A shale gas fault plane analysis and evaluation system based on seismic data analysis

Abstract

The present invention relates to the field of data processing systems suitable for shale gas development management and prediction, and specifically to a shale gas fault plane analysis and evaluation system based on seismic data analysis, the system comprising: a data acquisition module, a fault feature analysis module, a fault analysis module, and an enrichment effect evaluation module. In the present invention, by collecting and aggregating seismic data, a formation attribute data set is generated, and by extracting and clustering fault features, the accuracy of revealing the spatial distribution characteristics of the fault is improved. A topological model is further constructed, and the connectivity is analyzed by calculating the connectivity between intersections and porosity, which enhances the understanding of the underground structure and makes the location and scale assessment of shale gas enrichment areas more accurate. In addition, the relationship between the fault structure and the gas enrichment area is analyzed, and the efficiency of the gas flow channel is calculated, which provides a scientific basis for gas field development decision-making, thereby predicting advantageous locations and optimizing development plans.

Description

Technical Field

[0001] The present invention relates to the field of data processing systems suitable for shale gas development management and prediction, and in particular to a shale gas-containing fault plane analysis and evaluation system based on seismic data analysis. Background Art

[0002] Currently, in the field of shale gas exploration, traditional evaluation methods rely on two-dimensional seismic data to analyze geological structures. However, this method has obvious limitations in understanding complex geological structures, especially the distribution and structure of low-order faults. Although these faults are small in space and complex in structure, they play an important role in controlling the occurrence and migration of shale gas. Therefore, traditional two-dimensional seismic analysis methods are difficult to accurately characterize the three-dimensional structure and planar distribution characteristics of these low-order faults, resulting in limited evaluation and exploration efficiency of oil and gas reservoirs.

[0003] In order to overcome these limitations, this application proposes to use geometric analysis and topological analysis, combined with seismic data attribute analysis, to conduct a more refined quantitative analysis. This method can provide a deeper analysis of the structural characteristics and distribution patterns of low-order faults, improve the understanding of the planar connectivity of shale gas faults, and more effectively evaluate the potential exploration areas of shale gas resources.

[0004] In addition, this application also focuses on the quantitative evaluation of the connectivity of low-order fault planes, and by establishing a set of fault spatial characteristics, evaluates the potential impact of its connectivity on gas enrichment. This method not only enhances the understanding of the formation and distribution of shale gas reservoirs, but also provides a scientific basis for guiding actual exploration operations and optimizing the selection of drilling locations. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a shale gas fault plane analysis and evaluation system based on seismic data analysis.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: A shale gas fault plane analysis and evaluation system based on seismic data analysis comprises:

[0007] The data acquisition module collects seismic data in the target area, reads amplitude, phase and frequency parameters from the seismic data, combines the seismic data time series, aggregates the parameters to form a data set, and obtains a formation attribute data set;

[0008] A fault feature analysis module uses the formation attribute data set to extract the length, width and strike parameters of the fault, conduct cluster analysis, integrate the cluster analysis results and establish a geometric feature library, derive the spatial distribution characteristics of the fault from the geometric feature library, including connectivity and branch number, and generate a fault spatial feature set;

[0009] The fault analysis module calls the geometric parameters of the fault from the fault spatial feature set, builds a topological model, sets intersections and connection relationships, calculates the connectivity and porosity between intersections, aggregates the calculation results to form a connectivity analysis, and obtains a description of the fault connectivity;

[0010] The enrichment effect evaluation module uses the fault connectivity description to analyze the impact of the fault structure on the shale gas enrichment area, calculates the efficiency of the gas flow channel, analyzes the relationship between the fault structure and the gas enrichment area, and generates a gas enrichment evaluation result.

[0011] Preferably, the steps of acquiring the formation attribute data set are:

[0012] Collect seismic data in the target area, read amplitude, phase and frequency parameters, and record the acquisition time of each data point to form an original parameter data set;

[0013] Based on the original parameter data set, the aggregate amplitude is calculated using the following formula:

[0014] ;

[0015] in, is the amplitude of the ith data point, is the frequency of the ith data point, is the acquisition time of the ith data point, is the phase of the ith data point, is an imaginary unit, is the number of data points, is the aggregation amplitude;

[0016] Based on the aggregate amplitude, an integrated analysis is performed to obtain a formation attribute data set.

