Fracture closure earthquake prediction method and system based on structural integrity constraint

Abstract

The invention discloses a fracture closure earthquake prediction method and system based on structural integrity constraint, and relates to the technical field of geological exploration, and the method comprises the steps: building a three-dimensional model of a fault zone fault according to the exploration data of a target region; based on the three-dimensional model, calculating information dimensions and chaotic parameters of fractal parameters in the fault zone; determining a constraint condition critical value of the internal structure integrity of the fault zone and a third-generation coherence value of the petroleum seismic exploration data; according to the information dimension, the chaos parameter and the third-generation coherence value, based on a constraint condition critical value, determining a fault zone internal structure complexity degree characteristic parameter; according to the complexity characteristic parameters of the internal structure of the fault zone, the shale component content of the fault zone filler and the fault deformation burial depth constant are combined, and a constraint sealing index is calculated; and according to the constraint sealing index, predicting the sealing performance of the fault zone fault based on the CSI lower limit threshold of the found oil and gas reservoir fault. According to the method, the sealing performance of the fracture layer can be evaluated more accurately.

Description

Technical Field

[0001] The present application relates to the field of geological exploration technology, and in particular to a method and system for predicting fracture closure earthquakes based on structural integrity constraints. Background Art

[0002] Faults are a ubiquitous geological structure. There are many different types of oil and gas exploration and development objects related to faults. The most common ones are block oil and gas reservoirs, fault-karst oil and gas reservoirs, and fault-type gas storage facilities. Fault closure is an important assessment item in the risk of oil exploration and development strategies. Fault closure has a profound impact on the formation conditions such as oil and gas accumulation and preservation, so it has always been a geological problem in the oil and gas industry. Traditional methods for evaluating fault closure at home and abroad are based on statistics of many single geological parameters, such as the mud content of the formation, fault distance, fault mud content SGR, and mudstone smear factor SSF. Most of these methods are limited by the limited drilling data, and their lateral evaluation accuracy needs to be improved, which is limited in industrial applications. In oil production, three-dimensional seismic data, due to its obvious lateral identification advantages, is used from oil and gas exploration to development. It carries a variety of rich information about the internal structure and closure performance of the fault zone.

[0003] At present, the direct use of seismic data to conduct internal structure research of fault zones, evaluation of sealing performance, and further exploration and development of fault-related oil and gas reservoirs and geological engineering evaluation of underground energy storage space has gradually become a new research hotspot with broad application scenarios. Summary of the invention

[0004] The purpose of this application is to provide a method and system for earthquake prediction of fracture closure based on structural integrity constraints, which can improve the reliability of fracture closure evaluation.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a method for predicting fracture closure earthquakes based on structural integrity constraints, comprising: Obtaining petroleum seismic exploration data of the target area; the petroleum seismic exploration data includes post-stack three-dimensional seismic data, target fault interpretation data and target layer stratigraphic level interpretation data.

[0006] A three-dimensional model of the fault zone and faults in the target area is established based on the petroleum seismic exploration data.

[0007] Based on the three-dimensional model of the fault zone, the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone are calculated.

[0008] Determine the constraint condition critical value K of the internal structural integrity of the fault zone and the third-generation coherence value C3 of the petroleum seismic exploration data; the critical value K of the constraint condition ranges from 0.5 to 0.9 and is determined based on the expert system of the target area.

[0009] According to the information dimension DI, chaos parameter LYAP and the third-generation coherence value C3, based on the critical value K of the constraint condition, the characteristic parameter FI of the complexity of the internal structure of the fault zone is determined.

[0010] The constraint closure index CSI is calculated based on the characteristic parameter FI of the internal structural complexity of the fault zone, combined with the mud content of the fault zone filling and the fault deformation burial depth constant.

[0011] According to the constraint sealing index (CSI), the sealing performance of faults in the fault zone is predicted based on the CSI lower limit threshold of the faults in the discovered oil and gas reservoirs.

[0012] Optionally, based on the three-dimensional model of the fault zone, calculating the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone specifically includes: According to the formula , calculate the information dimension DI of the fractal parameters in the fault zone.

[0013] In the formula, It is the smallest unit of scale used in fractal measurement, and I is the information entropy.

[0014] Optionally, the information entropy is calculated as follows: .

[0015] In the formula, p i is the probability of each measurement unit being observed.

[0016] Optionally, the formula expression of the third-generation coherence value C3 of the petroleum seismic exploration data is: .

