A method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information

Abstract

The present invention relates to a method for quantitatively evaluating the structural deformation strength of a fault zone based on seismic information. The method of the present invention can effectively identify multi-scale faults developed in deep underground target layers, effectively improving the accuracy of identifying fault zones and limiting the width of fault zones. In the process of extracting three-dimensional seismic information, the three-dimensional fault information is vectorized and extracted to achieve the effect of batch processing of data. At the same time, the method of the present invention is multi-scale when batch processing and extracting data, which effectively saves costs and improves accuracy. Finally, the method of the present invention achieves a quantitative evaluation of the structural deformation strength of the fault zone by integrating three structural parameters: the width of the fault zone, the vertical fault throw, and the fracture density within the zone.

Description

Technical Field

[0001] The present invention relates to the technical field of obtaining geological structures based on seismic information, and in particular to a method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information. Background Art

[0002] Fault zones are important tectonic features in the Earth's crust, and precise identification of their internal structure is crucial for oil and gas exploration, earthquake prediction, and engineering stability assessment. In recent years, researchers at home and abroad have developed a variety of fault zone structure identification methods through the integration of multidisciplinary techniques, including geological profiling, remote sensing image analysis, geophysical exploration, and numerical simulation.

[0003] The geological profiling method primarily involves drawing geological profiles through geological surveys to identify fault zone features such as morphology, scale, and occurrence. Its advantages lie in its intuitive nature and the direct acquisition of field data. However, due to topographical constraints, this method is difficult to implement in some areas and is labor-intensive. Remote sensing image analysis utilizes satellite or aerial imagery to identify fault zones through image interpretation and feature classification. This method has a wide coverage range and is suitable for areas where field surveys are difficult to conduct. However, due to resolution limitations, it is less effective at identifying subtle fault zones, and interpretation results are affected by image quality and interpretation level. Geophysical methods (such as seismic exploration and electromagnetic surveying) use physical detection techniques to identify fault zones, determining their distribution based on features such as seismic wave propagation anomalies and electromagnetic field variations. This method can detect fault zones deep underground and obtain three-dimensional spatial information, but it is characterized by high equipment costs and technical requirements, and its accuracy is limited by the geophysical techniques themselves. Numerical simulation methods simulate the formation process of fault zones by building geological models to identify their distribution patterns and characteristics. This method can simulate the dynamic evolution of fault zones and predict the existence of unknown fault zones, but the model establishment process is complex, requires a large amount of geological data support, and the simulation results depend on the accuracy of the model.

[0004] Furthermore, patents CN118732035A and CN110749924A, respectively, disclose methods for identifying fault zones by performing coherence volume calculation and fault enhancement data volume processing and analysis on seismic information. However, these methods only roughly identify the location of fault zones and are still limited in defining their width. Based on this, domestic and foreign scholars have developed methods for identifying and analyzing fault zone widths through field geological outcrop exploration, obtaining fault information, and using mathematical statistical analysis (Genter et al., 1997; Berg and Skar, et al., 2005; Choi et al., 2016). Because these methods use uniformly wide zones as data sampling areas during data analysis, their identification accuracy is limited by the zone width, and they also only analyze surface-visible fault zones. Therefore, in terms of accurate identification and analysis of oil, gas and mineral resource exploration and development and their key deep underground fault zones, although relevant patents have been published by predecessors, the identification and analysis precision still cannot meet the requirements of my country's deep oil, gas and mineral resource exploration and development work. Summary of the Invention

[0005] To solve the above problems, the present invention provides a method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information, comprising the following steps:

[0006] S1 imports the 3D seismic data and target stratum data of the work area into Petrel software respectively;

[0007] S2 builds a 3D model of the target stratum in Petrel software and uses seismic ant tracking technology to perform 3D seismic volume attribute analysis on the 3D seismic data. The 3D seismic volume attribute analysis result data volume is then superimposed with the 3D model of the target stratum to identify low-order faults in the target stratum and capture a high-definition bird's-eye view.

[0008] S3 imports the high-definition top view obtained in step S2 into 3D Move software and interprets the low-order fracture network; collects low-order fracture information data, and exports ASCII type data;

[0009] S4 opens the exported ASCII data with Notepad and copies all the information into an Excel spreadsheet. The fracture data are arranged from small to large according to the spatial coordinate values, and the cumulative fracture frequency is calculated. A scatter plot of distance-cumulative fracture frequency is drawn.