[0017] Preferably, the steps of integrating the cluster analysis results and establishing a geometric feature library are:

[0018] Using the formation attribute data set, extracting the length, width and strike data of the fault to generate a fault characteristic data set;

[0019] Based on the fault feature data set, normalization processing is performed to calculate the distance value between each fault feature and the cluster center. , the calculation formula is:

[0020] ;

[0021] in, is the length, width and strike of the current fault feature, is the mean of the cluster;

[0022] Based on the distance values, fault features are clustered, and the results are integrated to establish a geometric feature library.

[0023] Preferably, the steps of acquiring the fault space feature set are:

[0024] Accessing the geometric feature library, extracting fault length, width and strike data, and obtaining a fault description data set;

[0025] Based on the fault description data set, analyzing the spatial position relationship and distribution pattern of each fault to obtain spatial distribution characteristics;

[0026] Based on the spatial distribution characteristics, the position and mutual relationship of each fault in the geological structure are refined and described to generate a fault spatial feature set.

[0027] Preferably, the steps of calling the geometric parameters and position parameters of the fault from the fault space feature set, constructing the topological model, and setting the intersection points and connection relationships are as follows:

[0028] A topological model is constructed using the fault spatial feature set, wherein each intersection in the topological model represents an intersection between faults, each intersection has a corresponding number of connections, an attenuation coefficient, and a spatial degree of freedom, and the connection relationship between the intersections is set based on the physical contact of the faults to form a preliminary topological model;

[0029] The intersections and connection relationships in the preliminary topological model are adjusted, and the intersections and connections that incorrectly represent the fault position and direction are adjusted to form a topological model.

[0030] Preferably, the steps of obtaining the fault connectivity description are:

[0031] Extracting adjacent intersection information of each intersection and connection characteristics between intersections from the topological model to generate an intersection connection data set;

[0032] Based on the intersection connection data set, the connectivity and porosity are calculated using the following formula:

[0033] and ;

[0034] in, is the number of connections of intersection point i, is the spatial degrees of freedom around the intersection point i, is the attenuation coefficient, is the total number of intersection points in the model, is the connectivity, is the porosity, k is the number of intersections involved in the calculation;

[0035] Based on the porosity and connectivity, data aggregation analysis is performed to form a description of fault connectivity.

[0036] Preferably, the steps for obtaining the gas enrichment assessment result are:

[0037] Using the fault connectivity description, analyzing how the connectivity and porosity of the faults affect the distribution and mobility of shale gas, and forming an impact analysis result;

[0038] Based on the impact analysis results, the efficiency of the gas flow channel is calculated using the following formula:

[0039] ;

[0040] in, is the gas flow rate of the ith channel, is the connectivity of the corresponding channel, is the flow resistance coefficient, is the gas flow efficiency, Indicates the total number of gas flow channels;

[0041] Based on the gas flow efficiency, the relationship between the fault structure and the shale gas enrichment area is analyzed, and then the gas enrichment assessment result is generated according to the gas flow efficiency and the fault connectivity description.

[0042] Compared with the prior art, the advantages and positive effects of the present invention are:

[0043] In the present invention, by analyzing the characteristics of faults in the formation attribute data set and performing cluster analysis on these data, the accuracy of revealing the spatial distribution characteristics of faults is improved. The topological model further constructed enhances the quantitative analysis of connectivity by calculating the connectivity and porosity between intersections, making the location and scale assessment of shale gas-rich areas more accurate. In addition, the relationship between fault structure and gas-rich areas is analyzed, and the efficiency of gas flow channels is calculated, which provides a scientific basis for gas field development decisions, thereby improving resource utilization, optimizing development plans, and achieving effective cost control and risk minimization. The application of this system not only improves the accuracy of geological assessments, but also improves the efficiency of operations, especially in optimizing drilling plans and locating favorable exploration target areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0046] See also Figure 1 The present invention provides a technical solution: a shale gas fault plane analysis and evaluation system based on seismic data analysis includes:

[0047] The data acquisition module collects seismic data in the target area, reads amplitude, phase and frequency parameters from the seismic data, combines the seismic data time series, aggregates the parameters to form a data set, and obtains a formation attribute data set;

[0048] The fault feature analysis module uses the stratigraphic attribute data set to extract the length, width and strike parameters of the fault, conduct cluster analysis, integrate the cluster analysis results and establish a geometric feature library, derive the spatial distribution characteristics of the fault from the geometric feature library, including the number of intersections and branches, and generate a fault spatial feature set;

[0049] The fault analysis module calls the geometric parameters and position parameters of the fault from the fault spatial feature set, builds a topological model, sets intersections and connection relationships, calculates the connectivity and porosity between intersections, aggregates the calculation results to form a connectivity analysis, and obtains a description of the fault connectivity;

[0050] The enrichment effect evaluation module uses fault connectivity description to analyze the impact of fault structure on shale gas enrichment areas. By calculating the efficiency of gas flow channels, it analyzes the relationship between fault structure and gas enrichment areas and generates gas enrichment evaluation results.

