zones.

[0104] The present invention fully considers the differences in the formation mechanism, cluster occurrence and development degree of natural fractures in different structural units, accurately characterizes the spatial distribution state of various parameter data of natural fractures, and provides a more reliable geological model basis for the establishment of post-compression models of shale gas reservoirs and production capacity prediction. It has important practical significance for improving the technical level of shale gas geological modeling in my country, promoting the standard specifications of shale gas reservoir geological modeling, serving the production of shale gas fields, and effectively developing my country's shale gas resources. It also has reference and reference significance in the fields of carbonate oil reservoirs, shale oil reservoirs, coalbed methane, etc.

[0105] The present invention also provides a shale gas reservoir natural fracture model establishment device, comprising:

[0106] The module for establishing the in-situ stress intensity model determines the nature and direction of stress in different regions of shale, and then establishes the in-situ stress intensity model of shale. In one example, determining the nature and direction of stress in different regions of shale includes:

[0107] Based on the three-dimensional seismic data, the structure of the shale formation is interpreted in detail, the key shale layers and fault distribution data are obtained, the structural undulation characteristics of the shale formation are analyzed, the shale structural deformation is geologically analyzed, and the nature and direction of the stress in different shale areas are determined.

[0108] In one example, establishing a geostress intensity model for shale includes:

[0109] Based on geological data, fault distribution, structural deformation characteristics, and logging information data, three-dimensional geostress prediction is carried out under the constraint control of structural stress characteristics based on seismic analysis and single well stress sensitivity parameters to establish a shale geostress intensity model.

[0110] In one example, three-dimensional geostress prediction includes:

[0111] Analyze the pilot well pressure curve and determine the stress sensitive parameters;

[0112] Using the pilot well stress parameter data, the stress parameter distribution of the horizontal well section is established through fitting calculation formulas, deep learning and other methods;

[0113] According to the geological, fault, fold deformation and well logging information, a stress field simulation material library for the modeling area is established;

[0114] Determine the attribute bodies that are sensitive to the direction and intensity of the stress field, perform attribute correction through drilling stress parameter data, and achieve three-dimensional geostress prediction by fusing multiple attribute bodies.

[0115] Specifically, the structure of the shale formation is interpreted in detail based on three-dimensional seismic data, the key shale layers and fault distribution data are obtained, the structural undulation characteristics of the shale formation are analyzed, the shale structural deformation is geologically analyzed, and the nature and direction of the stress in different shale areas are obtained.

[0116] The structural undulation characteristics mainly refer to the fold morphology. The specific implementation steps are: use seismic interpretation to obtain the structural layers and fault distribution data of shale strata; determine the nature of the faults by analyzing the layer folds and the relationship between the layers and faults; use the fault properties to determine the regional stress background, such as reverse faults indicate compressive stress, and the direction of maximum stress is perpendicular to the fault direction.

[0117] According to geological data, fault distribution, structural deformation characteristics, and logging information data, three-dimensional geostress prediction is carried out under the control of structural stress characteristics analysis based on seismic analysis and single well stress sensitivity parameters, and a shale geostress strength model is established. Among them, single well stress sensitivity parameters include: horizontal maximum (minimum) principal stress direction, horizontal maximum (minimum) principal stress magnitude, pore fluid pressure, rock mechanics parameters, such as Poisson's ratio, Young's modulus, etc.

[0118] The module for establishing the spatial distribution model of the fracture phase is used to divide the fracture phase of shale, mark the fracture phase with discrete data, and establish the spatial distribution model of the fracture phase of shale. Specifically, the structural stress units are classified according to the three parameters of the ground stress properties, the maximum stress direction, and the stress intensity, and the shale fracture phase is divided accordingly, and the fracture phase is marked with discrete data. A deterministic method is used to establish the spatial distribution model of the shale fracture phase.

[0119] The fracture parameter determination module determines the relationship between the geostress and the fractures of each fracture phase, and determines the distribution state of parameters characterizing the fracture development characteristics. Specifically, based on the geomechanical theory of fracture genesis, the relationship between the geostress and the fractures of each fracture phase is analyzed and determined, and based on the fracture genesis mechanism, the distribution state of parameters characterizing the fracture development characteristics, such as the natural fracture cluster system, fracture inclination and inclination, and fracture opening, are obtained in each fracture phase area.

