Method, device, electronic device and storage medium for identifying fracture zone connectivity

Abstract

A method, apparatus, electronic device, and storage medium for identifying the connectivity of a fault zone provided by the present disclosure. The method includes obtaining three-dimensional seismic data of a target fault zone and establishing a three-dimensional structural model of the target fault zone based on the three-dimensional seismic data; obtaining logging data and core data of the target fault zone and determining the geomechanical parameters of the target fault zone based on the logging data and the core data; establishing a three-dimensional geomechanical model of the target fault based on the three-dimensional structural model and the geomechanical parameters; performing finite element analysis on the three-dimensional geomechanical model to obtain a stress field model; and calculating the connectivity coefficients of different attitudes of the target fault zone based on the stress field model, so as to evaluate the connectivity of different attitudes of the target fault zone. This method can give a quantitative judgment on the connectivity degree of the fault zone, which is of great significance.

Description

Technical Field

[0001] The present disclosure relates to the technical field of oil exploration, and particularly to a method, device, electronic device and storage medium for identifying the connectivity of fracture zones. Background Art

[0002] Existing fault connectivity detection technologies can be roughly divided into two categories: before drilling and after drilling. Before drilling, it mainly relies on the coupling relationship between the occurrence of faults and in-situ stress to judge the opening of the main fault plane, which is relatively macroscopic and applicable to clastic rock formations. After drilling, it mainly relies on the production dynamics of oil and gas wells and the geochemical indicators of the produced oil and gas for evaluation. This method is obviously not applicable to the evaluation of fracture zones before drilling and is difficult to achieve the effect of reducing drilling costs. Neither of these two methods deeply explores the significance of structural analysis results and ignores the control role of the current local in-situ stress field in fracture physical properties. Therefore, it has not been widely popularized in the process of oilfield production.

[0003] Existing fault connectivity detection methods specifically include crude oil fingerprint technology, fault connectivity probability method, inter-well dynamic connectivity inversion method based on oil and water well injection-production development data, and method for analyzing the connectivity of fracture-cavity reservoirs between oil reservoirs using dynamic information. However, these methods all ignore the influence of the local in-situ stress field and are not applicable to strike-slip fracture zones with complex structures in ultra-deep layers.

[0004] Small and medium-scale slip-distance strike-slip faults are widely developed local structures in the interior of cratonic basins (platform basin areas) and are three-dimensional geological bodies with complex structures. In the past, the research on thrust faults and fault-related folds in the foreland area and the research on platform basin areas and related structures were relatively mature, while the research on the fracture structures in the interior of platform basin areas was less, especially a large number of small and medium-scale slip-distance strike-slip faults have not been deeply studied due to the lack of obvious identification marks on seismic profiles. In recent years, with the progress of oil and gas exploration, especially the discovery of oil and gas in Shunbei and its adjacent areas, people have begun to pay attention to the research of such fracture structures. Although the slip amount of such strike-slip faults is not large, the cutting depth of the strata is relatively large, often communicating with the main source rock layers, and are widely distributed in the interior of the platform basin area, which has a very important influence and control on reservoir properties, especially the fracture-cavity type reservoir bodies developed along the main fault plane. Therefore, it has an important role in the migration and accumulation of oil and gas, and even controls the spatio-temporal distribution of oil and gas in related areas. Therefore, identifying the connectivity of fault-controlled fracture-cavity type reservoirs for strike-slip faults has important theoretical and practical significance for accurately grasping the law of oil and gas enrichment and reducing exploration and development costs.

[0005] However, due to the extremely high difficulty and cost of ultra-deep drilling, connectivity is usually an important evaluation index for fractured reservoirs during the development process, and there is still a lack of solutions to this problem. This is mainly because ultra-deep formations have characteristics such as large burial depth, complex geological conditions, high difficulty in obtaining data, and low seismic data resolution. It is difficult to accurately judge the connectivity of faults before drilling with conventional data. Summary of the Invention

[0006] In view of the above problems, the present disclosure provides a method, device, electronic device, and storage medium for identifying the connectivity of a fracture zone, which solves the technical problem of difficult evaluation of the connectivity of ultra-deep fracture zones in the prior art.

[0007] In a first aspect, the present disclosure provides a method for identifying the connectivity of a fracture zone, the method comprising:

[0008] Obtaining three-dimensional seismic data of a target fracture zone, and establishing a three-dimensional structural model of the target fracture zone based on the three-dimensional seismic data;

[0009] Obtaining logging data and core data of the target fracture zone, and determining geomechanical parameters of the target fracture zone based on the logging data and the core data;

[0010] Establishing a three-dimensional geomechanical model of the target fracture based on the three-dimensional structural model and the geomechanical parameters;

[0011] Performing finite element analysis on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the abnormal change of the local stress field at different occurrences of the target fracture zone;

[0012] Calculating the connectivity coefficient at different occurrences of the target fracture zone according to the stress field model;

[0013] Evaluating the connectivity at different occurrences of the target fracture zone according to the connectivity coefficient at different occurrences of the target fracture zone.

[0014] According to an embodiment of the present disclosure, optionally, in the above method for identifying the connectivity of a fracture zone, establishing a three-dimensional structural model of the target fracture zone based on the three-dimensional seismic data includes the following steps:

[0015] Establishing a three-dimensional structural model of the target fracture zone in a point-line-plane manner based on the three-dimensional seismic data.

[0016] According to an embodiment of the present disclosure, optionally, in the above method for identifying the connectivity of a fracture zone, the logging data includes density logging data, and the results of acid fracturing and formation breakdown tests.

[0017] According to an embodiment of the present disclosure, optionally, in the above-mentioned fracture zone connectivity identification method, the core data includes paleomagnetic experiment results, acoustic anisotropy experiment results, uniaxial compressive strength of the core, and indoor compression test results of the core.

[0018] According to an embodiment of the present disclosure, optionally, in the above-mentioned fracture zone connectivity identification method, the geomechanical parameters include: minimum horizontal principal stress direction, vertical principal stress, minimum horizontal principal stress, maximum horizontal principal stress, static elastic modulus, Poisson's ratio, compressive strength, cohesion, and internal friction angle;

[0019] Determining the geomechanical parameters of the target fracture zone according to the logging data and the core data includes the following steps:

[0020] Determining the minimum horizontal principal stress direction according to the paleomagnetic experiment results and the acoustic anisotropy experiment results;

[0021] Determining the vertical principal stress according to the density logging data;

[0022] Determining the minimum horizontal principal stress according to the vertical principal stress or acid fracturing and breakdown experiment results;

[0023] Determining the maximum horizontal principal stress according to the uniaxial compressive strength of the core;

[0024] Determining the static elastic modulus, the Poisson's ratio, the compressive strength, the cohesion, and the internal friction angle according to the indoor compression test results of the core.

[0025] According to an embodiment of the present disclosure, optionally, in the above-mentioned fracture zone connectivity identification method, determining the minimum horizontal principal stress direction according to the paleomagnetic experiment results and the acoustic anisotropy experiment results includes the following steps:

[0026] Calculating the magnetic declination according to the paleomagnetic experiment results by the following formula;

[0027]

[0028] where α is the magnetic declination, y is the remanent magnetic vector in the Y direction, and x is the remanent magnetic vector in the X direction;

[0029] Determining the included angle between the minimum horizontal principal stress and the core marking line of the paleomagnetic experiment according to the acoustic anisotropy experiment results;

[0030] Calculating the minimum horizontal principal stress direction by the following formula according to the magnetic declination and the included angle between the minimum horizontal principal stress and the core marking line of the paleomagnetic experiment:

[0031] θ = α + β;

[0032] Wherein, θ is the direction of the minimum horizontal principal stress, and β is the included angle between the minimum horizontal principal stress and the marked line of the paleomagnetic experiment core.