[0051] The steps to obtain the stratigraphic attribute dataset are as follows:

[0052] Collect seismic data in the target area, read amplitude, phase and frequency parameters, and record the acquisition time of each data point to form an original parameter data set;

[0053] Based on the original parameter data set, the aggregate amplitude is calculated using the following formula:

[0054] ;

[0055] in, is the amplitude of the ith data point, is the frequency of the ith data point, is the acquisition time of the ith data point, is the phase of the ith data point, is an imaginary unit, is the number of data points, is the aggregation amplitude;

[0056] Based on the aggregated amplitude, an integrated analysis is performed to obtain a formation attribute data set.

[0057] Specifically, when collecting seismic data in the target area, it is first necessary to deploy multiple seismic sensors and seismographs at specific locations. These devices excite vibration waves on the ground or underground and capture echoes to obtain the response data of the strata. The collected amplitude, phase and frequency data are directly converted into digital signals by sensors and stored in the data collection unit. The specific collection time of each data point is automatically marked by the connected GPS device to ensure the accuracy and consistency of the time data. The collected raw data will directly affect the processing accuracy and reliability of subsequent data. To ensure data quality, the safety threshold of signal strength is usually set to -20dBm to -60dBm. Data below this range will be regarded as noise and eliminated to ensure that the information in the data set is credible.

[0058] The formula is useful in that by introducing the amplitude ,frequency ,time , Phase Multiple measured parameters such as the amplitude change and phase shift can be taken into account in one calculation, making the analysis results more comprehensive.

[0059] The steps for obtaining the first The amplitude value of each data point is obtained by recording, for example, in actual monitoring, the peak value of the waveform output by the seismic sensor is collected, and the amplitude value is selected after standardization and correction;

[0060] The acquisition steps are: perform frequency domain analysis on the continuous waveform segments through the original parameter data set obtained previously, and extract the The dominant frequency value of each data point is determined by the established Fast Fourier Transform operation;

[0061] The acquisition steps are: directly read the first The data collection time of each data point is recorded by the data recording device at fixed time intervals, and each data point contains its corresponding precise collection time;

[0062] The acquisition steps are as follows: obtain phase information using Hilbert transform in the original parameter data set obtained previously, and correspond the phase component in the transformation result to the data points;

[0063] It is an imaginary unit and is directly applied through mathematical definition;

[0064] is the total number of data points, which is determined by the total number of record entries in the original parameter data set obtained previously;

[0065] Through the above data acquisition process, set up a practical example:

[0066] Select data points, the parameters obtained through actual measurement are: , , , ; , , , ; , , , ; , , , ;

[0067] Calculation process:

[0068] Item 1:

[0069] ;

[0070] ;

[0071] Item 2:

[0072] ;

[0073] ;

[0074] Item 3:

[0075] ;

[0076] ;

[0077] Item 4:

[0078] ;

[0079] ;

[0080] Add the terms together:

[0081] ;

[0082] Sum of real parts: ;

[0083] Sum of the imaginary parts: ;

[0084] final: ;

[0085] The obtained aggregate amplitude is a complex value, and the real and imaginary parts of the value jointly reflect the comprehensive amplitude characteristics of multiple data points at different times and frequencies. When the absolute values ​​of the real and imaginary parts are large, it means that the seismic signal has more significant composite vibration characteristics under the corresponding time series and frequency distribution. When the real and imaginary parts approach smaller values, it means that the comprehensive vibration in this time period and frequency range is weak. This result provides input basis for the subsequent analysis of the stratigraphic attribute data set.

[0086] After the aggregate amplitude is obtained, the value is loaded into the internal comparison module as an input parameter. A set of stratigraphic reference values ​​and a list of known characteristic parameters pre-exist in the module. These lists are obtained by sorting out the acoustic wave, vibration and stress tests of known layers during geological exploration. The aggregate amplitude value is compared with these reference values ​​internally, and each reference data row corresponding to the aggregate amplitude value range is selected to match the stratigraphic identification parameters contained therein. The successfully matched identification parameters and their associated lithological characteristic parameters are recorded together. By checking the aggregate amplitude of adjacent data points and the reference value matching list in turn, a series of clearly marked stratigraphic attribute information sets are obtained. These attribute information are summarized at one time to integrate a complete stratigraphic attribute data set.