[0017] in, is the maximum eigenvalue, M is the total number of eigenvalues, is the characteristic value of any seismic trace in the time window.

[0018] Optionally, according to the information dimension DI, the chaos parameter LYAP and the third-generation coherence value C3, based on the constraint condition critical value K, the characteristic parameter FI of the complexity of the internal structure of the fault zone is determined, specifically including: When C3 is greater than or equal to the critical value K of the constraint condition, according to the formula FI= ( layp+DI ) / C3Calculate the characteristic parameter FI of the internal structure complexity of the fault zone.

[0019] When C3 is less than the critical value K of the constraint condition, according to the formula Calculate the characteristic parameter FI of the internal structure complexity of the fault zone.

[0020] Optionally, the constraint closure index CSI is calculated based on the characteristic parameter FI of the complexity of the internal structure of the fault zone, combined with the mud content of the fault zone filling and the fault deformation burial depth constant, specifically including: According to the formula , calculate the constraint closure index CSI; where SGR is the mud content of the fault zone filling.

[0021] Optionally, the calculation formula for the mud content of the fault zone filling is: .

[0022] Where i is the i-th rock layer that slides across the breakpoint, T i is the thickness of the i-th rock layer that slides across the fault point, VSH i is the mud content of the i-th rock layer that slides across the fault point, and D is the vertical fault throw of the fault.

[0023] Optionally, according to the constraint sealing index CSI, based on the CSI lower limit threshold of the discovered oil and gas reservoir fault, the sealing performance of the fault zone fault is predicted, specifically including: The constraint closure index (CSI) is compared with the lower threshold of CSI of faults in discovered oil and gas reservoirs.

[0024] If the constraint closure index CSI is greater than the CSI lower limit threshold, the fault is predicted to be lateral open.

[0025] If the constraint closure index CSI is less than or equal to the CSI lower threshold, the fault is predicted to be laterally closed.

[0026] In a second aspect, the present application provides a fracture closure earthquake prediction system based on structural integrity constraints, comprising: The data acquisition module is used to acquire the oil seismic exploration data of the target area.

[0027] The model building module is used to establish a three-dimensional model of the fault zone and fault in the target area based on the petroleum seismic exploration data; the petroleum seismic exploration data includes post-stack three-dimensional seismic data, target fault interpretation data and target layer stratigraphic level interpretation data.

[0028] The parameter calculation module is used to calculate the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone based on the three-dimensional model of the fault zone.

[0029] The parameter determination module is used to determine the constraint condition critical value K of the internal structural integrity of the fault zone and the third-generation coherence value C3 of the petroleum seismic exploration data; the critical value K of the constraint condition ranges from 0.5 to 0.9 and is determined according to the expert system of the target area.

[0030] The complexity characteristic parameter calculation module is used to determine the complexity characteristic parameter FI of the internal structure of the fault zone based on the information dimension DI, the chaos parameter LYAP and the third-generation coherence value C3 and the constraint condition critical value K.

[0031] The constraint closure index calculation module is used to calculate the constraint closure index CSI according to the characteristic parameter FI of the internal structural complexity of the fault zone, combined with the mud content of the fault zone filling and the fault deformation burial depth constant.

[0032] The prediction module is used to predict the sealing performance of the fault zone fault according to the constraint sealing index CSI and based on the CSI lower limit threshold of the discovered oil and gas reservoir faults.

[0033] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application provides a method and system for earthquake prediction of fault closure based on structural integrity constraints. The method comprehensively considers the internal structure of the fault zone and realizes a comprehensive analysis of the degree of development of cracks in the fault zone, structural complexity, integrity, mud content of filling materials, and compaction effect caused by deformation burial depth. By introducing the information dimension DI to describe the development of fault zone cracks, a chaotic system research method is used to characterize the chaotic characteristics of the disordered reflection of the fault zone in earthquakes, which corresponds to the complexity of the fault zone structure; using seismic coherence attributes represented by eigenvalue coherence C3, the integrity of the internal structure of the fault sliding surface is effectively constrained; the fault deformation burial depth constant reflects the influence of compaction on closure. Therefore, the method proposed in the present application can provide an evaluation effect that is more consistent with actual geological laws. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 A schematic flow chart of a method for predicting fracture closure earthquakes based on structural integrity constraints provided in one embodiment of the present application.

