Method and electronic device for establishing oil and gas reservoir fracture model

Abstract

The present invention discloses a method for establishing an oil and gas reservoir fracture model and an electronic device. The method comprises: separately establishing a structural-stratigraphic framework model and an oil and gas reservoir fracture geological concept model; extracting multiple seismic fracture detection attribute bodies and selecting the most similar seismic fracture detection attribute body; calculating ant-body fracture tracking attributes and obtaining a set of fracture slices in the target oil and gas reservoir area, thereby obtaining a target oil and gas reservoir fracture envelope attribute body; dividing the fracture system envelope into a fault-joint zone and a dispersed fracture zone; performing discrete data labeling on the fracture development phase zone and establishing a discrete geological model of the fracture development phase zone; and establishing a large-scale fracture model, a medium-scale fracture model, and a small-scale fracture model. The method solves the problem in the prior art that the existing fracture model, due to the use of a discrete fracture network modeling method, is unable to reflect the spatial configuration relationship of fractures at various scales in the entire fracture system.

Description

Technical Field

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

[0002] With the advancement of oil and gas exploration and development, conventional, simple reservoirs have been fully developed and utilized. Consequently, domestic and even international oil and gas resources increasingly require exploration and development in unconventional or complex reservoirs. These reservoirs generally face the challenge of well-developed fracture systems and fracture-controlled oil and production. Therefore, the detailed characterization and modeling of fractured reservoirs is a crucial topic in the current and future oil and gas fields. Natural fracture modeling is a crucial and crucial research area in geological modeling. High-quality fracture models must accurately reflect the distribution characteristics of fractures within the study area. Currently, the characterization and modeling of fractures in fractured reservoirs is still in its early stages, with research focusing on the description and prediction of fractures based on outcrop, drilling, and seismic data. A reliable fracture model is not only a comprehensive representation of fracture characterization results but also a quantitative means of fracture characterization. To date, research that deeply explores fracture detection properties and effectively and comprehensively applies them to construct spatial distribution models of natural fractures is limited.

[0003] At present, the discrete fracture network modeling method has become the mainstream of fracture reservoir modeling, but the discrete fracture modeling method requires accurate knowledge of the spatial distribution of fractures as the driving force for the generation of fracture fragments between wells. There are still many points worth noting when establishing reservoir fracture models: (1) It is necessary to more accurately distinguish the fractures of each scale in the multi-scale fracture system and clarify the spatial distribution of fractures of each scale; (2) Currently, the fractures that can be responded to by seismic attributes are mostly used to qualitatively or semi-quantitatively characterize the development degree of fractures. The means and methods to fully explore seismic fracture information and convert seismic fracture detection results into fracture models are still relatively scarce; (3) The occurrence, density, and opening of fractures in fractured reservoirs are mostly obtained from limited imaging logging interpretation. The fracture parameters of unimaged logging and inter-well locations are still difficult to determine; (4) The most important point is that the multi-scale fracture is a complete fracture system, while the current multi-scale fracture models are mostly constructed step by step by fractures of each scale, which are not related to each other. The existing fracture models are difficult to reflect the spatial configuration relationship of fractures of each scale in the entire fracture system.

[0004] Therefore, it is expected to invent a method for establishing a fracture model of an oil and gas reservoir, which can solve the problem in the prior art that the existing fracture model is difficult to reflect the spatial configuration relationship of fractures at various scales in the entire fracture system due to the use of a discrete fracture network modeling method. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for establishing an oil and gas reservoir fracture model to solve the problem in the prior art that the existing fracture model is difficult to reflect the spatial configuration relationship of fractures at various scales in the entire fracture system due to the use of discrete fracture network modeling methods.

[0006] In order to achieve the above object, the present invention provides a method for establishing an oil and gas reservoir fracture model, comprising:

[0007] Step 1: Establish a structural-stratigraphic framework model and a conceptual geological model of oil and gas reservoir fractures;

[0008] Step 2: Acquire 3D seismic data, extract multiple seismic fracture detection attribute bodies from the 3D seismic data, and select the most similar seismic fracture detection attribute body based on the structural-stratigraphic framework model and the oil and gas reservoir fracture geological conceptual model;

[0009] Step 3: Based on the most similar seismic fracture detection attribute volume, calculate the ant body fracture tracking attribute and obtain the fracture slice set of the target oil and gas reservoir area. Based on the most similar seismic fracture detection attribute volume, calculate multiple fracture sweep range attribute volumes and obtain the fracture envelope attribute volume of the target oil and gas reservoir.

[0010] Step 4: Selecting a fracture sweep attribute body that is most similar to the development range of fractures associated with the target area from the target oil and gas reservoir fracture envelope attribute body as the target oil and gas reservoir fault joint zone attribute body, and dividing the fracture system envelope into a fault joint zone and a scattered fracture zone based on the target oil and gas reservoir fault joint zone attribute body;

[0011] Step 5: Based on the fault joint zone and the scattered fracture zone, discrete data marking is performed on the fracture development facies zone, and a discrete geological model of the fracture development facies zone is established using a deterministic method;

[0012] Step 6: Based on the structural-stratigraphic framework model, the fracture slice set of the target oil and gas reservoir area and the discrete geological model of the fracture development phase belt, a large-scale fracture model, a medium-scale fracture model and a small-scale fracture model are established.

[0013] Optionally, step 1 includes:

[0014] Conduct structural interpretation of the target layer of the oil and gas reservoir based on 3D seismic data to obtain key layer data and fault distribution data of the target layer of the oil and gas reservoir as well as structural deformation characteristics of the oil and gas reservoir;

[0015] Based on the key layer data and the fault distribution data, the structural-stratigraphic framework model is established according to the selected modeling area and grid step size;

[0016] A geological interpretation is performed on the structural deformation characteristics to establish a conceptual geological model of the oil and gas reservoir fractures. The conceptual geological model of the oil and gas reservoir fractures characterizes the parameter distribution state of the fracture development characteristics, and the fracture development characteristics include at least one of the fracture cluster system, fracture tendency and inclination, and fracture aperture of the multi-scale fracture system.