[0087] The steps to integrate the cluster analysis results and establish a geometric feature library are:

[0088] Using the stratigraphic attribute dataset, the length, width and strike data of the fault are extracted to generate a fault characteristic dataset;

[0089] Based on the fault feature dataset, calculate the distance value between each fault feature and the cluster center , the calculation formula is:

[0090] ;

[0091] in, is the length, width and strike of the current fault feature, is the mean of the cluster;

[0092] Based on the distance value, the fault features are clustered, and the results are integrated to establish a geometric feature library.

[0093] Specifically, using the stratigraphic attribute dataset first involves the process of extracting the length, width and strike data of the fault from the stratigraphic attribute dataset, screening and identifying the fault characteristics from the multidimensional data model, querying the geographical location and depth range of the fault, calculating and displaying the physical size and spatial direction of the fault, and the obtained length, width and strike data are further processed to filter out outliers. For example, the length and width data will be compared, and data points that deviate significantly from the average value will be eliminated to ensure the accuracy and reliability of the data. Thereafter, the generated fault characteristic dataset will serve as the basis for subsequent clustering analysis.

[0094] The benefit of the formula is that by normalizing the length, width and strike data respectively and then summing the squares of the differences, the deviation between the characteristics of the stratigraphic fault and the cluster center can be evaluated in the same dimension, which is convenient for the subsequent rapid determination of the proximity of each fault to the cluster center.

[0095] The parameter acquisition step is to record the measurement data of the lateral fault extension in the seismic monitoring network deployed in the target area, and finally obtain the lateral fault extension data by continuous multiple measurements and comparing them with the lateral depth measurement records obtained in geological exploration. The specific value of rice;

[0096] The step of obtaining the parameters is to select all faults within the same cluster. The length values ​​of each fault under the same measurement conditions are recorded, and then the average is obtained. For example, after recording the lengths of several faults in the same area, we can find the average value and finally get rice;

[0097] The parameter acquisition step is to measure the actual profile width of each fault, estimate it by combining the shear wave attenuation interval and the longitudinal wave response, and then obtain the effective value by merging and summarizing the repeated detection records, such as the final determination rice;

[0098] The step of obtaining the parameters is to count all fault width values ​​within the same cluster range and average them to get the cluster width mean. For example, the fault widths within the same area are summed up and averaged to get rice;

[0099] The parameter acquisition step is to record the strike angle of the fault in the plane projection, refer to the geographic coordinate system and combine the multi-point measurement results, and then centrally process the measured strike angles to obtain specific values, such as recording Spend;

[0100] The parameter acquisition step is to take the average value of all fault strikes in the same cluster, and average the strike angles of multiple faults. For example, Spend;

[0101] Calculation process:

[0102] First calculate , squaring this value gives ;

[0103] Then calculate , squaring this value gives ;

[0104] Then calculate , squaring this value gives ;

[0105] Adding these three terms gives ;

[0106] Finally take the square root ;

[0107] The results show that the comprehensive gap between the fault and the corresponding cluster center in terms of length, width and strike is about 0.137. The smaller the value, the closer the fault is to the center of this type. If it is greater than 1, it means that the deviation is high. The D value obtained by this formula is used to measure the difference between each fault and the cluster center and classify it in the subsequent cluster analysis.

[0108] The process of clustering fault features uses the distance values ​​between each fault feature and the cluster center calculated previously. These distance values ​​are input into the clustering algorithm. Commonly used clustering algorithms include K-means or hierarchical clustering. These algorithms group faults into the nearest cluster center by calculating and comparing distance values, thereby forming different fault groups. The identification of these groups helps to further analyze the distribution patterns of faults and the potential impact of related geological activities. The detailed characteristics of each fault group will be collected and integrated into a geometric feature library. The data in the library can be used for further research and resource development planning.

[0109] The steps to obtain the fault space feature set are:

[0110] Access the geometric feature library, extract the fault length, width and strike data, and obtain the fault description data set;

[0111] Based on the fault description data set, the spatial position relationship and distribution pattern of each fault are analyzed to obtain the spatial distribution characteristics;

[0112] Based on the spatial distribution characteristics, the position and mutual relationship of each fault in the geological structure are refined and described to generate a fault spatial feature set.

[0113] Specifically, the geometric feature library is accessed to obtain the fault description data set, and key data such as the length, width and strike of the fault are extracted from the geological database. These data undergo preliminary data verification and cleaning, such as eliminating data items that are obviously abnormal or inconsistent with geological logic to ensure the accuracy and consistency of the obtained data. After data extraction, the geological features are organized into a table form to form a fault description data set, which will be used for further geological analysis and model construction.