[0120] A module for establishing a spatial distribution model of crack development intensity determines seismic crack detection attributes, establishes a crack development probability model, constrains and corrects the crack development probability model through a ground stress intensity model, and determines a spatial distribution model of crack development intensity; in one example, determining seismic crack detection attributes includes:

[0121] Extracting multiple seismic fracture detection attribute volumes;

[0122] Calculate the inter-layer average value of each seismic fracture detection attribute volume;

[0123] Extract the interlayer average value of the attribute body at the well point with imaging logging, and make intersection statistics with the fracture interpretation density value of imaging logging;

[0124] The correlation between each seismic fracture detection attribute body and the imaging logging fracture interpretation density value is obtained to determine the seismic fracture detection attribute with the best correlation.

[0125] In one example, constraining and correcting the fracture development probability model through the ground stress intensity model includes:

[0126] Perform normalization calculation on the ground stress intensity model and transform the model value into distribution data in the interval [0,1];

[0127] Perform normalization calculation on the fracture development probability model and transform the model value into distribution data in the interval [0,1];

[0128] Based on the normalized ground stress model and fracture development probability model, the percentage coefficients are multiplied respectively, and the sum of the coefficients is 100%;

[0129] The calculated ground stress model is added to the calculated crack probability model to obtain a three-dimensional distribution model of crack development intensity.

[0130] The fracture attribute parameter distribution model establishment module establishes a discrete fracture network model and repeatedly verifies it, thereby establishing a natural fracture model of a shale gas reservoir. In one example, establishing a discrete fracture network model and repeatedly verifying it, thereby establishing a natural fracture model of a shale gas reservoir includes:

[0131] Based on the spatial distribution model of fracture phases, the parameters characterizing fracture development characteristics are used as conditional data, and random simulation is performed for each fracture phase to establish discrete fracture network models in turn.

[0132] By adjusting the fracture parameter input, the discrete fracture network model is repeatedly verified until the geometry of the discrete fracture network model is consistent with the fracture parameters interpreted by the imaging logging;

[0133] Based on the discrete fracture network model, a natural fracture model of shale gas reservoirs is established.

[0134] Specifically, according to the fracture phase space distribution model, different fracture phase discrete data values ​​are set as different regions, and according to the fracture occurrence and strength parameter data distribution of each fracture phase as conditional data, each fracture phase is randomly simulated using the characteristic point method, and discrete fracture network (DFN) models are established in sequence; the partition phase control approach is adopted during modeling, and fracture modeling is performed separately in each fracture phase area, and the fracture modeling parameters of each fracture phase area are controlled by the fracture phase characterization results of the corresponding area; if the tectonic stresses of different shale layers are different, the fracture development conditions are also different. At this time, the fracture phase space distribution model needs to be divided not only in the plane, but also in the vertical direction.

[0135] The established fracture DFN model is verified by using the fracture tendency, dip angle and fracture density parameters interpreted by imaging logging. The fracture parameter input of the fracture phase where the verification target area is located is adjusted until the geometric shape of the generated fracture model is consistent with the fracture parameters interpreted by imaging logging. The modification and verification are repeated until the entire fracture model meets the conditions of all imaging logging fracture interpretation parameters.

[0136] The fracture aperture data interpreted from imaging logging and the stress properties of different fracture phases are integrated to obtain the data distribution characteristics such as the distribution range, mean and variance of the fracture aperture parameters in each fracture phase. Based on the constructed fracture DFN model, the natural fracture model of shale gas reservoirs is calculated and generated.

[0137] The present invention also provides an electronic device, which includes: a memory storing executable instructions; and a processor, which runs the executable instructions in the memory to implement the above-mentioned method for establishing a natural fracture model of a shale gas reservoir.

[0138] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for establishing a natural fracture model of a shale gas reservoir is implemented.

[0139] To facilitate understanding of the solutions and effects of the embodiments of the present invention, four specific application examples are given below. Those skilled in the art should understand that the examples are only for facilitating understanding of the present invention, and any specific details thereof are not intended to limit the present invention in any way.

[0140] Example 1

[0141] Figure 1 A flow chart showing the steps of a method for establishing a natural fracture model of a shale gas reservoir according to an embodiment of the present invention.