[0033] According to an embodiment of the present disclosure, optionally, in the above method for identifying the connectivity of the fracture zone, determining the vertical principal stress according to the density logging data includes the following steps:

[0034] Calculate the vertical principal stress according to the density logging data by the following formula:

[0035]

[0036] Wherein, Sv is the vertical principal stress, ρ(h) is the density at the logging depth of h, and g is the acceleration of gravity.

[0037] According to an embodiment of the present disclosure, optionally, in the above method for identifying the connectivity of the fracture zone, determining the minimum horizontal principal stress according to the vertical principal stress includes the following steps:

[0038] Calculate the minimum horizontal principal stress according to the vertical principal stress by the following formula:

[0039] Sh = Pp + (Sv - Pp)γ;

[0040] Wherein, Sh is the minimum horizontal principal stress, Pp is the reservoir pore pressure, Sv is the vertical principal stress, and γ is the effective stress coefficient related to the geological situation.

[0041] According to an embodiment of the present disclosure, optionally, in the above method for identifying the connectivity of the fracture zone, determining the minimum horizontal principal stress according to the acid fracturing and formation breakdown test results includes the following steps:

[0042] Obtain the closure pressure of the acid fracturing fracture according to the acid fracturing and formation breakdown test results;

[0043] Determine the minimum horizontal principal stress according to the closure pressure of the acid fracturing fracture by the following formula:

[0044] Sh = P b ;

[0045] Wherein, Sh is the minimum horizontal principal stress, and Pb is the closure pressure of the acid fracturing fracture.

[0046] According to an embodiment of the present disclosure, optionally, in the above method for identifying the connectivity of the fracture zone, determining the maximum horizontal principal stress according to the uniaxial compressive strength of the core includes the following steps:

[0047] Calculate the maximum horizontal principal stress by the stress quadrilateral method according to the uniaxial compressive strength of the core.

[0048] According to an embodiment of the present disclosure, optionally, in the above fracture zone connectivity identification method, a finite element analysis is performed on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the abnormal change of the local stress field at different occurrences of the target fracture zone, including the following steps:

[0049] Perform mesh division on the three-dimensional geomechanical model, and perform local mesh encryption on the complex geology part of the three-dimensional geomechanical model to obtain a finite element mesh model;

[0050] Apply a three-dimensional body stress field to the finite element mesh model to apply stress boundary conditions to the finite element mesh model, and obtain a stress field model, so as to simulate the abnormal change of the local stress field at different occurrences of the target fracture zone.

[0051] According to an embodiment of the present disclosure, optionally, in the above fracture zone connectivity identification method, according to the stress field model, calculate the connectivity coefficient at different occurrences of the target fracture zone, including the following steps:

[0052] According to the stress field model, determine the local minimum horizontal principal stress, local maximum horizontal principal stress and local vertical principal stress at the location of the current occurrence, as well as the angle between the local fracture dip and the local maximum horizontal principal stress, and the angle between the local fracture strike and the local maximum horizontal principal stress;

[0053] According to the local minimum horizontal principal stress, the local maximum horizontal principal stress and the local vertical principal stress, as well as the angle between the local fracture dip and the local maximum horizontal principal stress, and the angle between the local fracture strike and the local maximum horizontal principal stress, calculate the first coefficient and the second coefficient through the following formula:

[0054]

[0055]

[0056] where A is the first coefficient, β is the angle between the local fracture dip and the local maximum horizontal principal stress, θ is the angle between the local fracture strike and the local maximum horizontal principal stress, Sh is the local minimum horizontal principal stress, SH is the local maximum horizontal principal stress, Sv is the local vertical principal stress, and B is the second coefficient;

[0057] According to the first coefficient and the second coefficient, calculate the connectivity coefficient at the location of the current occurrence of the target fracture zone through the following formula:

[0058]

[0059] Wherein, L is the connectivity coefficient of the current occurrence part of the target fault zone, α is a coefficient related to the formation conditions, and Ks is the initial stability coefficient related to the fault strength.

[0060] According to an embodiment of the present disclosure, optionally, in the above-mentioned fault zone connectivity identification method, according to the connectivity coefficients of different occurrence parts of the target fault zone, the connectivity of different occurrence parts of the target fault zone is evaluated, including the following steps:

[0061] According to the connectivity coefficients of different occurrence parts of the target fault zone, the connectivity of different occurrence parts of the target fault zone is divided into four levels: poor connectivity, medium connectivity, good connectivity, and excellent connectivity;

[0062] Among them, the connectivity coefficient corresponding to poor connectivity is less than 0, the connectivity coefficient corresponding to medium connectivity is greater than or equal to 0 and less than 0.05, the connectivity coefficient corresponding to good connectivity is greater than or equal to 0.05 and less than 0.1, and the connectivity coefficient corresponding to excellent connectivity is greater than or equal to 0.1.

[0063] In a second aspect, the present disclosure provides a device for identifying the connectivity of a fault zone, and the device includes:

[0064] A data acquisition module, configured to acquire three-dimensional seismic data of a target fault zone, and establish a three-dimensional structural model of the target fault zone according to the three-dimensional seismic data;

[0065] A mechanical parameter determination module, configured to acquire logging data and core data of the target fault zone, and determine the geomechanical parameters of the target fault zone according to the logging data and the core data;

[0066] A mechanical model establishment module, configured to establish a three-dimensional geomechanical model of the target fault according to the three-dimensional structural model and the geomechanical parameters;

[0067] A stress field model establishment module, configured to perform finite element analysis on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the local stress field abnormal change situation of different occurrence parts of the target fault zone;

[0068] A connectivity coefficient calculation module, configured to calculate the connectivity coefficients of different occurrence parts of the target fault zone according to the stress field model;

[0069] A connectivity evaluation module, configured to evaluate the connectivity of different occurrence parts of the target fault zone according to the connectivity coefficients of different occurrence parts of the target fault zone.

[0070] In a third aspect, the present disclosure provides an electronic device, including a memory and a processor. A computer program is stored on the memory, and when the computer program is executed by the processor, it executes the fracture zone connectivity identification method described in any one of the first aspects.

[0071] In a fourth aspect, the present disclosure provides a storage medium. The computer program stored on the storage medium can be executed by one or more processors and can be used to implement the fracture zone connectivity identification method described in any one of the first aspects.