[0036] Figure 2A schematic diagram of the functional modules of a fracture closure earthquake prediction method system based on structural integrity constraints provided in one embodiment of the present application. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0038] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0039] Embodiment 1 like Figure 1 As shown, this embodiment provides a method for predicting fracture closure earthquakes based on structural integrity constraints, including: Step 101: Acquire petroleum seismic exploration data of a target area; the petroleum seismic exploration data includes post-stack three-dimensional seismic data, target fault interpretation data, and target layer stratigraphic interpretation data.

[0040] Step 102: Establish a three-dimensional model of the fault zone and fault in the target area based on the petroleum seismic exploration data.

[0041] Step 103: Based on the three-dimensional model of the fault zone, the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone are calculated.

[0042] Step 104: Determine the constraint condition critical value K of the internal structural integrity of the fault zone and the third-generation coherence value C3 of the petroleum seismic exploration data; the constraint condition critical value K ranges from 0.5 to 0.9 and is determined based on the expert system of the target area.

[0043] Step 105: According to the information dimension DI, the chaos parameter LYAP and the third-generation coherence value C3, based on the constraint condition critical value K, determine the characteristic parameter FI of the complexity of the internal structure of the fault zone.

[0044] Step 106: Calculate the constraint closure index CSI according to the characteristic parameter FI of the complexity of the internal structure of the fault zone, combined with the mud content of the fault zone filling and the fault deformation burial depth constant.

[0045] Step 107: According to the constraint sealing index CSI, based on the CSI lower limit threshold of the discovered oil and gas reservoir faults, the sealing performance of the fault zone fault is predicted.

[0046] In some embodiments, when executing steps 101-102, the specific steps may be as follows: The three-dimensional geometric modeling of the fault zone fault uses the interpretation results of 3D seismic data to establish the geometric model distribution of the fault in three-dimensional space, and at the same time calculate the fault distance distribution in three-dimensional space.

[0047] In some embodiments, when executing step 103, the specific steps may be as follows: Based on the three-dimensional model of the fault zone, the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone are calculated, specifically including: According to the formula , calculate the information dimension DI of the fractal parameters in the fault zone.

[0048] In the formula, It is the smallest unit of scale used in fractal measurement, and I is the information entropy.

[0049] Specifically, DI stands for information dimension, which is a dimensional parameter to measure the complexity in fractal geometry. It captures the irregularity and complexity within the fractal structure.

[0050] Information dimension DI quantifies the information content and complexity of the fractal structure through this formula, and is an important concept in fractal geometry. In practical applications, information dimension can be used as a tool to distinguish the characteristics of different fractal structures. It helps to identify and analyze the complex structure inside the fault zone, and can be regarded as a response to the degree of crack development inside the fault zone; it can be obtained by the box method.

[0051] In the process of obtaining DI, we no longer rely on the traditional fault identification results based on the structural map, but directly use the algorithm based on the curvature of seismic data to obtain it. In this way, the complex structure of the rupture zone can be handled more objectively and the details will be more obvious.

[0052] Specifically, the calculation formula of information entropy is: .

[0053] In the formula, p i is the probability of each measurement unit being observed.

[0054] The chaos parameter LYAP is the abbreviation of Lyapunov exponent, which is an important concept in the field of chaos theory and dynamic system. It is one of the numerical characteristics for identifying chaotic motion. In this embodiment, it is used to represent the chaotic characteristics in seismic data, which is a representation of the chaotic characteristics of the complex structure inside the fault zone and is dimensionless.

[0055] Specifically, the Lyapunov exponent can be defined as the limit of the logarithm of the ratio of the distance between two trajectories over time. Specifically, it is expressed as: .

[0056] Where d(x(t),y(t)) represents the distance between two trajectories x(t) and y(t) at time t.

[0057] In the process of calculating the Lyapunov index, the basic steps involve determining the dynamic equations of the system, selecting an initial state of the system and calculating the distance between adjacent trajectories of the system, solving the Jacobian matrix, and solving the eigenvalues ​​of the Jacobian matrix at each step of time evolution. Since petroleum seismic data is a record of the travel time of artificially excited seismic waves, it is suitable for Lyapunov index characterization.

[0058] As for the judgment of chaos, if the maximum Lyapunov exponent of a system is greater than zero, it indicates that the system exhibits chaotic characteristics, which means that the system is complex and nonlinear; conversely, if the maximum Lyapunov exponent is less than or equal to zero, the system behaves simple and linear.