[0142] like Figure 1 As shown, the method for establishing a natural fracture model of a shale gas reservoir comprises: step 101, determining the nature and direction of stress in different regions of shale, and then establishing a geostress intensity model of shale; step 102, dividing the fracture phases of shale, performing discrete data marking on the fracture phases, and establishing a fracture phase spatial distribution model of shale; step 103, judging the relationship between the geostress and the fractures of each fracture phase, and determining the distribution state of parameters characterizing the fracture development characteristics; step 104, determining the seismic fracture detection attributes, establishing a fracture development probability model, constraining and correcting the fracture development probability model through the geostress intensity model, and determining the spatial distribution model of the fracture development intensity; step 105, establishing a discrete fracture network model and repeatedly verifying it, and then establishing a natural fracture model of a shale gas reservoir.

[0143] The test area contains a certain area of ​​flat structure and structural slope area, and the stratigraphic structural morphology, shale gas content and production capacity of these two areas are very different. The study area has three-dimensional seismic data, covering dozens of well platforms, a total of 26 wells (3 pilot wells, recorded as A, B, C wells; 23 horizontal wells, recorded as DZ wells), with an average well spacing of about 600m. At present, the seismic information has been processed and interpreted to interpret the bottom and top surfaces of the shale gas layer. The wells all contain logging curves, logging data, test well production and other data. Among them, 3 pilot wells have imaging logging, and their logging interpretation can provide information such as fracture inclination and fracture tendency.

[0144] The shale layer in the study area is a deep-water shelf deposit, and shale is mainly produced in the siliceous shelf and sandy shelf. Drilling revealed that the parameters such as TOC and gas content of the shale layer in the study area have obvious differences in the vertical direction, and the lower shale section is the best. The fracturing effect in different structural areas shows that the degree of development of natural fractures in shale in the structural gentle area and the structural slope area is different, and the cumulative gas production has a large difference. Therefore, it is necessary to characterize the spatial distribution of natural fractures in detail in order to further evaluate the fracturing effect and predict the development capacity.

[0145] Figure 2 A schematic diagram of a shale formation seismic interpretation plane and its structural and stress characteristics according to an embodiment of the present invention is shown.

[0146] Figure 3 A schematic diagram of shale structure and fault distribution according to an embodiment of the present invention is shown.

[0147] Through fine seismic interpretation, the top structural map of shale was extracted. The shale in the test area generally presents a box-shaped anticline with the major axis direction of northeast (NE)-southwest (SW). On the basis of the overall anticline structure, there is a secondary syncline structure in the north. Based on the undulating structural characteristics of the shale strata, the overall compression stress of the shale was obtained, and the maximum principal stress direction is northwest (NW)-southeast (SE), such as Figure 2 As shown. Based on the calculation of the maximum curvature attribute of the seismic data volume, the maximum curvature attribute value of the shale top surface is extracted, and the distribution characteristics of the faults are analyzed. The shale in the test area is affected by the compression stress, and three thrust faults with northeast direction (referred to as the southeastern fault F1, the northwest fault F2 and the fault F3 separating the syncline-anticline landform in the middle) and three translation faults with northwest direction (referred to as F4, F5, and F6) are obtained in the test area. Figure 3 shown.

[0148] The pressure curve of the pilot well was analyzed, and the relationship between the pressure curve and the logging stress parameters was statistically analyzed. The stress sensitive parameters of the test area were mainly the horizontal maximum principal stress direction, pore fluid pressure and rock mechanics parameters. The stress parameter data of the three pilot wells were fitted with the polynomial calculation function of each stress sensitive parameter, and the stress parameter data of all horizontal well sections were calculated using the fitting formula. The elastic parameter inversion calculation was performed using the pre-stack three-dimensional seismic data body to obtain a preliminary stress field strength body. The obtained stress field strength was corrected using the drilling maximum principal stress parameter data, and a three-dimensional spatial distribution model of ground stress intensity was constructed.

[0149] Figure 4 A schematic diagram of fracture phase division based on stress difference according to an embodiment of the present invention is shown.