[0017] Optionally, the step of selecting the most similar seismic fracture detection attribute body includes:

[0018] Each of the seismic fracture detection attribute bodies is matched with the structural-stratum framework model and the oil and gas reservoir fracture geological concept model, and the most similar seismic fracture detection attribute body is selected.

[0019] Optionally, step 3 includes:

[0020] Step 31: Calculating the ant body crack tracking attribute based on the most similar earthquake crack detection attribute body;

[0021] Step 32: extracting a set of fracture slices in the target area of the oil and gas reservoir based on the ant body fracture tracking attributes;

[0022] Step 33: Based on the most similar seismic fracture detection attribute body, multiple fracture impact range attribute bodies are calculated, and each fracture impact range attribute body is calibrated and optimized in turn to obtain a target oil and gas reservoir fracture envelope attribute body;

[0023] The step 33 includes:

[0024] Randomly select multiple sample points within the most similar earthquake fracture detection attribute volume, and set a fracture development degree statistical radius corresponding to each sample point with each sample point as the center;

[0025] For each sample point, the radius is calculated based on the corresponding fracture development degree, the fracture affected area at the sample point is circled, and the number of fracture detection attribute passing seismic traces within the fracture affected area is counted;

[0026] Calculating the ratio of the number of seismic traces passing the crack detection attribute within the crack affected area corresponding to each sample point to the total number of seismic traces within the unit area, and using the ratio as the crack development density within the crack affected area corresponding to the sample point;

[0027] Changing the fracture development degree statistical radius to obtain a plurality of fracture impact range attribute bodies and internal fracture development density bodies thereof;

[0028] Calculating an inter-layer average value of a plurality of the crack impact range attribute bodies within a target layer;

[0029] Extracting the value at the imaging logging well point from the interlayer average value of each fracture sweep attribute body;

[0030] Calculating an average value of fracture density interpreted by imaging logging within the target layer;

[0031] The interlayer average value of each fracture sweep attribute body at the imaging logging well point and the fracture density average value interpreted by the imaging logging are intersected and statistically analyzed, and the fracture sweep attribute body with the best correlation is selected as the fracture envelope attribute body of the target oil and gas reservoir.

[0032] Optionally, after step 3, the following steps are further included:

[0033] Performing grid sampling on the target oil and gas reservoir fracture envelope attribute body through the structural-stratigraphic framework model to obtain a fracture system envelope geological model;

[0034] The numerical values of the fracture system envelope geological model are normalized and calculated according to the 0-1 interval distribution to obtain a fracture development probability continuity geological model.

[0035] Optionally, after step 5, the following steps are further included:

[0036] Based on the discrete geological model of the fracture development facies, the distribution range, mean, variance and variation of the fracture strike, fracture dip, fracture aperture and fracture density of the imaging logging in each fracture development facies are statistically analyzed.

[0037] Optionally, step 6 includes:

[0038] Step 61: Based on the structural-stratum framework model, establish the large-scale fracture model using a deterministic method;

[0039] Step 62: Based on the set of fracture slices in the target area of the oil and gas reservoir, a mesoscale fracture model is established using a deterministic method;

[0040] Step 63: Based on the discrete geological model of the fracture development phase belt, a small-scale fracture model is established using a zoning phase control method;

[0041] Among them, the large-scale fracture model, the medium-scale fracture model and the small-scale fracture model all include a discrete fracture network model and a fracture attribute parameter distribution model. The fracture attribute parameter distribution model includes fracture porosity and fracture permeability and fluid crossflow coefficient in the x, y and z directions.

[0042] Optionally, step 63 includes:

[0043] For the fault-fracture joint zone, based on the distribution range, mean, variance and degree of variation of the fracture strike, fracture dip, fracture aperture and fracture density interpreted by the imaging logging, a point-indicating method is used for random simulation to obtain a discrete fracture network model of the fault-fracture joint zone and a distribution model of the fracture attribute parameters;

[0044] For the dispersed fracture zone, based on the fracture development probability continuity geological model and the correlation between fracture intensity and fracture attribute parameters obtained from drilling statistics, a fracture attribute parameter distribution model is equivalently calculated.

[0045] Optionally, after step 6, the following steps are further included:

[0046] Step 7: Perform model grid calculations on the large-scale fracture model, the medium-scale fracture model, and the small-scale fracture model respectively to obtain a three-dimensional geological model integrating multi-scale fracture system attribute parameters.

[0047] An electronic device, comprising:

[0048] a memory storing executable instructions;

[0049] A processor runs the executable instructions in the memory to implement the method for establishing an oil and gas reservoir fracture model.

[0050] The beneficial effects of the present invention are:

[0051] The method for establishing a fracture model for a reservoir of the present invention targets the fracture system, incorporates the fracture envelope attribute body, and sorts out the multi-scale fracture relationships and modeling process, thus achieving the organic integration of multi-scale fracture models. Furthermore, the method for establishing a fracture model for a reservoir of the present invention fully utilizes multiple seismic fracture attributes to establish a fracture density model, namely, a large-scale fracture model, a medium-scale fracture model, and a small-scale fracture model. This model reflects the differences in fracture development under the constraints of fractures of different scales, resulting in a more accurate model. Furthermore, the method for establishing a fracture model for a reservoir of the present invention treats each scale of fracture and fracture system as a whole, fully considering the spatial configuration relationship of fracture systems of different scales within it, fully mining and applying various types of fault detection information from seismic data bodies, and accurately characterizing the spatial distribution of various parameter data of natural fractures. This provides a more reliable geological model foundation for the efficient development of fractured reservoirs, thereby providing a more reliable geological model guarantee for subsequent reservoir engineering analysis or fracturing process modification. Therefore, the method for establishing a fracture model for a reservoir of the present invention solves the problem in the prior art that existing fracture models, due to the use of discrete fracture network modeling methods, are unable to reflect the spatial configuration relationship of fractures of various scales in the entire fracture system.