[0114] The spatial relationship and distribution pattern of faults are analyzed based on the fault description dataset. This step includes using GIS to depict the geometric arrangement and relative position of faults. By integrating geochronological data and fault strike data, the spatial distribution characteristics of faults are compared and classified, which includes identifying the continuity, interlacing and distribution density of fault lines. The analysis results help understand the spatial interaction of fault groups and their impact on the surrounding geological structures.

[0115] Refine and describe the position and relationship of each fault in the geological structure. By comparing and analyzing the geological data set with the existing geological model, using 3D geological modeling software such as Petrel or GOCAD, the model will reconstruct the 3D view of the fault based on the input fault feature data set, showing the specific location of each fault and its relationship with adjacent faults. The input fault's spatial coordinates, length, width, and strike information can be used to more accurately predict the impact of fault activity on the reservoir by simulating the interaction between faults and other geological layers. The generated fault spatial feature set provides an important decision-making basis for subsequent resource exploration.

[0116] The steps of calling the geometric parameters of the fault from the fault space feature set, building the topological model, and setting the intersection and connection relationship are as follows:

[0117] A topological model is constructed using the fault spatial feature set. Each intersection in the topological model represents the intersection between faults. The connection relationship between the intersections is set based on the direction and physical contact of the faults to form a preliminary topological model.

[0118] The intersections and connections in the preliminary topological model are adjusted, and the intersections and connections that incorrectly represent the fault position and direction are adjusted to form a topological model.

[0119] Specifically, geometric parameters are extracted from the spatial feature set of the fault, such as the length, width and direction of the fault, and the intersection points in the topological model are set based on this. Each intersection point represents the specific location of a fault, and the connection relationship between the intersection points is determined by the physical contact and relative direction of the faults. For example, when the trend data of two faults show that they may intersect at a certain location, a connection will be established between the two intersection points. The basis for setting this connection relationship is the detailed analysis of geological mapping and fault direction. The setting of the safety threshold and range is based on previous geological research and seismic data to ensure the accuracy of the connection and the reliability of the geological model. Constructing such a topological model helps to predict the paths and channels of oil and gas migration, thereby guiding the analysis of oil and gas storage laws.

[0120] The adjustment of the intersections and connection relationships in the topological model is based on the precise analysis and representation of the geometric characteristics of the faults. Each connection in the model is checked and those representation errors that do not correctly reflect the position or direction of the faults are corrected. During the adjustment process, the relative position and direction between the faults are analyzed in detail. Any connection that needs to be changed will be recalculated based on the new geological data to ensure that each intersection and connection accurately reflects the actual situation of the fault. This step is crucial to building an accurate geological model. The revised model will more accurately describe the interactions between faults and provide a solid foundation for further geological analysis and related decision-making.

[0121] The steps to obtain the fault connectivity description are:

[0122] Extract the adjacent intersection information of each intersection and the connection characteristics between the intersections from the topological model to generate an intersection connection data set;

[0123] Based on the intersection connection data set, the connectivity and porosity are calculated using the following formula:

[0124] and ;

[0125] in, is the number of connections of intersection point i, is the spatial degrees of freedom around the intersection point i, is the attenuation coefficient, is the total number of intersection points in the model, is the connectivity, is the porosity, k is the number of intersections involved in the calculation;

[0126] Based on the porosity and connectivity, data aggregation analysis is performed to form a description of fault connectivity.

[0127] Specifically, based on the adjacent intersection information of each intersection and the records of the connection characteristics between intersections in the previously established topological model, the information is disassembled and extracted, and each intersection in the topological model is marked as an ordered index, starting from index 1 and incrementing, and the intersection coordinates and connection identifiers recorded in the topological model are scanned item by item. According to the established internal data structure, the adjacency relationship of the intersections is first confirmed one by one in the existing records. For each intersection, the adjacent intersection list information is extracted one by one according to the index order, the adjacent intersection index number corresponding to each intersection is matched, and the connection characteristic parameters between the intersection and the adjacent intersection are recorded.