[0072] Compared with the prior art, one or more embodiments in the above solutions may have the following advantages or beneficial effects:

[0073] A fracture zone connectivity identification method, device, electronic device, and storage medium provided by the present disclosure. The method includes obtaining three-dimensional seismic data of a target fracture zone and establishing a three-dimensional structural model of the target fracture zone according to the three-dimensional seismic data; obtaining logging data and core data of the target fracture zone and determining geomechanical parameters of the target fracture zone according to the logging data and the core data; establishing a three-dimensional geomechanical model of the target fracture according to the three-dimensional structural model and the geomechanical parameters; performing finite element analysis on the three-dimensional geomechanical model to obtain a stress field model; calculating connectivity coefficients of different attitudes of the target fracture zone according to the stress field model; and evaluating the connectivity of different attitudes of the target fracture zone according to the connectivity coefficients of different attitudes of the target fracture zone. This method introduces numerical simulation technology for local stress field anomalies of faults and gives a quantitative (connectivity coefficient) judgment on the connectivity degree of fracture zones within a specific range by combining logging data with digital simulation structures, which is of great significance for studying favorable reservoir development parts and hydrocarbon migration and accumulation in carbonate strike-slip fault systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Hereinafter, the present disclosure will be described in more detail based on embodiments and with reference to the drawings:

[0075] Figure 1 It is a schematic flow chart of a fracture zone connectivity identification method provided by an embodiment of the present disclosure;

[0076] Figure 2 It is a fine point-line-plane analysis diagram of a certain target fracture zone provided by an embodiment of the present disclosure;

[0077] Figure 3 It is a three-dimensional structural model diagram of the above-mentioned target fracture zone provided by an embodiment of the present disclosure;

[0078] Figure 4 It is a calculation result diagram of the connectivity coefficient of the above-mentioned target fracture zone provided by an embodiment of the present disclosure;

[0079] Figure 5 The connectivity segmentation evaluation result diagram of the above-mentioned target fracture zone provided by the embodiments of the present disclosure

[0080] Figure 6 The structural schematic diagram of a fracture zone connectivity identification device provided by the embodiments of the present disclosure;

[0081] In the drawings, the same components are denoted by the same reference numerals, and the drawings are not drawn to actual scale. Detailed implementation manners

[0082] The following will describe in detail the implementation manners of the present disclosure in conjunction with the drawings and embodiments, so as to fully understand how the present disclosure uses technical means to solve technical problems and the implementation process of achieving corresponding technical effects. Each feature in the embodiments of the present disclosure can be combined with each other on the premise of not conflicting, and the formed technical solutions are all within the protection scope of the present disclosure.

[0083] At the same time, in the following description, many specific details are set forth for the purpose of explanation in order to provide a thorough understanding of the embodiments of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without the specific details described herein or in a specific manner described.

[0084] Example 1

[0085] Figure 1 The flowchart of a fracture zone connectivity identification method provided by the embodiments of the present disclosure, please refer to Figure 1 , this embodiment provides a fracture zone connectivity identification method, including:

[0086] Step S110: Obtain the three-dimensional seismic data of the target fracture zone, and establish a three-dimensional structural model of the target fracture zone according to the three-dimensional seismic data.

[0087] Specifically, if the target fracture layer is in the Shunbei area, based on the fine analysis of the high-precision ultra-deep three-dimensional seismic data in the "vertical stratification, plane segmentation, and vertical multi-stage superposition of small and medium-scale strike-slip fractures in the basin" mode of the Shunbei ultra-deep strike-slip fracture, a three-dimensional structural model of the fracture zone is established based on the point-line-plane mode.

[0088] Step S120: Obtain the logging data and core data of the target fracture zone, and determine the geomechanical parameters of the target fracture zone according to the logging data and the core data.

[0089] Among them, the logging data includes density logging data, as well as the results of acid fracturing and formation breakdown experiments.

[0090] The core data includes the results of paleomagnetic experiments, acoustic anisotropy experiments, uniaxial compressive strength of the core, and the results of indoor compression tests on the core.

[0091] The geomechanical parameters include: the direction of the minimum horizontal principal stress, the vertical principal stress, the minimum horizontal principal stress, the maximum horizontal principal stress, the static elastic modulus, the Poisson's ratio, the compressive strength, the cohesion, and the internal friction angle.

[0092] Specifically, step S120 includes the following steps:

[0093] S121: Determine the direction of the minimum horizontal principal stress according to the results of the paleomagnetic experiment and the results of the acoustic anisotropy experiment;

[0094] S123: Determine the vertical principal stress according to the density logging data;

[0095] S125: Determine the minimum horizontal principal stress according to the vertical principal stress;

[0096] S127: Determine the maximum horizontal principal stress according to the uniaxial compressive strength of the core;

[0097] S129: Determine the static elastic modulus, the Poisson's ratio, the compressive strength, the cohesion, and the internal friction angle according to the results of the indoor compression test on the core.

[0098] Specifically, in S121, determining the direction of the minimum horizontal principal stress according to the results of the paleomagnetic experiment and the results of the acoustic anisotropy experiment includes the following steps:

[0099] (a) Calculate the magnetic declination according to the results of the paleomagnetic experiment by the following formula:

[0100]

[0101] where α is the magnetic declination;

[0102] y is the remanent magnetic vector in the Y direction;

[0103] x is the remanent magnetic vector in the X direction;

[0104] (b) Determine the angle between the minimum horizontal principal stress and the core marker line of the paleomagnetic experiment according to the results of the acoustic anisotropy experiment;

[0105] (c) Calculate the direction of the minimum horizontal principal stress by the following formula according to the magnetic declination and the angle between the minimum horizontal principal stress and the core marker line of the paleomagnetic experiment:

[0106] θ = α + β;

[0107] where θ is the direction of the minimum horizontal principal stress;

[0108] β is the included angle between the minimum horizontal principal stress and the marked line of the paleomagnetic experiment core.

[0109] Specifically, in S123, determining the vertical principal stress according to the density logging data includes the following steps:

[0110] Calculating the vertical principal stress according to the density logging data by the following formula:

[0111]

[0112] where Sv is the vertical principal stress;

[0113] ρ(h) is the density at the logging depth of h;

[0114] g is the acceleration of gravity.

[0115] Specifically, in S125, determining the minimum horizontal principal stress according to the vertical principal stress includes the following steps:

[0116] Calculating the minimum horizontal principal stress according to the vertical principal stress by the following formula:

[0117] Sh = Pp + (Sv - Pp)γ;

[0118] where Sh is the minimum horizontal principal stress;

[0119] Sv is the vertical principal stress;

[0120] Pp is the reservoir pore pressure;

[0121] γ is the effective stress coefficient related to the geological situation.

[0122] where both the reservoir pore pressure (Pp) and the effective stress coefficient (γ) related to the geological situation can be obtained from the logging data.

[0123] In addition, in S125, determining the minimum horizontal principal stress according to the acid fracturing and formation breakdown test results includes the following steps:

[0124] (a) Obtaining the acid fracturing fracture closure pressure according to the acid fracturing and formation breakdown test results;

[0125] (b) Determining the minimum horizontal principal stress according to the acid fracturing fracture closure pressure by the following formula:

[0126] Sh = P b ;

[0127] where Sh is the minimum horizontal principal stress;

[0128] P b is the closure pressure of the acid fracturing crack.

[0129] Specifically, in step S127, determining the maximum horizontal principal stress according to the uniaxial compressive strength of the core includes the following steps:

[0130] Calculate the maximum horizontal principal stress by the stress quadrilateral method according to the uniaxial compressive strength of the core.

[0131] Under ideal conditions, the specific method for calculating the maximum horizontal principal stress by the stress quadrilateral method is to divide the uniaxial compressive strength of the core by 4, and the obtained value is the maximum horizontal principal stress.

[0132] The above geomechanical parameters constitute a one-dimensional geomechanical profile.