[0052] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] 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 with reference to the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.

[0054] Figure 1 A flow chart of a method for establishing an oil and gas reservoir fracture model according to an embodiment of the present invention is shown.

[0055] Figure 2 The invention shows a method for establishing a fracture model of an oil and gas reservoir in a study area and a geological concept model of fractures in the oil and gas reservoir.

[0056] Figure 3 The ant tracking attribute body of the most similar seismic fracture detection attribute body is shown in the study area of a method for establishing a fracture model of an oil and gas reservoir according to an embodiment of the present invention.

[0057] Figure 4 The invention shows a fracture envelope attribute body of a study area of a method for establishing a fracture model of a fracture in a fractured reservoir according to an embodiment of the present invention.

[0058] Figure 5 The invention shows a method for establishing a fracture model of an oil and gas reservoir in a study area and a fault joint zone attribute body thereof.

[0059] Figure 6 A discrete geological model of fracture development phases of different fracture development zones in a study area of an oil and gas reservoir according to a method for establishing a fracture model of an oil and gas reservoir in one embodiment of the present invention is shown.

[0060] Figure 7 A discrete fracture network (DFN) model of fault-fracture systems of different scales in a study area of a method for establishing a fracture model of an oil and gas reservoir according to an embodiment of the present invention is shown.

[0061] Figure 8 A three-dimensional porosity distribution model of a multi-scale fault-fracture system in a study area according to a method for establishing a fracture model of an oil and gas reservoir according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0062] 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 by the embodiments set forth herein. Instead, these embodiments are provided to make the present invention more thorough and complete and to fully convey the scope of the present invention to those skilled in the art.

[0063] A method for establishing an oil and gas reservoir fracture model according to the present invention includes:

[0064] Step 1: Establish a structural-stratigraphic framework model and a conceptual geological model of oil and gas reservoir fractures;

[0065] Step 2: Acquire 3D seismic data and extract multiple seismic fracture detection attribute volumes from the 3D seismic data. Based on the structural-stratigraphic framework model and the reservoir fracture geological conceptual model, select the most similar seismic fracture detection attribute volume.

[0066] Step 3: Based on the most similar seismic fracture detection attribute volume, the ant body fracture tracking attributes are calculated to obtain a set of fracture slices in the target oil and gas reservoir area. Based on the most similar seismic fracture detection attribute volume, multiple fracture sweep range attribute volumes are calculated to obtain a fracture envelope attribute volume in the target oil and gas reservoir area.

[0067] Step 4: Select the fracture sweep attribute body that is most similar to the development range of fractures associated with the target area from the target oil and gas reservoir fracture envelope attribute body as the target oil and gas reservoir fault joint zone attribute body. Based on the target oil and gas reservoir fault joint zone attribute body, divide the fracture system envelope into the fault joint zone and the scattered fracture zone.

[0068] Step 5: Based on the fault joint zone and the scattered fracture zone, the fracture development facies belt is discretely marked, and a discrete geological model of the fracture development facies belt is established using a deterministic method;

[0069] Step 6: Based on the structural-stratigraphic framework model, the fracture slice set of the target oil and gas reservoir area, and the discrete geological model of the fracture development facies belt, establish large-scale fracture models, medium-scale fracture models, and small-scale fracture models.

[0070] Specifically, the method for establishing a fracture model for an oil and gas reservoir of the present invention targets the fracture system, incorporates fracture envelope attributes, and organizes multi-scale fracture relationships and modeling processes, achieving an organic integration of multi-scale fracture models. Furthermore, the method for establishing a fracture model for an oil and gas reservoir of the present invention fully utilizes multiple seismic fracture attributes to establish large-scale fracture models, mesoscale fracture models, and small-scale fracture models. By establishing models of different fracture development phases, the method reflects the differences in fracture development under the constraints of fractures of different scales, resulting in a more accurate model. Furthermore, the method for establishing a fracture model for an oil and gas reservoir of the present invention treats each scale of fractures and the fracture system as a whole, fully considering the spatial configuration relationship of fracture systems of different scales within the system, fully mining and applying various types of fault detection information from seismic data, and accurately characterizing the spatial distribution of various parameter data of natural fractures. This provides a more reliable geological model foundation for the efficient development of fractured oil and gas reservoirs, thereby providing a more reliable geological model guarantee for subsequent oil and gas reservoir engineering analysis or fracturing process modification. Therefore, the method for establishing a fracture model for an oil and gas reservoir of the present invention solves the problem in the prior art that the existing fracture models, due to the use of discrete fracture network modeling methods, are unable to reflect the spatial configuration relationship of fractures of various scales in the entire fracture system.

[0071] Furthermore, in practical applications, based on the control range D{d1, d2, ... dn} of the large-scale fault F{f1, f2, ... fn} on the development of small-scale fractures, the fracture sweep attribute body that is most similar to the control range D is selected. Among them, the control range D{d1, d2, ... dn} of the large-scale fault F{f1, f2, ... fn} on the development of small-scale fractures can be statistically correlated with the fracture development degree data of actual drilling data and the distance between the drilling well and the adjacent fault fn, so as to obtain the farthest distance dn that the fault can affect the development of fractures.

[0072] Furthermore, the fault-joint zone refers to the cracks associated with large-scale faults. It has a unified tectonic stress field with the formation and development of large-scale faults, and the crack occurrence has consistent directionality. At the same time, the scattered fracture zone refers to the cracks formed mainly under local tectonic deformation conditions induced during the tectonic deformation process. The cracks are distributed in a disorderly manner and do not have a unified directionality.