[0150] The maximum principal stress direction of shale in the test area is NW-SE compression, and it has the characteristics of alternating synclines and anticlines on the overall box-type anticline structural background. Based on the correlation between the development law of faults in the test area and tectonic stress, combined with the distribution of 6 faults, the study area is divided into 5 fracture phases, such as Figure 4 As shown in Table 1, they are: ① The development phase of high-strength compressive fractures is mainly in the southeast of the test area; ② The development phase of medium-strength tensile fractures is mainly in the southwest of the test area; ③ The development phase of low-strength compressive fractures is developed in the northwest of the central part of the test area, and is generally located in the secondary syncline of the main area; ④ The development phase of medium-high strength shear fractures is in the intersection of F1 and F4 faults in the east of the test area; ⑤ The development phase of medium-strength compressive fractures is developed in the northwest of the test area. The fracture phase types are recorded as 1-5 discrete data, and divided according to the distribution area of ​​each fracture phase. The deterministic method is used to construct a three-dimensional geological model of the fracture phase.

[0151] Table 1

[0152]

[0153]

[0154] Based on the geomechanical theory of fracture genesis, the fracture development characteristics of each fracture phase are analyzed, as shown in Table 2.

[0155] Table 2

[0156]

[0157] ① The fracture phase 1 area is affected by the F1 fault, and the fractures are mainly compression fractures. The occurrence is parallel to the F1 fault, and the fractures are distributed in the northeast (NE) direction. The fracture development intensity is strong. ② The fracture phase 2 area is strongly compressed and deformed by the east-west structure, forming a low uplift. Some tensile fractures with a northeast (NE) trend are developed in the bending part. The occurrence of the fractures is mostly distributed in the northeast (NE) direction. The fracture extension length in this phase belt is large and the continuity is good. Although the intensity of fracture development is not as good as that of fracture phase 1, it is also relatively developed. ③ The fracture phase 3 area is a low-amplitude syncline, the compression deformation is not obvious, the ground stress is weak, and two clusters of fractures with east-west (EW) and northwest (NW) trends are developed. The overall development intensity of fractures is low. ④ The stress deformation in the fracture phase 4 area is strong. The fractures in this fracture phase are controlled by both compression and shear. The overall occurrence is relatively chaotic. Two clusters of fractures with northeast (NE) and northwest west (NWW) trends are mainly developed, and the fracture development intensity is relatively strong. ⑤ The fracture phase 5 area is affected by the F2 fault. The fractures are mainly compressive fractures. The occurrence is parallel to the F2 fault and extends in a northeast (NE) direction. The fracture development intensity is medium.

[0158] Figure 5A schematic diagram of a fracture development probability model according to an embodiment of the present invention is shown.

[0159] Extract the seismic attributes such as variance, coherence, and fault likelihood (FL), compare each seismic attribute value at the imaging logging fracture interpretation layer with the imaging logging fracture interpretation density value, and select the seismic fracture detection attribute of the fault likelihood (FL) with the best correlation. The attribute value of the fault likelihood (FL) is between 0 and 1. The larger the value, the greater the probability of fracture development. The deterministic method is used to directly convert the fault likelihood (FL) attribute into a fracture development probability model based on seismic detection. The established stress field strength model is normalized to the numerical range of 0 to 1. The fracture development probability body obtained based on the fault likelihood (FL) attribute and the three-dimensional body obtained based on the ground stress intensity are compared. Since the imaging logging calibration seismic has a higher accuracy in fracture detection, a higher weight ratio of 0.6 can be given to the seismic fracture probability body, and a weight ratio of 0.4 can be given to the stress field strength body. A comprehensive fracture development probability model based on geomechanical stress field intensity and geophysical prediction is constructed, such as Figure 5 As shown in Figure 3, the model reflects the heterogeneous development of fractures in each fracture phase area.

[0160] Figure 6 A schematic diagram of a discrete fracture network model based on fracture phase control according to an embodiment of the present invention is shown.

[0161] Based on the established fracture phase spatial distribution model, five different areas were set up with different fracture phase discrete data values. Based on the fracture occurrence and fracture strength parameter data of each fracture phase area, the fracture phase belts were divided and different parameter inputs were given according to the corresponding fracture development law and occurrence. Each fracture phase was randomly simulated and generated with the characteristic point method. The occurrence of the fracture slices was controlled by the fracture input parameters of different fracture phases, and the number and distribution of the fracture slices were uniformly controlled by the fracture strength model. The discrete fracture slice models simulated by the five fracture phases were integrated to construct a unified and complete discrete fracture network (DFN) model of the test area, as shown in Figure 1. Figure 6 shown.