[0133] Step S130: Establish a three-dimensional geomechanical model of the target fracture according to the three-dimensional structural model and the geomechanical parameters.

[0134] Specifically, based on a reliable geological model of the ultra-deep strike-slip fault structure and the one-dimensional geomechanical profile (geomechanical parameters) of the characteristic wells, a three-dimensional static geomechanical model is established.

[0135] Step S140: Perform finite element analysis on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the abnormal change of the local stress field at different occurrences of the target fracture zone.

[0136] Specifically, step S140 includes the following steps:

[0137] S141: Divide the mesh of the three-dimensional geomechanical model, and perform local mesh refinement on the parts with complex geology in the three-dimensional geomechanical model to obtain a finite element mesh model;

[0138] S143: Apply a three-dimensional body stress field to the finite element mesh model to apply stress boundary conditions to the finite element mesh model, and obtain a stress field model, so as to simulate the abnormal change of the local stress field at different occurrences of the target fracture zone.

[0139] In this embodiment, structured mesh division is performed on the three-dimensional geomechanical model, and local mesh refinement technology is adopted in complex geological conditions to ensure the accuracy of the calculation results. By applying a three-dimensional body stress field to the model, the abnormal change of the local stress field at different occurrences of the strike-slip fault is accurately simulated.

[0140] During the application of stress boundary conditions, by continuously changing the acting mode and magnitude of the boundary force, the calculated values of the tectonic principal stresses (including magnitude and direction) at certain specific points in the calculation area are made to achieve the best fit with the in-situ stress values at the measurement points (the geomechanical parameters in step S120), and the simulation of the stress-deformation field obtained thereby.

[0141] Step S150: According to the stress field model, calculate the connectivity coefficients at the locations of different attitudes of the target fracture zone.

[0142] Specifically, step S150 includes the following steps:

[0143] S151: According to the stress field model, determine the local minimum horizontal principal stress, the local maximum horizontal principal stress, and the local vertical principal stress at the location of the current attitude, as well as the included angle between the local dip angle of the fracture and the local maximum horizontal principal stress, and the included angle between the local strike of the fracture and the local maximum horizontal principal stress;

[0144] S153: According to the local minimum horizontal principal stress, the local maximum horizontal principal stress, and the local vertical principal stress, as well as the included angle between the local dip angle of the fracture and the local maximum horizontal principal stress, and the included angle between the local strike of the fracture and the local maximum horizontal principal stress, calculate the first coefficient and the second coefficient through the following formula:

[0145]

[0146]

[0147] where A is the first coefficient;

[0148] β is the included angle between the local dip angle of the fracture and the local maximum horizontal principal stress;

[0149] θ is the included angle between the local strike of the fracture and the local maximum horizontal principal stress;

[0150] Sh is the local minimum horizontal principal stress;

[0151] SH is the local maximum horizontal principal stress;

[0152] Sv is the local vertical principal stress;

[0153] B is the second coefficient;

[0154] S155: According to the first coefficient and the second coefficient, calculate the connectivity coefficient at the location of the current attitude of the target fracture zone through the following formula:

[0155]

[0156] Among them, L is the connectivity coefficient of the part where the current occurrence of the target fault zone is located;

[0157] α is a coefficient related to the formation conditions;

[0158] Ks is the initial stability coefficient related to the fault strength.

[0159] Among them, the coefficient related to the formation conditions (α) and the initial stability coefficient related to the fault strength (Ks) can both be obtained according to the stress field model.

[0160] Step S160: Evaluate the connectivity of the parts where the target fault zone has different occurrences according to the connectivity coefficients of the parts where the target fault zone has different occurrences.

[0161] Specifically, according to the connectivity coefficients of the parts where the target fault zone has different occurrences, the connectivity of the parts where the target fault zone has different occurrences is divided into four levels: poor connectivity, medium connectivity, good connectivity, and excellent connectivity;

[0162] Among them, the connectivity coefficient corresponding to poor connectivity is less than 0, the connectivity coefficient corresponding to medium connectivity is greater than or equal to 0 and less than 0.05, the connectivity coefficient corresponding to good connectivity is greater than or equal to 0.05 and less than 0.1, and the connectivity coefficient corresponding to excellent connectivity is greater than or equal to 0.1.

[0163] That is to say, when L < 0, it indicates poor connectivity;

[0164] When 0 ≤ L < 0.05, it indicates medium connectivity;

[0165] When 0.05 ≤ L < 0.1, it indicates good connectivity;

[0166] When L ≥ 0.1, it indicates excellent connectivity.

[0167] Based on the three-dimensional geological model of the strike-slip fault in this embodiment, with the help of the finite element simulation method of the local stress field, the connectivity coefficients of different parts of the main fault surface are quantitatively calculated, and then the three-dimensional stereoscopic connectivity model is displayed, realizing the rapid quantitative evaluation of the connectivity of different parts of the fault zone. The application effect is good, providing an effective method for the quantitative evaluation of the connectivity of carbonate strike-slip fault-controlled reservoirs.

[0168] This method utilizes the local in-situ stress field data obtained from well drilling. By means of 3D geological modeling and finite element stress field simulation, it can give a quantitative judgment on the connectivity of fault zones within a specific range. It can be widely applied to quantitatively evaluate the connectivity of strike-slip fault systems in the subsurface of basins, solving the problem that conventional data are difficult to accurately determine the permeability and openness at different positions of faults, and thus unable to evaluate fault connectivity. It is of great significance for studying the favorable reservoir development areas and hydrocarbon migration and accumulation in carbonate strike-slip fault systems.

[0169] A method for identifying the connectivity of fault zones provided by the present disclosure, the method includes obtaining 3D seismic data of a target fault zone, and establishing a 3D structural model of the target fault zone according to the 3D seismic data; obtaining logging data and core data of the target fault zone, and determining the geomechanical parameters of the target fault zone according to the logging data and the core data; establishing a 3D geomechanical model of the target fault according to the 3D structural model and the geomechanical parameters; performing finite element analysis on the 3D geomechanical model to obtain a stress field model; calculating the connectivity coefficient of different occurrence parts of the target fault zone according to the stress field model; evaluating the connectivity of different occurrence parts of the target fault zone according to the connectivity coefficient of different occurrence parts of the target fault zone. This method introduces the numerical simulation technology of local stress field anomalies of faults, and gives a quantitative (connectivity coefficient) judgment on the connectivity of fault zones within a specific range by combining logging data with the digital model structure, which is of great significance for studying the favorable reservoir development areas and hydrocarbon migration and accumulation in carbonate strike-slip fault systems.

[0170] Example 2

[0171] This embodiment provides another method for identifying the connectivity of fault zones, including:

[0172] Step S210: Obtain 3D seismic data of a target fault zone, and establish a 3D structural model of the target fault zone according to the 3D seismic data.

[0173] Specifically, if the target fault layer is in Shunbei area, based on the fine analysis of high-precision ultra-deep 3D seismic data in the "vertical stratification, plane segmentation, and vertical multi-stage superposition" mode of small and medium-scale strike-slip faults in the basin within the ultra-deep strike-slip faults in Shunbei, a 3D structural model of the fault zone is established based on the point-line-plane mode.

[0174] Step S220: Obtain logging data and core data of the target fault zone, and determine the geomechanical parameters of the target fault zone according to the logging data and the core data.