[0073] In one example, step 1 includes:

[0074] Conduct structural interpretation of the target layer of the oil and gas reservoir based on 3D seismic data to obtain key layer data and fault distribution data of the target layer of the oil and gas reservoir, as well as the structural deformation characteristics of the oil and gas reservoir;

[0075] Based on key layer data and fault distribution data, a structural-stratigraphic framework model is established according to the selected modeling area and grid step size;

[0076] A geological interpretation of structural deformation characteristics is conducted to establish a conceptual geological model of oil and gas reservoir fractures. The conceptual geological model of oil and gas reservoir fractures characterizes the parameter distribution state of fracture development characteristics. The fracture development characteristics include at least one of the fracture cluster system, fracture tendency and inclination, and fracture aperture of the multi-scale fracture system.

[0077] Specifically, establishing a tectonic-stratigraphic framework model based on key layer data and fault distribution data, in accordance with a selected modeling region and grid step size, includes: establishing layer and fault models based on the key layer data and fault distribution data; and establishing a tectonic-stratigraphic framework model based on the layer and fault models, in accordance with the selected modeling region and grid step size. In practical applications, the establishment of a simple tectonic-stratigraphic framework model should be carried out in accordance with the technical content of fault models and layer models specified in the industry standard (SY / T 7378). The establishment of a complex tectonic-stratigraphic framework model should be based on geological understanding and geometric characteristics, adjusting the fault plane morphology and setting the cutting relationship between faults.

[0078] Furthermore, a geological analysis is conducted on the structural deformation characteristics of the oil and gas reservoir to obtain the nature and direction of the stress in different regions. Based on the geomechanical theory of fracture genesis, the multi-scale nature of the fractures is analyzed, and a geological conceptual model of oil and gas reservoir fractures is established. Among them, the structural deformation characteristics refer to the degree of folding and undulation of the layer and the degree of fracture cutting of the layer. According to the nature of the fault interpreted by seismic interpretation, the regional stress background is judged. For example, reverse faults indicate compressive stress, and the direction of maximum stress is perpendicular to the fault direction. The geological conceptual model of oil and gas reservoir fractures is a comprehensive geological understanding of the development of oil and gas reservoir fractures, and does not represent the actual or final fracture model. The geological conceptual model of oil and gas reservoir fractures includes the distribution state of parameters such as fracture clusters, fracture inclination and dip, and fracture aperture of the multi-scale fracture system that characterize the characteristics of fracture development.

[0079] In one example, selecting the most similar seismic fracture detection attribute body includes:

[0080] Each seismic fracture detection attribute body is matched with the structural-stratigraphic framework model and the oil and gas reservoir fracture geological conceptual model, and the most similar seismic fracture detection attribute body is selected.

[0081] Specifically, based on 3D seismic data, multiple seismic fracture detection attribute bodies are extracted, and the matching relationship between each seismic fracture detection attribute body and the structural-stratigraphic framework model and the oil and gas reservoir fracture geological conceptual model is compared to select the most similar seismic fracture detection attribute body.

[0082] In one example, step 3 includes:

[0083] Step 31: Calculate the ant body crack tracking attributes based on the most similar earthquake crack detection attribute body;

[0084] Step 32: extracting a set of fracture slices in the target area of the oil and gas reservoir based on the ant body fracture tracking attributes;

[0085] Step 33: Based on the most similar seismic fracture detection attribute volume, multiple fracture sweep attribute volumes are calculated, and each fracture sweep attribute volume is calibrated and optimized in turn to obtain the target oil and gas reservoir fracture envelope attribute volume;

[0086] Step 33 includes:

[0087] Randomly select multiple sample points within the most similar earthquake fracture detection attribute volume, and set the fracture development degree statistical radius corresponding to each sample point with each sample point as the center;

[0088] For each sample point, the radius is calculated based on the corresponding fracture development degree, the fracture affected area at the sample point is circled, and the number of fracture detection attributes passing through the seismic trace within the fracture affected area is counted;

[0089] Calculate the ratio of the number of seismic traces with crack detection attributes within the crack affected area corresponding to each sample point to the total number of seismic traces per unit area, and use the ratio as the crack development density within the crack affected area corresponding to the sample point;

[0090] Changing the statistical radius of fracture development degree to obtain multiple fracture sweep range attribute bodies and their internal fracture development density bodies;

[0091] Calculate the inter-layer average value of multiple crack sweep attribute bodies within the target layer;

[0092] Extract the attribute value at the imaging logging well point from the inter-layer average value of each fracture sweep range attribute volume;

[0093] Calculate the average fracture density interpreted by imaging logging within the target layer;

[0094] The interlayer average value of each fracture sweep attribute body at the imaging logging well point and the average value of fracture density interpreted by imaging logging are intersected and statistically analyzed, and the fracture sweep attribute body with the best correlation is selected as the fracture envelope attribute body of the target oil and gas reservoir.

[0095] Specifically, when calculating the ant body fracture tracking properties, the calculation parameters should be optimized multiple times according to the calculation results until the displayed fracture prominence and fracture continuity are optimal; at the same time, when extracting the fracture slice set in the target area of the oil and gas reservoir, the extraction parameters should be optimized multiple times according to the extraction results until the displayed fracture slice number and fracture slice continuity are most consistent with the ant body fracture tracking results.

[0096] Furthermore, based on the most similar seismic fracture detection attribute body, multiple fracture sweep attribute bodies are calculated, and each fracture sweep attribute body is calibrated and optimized in turn according to the fracture information obtained from actual drilling to obtain the fracture envelope attribute body of the target oil and gas reservoir. Among them, the fracture sweep attribute body is a quantitative description of the degree of fracture development at each sample point in space.