[0162] Figure 7 A statistical diagram of the number of fractures in a shale gas reservoir fracture model at a drilling site according to an embodiment of the present invention is shown.

[0163] The initial discrete fracture network (DFN) model was compared with the fracture parameters interpreted by the three imaging logging wells, and it was found that the error between the fracture model and Well A was relatively large. Under the premise that the overall fracture distribution state remains unchanged, the fracture input parameters of the fracture phase 3 zone where Well A is located are finely adjusted until the generated discrete fracture network (DFN) model fracture slices are consistent with the fracture distribution state interpreted by Well A. The final discrete fracture network (DFN) model of the shale gas reservoir in the test area was constructed. According to the final test area fracture model, the number of fracture slices encountered by drilling was counted, among which the maximum number of fractures encountered was 83 and the minimum was 2. The average number of fractures encountered by drilling in the test area as a whole was 14. The fracture model reflects the heterogeneity of fracture development, such as Figure 7 shown.

[0164] Each fracture slice in the discrete fracture network (DFN) model has relevant fracture properties, including fracture aperture, fracture permeability, and conductivity, among which the number, direction, length, and area of ​​fractures are all known data, and the fracture aperture data can be obtained based on drilling statistics. Different aperture parameters are used based on the fracture properties of different fracture phases. For example, the fractures in fracture phases 1 and 5, which are mainly developed with compression fractures, have a small input value of fracture aperture; while the fractures in fracture phase 2, which are mainly developed with tension fractures, need to be assigned a larger value of fracture aperture, thus reflecting that the connectivity coefficient (affecting the fracture permeability attribute) is different due to the fracture properties. Based on the discrete fracture network (DFN) model and fracture aperture data, according to the fracture attribute calculation formula, the fracture porosity, fracture permeability (in three directions of i, j, and k) and sigma coefficient (reflecting the degree of crossflow communication between fractures and matrix) models are calculated to form a complete natural fracture model of shale gas reservoirs.

[0165] By comparison, it is found that the natural fracture model of shale gas reservoirs established by this method well describes the spatial distribution of fractures in different structural stress units inside shale, ensuring that the distribution relationship of different stress field parameters matches the geological law of shale natural fracture generation, and can more accurately reflect the spatial distribution of shale fracture attribute parameters. The established shale natural fracture model is more accurate and reliable, and can also ensure the spatial distribution of natural fracture parameters in the shale layer. Based on this fracture model, the quality and distribution of sweet spots can be more targeted for high-quality shale lithofacies, providing guarantees for subsequent optimization of well locations, fracturing evaluation, and establishment of post-fracturing fracture network models.

[0166] Example 2

[0167] Figure 8 A block diagram of a device for establishing a natural fracture model of a shale gas reservoir according to an embodiment of the present invention is shown.

[0168] like Figure 8 As shown, the shale gas reservoir natural fracture model establishment device comprises:

[0169] A ground stress intensity model building module 201 determines the nature and direction of stress in different regions of shale, and then builds a ground stress intensity model of shale;

[0170] A fracture phase spatial distribution model building module 202 is used to divide the fracture phases of shale, mark the fracture phases with discrete data, and build a fracture phase spatial distribution model of shale;

[0171] The fracture parameter determination module 203 determines the relationship between the ground stress and the fracture of each fracture phase, and determines the distribution state of the parameters characterizing the fracture development characteristics;

[0172] A module 204 for establishing a spatial distribution model of fracture development intensity determines seismic fracture detection attributes, establishes a fracture development probability model, constrains and corrects the fracture development probability model through a ground stress intensity model, and determines a spatial distribution model of fracture development intensity;

[0173] The fracture attribute parameter distribution model building module 205 builds a discrete fracture network model and performs repeated verification to further build a natural fracture model of a shale gas reservoir.

[0174] As an alternative, methods of determining the nature and direction of stresses in different regions of the shale include:

[0175] Based on the three-dimensional seismic data, the structure of the shale formation is interpreted in detail, the key shale layers and fault distribution data are obtained, the structural undulation characteristics of the shale formation are analyzed, the shale structural deformation is geologically analyzed, and the nature and direction of the stress in different shale areas are determined.