[0175] Among them, the logging data includes density logging data, as well as acid fracturing and formation breakdown test results.

[0176] The core data includes paleomagnetic experiment results, acoustic anisotropy experiment results, uniaxial compressive strength of the core, and indoor compression test results of the core.

[0177] The geomechanical parameters include: minimum horizontal principal stress direction, vertical principal stress, minimum horizontal principal stress, maximum horizontal principal stress, static elastic modulus, Poisson's ratio, compressive strength, cohesion, and internal friction angle.

[0178] Specifically, step S220 includes the following steps

[0179] S221: Determine the minimum horizontal principal stress direction according to the paleomagnetic experiment results and the acoustic anisotropy experiment results;

[0180] S223: Determine the vertical principal stress according to the density logging data;

[0181] S225: Determine the minimum horizontal principal stress according to the acid fracturing and formation breakdown test results;

[0182] S227: Determine the maximum horizontal principal stress according to the uniaxial compressive strength of the core;

[0183] S229: Determine the static elastic modulus, the Poisson's ratio, the compressive strength, the cohesion, and the internal friction angle according to the indoor compression test results of the core.

[0184] Specifically, in S221, determining the minimum horizontal principal stress direction according to the paleomagnetic experiment results and the acoustic anisotropy experiment results includes the following steps:

[0185] (a) Calculate the magnetic declination according to the paleomagnetic experiment results through the following formula;

[0186]

[0187] where α is the magnetic declination;

[0188] y is the remanent magnetic vector in the Y direction;

[0189] x is the remanent magnetic vector in the X direction;

[0190] (b) Determine the included angle between the minimum horizontal principal stress and the core marker line of the paleomagnetic experiment according to the acoustic anisotropy experiment results;

[0191] (c) Calculate the minimum horizontal principal stress direction through the following formula according to the magnetic declination and the included angle between the minimum horizontal principal stress and the core marker line of the paleomagnetic experiment:

[0192] θ = α + β;

[0193] Where θ is the direction of the minimum horizontal principal stress;

[0194] β is the angle between the minimum horizontal principal stress and the marked line of the paleomagnetic experiment core.

[0195] Specifically, in S223, determining the vertical principal stress according to the density logging data includes the following steps:

[0196] Calculate the vertical principal stress according to the density logging data through the following formula:

[0197]

[0198] Where Sv is the vertical principal stress;

[0199] ρ(h) is the density at the logging depth of h;

[0200] g is the acceleration due to gravity.

[0201] Specifically, in S225, determining the minimum horizontal principal stress according to the acid fracturing and formation breakdown test results includes the following steps:

[0202] (a) Obtain the acid fracturing fracture closure pressure according to the acid fracturing and formation breakdown test results;

[0203] (b) Determine the minimum horizontal principal stress through the following formula according to the acid fracturing fracture closure pressure:

[0204] Sh = P b ;

[0205] Where Sh is the minimum horizontal principal stress;

[0206] P b is the acid fracturing fracture closure pressure.

[0207] Specifically, in step S227, determining the maximum horizontal principal stress according to the uniaxial compressive strength of the core includes the following steps:

[0208] Calculate the maximum horizontal principal stress according to the uniaxial compressive strength of the core by the stress quadrilateral method.

[0209] Under ideal conditions, the specific method of calculating the maximum horizontal principal stress by the stress quadrilateral method is to divide the uniaxial compressive strength of the core by 4, and the obtained value is the maximum horizontal principal stress.

[0210] The above geomechanical parameters constitute a one-dimensional geomechanical profile.

[0211] Step S230: Establish a three-dimensional geomechanical model of the target fault according to the three-dimensional structural model and the geomechanical parameters.

[0212] Specifically, based on a reliable geological model of deep strike-slip faults and the one-dimensional geomechanical profiles (geomechanical parameters) of characteristic wells, a three-dimensional static geomechanical model is established.

[0213] Step S240: Conduct finite element analysis on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the abnormal change of the local stress field at different occurrences of the target fault zone.

[0214] Specifically, step S240 includes the following steps:

[0215] S241: Divide the grid of the three-dimensional geomechanical model, and perform local grid encryption on the parts with complex geology in the three-dimensional geomechanical model to obtain a finite element grid model;

[0216] S243: Apply a three-dimensional body stress field to the finite element grid model to apply stress boundary conditions to the finite element grid model, and obtain a stress field model, so as to simulate the abnormal change of the local stress field at different occurrences of the target fault zone.

[0217] In this embodiment, structured grid division is performed on the three-dimensional geomechanical model, and local grid encryption technology is adopted in complex geological conditions to ensure the accuracy of the calculation results. By applying a three-dimensional body stress field to the model, the abnormal change of the local stress field at different occurrences of the strike-slip fault is accurately simulated.

[0218] During the process of applying stress boundary conditions, by continuously changing the action mode and magnitude of the boundary force, the calculated values (including magnitude and direction) of the tectonic principal stresses at certain specific points in the calculation area are made to achieve the best fit with the measured in-situ stress values (the geomechanical parameters in step S220), and the simulation of the stress-deformation field is obtained accordingly.

[0219] Step S250: Calculate the connectivity coefficient at different occurrences of the target fault zone according to the stress field model.

[0220] Specifically, step S250 includes the following steps:

[0221] S251: According to the stress field model, determine the local minimum horizontal principal stress, local maximum horizontal principal stress and local vertical principal stress at the location of the current occurrence, as well as the included angle between the local dip angle of the fault and the local maximum horizontal principal stress, and the included angle between the local strike of the fault and the local maximum horizontal principal stress;

[0222] S253: Calculate the first coefficient and the second coefficient according to the local minimum horizontal principal stress, the local maximum horizontal principal stress, the local vertical principal stress, the included angle between the local dip angle of the fracture and the local maximum horizontal principal stress, and the included angle between the local strike of the fracture and the local maximum horizontal principal stress, by the following formula:

[0223]

[0224]

[0225] where A is the first coefficient;

[0226] β is the included angle between the local dip angle of the fracture and the local maximum horizontal principal stress;

[0227] θ is the included angle between the local strike of the fracture and the local maximum horizontal principal stress;

[0228] Sh is the local minimum horizontal principal stress;

[0229] SH is the local maximum horizontal principal stress;

[0230] Sv is the local vertical principal stress;

[0231] B is the second coefficient;

[0232] S255: Calculate the connectivity coefficient of the location where the current attitude of the target fracture zone is located according to the first coefficient and the second coefficient, by the following formula:

[0233]

[0234] where L is the connectivity coefficient of the location where the current attitude of the target fracture zone is located;

[0235] α is a coefficient related to the formation conditions;

[0236] Ks is the initial stability coefficient related to the fault strength.

[0237] where the coefficient related to the formation conditions (α) and the initial stability coefficient related to the fault strength (Ks) can both be obtained according to the stress field model.

[0238] Step S260: Evaluate the connectivity of the locations where different attitudes of the target fracture zone are located according to the connectivity coefficients of the locations where different attitudes of the target fracture zone are located.