[0097] Furthermore, extracting the attribute values at the imaging logging wellpoint from the interlayer averages of each fracture-affected attribute volume can be understood as statistically analyzing only the data at the wellpoint. This means: the interlayer averages of the fracture seismic attribute volume at the wellpoint form one column of data, denoted as x; the average fracture density values calculated through well logging imaging interpretation form another column of data, denoted as y. The correlation between x and y is then calculated. In essence, well logging is used to calibrate seismic data to determine which seismic attribute best aligns with the well logging.

[0098] Furthermore, the fracture envelope refers to the entire spatial range where fracture systems of all scales develop, and there are basically no fractures outside the envelope.

[0099] In one example, step 3 is followed by:

[0100] The fracture envelope attribute volume of the target oil and gas reservoir is grid sampled through the structural-stratigraphic framework model to obtain the fracture system envelope geological model;

[0101] The geological model values of the fracture system envelope are normalized according to the 0-1 interval distribution to obtain the fracture development probability continuity geological model.

[0102] In one example, step 5 further includes:

[0103] Based on the discrete geological model of fracture development facies, the distribution range, mean, variance and variation of fracture strike, fracture dip, fracture aperture and fracture density in each fracture development facies were statistically analyzed.

[0104] In one example, step 6 includes:

[0105] Step 61: Based on the structural-stratum framework model, a deterministic method is used to establish the large-scale fracture model;

[0106] Step 62: Based on the set of fracture slices in the target area of the oil and gas reservoir, a mesoscale fracture model is established using a deterministic method;

[0107] Step 63: Based on the discrete geological model of the fracture development facies, a small-scale fracture model is established using a zoning phase control method;

[0108] Among them, the large-scale fracture model, the medium-scale fracture model and the small-scale fracture model all include discrete fracture network models and fracture attribute parameter distribution models. The fracture attribute parameter distribution models include fracture porosity and fracture permeability and fluid crossflow coefficient in the x, y and z directions.

[0109] In one example, step 63 includes:

[0110] For the fault-fracture joint zone, based on the distribution range, mean, variance, and variation of fracture strike, fracture dip, fracture aperture, and fracture density interpreted by imaging logging, a point-based random simulation was used to obtain a discrete fracture network model and a fracture attribute parameter distribution model for the fault-fracture joint zone.

[0111] For dispersed fracture zones, based on the fracture development probability continuity geological model and the correlation between fracture intensity and fracture attribute parameters obtained from drilling statistics, the fracture attribute parameter distribution model is equivalently calculated.

[0112] In one example, step 6 further includes:

[0113] Step 7: Perform model grid calculations on the large-scale fracture model, the medium-scale fracture model, and the small-scale fracture model respectively to obtain a three-dimensional geological model that integrates the attribute parameters of the multi-scale fracture system.

[0114] Specifically, if the model grid has only one-scale fracture attribute parameter data, the grid value remains unchanged; if the model grid contains fracture attribute parameter data of two or more scales, the fracture attribute parameter data of the larger scale is used as the fracture attribute parameter data of the grid, forming a three-dimensional geological model that integrates the attribute parameters of the multi-scale fracture system.

[0115] An electronic device, comprising:

[0116] a memory storing executable instructions;

[0117] A processor runs the executable instructions in the memory to implement the method for establishing an oil and gas reservoir fracture model.

[0118] Example 1

[0119] like Figure 1 As shown, a method for establishing an oil and gas reservoir fracture model includes:

[0120] Step 1: Establish a structural-stratigraphic framework model and a conceptual geological model of oil and gas reservoir fractures;

[0121] Step 2: Acquire 3D seismic data and extract multiple seismic fracture detection attribute volumes from the 3D seismic data. Based on the structural-stratigraphic framework model and the reservoir fracture geological conceptual model, select the most similar seismic fracture detection attribute volume.

[0122] Step 3: Based on the most similar seismic fracture detection attribute volume, the ant body fracture tracking attributes are calculated to obtain a set of fracture slices in the target oil and gas reservoir area. Based on the most similar seismic fracture detection attribute volume, multiple fracture sweep range attribute volumes are calculated to obtain a fracture envelope attribute volume in the target oil and gas reservoir area.

[0123] Step 4: Select the fracture sweep attribute body that is most similar to the development range of fractures associated with the target area from the target oil and gas reservoir fracture envelope attribute body as the target oil and gas reservoir fault joint zone attribute body. Based on the target oil and gas reservoir fault joint zone attribute body, divide the fracture system envelope into the fault joint zone and the scattered fracture zone.

[0124] Step 5: Based on the fault joint zone and the scattered fracture zone, the fracture development facies belt is discretely marked, and a discrete geological model of the fracture development facies belt is established using a deterministic method;

[0125] Step 6: Based on the structural-stratigraphic framework model, the fracture slice set of the target oil and gas reservoir area, and the discrete geological model of the fracture development facies belt, establish large-scale fracture models, medium-scale fracture models, and small-scale fracture models.

[0126] The specific implementation is as follows:

[0127] The test area is the Ahnet B reservoir in the study area, a structural gas reservoir controlled by a fault anticline. The reservoir has low porosity and permeability and well-developed fractures, resulting in a fractured gas reservoir with a dual media structure of fractures and pores. Three-dimensional seismic data is available from 25 wells in the study area, including well logs, mud logging data, and well test production data. Eight of these wells have imaging logs, whose interpretation provides information on fracture dip and orientation. Seismic data has been processed and interpreted, revealing multiple stratigraphic boundaries within the reservoir. The primary strata in the study area are Ordovician, characterized by transitional marine-continental sedimentary formations. Natural gas is primarily produced in deltaic, beach-bar, and other sedimentary sand bodies. Drilling revealed significant vertical variations in gas-bearing properties within the reservoir, generally dividing it into upper and lower intervals. Drilling and gas logging results indicate that fractures are multi-scale, with varying degrees of natural fracture development in different structural zones and significant variations in cumulative gas production. Therefore, it is necessary to characterize the spatial distribution of natural fractures in detail in order to further evaluate the fracturing effect and predict development productivity.