[0176] As an optional solution, the in-situ stress intensity model of shale includes:

[0177] Based on geological data, fault distribution, structural deformation characteristics, and logging information data, three-dimensional geostress prediction is carried out under the constraint control of structural stress characteristics based on seismic analysis and single well stress sensitivity parameters to establish a shale geostress intensity model.

[0178] As an option, 3D geostress prediction includes:

[0179] Analyze the pilot well pressure curve and determine the stress sensitive parameters;

[0180] Using the pilot well stress parameter data, the stress parameter distribution of the horizontal well section is established;

[0181] According to the geological, fault, fold deformation and well logging information, a stress field simulation material library for the modeling area is established;

[0182] Determine the attribute bodies that are sensitive to the direction and intensity of the stress field, perform attribute correction through drilling stress parameter data, and achieve three-dimensional geostress prediction by fusing multiple attribute bodies.

[0183] Optionally, determining seismic fracture detection attributes includes:

[0184] Extracting multiple seismic fracture detection attribute volumes;

[0185] Calculate the inter-layer average value of each seismic fracture detection attribute volume;

[0186] Extract the interlayer average value of the attribute body at the well point with imaging logging, and make intersection statistics with the fracture interpretation density value of imaging logging;

[0187] The correlation between each seismic fracture detection attribute body and the imaging logging fracture interpretation density value is obtained to determine the seismic fracture detection attribute with the best correlation.

[0188] As an optional solution, constraining and correcting the fracture development probability model through the ground stress intensity model includes:

[0189] Perform normalization calculation on the ground stress intensity model and transform the model value into distribution data in the interval [0,1];

[0190] Perform normalization calculation on the fracture development probability model and transform the model value into distribution data in the interval [0,1];

[0191] Based on the normalized ground stress model and fracture development probability model, the percentage coefficients are multiplied respectively, and the sum of the coefficients is 100%;

[0192] The calculated ground stress model is added to the calculated crack probability model to obtain a three-dimensional distribution model of crack development intensity.

[0193] As an optional solution, a discrete fracture network model is established and repeatedly verified to establish a natural fracture model for shale gas reservoirs, including:

[0194] Based on the spatial distribution model of fracture phases, the parameters characterizing fracture development characteristics are used as conditional data, and random simulation is performed for each fracture phase to establish discrete fracture network models in turn.

[0195] By adjusting the fracture parameter input, the discrete fracture network model is repeatedly verified until the geometry of the discrete fracture network model is consistent with the fracture parameters interpreted by the imaging logging;

[0196] Based on the discrete fracture network model, a natural fracture model of shale gas reservoirs is established.

[0197] Example 3

[0198] The present disclosure provides an electronic device, which includes: a memory storing executable instructions; a processor, which runs the executable instructions in the memory to implement the above-mentioned method for establishing a natural fracture model of a shale gas reservoir.

[0199] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0200] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0201] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0202] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0203] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0204] Example 4

[0205] An embodiment of the present disclosure provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for establishing a natural fracture model of a shale gas reservoir is implemented.

[0206] According to the computer-readable storage medium of the embodiment of the present disclosure, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the method of each embodiment of the present disclosure are executed.

[0207] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0208] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.

[0209] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for establishing a natural fracture model of a shale gas reservoir, characterized in that: include: Determine the nature and direction of stress in different areas of shale, and then establish a shale ground stress intensity model; Dividing the fracture phases of shale, marking the fracture phases with discrete data, and establishing a spatial distribution model of the fracture phases of shale; Determine the relationship between the ground stress and the cracks in each fracture phase, and determine the distribution state of the parameters that characterize the fracture development characteristics; Determine the seismic fracture detection attributes, establish a fracture development probability model, constrain and correct the fracture development probability model through the in-situ stress intensity model, and determine the spatial distribution model of fracture development intensity; A discrete fracture network model was established and calibrated repeatedly to establish a natural fracture model of shale gas reservoirs.