[0239] Specifically, according to the connectivity coefficients of the locations where different attitudes of the target fracture zone are located, classify the connectivity of the locations where different attitudes of the target fracture zone are located into four levels: poor connectivity, medium connectivity, good connectivity, and excellent connectivity;

[0240] Among them, the connectivity coefficient corresponding to poor connectivity is less than 0, the connectivity coefficient corresponding to medium connectivity is greater than or equal to 0 and less than 0.05, the connectivity coefficient corresponding to good connectivity is greater than or equal to 0.05 and less than 0.1, and the connectivity coefficient corresponding to excellent connectivity is greater than or equal to 0.1.

[0241] That is to say, when L < 0, it indicates poor connectivity;

[0242] When 0 ≤ L < 0.05, it indicates medium connectivity;

[0243] When 0.05 ≤ L < 0.1, it indicates good connectivity;

[0244] When L ≥ 0.1, it indicates excellent connectivity.

[0245] Based on the three-dimensional geological model of strike-slip faults, this embodiment uses the finite element simulation method of the local stress field to quantitatively calculate the connectivity coefficients of different parts of the main fault surface, and then displays the three-dimensional stereo connectivity model, realizing the rapid quantitative evaluation of the connectivity of different parts of the fault zone. The application effect is good, providing an effective method for the quantitative evaluation of the connectivity of carbonate strike-slip fault-controlled reservoirs. With this method, the connectivity of faults without deployed wells can be predicted, greatly reducing the exploration cost and providing an effective technology for the efficient development of ultra-deep fault-controlled oil and gas reservoirs.

[0246] This method uses the local in-situ stress field data obtained by drilling measurements. By means of three-dimensional geological modeling and finite element stress field simulation, it can give a quantitative judgment on the connectivity degree of the fault zone within a specific range. It can be widely used in the quantitative evaluation of the connectivity of the strike-slip fault system underground in the basin, solving the problem that it is difficult to accurately measure the permeability and openness of different positions of the fault with conventional data, and thus unable to evaluate the fault connectivity. It is of great significance for studying the favorable parts of reservoir development and oil and gas migration and accumulation in the carbonate strike-slip fault system.

[0247] A method for identifying the connectivity of a fault zone provided by the present disclosure, the method comprising obtaining three-dimensional seismic data of a target fault zone and establishing a three-dimensional structural model of the target fault zone according to the three-dimensional seismic data; obtaining logging data and core data of the target fault zone and determining geomechanical parameters of the target fault zone according to the logging data and the core data; establishing a three-dimensional geomechanical model of the target fault according to the three-dimensional structural model and the geomechanical parameters; performing finite element analysis on the three-dimensional geomechanical model to obtain a stress field model; calculating a connectivity coefficient of different occurrences of the target fault zone according to the stress field model; and evaluating the connectivity of different occurrences of the target fault zone according to the connectivity coefficient of different occurrences of the target fault zone. This method introduces the numerical simulation technology of local stress field anomaly of faults and gives a quantitative (connectivity coefficient) judgment on the connectivity degree of the fault zone within a specific range by combining logging data with the digital model structure, which is of great significance for studying the favorable parts of reservoir development and oil and gas migration and accumulation in carbonate strike-slip fault systems.

[0248] Example 3

[0249] In this embodiment, the method described in Embodiment 1 or Embodiment 2 is illustrated by a specific implementation case.

[0250] In this embodiment, a certain fault zone in the Shunbei Oil and Gas Field is selected as the target fault zone. The method provided in Embodiment 1 or 2 is used to quantitatively evaluate the connectivity degree of the above-mentioned fault zone in the Shunbei Oil and Gas Field in a set of strata. The length of the target fault zone in the work area is 28 km, and there are currently 22 development characteristic wells.

[0251] Table 1 is a table of abnormal working conditions of each characteristic well on the target fault zone.

[0252] Table 1

[0253]

[0254]

[0255] First, based on the mode of "longitudinal stratification, planar segmentation, and vertical multi-stage superposition of small and medium-scale strike-slip faults in the basin" of the Shunbei ultra-deep strike-slip faults and combined with the fine analysis of high-precision ultra-deep three-dimensional seismic data, a three-dimensional structural model of the fault zone is established based on the point-line-plane mode. The point-line-plane fine analysis diagram of the target fault zone is as Figure 2 shown. Based on this point-line-plane fine analysis diagram, the established three-dimensional structural model of the fault zone is as Figure 3 shown.

[0256] According to the fracture zone connectivity identification method provided in Embodiment 1 or 2, the connectivity coefficients of different attitudes of the target fracture zone are calculated, and the results are as follows Figure 4 shown. The larger the gray value in the figure, the smaller the connectivity coefficient of this part, and the smaller the gray value (the darker), the larger the connectivity coefficient of this part.

[0257] Along the strike of the fracture zone, it can be divided into 5 segments according to the range of the connectivity coefficient. The length, connectivity coefficient range and average value of the connectivity coefficient of each segment are listed in Table 2. Table 2 is the connectivity evaluation result table of the target fracture zone.

[0258] Table 2

[0259] Segmental numbering Connectivity coefficient Connectivity Length range 1 -0.25 Difference 11.91 km 2 0.17 Excellent 2.68 km 3 -0.14 Poor 1.01 km 4 0.15 Excellent 3.93 km 5 0.02 Medium 9.30 km

[0260] The connectivity evaluation result of the target fracture zone is as follows Figure 5 shown. Among them, when the connectivity coefficient is >0.1, it means that the adjacent two wells are connected. After adjusting the working system of one well, the wellhead pressure of the other well immediately responds; when the connectivity coefficient is <0, the adjacent two wells are not connected and are independent of each other in production. Based on this, the connectivity between wells can be better distinguished and quantitatively evaluated.

[0261] Example 4

[0262] Figure 6 The following is a schematic structural diagram of a fracture zone connectivity identification device provided by an embodiment of the present disclosure. Please refer to Figure 6 , this embodiment provides a fracture zone connectivity identification device 100, including a data acquisition module 110, a mechanical parameter determination module 120, a mechanical model establishment module 130, a stress field model establishment module 140, a connectivity coefficient calculation module 150 and a connectivity evaluation module 160.

[0263] The data acquisition module 110 is used to acquire three-dimensional seismic data of the target fracture zone, and establish a three-dimensional structural model of the target fracture zone according to the three-dimensional seismic data;

[0264] The mechanical parameter determination module 120 is used to acquire well logging data and core data of the target fracture zone, and determine the geomechanical parameters of the target fracture zone according to the well logging data and the core data;

[0265] The mechanical model establishment module 130 is used to establish a three-dimensional geomechanical model of the target fracture according to the three-dimensional structural model and the geomechanical parameters;

[0266] A stress field model establishment module 140 is configured to perform finite element analysis on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the abnormal change of the local stress field at the parts with different attitudes of the target fault zone;

[0267] A connectivity coefficient calculation module 150 is configured to calculate the connectivity coefficients of the parts with different attitudes of the target fault zone according to the stress field model;

[0268] A connectivity evaluation module 160 is configured to evaluate the connectivity of the parts with different attitudes of the target fault zone according to the connectivity coefficients of the parts with different attitudes of the target fault zone.