[0059] In some embodiments, when executing step 104, the specific steps may be as follows: The value of K depends on the knowledge or experience of the integrity of the internal structure of the fault reflected in the existing seismic data in the neighboring area or the region. The value range is generally between 0.5 and 0.9, which is a critical division of C3.

[0060] C3 represents the result of the eigenvalue characteristic algorithm operation in the third-generation coherent attribute of seismic data. It is dimensionless and ranges from 0 to 1. Its definition is as follows: The formula for the third-generation coherence value C3 of petroleum seismic exploration data is: .

[0061] in, is the maximum eigenvalue, M is the total number of eigenvalues, is the characteristic value of any seismic trace in the time window.

[0062] In some embodiments, when executing step 105, the specific steps may be as follows: The implementation of step-by-step constraints on the integrity of the internal structure of the fault zone is based on the third-generation coherence value C3 of the seismic data. According to the information dimension DI, the chaos parameter LYAP and the third-generation coherence value C3, based on the critical value K of the constraint condition, the characteristic parameters FI of the complexity of the internal structure of the fault zone are determined, including: When C3 is greater than or equal to the constraint critical value K, it represents high internal structural integrity, few fragments, high coherence of the corresponding seismic waveform, and strong waveform consistency. According to the formula FI= ( layp+DI ) / C3 Calculate the characteristic parameter FI of the internal structure complexity of the fault zone.

[0063] When C3 is less than the constraint critical value K, it represents relatively low internal integrity of the fault zone, many fragments, low coherence of the corresponding seismic waveform, and poor waveform consistency. According to the formula Calculate the characteristic parameter FI of the internal structure complexity of the fault zone.

[0064] Among them, in some embodiments, when performing step 106, specifically, it can be as follows: The compaction effect reflects the influence of burial depth on formation porosity. The fillings (fault rocks) inside the fault zone are also affected by the compaction effect, and it is evaluated using the geological constant c related to the burial depth of fault deformation. c reflects the influence of the compaction degree of the rocks inside the fault zone on the constraint sealing index CSI, and the two are directly proportional. If the depth of the fault is less than 3000 meters, then the corresponding c value is 0.5; if the depth of the fault is between 3000 meters and 3500 meters, the corresponding c value is 0.25; if the fault observation point exceeds a depth of 3500 meters, the corresponding value is 0.

[0065] According to the formula , calculate the constraint sealing index CSI; where SGR is the shale component content of the fault zone filling.

[0066] Among them, the calculation formula for the shale component content of the fault zone filling is: .

[0067] Among them, SGR is the shale component content of the fault zone filling (fault rock), which is a commonly used parameter in the industry to evaluate fault sealing. According to petroleum seismic exploration data and vertical fault throw, calculate the SGR value of the shale component content of the fault zone filling at the calculation point. In the formula, SGR is the shale component content of the fault zone filling, %; i is the i-th rock layer passing through the fault break; T i is the thickness of the i-th rock layer passing through the fault break, m; VSH i is the shale content of the i-th rock layer passing through the fault break, %; D is the vertical fault throw of the fault, m.

[0068] Specifically, when 0 < C3 < k, the calculation formula for CSI is as follows: .

[0069] When K < C3 < 1, the calculation formula for CSI is as follows: .

[0070] In some embodiments, when executing step 107, the specific steps may be as follows: According to the constraint sealing index CSI, based on the CSI lower limit threshold of the discovered oil and gas reservoir faults, the sealing performance of the fault zone fault is predicted, including: The constraint closure index (CSI) is compared with the lower threshold of CSI of faults in discovered oil and gas reservoirs.

[0071] If the constraint closure index CSI is greater than the CSI lower limit threshold, the fault is predicted to be lateral open.

[0072] If the constraint closure index CSI is less than or equal to the CSI lower threshold, the fault is predicted to be laterally closed.

[0073] Specifically, the oil reservoirs discovered in the exploration area are counted, the lower limit threshold of the CSI of the fault closure is calibrated, the CSI value of the fault to be evaluated is compared with the lower limit threshold, and the sealing performance of the fault is quantitatively evaluated according to the comparison results, including: The CSI value of the fault to be predicted is compared with the closed lower limit threshold; if the CSI is greater than the closed lower limit threshold, the fault is laterally open, otherwise the fault is laterally closed.

[0074] The sealing capacity of each measured point in the fault zone is characterized by the difference between the CSI value and the lower limit of the sealing threshold. If the difference is larger, the permeability of the fault is stronger, which means the sealing capacity is weaker, and vice versa.