[0128] The connection characteristic parameters are obtained by searching in the connection identification data that have been allocated during the topological model construction process. These connection identification data have been allocated in the topological construction stage and contain the physical information parameters of each connection line segment, including the length value of the line segment and the distance between the intersections. For the length value, a reference value is extracted from the average spatial scale obtained from the seismic data actually measured in the geological field, and the applicable length value is obtained after proportional conversion. These length values ​​are uniformly quantified into numerical parameters, and then the corresponding relationship between the connection characteristics and the adjacent intersections is checked one by one to ensure that the adjacent intersection list of each intersection contains not only the index of the adjacent intersection, but also the length of the line segment connecting the intersection and the adjacent intersection. The direction value of the connection segment is calculated by quantifying the coordinate difference between the intersections. When calculating, the current intersection coordinate is subtracted from the adjacent intersection coordinate to obtain a vector, and then the direction angle parameter is calculated according to the components of the vector. In order to prevent incomplete records of the direction parameters, all direction data are converted into numerical parameters in the range of 0 to 360 degrees.

[0129] The direction parameters are calculated through the coordinate difference in the intersection coordinate system. The coordinate data comes from the location information of the seismic characteristic points recorded by the seismic sensors deployed on site in a specific coordinate system. The intersection coordinate point set is obtained through geophysical imaging and entered into the internal data list in the topology generation stage. Finally, the adjacent intersection index, connecting line segment length value and direction angle parameter of each intersection are integrated, and these parameters are arranged in an ordered data structure according to the intersection index. The intersection index is used as the primary key. Each intersection corresponds to a set of adjacent intersections and their connection parameter records, thus forming an intersection connection data set.

[0130] The formula is useful in that it takes into account the number of intersection connections and spatial freedom Two types of parameters are weighted in logarithmic and exponential functions to make the connectivity and porosity The calculation results can more comprehensively reflect the relationship between topological structure and spatial characteristics, thus obtaining a more accurate quantitative description in fault analysis and evaluation;

[0131] The steps to obtain the parameters are: connect the data set according to the intersection points obtained previously, and retrieve the The number of adjacent intersections of an intersection can be directly obtained by counting the adjacent intersection list of the intersection. ;

[0132] The steps for obtaining the parameters are as follows: by measuring the spatial position around the intersection in the topological model, the effective spatial volume around the intersection that can be used for fluid or gas diffusion is proportional to the standard volume of the area around the intersection, and the proportional value is mapped to The ratio is a numerical parameter, and the ratio is determined by microseismic location data obtained during geophysical exploration and three-dimensional reconstruction mapping;

[0133] The steps of obtaining parameters are as follows: During the analysis process, the parameters are determined by analyzing the rock microstructure according to the lithology and fracture distribution inside the formation. The specific value of the micron-level pore structure is analyzed by core CT scanning data to find out the pore change law in a specific interval. ;

[0134] The steps to obtain the parameters are as follows: Determine by counting the total number of intersections in the topological model obtained previously ;

[0135] The steps to obtain the parameters are as follows: Select the number of intersection points to be analyzed in this calculation , 10 typical and representative intersection points are selected from the intersection connection data set for calculation;

[0136] Parameter Values:

[0137] Select the number of connections for 10 intersection points: , , , , , , , , , ;

[0138] Select the spatial degrees of freedom corresponding to the 10 intersection points: , , , , , , , , , ;

[0139] Calculation process:

[0140] calculate :

[0141] ;

[0142] = ;

[0143] ;

[0144] calculate :

[0145] ;

[0146] = ;

[0147] = ;

[0148] ;

[0149] The results show that It is slightly lower than the reference threshold of 0.3 for stratum connectivity determination, indicating that the overall connectivity of the current intersection set is relatively limited. It is close to the empirical threshold of 0.2, indicating that the porosity is low;

[0150] The reference threshold for determining formation connectivity comes from field measurements and monitoring of the same type of faults to obtain representative samples of measured data on intersection connectivity. Distribution analysis is performed on these sample data, all measured intersection connectivity data are sorted, and the value intervals at the median and specific quantiles in the data distribution are determined. By comparing these measured data with the corresponding results of subsequent production and injection tests, it is found that when the connectivity When it is around 0.3, the actual fluid flow and gas transport in the formation begin to change significantly, that is, the relevant substances along the fault seepage path are observed to increase significantly in the production monitoring data. It is confirmed that the connectivity threshold is set at 0.3. When it is close to or higher than 0.3, the field measured data show that the stratum structure has a high degree of connectivity.

[0151] Porosity empirical threshold source: CT scanning and microstructure measurement of core samples are performed to obtain measured porosity data. After statistical and cluster analysis, these data are used to determine the porosity threshold. When the porosity is about 0.2, the corresponding microstructure shows that the pore space inside the rock has significant gas or fluid carrying capacity. In addition, compared with the production monitoring data of the area, it is found that when the porosity is higher than or close to 0.2, the actual flow rate in the field injection / output test has a statistical feature of significant improvement. 0.2 is used as the empirical threshold for porosity determination to identify the distinction standard of porosity in fault structure analysis.