[0269] A data acquisition module 110 acquires three-dimensional seismic data of a target fault zone and establishes a three-dimensional structural model of the target fault zone according to the three-dimensional seismic data; a mechanical parameter determination module 120 acquires logging data and core data of the target fault zone and determines the geomechanical parameters of the target fault zone according to the logging data and the core data; a mechanical model establishment module 130 establishes a three-dimensional geomechanical model of the target fault according to the three-dimensional structural model and the geomechanical parameters; a stress field model establishment module 140 performs finite element analysis on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the abnormal change of the local stress field at the parts with different attitudes of the target fault zone; a connectivity coefficient calculation module 150 calculates the connectivity coefficients of the parts with different attitudes of the target fault zone according to the stress field model; a connectivity evaluation module 160 evaluates the connectivity of the parts with different attitudes of the target fault zone according to the connectivity coefficients of the parts with different attitudes of the target fault zone.

[0270] Specific embodiments of the fault zone connectivity identification method executed based on the above modules have been described in detail in Embodiment 1 and Embodiment 2, and will not be elaborated here.

[0271] Example 5

[0272] This embodiment provides an electronic device, which may be a mobile phone, a computer, a tablet computer, etc., including a memory and a processor. A calculator program is stored on the memory, and when the computer program is executed by the processor, the fault zone connectivity identification method described in Embodiment 1 is implemented. It can be understood that the electronic device may further include an input / output (I / O) interface and a communication component.

[0273] Wherein, the processor is configured to execute all or part of the steps in the fault zone connectivity identification method in Embodiment 1. The memory is configured to store various types of data, which may include, for example, instructions of any application program or method in the electronic device, as well as data related to the application program.

[0274] The processor may be implemented by an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is used to execute the fracture zone connectivity identification method in the first embodiment above.

[0275] The memory may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk, or an optical disc.

[0276] Example 6

[0277] This embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disc, a server, an App application store, etc., on which a computer program is stored. When the computer program is executed by a processor, the following method steps can be implemented:

[0278] Step S110: Obtain three-dimensional seismic data of a target fracture zone, and establish a three-dimensional structural model of the target fracture zone according to the three-dimensional seismic data;

[0279] Step S120: Obtain the logging data and core data of the target fault zone, and determine the geomechanical parameters of the target fault zone according to the logging data and the core data;

[0280] Step S130: Establish a three-dimensional geomechanical model of the target fault according to the three-dimensional structural model and the geomechanical parameters;

[0281] Step S140: Perform finite element analysis on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the abnormal change of the local stress field at the parts with different attitudes of the target fault zone;

[0282] Step S150: Calculate the connectivity coefficients of the parts with different attitudes of the target fault zone according to the stress field model;

[0283] Step S160: Evaluate the connectivity of the parts with different attitudes of the target fault zone according to the connectivity coefficients of the parts with different attitudes of the target fault zone.

[0284] For the specific implementation process of the above method steps, reference can be made to Embodiment 1 and Embodiment 2, and this embodiment will not be repeated here.

[0285] In summary, a method, device, electronic device and storage medium for identifying the connectivity of a fault zone provided by the present disclosure, the method includes obtaining three-dimensional seismic data of a target fault zone, and establishing a three-dimensional structural model of the target fault zone according to the three-dimensional seismic data; obtaining logging data and core data of the target fault zone, and determining the geomechanical parameters of the target fault zone according to the logging data and the core data; establishing a three-dimensional geomechanical model of the target fault according to the three-dimensional structural model and the geomechanical parameters; performing finite element analysis on the three-dimensional geomechanical model to obtain a stress field model; calculating the connectivity coefficients of the parts with different attitudes of the target fault zone according to the stress field model; evaluating the connectivity of the parts with different attitudes of the target fault zone according to the connectivity coefficients of the parts with different attitudes of the target fault zone. This method introduces the numerical simulation technology of the abnormal local stress field of the fault, and gives a quantitative (connectivity coefficient) judgment on the connectivity degree of the fault zone within a specific range by combining logging data with the digital model structure, which is of great significance for studying the favorable parts of reservoir development and oil and gas migration and accumulation in the carbonate strike-slip fault system.

[0286] It should be noted that in this document, the term "including", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0287] Although the embodiments disclosed in the present disclosure are as above, the said content is only an embodiment adopted for the convenience of understanding the present disclosure, and is not intended to limit the present disclosure. Any person skilled in the art within the technical field to which the present disclosure pertains may make any modifications and variations in the form of implementation and details without departing from the spirit and scope disclosed in the present disclosure. However, the scope of patent protection of the present disclosure shall still be subject to the scope defined by the appended claims.

Claims

1. A method for identifying the connectivity of a fault zone, characterized in that, The method includes: Obtaining three-dimensional seismic data of the target fault zone, and establishing a three-dimensional structural model of the target fault zone based on the three-dimensional seismic data; Obtaining well logging data and core data of the target fault zone, and determining the geomechanical parameters of the target fault zone based on the well logging data and the core data; Establishing a three-dimensional geomechanical model of the target fault based on the three-dimensional structural model and the geomechanical parameters; Performing finite element analysis on the three-dimensional geomechanical model to obtain a stress field model, so as to simulate the abnormal change of the local stress field at different occurrences of the target fault zone; Calculating the connectivity coefficient of different occurrences of the target fault zone based on the stress field model; Evaluating the connectivity of different occurrences of the target fault zone according to the connectivity coefficient of different occurrences of the target fault zone; Among them, calculating the connectivity coefficient of different occurrences of the target fault zone based on the stress field model includes the following steps: Based on the stress field model, determining the local minimum horizontal principal stress, local maximum horizontal principal stress and local vertical principal stress at the location of the current occurrence, as well as the included angle between the local dip angle of the fault and the local maximum horizontal principal stress, and the included angle between the local strike of the fault and the local maximum horizontal principal stress; Calculating a first coefficient and a second coefficient according to the local minimum horizontal principal stress, the local maximum horizontal principal stress and the local vertical principal stress, as well as the included angle between the local dip angle of the fault and the local maximum horizontal principal stress, and the included angle between the local strike of the fault and the local maximum horizontal principal stress, by the following formula: Wherein, A is the first coefficient, β is the included angle between the local dip angle of the fault and the local maximum horizontal principal stress, θ is the included angle between the local strike of the fault and the local maximum horizontal principal stress, Sh is the local minimum horizontal principal stress, SH is the local maximum horizontal principal stress, Sv is the local vertical principal stress, and B is the second coefficient; Calculating the connectivity coefficient of the location of the current occurrence of the target fault zone according to the first coefficient and the second coefficient by the following formula: Wherein, L is the connectivity coefficient of the location of the current occurrence of the target fault zone, α is a coefficient related to the formation conditions, and Ks is an initial stability coefficient related to the fault strength; Evaluating the connectivity of different occurrences of the target fault zone according to the connectivity coefficient of different occurrences of the target fault zone includes the following steps: Dividing the connectivity of different occurrences of the target fault zone into four levels: poor connectivity, medium connectivity, good connectivity and excellent connectivity according to the connectivity coefficient of different occurrences of the target fault zone; Among them, the connectivity coefficient corresponding to poor connectivity is less than 0, the connectivity coefficient corresponding to medium connectivity is greater than or equal to 0 and less than 0.05, the connectivity coefficient corresponding to good connectivity is greater than or equal to 0.05 and less than 0.1, and the connectivity coefficient corresponding to excellent connectivity is greater than or equal to 0.

1.

2. The method according to claim 1, characterized in that, Establishing a three-dimensional structural model of the target fault zone based on the three-dimensional seismic data includes the following steps: Based on the 3D seismic data, a 3D structural model of the target fault zone is established in a point-line-plane manner.