[0075] From the analysis of the above-mentioned factors and parameters, the CSI index is composed of multiple parameters that affect the permeability of the fault zone. The DI parameter is related to cracks, C3 is related to the integrity of the internal structure of the fault zone, Lyap is a representation of the complexity of the structure, SGR is related to the properties of the filling material and the content of mud components in the fault zone, and c is related to the compaction degree of the fault zone.

[0076] Embodiment 2 like Figure 2 As shown, this embodiment provides a fracture closure earthquake prediction system based on structural integrity constraints, including: The data acquisition module 201 is used to acquire petroleum seismic exploration data of the target area; the petroleum seismic exploration data includes post-stack three-dimensional seismic data, target fault interpretation data and target layer stratigraphic level interpretation data.

[0077] The model building module 202 is used to build a three-dimensional model of the fault zone and fault in the target area according to the petroleum seismic exploration data.

[0078] The parameter calculation module 203 is used to calculate the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone based on the three-dimensional model of the fault zone.

[0079] The parameter determination module 204 is used to determine the constraint condition critical value K of the internal structural integrity of the fault zone and the third-generation coherence value C3 of the petroleum seismic exploration data; the constraint condition critical value K ranges from 0.5 to 0.9 and is determined according to the expert system of the target area.

[0080] The complexity characteristic parameter calculation module 205 is used to determine the complexity characteristic parameter FI of the internal structure of the fault zone according to the information dimension DI, the chaos parameter LYAP and the third-generation coherence value C3, based on the constraint condition critical value K.

[0081] The constraint closure index calculation module 206 is used to calculate the constraint closure index CSI according to the characteristic parameter FI of the internal structural complexity of the fault zone, combined with the mud content of the fault zone filling and the fault deformation burial depth constant.

[0082] The prediction module 207 is used to predict the sealing performance of the fault zone fault according to the constraint sealing index CSI and based on the CSI lower limit threshold of the discovered oil and gas reservoir fault.

[0083] In summary, this application has the following technical effects: This application takes into account the factors of the internal structure of the fault zone and its seismic reflection characteristics, and realizes the coupling effect of the degree of development of internal cracks in the fault zone, the complexity of the internal structure, the integrity of the structure, the mud content of the fault zone filling, and the compaction caused by the deformation burial depth. The fractal dimension parameter DI is introduced to describe the development of fault zone cracks, and the parameter LYAP that characterizes the chaotic characteristics is introduced to reflect the chaotic and disordered reflection characteristics of the fault zone in earthquakes, which corresponds to the complexity of the fault zone structure; the seismic coherence attribute represented by the eigenvalue coherence C3 realizes the characterization and constraint of the response of the internal structural integrity of the fault sliding surface; compared with the existing methods, this application also highlights the influence of the mud content SGR of the fault zone filling and the fault deformation burial depth constant c on the fault closure; the whole process reflects the coupling effect of multiple geological factors and realizes the quantitative seismic prediction of the fault closure; the invention proposes a constrained closure index CSI that is closely related to the internal structure of the fault zone and the seismic reflection characteristics, reflecting the more objective closure characteristics of the internal structure of the fault zone, and the evaluation effect brought by this method is more in line with the actual geological laws.

[0084] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0085] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for predicting fracture closure earthquakes based on structural integrity constraints, characterized in that: The fracture closure earthquake prediction method based on structural integrity constraints comprises: Acquiring petroleum seismic exploration data of the target area; the petroleum seismic exploration data includes post-stack three-dimensional seismic data, target fault interpretation data and target layer stratigraphic interpretation data; Based on the petroleum seismic exploration data, a three-dimensional model of the fault zone and faults in the target area is established; Based on the three-dimensional model of the fault zone, the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone are calculated; Determine the constraint condition critical value K of the internal structural integrity of the fault zone and the third-generation coherence value C3 of the petroleum seismic exploration data; the critical value K of the constraint condition has a value range of 0.5-0.9 and is determined according to the expert system of the target area; According to the information dimension DI, the chaos parameter LYAP and the third generation coherence value C3, based on the critical value K of the constraint condition, the characteristic parameter FI of the complexity of the internal structure of the fault zone is determined; The constraint closure index CSI is calculated based on the characteristic parameter FI of the internal structural complexity of the fault zone, combined with the mud content of the fault zone filling and the fault deformation depth constant. According to the constraint sealing index (CSI), the sealing performance of faults in the fault zone is predicted based on the CSI lower limit threshold of the faults in the discovered oil and gas reservoirs.