[0128] The oil and gas reservoir fracture model establishment method of this invention is used to establish a natural fracture model of the gas reservoir.

[0129] (1) Based on the drilling stratification data and seismic horizon interpretation, a layer model for each layer was established. Based on the seismic interpretation of the fault data, a fault distribution model was established. A total of 56 fault models were established in the test area. The horizontal and vertical grid steps were designed to establish a structural-stratigraphic framework model of the B gas reservoir in the test area.

[0130] (2) Analyze the structural undulations and fault distribution characteristics of the layers. According to the interpretation of the layers and faults, the faults on the east and west sides of the anticline where the B gas reservoir is located are all high-angle reverse faults with a NS trend. It is judged that the maximum principal stress direction when the structure was formed was EW compression. In the western part of the test area, high-angle strike-slip faults with a NS trend were developed. It is judged that shear stress in the NS direction also existed during the formation of the structure. Figure 2 As shown, a conceptual geological model of fracture development in gas reservoir B was constructed based on the geomechanical theory of fracture genesis. In this model, large-scale fractures of both compressional and shearing nature develop under two principal stress settings, vertically cutting through the entire formation. Small- to medium-scale associated fractures develop near compressional reverse faults, with strikes generally aligned with the faults, trending north-south. Small- to medium-scale associated fractures (or joints) develop near shearing strike-slip faults, with strikes at an angle to the faults, generally trending north-south. Farther from the faults, localized small-scale fractures develop due to folding, often exhibiting nonuniform fracture occurrence within a given interval.

[0131] (3) Based on 3D seismic data, various seismic fracture detection attribute bodies such as coherence body, curvature body, variance body, and maximum likelihood are extracted. By comparing with the geological concept model and the structural-stratigraphic framework model, the FL attribute shows a strong anomaly at the main fault location, and a relatively continuous and staggered linear response of varying strengths is presented between wells. The numerical value reflects the probability of fracture development at different scales. The FL attribute body with the best matching relationship is selected as the data basis for subsequent fracture modeling.

[0132] (4) Figure 3 As shown in the figure, ant-body fracture tracking attributes are calculated based on the FL attribute volume, and the fracture geological volume is strengthened. By adjusting appropriate parameters, two ant-body tracking runs are performed to achieve optimal fracture characterization. Based on the final ant-body seismic attribute volume, a set of fracture slices is extracted. After multiple parameter optimizations, a set of fracture slices that best matches the ant-body attributes of the test area is obtained.

[0133] (5) Based on the FL attribute body, multiple fracture impact range attribute bodies are calculated, that is, the ratio of the number of seismic traces passing through the fracture in a unit area to the total number of seismic traces in a unit area. The key parameter in the fracture impact range attribute calculation process is the fracture impact range extraction radius, which represents the range of fractures that affect the FL attribute at a certain sampling point. By trying multiple fracture impact range extraction radii and intersecting the average value of the interlayer fracture impact range attribute with the average value of the fracture density at the imaging logging well point, it was found that when 600m was taken as the extraction radius, the extracted fracture impact range attribute showed a good positive correlation with the fracture density interpreted by the actual drilling. With 600m as the extraction radius, the fracture impact range attribute based on the FL attribute was calculated as the fracture envelope attribute body of the B gas reservoir. As shown in Figure 4 As shown in the figure, all scale fracture systems are included within the fracture envelope, and outside the fracture envelope, it is considered that there is basically no fracture development.

[0134] (6) The intensity of fracture development interpreted by imaging logging is statistically analyzed with the distance of the well location from the main fault. It is found that the closer to the large-scale fault, the greater the intensity of small-scale fracture development, and the farther from the large-scale fault, the lower the intensity of small-scale fracture development. It is found that the small-scale fractures associated with the main fault are mainly developed within 400m from the fault. Based on the FL attribute, the fracture sweep range attribute body is calculated again, and the extraction radius is continuously reduced during the calculation. It is found that when the extraction radius is 400m, the obtained fracture sweep range attribute can meet the development range of small-scale associated fractures controlled by the large-scale fault. Figure 2 As shown in Figure 2, the fractures associated with large-scale faults have a unified tectonic stress field with the formation and development of large-scale faults, and the fracture occurrence has a consistent directionality. Taking 400m as the extraction radius, the fracture sweep range attribute based on the FL attribute is calculated as the fault joint zone attribute body of gas reservoir B, as shown in Figure 2. Figure 5 Therefore, within the fracture envelope, we further focus on the development sites of large-scale faults and their associated fractures to obtain the fault-fracture joint zone. In the areas farther away from the large-scale faults, there are also fractures. These fractures are mainly formed under the local structural deformation conditions induced during the structural deformation process and are called scattered fracture zones, as shown in Figure 2. Figure 2 The attribute volume of the dispersed fracture zone of gas reservoir B is obtained by deducting the fault joint zone from the fracture envelope zone.

[0135] (7) The fracture envelope attribute volume is converted into a depth domain attribute volume through time-depth, and a deterministic method is used to directly grid-sample the structure-stratum grid model. The model values are normalized and calculated according to the 0-1 interval distribution, which is used as the fracture development probability (or fracture intensity) model of gas reservoir B. The fault joint zone and the scattered fracture zone attribute volume are converted into a depth domain attribute volume through time-depth, and a deterministic method is used to directly grid-sample the structure-stratum grid model. According to the distribution range of the two, a discrete geological model of the fracture development phase belt is constructed, such as Figure 6 As shown, discrete data marking is performed, for example, phase belt 1 can be used as a fault joint belt, and phase belt 2 can be used as a dispersed fracture belt.