[0152] According to the porosity and connectivity values ​​obtained previously, when selecting the reference list of internal records for data aggregation analysis, the connectivity value is first compared with a set of connectivity reference values ​​of a set of known geological measured intersection sets. These reference values ​​are obtained through several typical fault samples collected at the geological site. The connection status of the intersections in each group of typical faults is quantified to form a basic reference list, which contains mapping records of intersection indexes and connectivity values. Then, the connectivity parameters of the intersection set to be analyzed are matched one by one with the corresponding reference values ​​in the reference list, and the interval of the connectivity of the intersection to be analyzed is determined by numerical comparison. The identification parameters corresponding to the identified connectivity interval are recorded in the internal data structure for subsequent processing. Then, for the porosity parameters, the same method is used from Porosity identification records of the corresponding range are selected from the pre-constructed porosity reference data set, which comes from microstructure measurement and multi-point pore testing and contains matching information of known porosity and corresponding rock microstructure types. Then, a merge operation is performed based on the connectivity identification and the porosity identification, and the two identification values ​​are associated and matched. For example, the numerical sequence of the connectivity identification and the numerical sequence of the porosity identification are compared through indexes to determine the final matching mode. After the identification merging is completed in the internal data processing, the results are numerically sorted. By comparing the index levels of the sorted identifications, the finally identified fault connectivity description is quantified into an ordered parameter set, and each item of the parameter set is compared and verified again. After confirming that there are no duplicate records and missing items, the fault connectivity description is finally obtained.

[0153] The steps to obtain the gas enrichment assessment results are:

[0154] Using the fault connectivity description, analyze how the fault connectivity and porosity affect the distribution and mobility of shale gas to form impact analysis results;

[0155] Based on the impact analysis results, the efficiency of the gas flow channel is calculated using the following formula:

[0156] ;

[0157] in, is the gas flow rate of the ith channel, is the connectivity of the corresponding channel, is the flow resistance coefficient, is the gas flow efficiency, Indicates the total number of gas flow channels;

[0158] Based on the gas flow efficiency, the relationship between fault structure and shale gas enrichment area is analyzed, and then the gas enrichment assessment results are generated according to the gas flow efficiency and fault connectivity description.

[0159] Specifically, the fault connectivity description is used to analyze how the connectivity and porosity of the fault affect the distribution and mobility of shale gas. Through geological simulation and fault data, fault areas with high connectivity and high porosity are identified, which generally show higher shale gas accumulation potential. This analysis compares the connectivity and porosity data of different fault areas to evaluate their specific impact on shale gas mobility. High connectivity generally indicates that the gas flow channel is more open, while high porosity provides more gas storage space.

[0160] The usefulness of the formula is that it calculates the gas flow efficiency by quantifying the gas flow rate of each channel and the connectivity of the corresponding channel. The specific calculation is as follows: There are 5 channels, the specific gas flow rate and the corresponding connectivity for: , , , , , , , , , , flow resistance coefficient ;but:

[0161] ;

[0162] ;

[0163] ;

[0164] ;

[0165] ;

[0166] This result indicates that the average efficiency of the gas flow channel is 82.225%, that is, under the current conditions of fault connectivity and resistance coefficient, the average gas flow efficiency is relatively high, which is conducive to the effective exploitation of shale gas; specifically, greater than 80% is favorable and less than 50% is unfavorable.

[0167] Based on the calculated gas flow efficiency, the relationship between fault structure and shale gas enrichment areas was further analyzed. By combining the data of fault connectivity, porosity, and gas flow efficiency, efficient gas flow channels can be identified. These channels are usually associated with high-connectivity faults, indicating potential high-gas production areas. This analysis helped determine the best areas for shale gas enrichment and provided important geological information for resource development. Further, using these data, the specific impact of fault structure on shale gas enrichment and mobility was evaluated, generating gas enrichment assessment results.