2. A method for predicting fracture closure earthquakes based on structural integrity constraints according to claim 1, characterized in that: Based on the three-dimensional model of the fault zone, the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone are calculated, specifically including: According to the formula , calculate the information dimension DI of the fractal parameters in the fault zone; In the formula, It is the smallest unit of scale used in fractal measurement, and I is the information entropy.

3. A method for predicting fracture closure earthquakes based on structural integrity constraints according to claim 2, characterized in that: The calculation formula of the information entropy is: ； In the formula, p i is the probability of each measurement unit being observed.

4. A method for predicting fracture closure earthquakes based on structural integrity constraints according to claim 1, characterized in that: The formula expression of the third generation coherence value C3 of the petroleum seismic exploration data is: ； in, is the maximum eigenvalue, M is the total number of eigenvalues, is the characteristic value of any seismic trace in the time window.

5. A method for predicting fracture closure earthquakes based on structural integrity constraints according to claim 1, characterized in that: According to the information dimension DI, the chaos parameter LYAP and the third-generation coherence value C3, based on the critical value K of the constraint condition, the characteristic parameters FI of the complexity of the internal structure of the fault zone are determined, including: When C3 is greater than or equal to the critical value K of the constraint condition, according to the formula FI= ( layp+DI ) / C3 Calculate the characteristic parameter FI of the internal structural complexity of the fault zone; When C3 is less than the critical value K of the constraint condition, according to the formula Calculate the characteristic parameter FI of the internal structure complexity of the fault zone.

6. A method for predicting fracture closure earthquakes based on structural integrity constraints according to claim 5, characterized in that: According to the characteristic parameter FI of the complexity of the internal structure of the fault zone, combined with the mud content of the fault zone filling and the fault deformation depth constant, the constraint closure index CSI is calculated, which includes: According to the formula , calculate the constraint closure index CSI; where SGR is the mud content of the fault zone filling, and c is the influence of the compaction degree of the rock inside the fault zone on the constraint closure index CSI.

7. A method for predicting fracture closure earthquakes based on structural integrity constraints according to claim 6, characterized in that: The calculation formula for the mud content of the fault zone filling is: ； Where i is the i-th rock layer that slides across the breakpoint, T i is the thickness of the i-th rock layer that slides across the fault point, VSH i is the mud content of the i-th rock layer that slides across the fault point, and D is the vertical fault throw of the fault.

8. The method for predicting fracture closure earthquakes based on structural integrity constraints according to claim 1, characterized in that: According to the constraint sealing index CSI, based on the CSI lower limit threshold of the discovered oil and gas reservoir faults, the sealing performance of the fault zone fault is predicted, including: The constraint closure index (CSI) is compared with the lower threshold of CSI of faults in discovered oil and gas reservoirs; If the constraint closure index CSI is greater than the CSI lower threshold, the fault is predicted to be lateral open; If the constraint closure index CSI is less than or equal to the CSI lower threshold, the fault is predicted to be laterally closed.

9. A fracture closure earthquake prediction system based on structural integrity constraints, characterized in that: include: A data acquisition module is used to acquire oil seismic exploration data of a target area; the oil seismic exploration data includes post-stack three-dimensional seismic data, target fault interpretation data and target layer stratigraphic interpretation data; A model building module, used to build a three-dimensional model of the fault zone and fault in the target area based on the petroleum seismic exploration data; A parameter calculation module, used for calculating the information dimension DI and the chaos parameter LYAP of the fractal parameter in the fault zone based on the three-dimensional model of the fault zone; A parameter determination module is used to determine a constraint condition critical value K of the internal structural integrity of the fault zone and a third-generation coherence value C3 of the petroleum seismic exploration data; the critical value K of the constraint condition has a value range of 0.5-0.9 and is determined according to an expert system of the target area; The complexity characteristic parameter calculation module is used to determine the complexity characteristic parameter FI of the internal structure of the fault zone based on the information dimension DI, the chaos parameter LYAP and the third-generation coherence value C3 and the critical value K of the constraint condition; The constraint closure index calculation module is used to calculate the constraint closure index CSI according to the characteristic parameter FI of the internal structural complexity of the fault zone, combined with the mud content of the fault zone filling and the fault deformation burial depth constant; The prediction module is used to predict the sealing performance of the fault zone fault according to the constraint sealing index CSI and based on the CSI lower limit threshold of the discovered oil and gas reservoir faults.

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