[0136] (8) Based on the discrete geological model of fracture development facies, the distribution range, mean, variance, and coefficient of variation of the parameters of the small-scale fracture system interpreted by phase zone statistical imaging logging, such as fracture direction, fracture dip, fracture aperture, and fracture density, were analyzed in each fracture development facies. Statistical results show that within the fault-fracture joint zone, the fractures revealed at the drilling site are more developed, with a main fracture density of 8 fractures / m, and the fracture trend is mainly NW-NE, which is basically consistent with the large-scale fault; within the dispersed fracture zone, the main fracture density revealed at the drilling site is 4 fractures / m, and the fracture occurrence is chaotic and does not have a uniform direction.

[0137] (9) Construct large-scale, medium-scale, and small-scale fracture models respectively: ① Based on the fault model, the 56 fault models are directly converted into large-scale discrete fracture network (DFN) models using a deterministic method, such as Figure 7 As shown in Figure 2; ② The set of fracture slices extracted based on the seismic attributes of the ant body is directly converted into a mesoscale discrete fracture network (DFN) model using a deterministic method, as shown in Figure 2. Figure 7 As shown in the figure; ③ Based on the fracture development facies model, the idea of zoning phase control is adopted. For the fault-fracture joint zone, the fracture occurrence, fracture density, and fracture aperture revealed by imaging logging are used as conditional data, and the fault-fracture joint zone attribute volume is used as the constraint variable for the degree of inter-well fracture development. The characteristic point method is used for random simulation to establish a discrete fracture network (DFN) model of the small-scale fault-fracture joint zone, as shown in the figure. Figure 7 ④ Based on the fracture development phase belt model, the partition phase control idea is adopted. For the dispersed fracture zone, according to the correlation between the fracture intensity and fracture attribute parameters obtained from drilling statistics, the fracture development probability model is equivalently calculated to obtain the fracture attribute parameter distribution model. ⑤ Based on the equivalent medium method of the discrete fracture network (DFN) model, on the basis of fracture scale, fracture dip, fracture aperture and conductivity, the fracture attribute parameter distribution models such as large-scale, medium-scale and small-scale (fault-fracture joint zone) fracture porosity and fracture permeability are obtained respectively, as shown in the figure below. Figure 8As shown in Figure 2, the fracture attribute parameter models for the fault-joint zone and the scattered fracture zone are combined to form a complete small-scale fracture attribute parameter distribution model. The large-scale, medium-scale, and small-scale fracture attribute parameter distribution models can be simplified into a large-scale fracture model, a medium-scale fracture model, and a small-scale fracture model.

[0138] (10) Based on the large, medium, and small scale fracture attribute parameter distribution models, and in light of the fracture genesis and development patterns, a multi-scale fracture attribute model fusion principle is formulated: each grid fracture scale is unique, the fracture scale is faithful to the well point interpretation, the large scale is prioritized, the medium and small scales are secondary, and the grid value is unique. If the model grid only has fracture attribute parameter data at one scale, the grid value remains unchanged; if the model grid contains fracture attribute parameter data at two or more scales, the data is fused according to the above principle, ultimately forming a three-dimensional geological model of the multi-scale fracture system attribute parameters of the B gas reservoir.

[0139] Comparison revealed that the natural fracture model established by the method of this invention effectively depicts the spatial distribution of fracture systems of varying scales within oil and gas reservoirs, ensuring that the distribution of multi-scale fractures under different regional in-situ stress conditions matches the geological laws governing fracture formation. It also more accurately reflects the spatial distribution of fracture attribute parameters. The fracture model established by this invention is more accurate and reliable, and also ensures the spatial distribution of natural fracture parameters. This fracture model allows for more targeted assessment of reservoir quality and distribution within oil and gas reservoirs, providing support for subsequent well placement optimization, fracturing evaluation, and the establishment of post-fracturing fracture network models.

[0140] Example 2

[0141] The present disclosure provides an electronic device comprising: a memory storing executable instructions; and a processor executing the executable instructions in the memory to implement the above-mentioned method for establishing an oil and gas reservoir fracture model.

[0142] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0143] The memory is used to store non-transitory 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 include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc.

[0144] The processor may be a central processing unit (CPU) or other form of processing unit having data processing capability and / or instruction execution capability, 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 execute the computer-readable instructions stored in the memory.

[0145] Those skilled in the art should understand that in order to solve the technical problem of how to obtain a good user experience, this 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 scope of protection of this disclosure.

[0146] For detailed description of this embodiment, please refer to the corresponding description in the aforementioned embodiments, which will not be repeated here.

[0147] While various embodiments of the present invention have been described above, the above description is intended to be illustrative, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations 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 fracture model of an oil and gas reservoir, characterized in that: include: Step 1: Establish a structural-stratigraphic framework model and a conceptual geological model of oil and gas reservoir fractures; Step 2: Acquire 3D seismic data, extract multiple seismic fracture detection attribute bodies from the 3D seismic data, and select the most similar seismic fracture detection attribute body based on the structural-stratigraphic framework model and the oil and gas reservoir fracture geological conceptual model; Step 3: Based on the most similar seismic fracture detection attribute volume, calculate the ant body fracture tracking attribute and obtain the fracture slice set of the target oil and gas reservoir area. Based on the most similar seismic fracture detection attribute volume, calculate multiple fracture sweep range attribute volumes and obtain the fracture envelope attribute volume of the target oil and gas reservoir. Step 4: Selecting a fracture sweep attribute body that is most similar to the development range of fractures associated with the target area from the target oil and gas reservoir fracture envelope attribute body as the target oil and gas reservoir fault joint zone attribute body, and dividing the fracture system envelope into a fault joint zone and a scattered fracture zone based on the target oil and gas reservoir fault joint zone attribute body; Step 5: Based on the fault joint zone and the scattered fracture zone, discrete data marking is performed on the fracture development facies zone, and a discrete geological model of the fracture development facies zone is established using a deterministic method; Step 6: Based on the structural-stratigraphic framework model, the fracture slice set of the target oil and gas reservoir area and the discrete geological model of the fracture development phase belt, a large-scale fracture model, a medium-scale fracture model and a small-scale fracture model are established.