Claims

1. A shale gas fault plane analysis and evaluation system based on seismic data analysis, characterized in that: The system comprises: The data acquisition module collects seismic data in the target area, reads amplitude, phase and frequency parameters from the seismic data, combines the seismic data time series, aggregates the parameters to form a data set, and obtains a formation attribute data set; A fault feature analysis module uses the formation attribute data set to extract the length, width and strike parameters of the fault, perform cluster analysis, integrate the cluster analysis results and establish a geometric feature library, derive the spatial distribution characteristics of the fault from the geometric feature library, and generate a fault spatial feature set; The fault analysis module calls the geometric parameters of the fault from the fault spatial feature set, builds a topological model, sets the intersections and connection relationships, calculates the connectivity and porosity between the intersections, aggregates the calculation results to form a connectivity analysis, and obtains a description of the fault connectivity; The enrichment effect evaluation module uses the fault connectivity description to analyze the impact of the fault structure on the shale gas enrichment area, calculates the efficiency of the gas flow channel, analyzes the relationship between the fault structure and the gas enrichment area, and generates a gas enrichment evaluation result.

2. The shale gas fault plane analysis and evaluation system based on seismic data analysis according to claim 1 is characterized in that: The steps for obtaining the formation attribute data set are: Collect seismic data in the target area, read amplitude, phase and frequency parameters, and record the acquisition time of each data point to form an original parameter data set; Based on the original parameter data set, the aggregate amplitude is calculated using the following formula: ; in, is the amplitude of the ith data point, is the frequency of the ith data point, is the acquisition time of the ith data point, is the phase of the ith data point, is an imaginary unit, is the number of data points, is the aggregation amplitude; Based on the aggregate amplitude, an integrated analysis is performed to obtain a formation attribute data set.

3. The shale gas fault plane analysis and evaluation system based on seismic data analysis according to claim 1 is characterized in that: The steps to integrate the cluster analysis results and establish a geometric feature library are: Using the formation attribute data set, extracting the length, width and strike data of the fault to generate a fault characteristic data set; Based on the fault feature data set, normalization processing is performed to calculate the distance value between each fault feature and the cluster center. , the calculation formula is: ; in, is the length, width and strike of the current fault feature, is the mean of the cluster; Based on the distance values, fault features are clustered, and the results are integrated to establish a geometric feature library.

4. The shale gas fault plane analysis and evaluation system based on seismic data analysis according to claim 1 is characterized in that: The steps of obtaining the fault space feature set are: Accessing the geometric feature library, extracting fault length, width and strike data, and obtaining a fault description data set; Based on the fault description data set, analyzing the spatial position relationship and distribution pattern of each fault to obtain spatial distribution characteristics; Based on the spatial distribution characteristics, the position and mutual relationship of each fault in the geological structure are refined and described to generate a fault spatial feature set.

5. The shale gas fault plane analysis and evaluation system based on seismic data analysis according to claim 1 is characterized in that: The steps of calling the geometric parameters and position parameters of the fault from the fault space feature set, building the topological model, and setting the intersection and connection relationship are as follows: A topological model is constructed using the fault spatial feature set, wherein each intersection in the topological model represents an intersection between faults, each intersection has a corresponding number of connections, an attenuation coefficient, and a spatial degree of freedom, and the connection relationship between the intersections is set based on the physical contact of the faults to form a preliminary topological model; The connection relationship in the preliminary topological model is adjusted, and the intersection connection that incorrectly represents the fault position and direction is adjusted to form a topological model.

6. The shale gas fault plane analysis and evaluation system based on seismic data analysis according to claim 1 is characterized in that: The steps for obtaining the fault connectivity description are: Extracting adjacent intersection information of each intersection and connection characteristics between intersections from the topological model to generate an intersection connection data set; Based on the intersection connection data set, the connectivity and porosity are calculated using the following formula: and ; in, is the number of connections of intersection point i, is the spatial degrees of freedom around the intersection point i, is the attenuation coefficient, is the total number of intersections in the model, is the connectivity, is the porosity, k is the number of intersections involved in the calculation; Based on the porosity and connectivity, data aggregation analysis is performed to form a description of fault connectivity.

7. The shale gas fault plane analysis and evaluation system based on seismic data analysis according to claim 1 is characterized in that: The steps for obtaining the gas enrichment assessment result are: Using the fault connectivity description, analyzing how the connectivity and porosity of the faults affect the distribution and mobility of shale gas, and forming an impact analysis result; Based on the impact analysis results, the efficiency of the gas flow channel is calculated using the following formula: ; in, is the gas flow rate of the ith channel, is the connectivity of the corresponding channel, is the flow resistance coefficient, is the gas flow efficiency, Indicates the total number of gas flow channels; Based on the gas flow efficiency, the relationship between the fault structure and the shale gas enrichment area is analyzed, and then the gas enrichment assessment result is generated according to the gas flow efficiency and the fault connectivity description.

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