2. The method for establishing a natural fracture model of a shale gas reservoir according to claim 1, wherein: Determining the nature and direction of stresses in different areas of shale includes: Based on the three-dimensional seismic data, the structure of the shale formation is interpreted in detail, the key shale layers and fault distribution data are obtained, the structural undulation characteristics of the shale formation are analyzed, the shale structural deformation is geologically analyzed, and the nature and direction of the stress in different shale areas are determined.

3. The method for establishing a natural fracture model of a shale gas reservoir according to claim 1, wherein: The establishment of the in-situ stress intensity model of shale includes: Based on geological data, fault distribution, structural deformation characteristics, and logging information data, three-dimensional geostress prediction is carried out under the constraint control of structural stress characteristics based on seismic analysis and single well stress sensitivity parameters to establish a shale geostress intensity model.

4. The method for establishing a natural fracture model of a shale gas reservoir according to claim 3, wherein: The three-dimensional geostress prediction includes: Analyze the pilot well pressure curve and determine the stress sensitive parameters; Using the pilot well stress parameter data, the stress parameter distribution of the horizontal well section is established; According to the geological, fault, fold deformation and well logging information, a stress field simulation material library for the modeling area is established; The attribute bodies that are sensitive to the direction and intensity of the stress field are determined, the attribute correction is performed through the drilling stress parameter data, and the three-dimensional ground stress prediction is achieved by fusing multiple attribute bodies.

5. The method for establishing a natural fracture model of a shale gas reservoir according to claim 1, wherein: Determining the seismic fracture detection attribute includes: Extracting multiple seismic fracture detection attribute volumes; Calculate the inter-layer average value of each seismic fracture detection attribute volume; Extract the interlayer average value of the attribute body at the well point with imaging logging, and make intersection statistics with the fracture interpretation density value of imaging logging; The correlation between each seismic fracture detection attribute body and the imaging logging fracture interpretation density value is obtained to determine the seismic fracture detection attribute with the best correlation.

6. The method for establishing a natural fracture model of a shale gas reservoir according to claim 1, wherein: The constraint correction of the fracture development probability model by using the in-situ stress intensity model includes: Performing normalization calculation on the in-situ stress intensity model to convert the model value into distribution data in the interval [0,1]; Performing normalization calculation on the fracture development probability model to convert the model value into distribution data in the interval [0,1]; The weighted coefficients of the normalized geostress intensity model and the fracture development probability model are determined, and the weighted geostress intensity model and the fracture development probability model are added together to obtain a three-dimensional distribution model of fracture development intensity.

7. The method for establishing a natural fracture model of a shale gas reservoir according to claim 1, wherein: Establishing a discrete fracture network model and repeatedly verifying it, and then establishing a natural fracture model for shale gas reservoirs includes: Based on the fracture phase spatial distribution model, taking the parameters characterizing fracture development characteristics as conditional data, performing random simulation for each fracture phase, and sequentially establishing discrete fracture network models; By adjusting the fracture parameter input, the discrete fracture network model is repeatedly verified until the geometry of the discrete fracture network model is consistent with the fracture parameters interpreted by the imaging logging; A natural fracture model of shale gas reservoir is established based on the discrete fracture network model.

8. A device for establishing a natural fracture model of a shale gas reservoir, characterized in that: include: The module for establishing the in-situ stress intensity model determines the nature and direction of stress in different areas of shale, and then establishes the in-situ stress intensity model of shale; A fracture phase spatial distribution model establishment module is used to divide the fracture phases of shale, to perform discrete data marking on the fracture phases, and to establish a fracture phase spatial distribution model of shale; The fracture parameter determination module determines the relationship between the ground stress and the fracture of each fracture phase and determines the distribution state of the parameters that characterize the fracture development characteristics; A module for establishing a spatial distribution model of fracture development intensity, determining seismic fracture detection attributes, establishing a fracture development probability model, constraining and correcting the fracture development probability model through the in-situ stress intensity model, and determining a spatial distribution model of fracture development intensity; The fracture attribute parameter distribution model establishment module establishes a discrete fracture network model and repeatedly verifies it, and then establishes a natural fracture model of shale gas reservoirs.

9. An electronic device, characterized in that: The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the method for establishing a natural fracture model of a shale gas reservoir according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for establishing a natural fracture model of a shale gas reservoir according to any one of claims 1 to 7 is implemented.

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