3. The method according to claim 1, characterized in that, The logging data includes density logging data, as well as acid fracturing and breakdown experiment results.

4. The method according to claim 3, characterized in that, The core data includes paleomagnetic experiment results, acoustic anisotropy experiment results, uniaxial compressive strength of the core, and indoor compression test results of the core.

5. The method according to claim 4, characterized in that, The geomechanical parameters include: minimum horizontal principal stress direction, vertical principal stress, minimum horizontal principal stress, maximum horizontal principal stress, static elastic modulus, Poisson's ratio, compressive strength, cohesion, and internal friction angle; Based on the logging data and the core data, determining the geomechanical parameters of the target fault zone includes the following steps: Based on the paleomagnetic experiment results and the acoustic anisotropy experiment results, determining the minimum horizontal principal stress direction; Based on the density logging data, determining the vertical principal stress; Based on the vertical principal stress or acid fracturing and breakdown experiment results, determining the minimum horizontal principal stress; Based on the uniaxial compressive strength of the core, determining the maximum horizontal principal stress; Based on the indoor compression test results of the core, determining the static elastic modulus, Poisson's ratio, compressive strength, cohesion, and internal friction angle.

6. The method according to claim 5, characterized in that, Based on the paleomagnetic experiment results and the acoustic anisotropy experiment results, determining the minimum horizontal principal stress direction includes the following steps: Based on the paleomagnetic experiment results, calculating the magnetic declination through the following formula; where α is the magnetic declination, y is the remanent magnetic vector in the Y direction, and x is the remanent magnetic vector in the X direction; Based on the acoustic anisotropy experiment results, determining the angle between the minimum horizontal principal stress and the core marker line of the paleomagnetic experiment; Based on the magnetic declination and the angle between the minimum horizontal principal stress and the core marker line of the paleomagnetic experiment, calculating the minimum horizontal principal stress direction through the following formula: where θ is the minimum horizontal principal stress direction, and β is the angle between the minimum horizontal principal stress and the core marker line of the paleomagnetic experiment.

7. The method according to claim 5, characterized in that, Based on the density logging data, determining the vertical principal stress includes the following steps: Based on the density logging data, calculating the vertical principal stress through the following formula: where Sv is the vertical principal stress, ρ(h) is the density at logging depth h, and g is the acceleration due to gravity.

8. The method according to claim 5, characterized in that, Based on the vertical principal stress, determining the minimum horizontal principal stress includes the following steps: Based on the vertical principal stress, calculating the minimum horizontal principal stress through the following formula: where Sh is the minimum horizontal principal stress, Pp is the reservoir pore pressure, Sv is the vertical principal stress, and γ is the effective stress coefficient related to the geological situation.

9. The method according to claim 5, characterized in that, Based on the acid fracturing and breakdown experiment results, determining the minimum horizontal principal stress includes the following steps: Based on the acid fracturing and breakdown experiment results, obtaining the acid fracturing fracture closure pressure; Based on the acid fracturing fracture closure pressure, determining the minimum horizontal principal stress through the following formula: where Sh is the minimum horizontal principal stress, and Pb is the acid fracturing fracture closure pressure.

10. The method according to claim 5, characterized in that, Based on the uniaxial compressive strength of the core, determining the maximum horizontal principal stress includes the following steps: Based on the uniaxial compressive strength of the core, calculating the maximum horizontal principal stress by the stress quadrilateral method.

11. The method according to claim 1, characterized in that, Perform finite element analysis on the three-dimensional geomechanical model to obtain a stress field model for simulating the abnormal variation of the local stress field at different occurrences of the target fault zone, including the following steps: Perform mesh division on the three-dimensional geomechanical model and perform local mesh refinement on the complex geological parts of the three-dimensional geomechanical model to obtain a finite element mesh model; Apply a three-dimensional body stress field to the finite element mesh model to apply stress boundary conditions to the finite element mesh model, and obtain a stress field model, thereby simulating the abnormal variation of the local stress field at different occurrences of the target fault zone.

12. A fracture zone connectivity identification device, characterized in that, The device includes: A data acquisition module for acquiring three-dimensional seismic data of the target fault zone and establishing a three-dimensional structural model of the target fault zone according to the three-dimensional seismic data; A mechanical parameter determination module for acquiring well logging data and core data of the target fault zone and determining the geomechanical parameters of the target fault zone according to the well logging data and the core data; A mechanical model establishment module for establishing a three-dimensional geomechanical model of the target fault according to the three-dimensional structural model and the geomechanical parameters; A stress field model establishment module for performing finite element analysis on the three-dimensional geomechanical model to obtain a stress field model for simulating the abnormal variation of the local stress field at different occurrences of the target fault zone; A connectivity coefficient calculation module for calculating the connectivity coefficients of different occurrences of the target fault zone according to the stress field model; A connectivity evaluation module for evaluating the connectivity of different occurrences of the target fault zone according to the connectivity coefficients of different occurrences of the target fault zone; Among them, the connectivity coefficient calculation module is used for: According to the stress field model, determine the local minimum horizontal principal stress, local maximum horizontal principal stress and local vertical principal stress at the location of the current occurrence, as well as the included angle between the local dip angle of the fault and the local maximum horizontal principal stress, and the included angle between the local strike of the fault and the local maximum horizontal principal stress; According to the local minimum horizontal principal stress, the local maximum horizontal principal stress and the local vertical principal stress, as well as the included angle between the local dip angle of the fault and the local maximum horizontal principal stress, and the included angle between the local strike of the fault and the local maximum horizontal principal stress, calculate the first coefficient and the second coefficient through the following formula: Among them, A is the first coefficient, β is the included angle between the local dip angle of the fault and the local maximum horizontal principal stress, θ is the included angle between the local strike of the fault and the local maximum horizontal principal stress, Sh is the local minimum horizontal principal stress, SH is the local maximum horizontal principal stress, Sv is the local vertical principal stress, and B is the second coefficient; According to the first coefficient and the second coefficient, calculate the connectivity coefficient of the current occurrence of the target fault zone through the following formula: Among them, L is the connectivity coefficient of the current occurrence of the target fault zone, α is a coefficient related to the formation conditions, and Ks is the initial stability coefficient related to the fault strength; Evaluating the connectivity of different occurrence parts of the target fault zone according to the connectivity coefficient of different occurrence parts of the target fault zone, including the following steps: Dividing the connectivity of different occurrence parts of the target fault zone into four levels: poor connectivity, medium connectivity, good connectivity, and excellent connectivity according to the connectivity coefficient of different occurrence parts of the target fault zone; Among them, the connectivity coefficient corresponding to poor connectivity is less than 0, the connectivity coefficient corresponding to medium connectivity is greater than or equal to 0 and less than 0.05, the connectivity coefficient corresponding to good connectivity is greater than or equal to 0.05 and less than 0.1, and the connectivity coefficient corresponding to excellent connectivity is greater than or equal to 0.

1.

13. An electronic device, characterized in that, Including a memory and a processor, a computer program is stored on the memory, and when the computer program is executed by the processor, it executes the fault zone connectivity identification method according to any one of claims 1 to 11.

14. A storage medium, characterized in that, The computer program stored in this storage medium can be executed by one or more processors and can be used to implement the fault zone connectivity identification method according to any one of claims 1 to 11.

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