2. The method for establishing a fracture model of an oil and gas reservoir according to claim 1, wherein: The step 1 comprises: Conduct structural interpretation of the target layer of the oil and gas reservoir based on 3D seismic data to obtain key layer data and fault distribution data of the target layer of the oil and gas reservoir as well as structural deformation characteristics of the oil and gas reservoir; Based on the key layer data and the fault distribution data, the structural-stratigraphic framework model is established according to the selected modeling area and grid step size; A geological interpretation is performed on the structural deformation characteristics to establish a conceptual geological model of the oil and gas reservoir fractures. The conceptual geological model of the oil and gas reservoir fractures characterizes the parameter distribution state of the fracture development characteristics, and the fracture development characteristics include at least one of the fracture cluster system, fracture tendency and inclination, and fracture aperture of the multi-scale fracture system.

3. The method for establishing a fracture model of an oil and gas reservoir according to claim 1, wherein: The method of selecting the most similar seismic fracture detection attribute body includes: Each of the seismic fracture detection attribute bodies is matched with the structural-stratum framework model and the oil and gas reservoir fracture geological concept model, and the most similar seismic fracture detection attribute body is selected.

4. The method for establishing a fracture model of an oil and gas reservoir according to claim 1, wherein: The step 3 comprises: Step 31: Calculating the ant body crack tracking attribute based on the most similar earthquake crack detection attribute body; Step 32: extracting a set of fracture slices in the target area of the oil and gas reservoir based on the ant body fracture tracking attributes; Step 33: Based on the most similar seismic fracture detection attribute body, multiple fracture impact range attribute bodies are calculated, and each fracture impact range attribute body is calibrated and optimized in turn to obtain a target oil and gas reservoir fracture envelope attribute body; The step 33 includes: Randomly select multiple sample points within the most similar earthquake fracture detection attribute volume, and set a fracture development degree statistical radius corresponding to each sample point with each sample point as the center; For each sample point, the radius is calculated based on the corresponding fracture development degree, the fracture affected area at the sample point is circled, and the number of fracture detection attribute passing seismic traces within the fracture affected area is counted; Calculating the ratio of the number of seismic traces passing the crack detection attribute within the crack affected area corresponding to each sample point to the total number of seismic traces within the unit area, and using the ratio as the crack development density within the crack affected area corresponding to the sample point; Changing the fracture development degree statistical radius to obtain a plurality of fracture impact range attribute bodies and internal fracture development density bodies thereof; Calculating an inter-layer average value of a plurality of the crack impact range attribute bodies within a target layer; Extracting the value at the imaging logging well point from the interlayer average value of each fracture sweep attribute body; Calculating an average value of fracture density interpreted by imaging logging within the target layer; The interlayer average value of each fracture sweep attribute body at the imaging logging well point and the fracture density average value interpreted by the imaging logging are intersected and statistically analyzed, and the fracture sweep attribute body with the best correlation is selected as the fracture envelope attribute body of the target oil and gas reservoir.

5. The method for establishing a fracture model of an oil and gas reservoir according to claim 1, wherein: After step 3, the following steps are also included: Performing grid sampling on the target oil and gas reservoir fracture envelope attribute body through the structural-stratigraphic framework model to obtain a fracture system envelope geological model; The numerical values of the fracture system envelope geological model are normalized and calculated according to the 0-1 interval distribution to obtain a fracture development probability continuity geological model.

6. The method for establishing an oil and gas reservoir fracture model according to claim 5, characterized in that: After step 5, the following steps are also included: Based on the discrete geological model of the fracture development facies, the distribution range, mean, variance and variation of the fracture strike, fracture dip, fracture aperture and fracture density of the imaging logging in each fracture development facies are statistically analyzed.

7. The method for establishing a fracture model of an oil and gas reservoir according to claim 6, wherein: The step 6 comprises: Step 61: Based on the structural-stratum framework model, establish the large-scale fracture model using a deterministic method; Step 62: Based on the set of fracture slices in the target area of the oil and gas reservoir, a mesoscale fracture model is established using a deterministic method; Step 63: Based on the discrete geological model of the fracture development phase belt, a small-scale fracture model is established using a zoning phase control method; Among them, the large-scale fracture model, the medium-scale fracture model and the small-scale fracture model all include a discrete fracture network model and a fracture attribute parameter distribution model. The fracture attribute parameter distribution model includes fracture porosity and fracture permeability and fluid crossflow coefficient in the x, y and z directions.

8. The method for establishing an oil and gas reservoir fracture model according to claim 7, characterized in that: The step 63 includes: For the fault-fracture joint zone, based on the distribution range, mean, variance and variation of the fracture strike, fracture dip, fracture aperture and fracture density from the imaging logging, a point-indicating method is used for random simulation to obtain the discrete fracture network model and the fracture attribute parameter distribution model; For the dispersed fracture zone, based on the fracture development probability continuity geological model and the correlation between fracture intensity and fracture attribute parameters obtained from drilling statistics, a fracture attribute parameter distribution model is equivalently calculated.

9. The method for establishing a fracture model of an oil and gas reservoir according to claim 1, wherein: After step 6, the following steps are also included: Step 7: Perform model grid calculations on the large-scale fracture model, the medium-scale fracture model, and the small-scale fracture model respectively to obtain a three-dimensional geological model integrating multi-scale fracture system attribute parameters.

10. An electronic device, characterized in that: The electronic device comprises: a memory storing executable instructions; A processor is configured to execute the executable instructions in the memory to implement the method for establishing an oil and gas reservoir fracture model according to any one of claims 1 to 9.

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