[0010] Combined with the three-dimensional model of the target stratum, the width of the fault zone is quantitatively identified, the vertical fault throw of the fault zone is quantitatively read, the fault density within the fault zone is quantitatively calculated, and the structural deformation intensity of the fault zone is quantitatively evaluated.

[0011] On the basis of the above scheme, in step S2, the specific method of superimposing the 3D seismic body attribute analysis result data volume with the target stratum 3D model is to use the RMS amplitude algorithm in the SurfaceAttribute analysis technology under the Seismic Interpretation module in Petrel to superimpose the 3D seismic body attribute analysis result data volume with the target stratum 3D model.

[0012] On the basis of the above scheme, in step S3, the specific interpretation method is: using the Create lines function under the ModelBuilding module in 3D Move to draw and interpret the fracture network to obtain numerical low-order fracture network data.

[0013] On the basis of the above scheme, in step S3, the specific method for collecting low-order fracture information data is as follows:

[0014] ①Use the Create Section function in the Model Building module to create a specific section according to your needs;

[0015] ②Use the To Section function in the Project function under the Model Building module to project the fracture network data information within a certain distance on both sides of the established specific section to the section;

[0016] ③ Select the fracture network data projected onto the section and export it as ASCII data.

[0017] Based on the above solution, the specific method for drawing the distance-fracture cumulative frequency scatter plot in step S4 is:

[0018] ① Use Notepad to open the ASCII data exported in step D and copy all the information into an Excel spreadsheet. Arrange the fracture data from small to large according to the spatial coordinate X or Y value and calculate the cumulative fracture frequency.

[0019] ② Using data L as the horizontal axis (X-axis) and the cumulative value of faults T as the vertical axis (Y-axis), a distance-fracture cumulative frequency scatter plot is drawn. The location where the slope of the scatter trend suddenly increases can be identified as the location where the fault zone develops.

[0020] Where (X, Y) is the plane coordinate of the fault development point, L is the distance between the fault development point and the statistical origin (X1, Y1), and T is the cumulative frequency of the fault;

[0021] Ti=i; (Xi, Yi) is the coordinate of the fault development position, where i is 1, 2, 3, ...

[0022] Based on the above scheme, the specific method for quantitatively identifying the width of the fault zone in step S4 is as follows: based on the distance-fracture cumulative frequency scatter plot, the distance span where the slope of the trend line increases is the width of the fault zone, which is recorded as W:

[0023]

[0024] Where W is the width of the fault zone, (Xm, Ym) and (Xn, Yn) are the plane coordinates of the fault data points on both sides of the slope increasing area.

[0025] Based on the above scheme, the specific method for quantitatively reading the vertical fault distance of the fault zone in step S4 is:

[0026] Based on the plane coordinates of the fault zone development point, the spatial coordinates (X, Y, Z) of the upper and lower plates of the fault zone are read in the three-dimensional model of the target stratum obtained in step S2. The difference between the spatial coordinates Z of the upper and lower plates is the vertical fault throw of the fault zone, which is recorded as P.

[0027] Based on the above scheme, the specific method for quantitatively calculating the fracture density within the fracture zone in step S4 is:

[0028] Based on the obtained cumulative fracture frequency, the fracture density D is calculated. The specific formula is:

[0029]

[0030] Where D is the fault density, Tm and Tn are the cumulative fault frequencies when counting on both sides of the fault zone, and W is the width of the fault zone.

[0031] Based on the above scheme, the specific method for quantitatively evaluating the structural deformation intensity of the fault zone in step S4 is:

[0032] ① Collect and calculate the fault zone data of multiple survey lines to obtain the structural parameter values of multiple fault zone development points, namely the fault zone width, vertical fault throw and fault density within the zone;

[0033] ② Based on the structural parameter values of the fault zone development points, quantitatively evaluate the characteristic value S of the structural deformation intensity of the fault zone:

[0034] S∈(0,1]; i=1,2,3,4,…;

[0035] Among them, S is the characteristic value of tectonic deformation intensity; Wmax is the maximum width of the fault zone, Wi is the width of the fault zone at each fault zone development point; Dmax is the maximum fault density within the fault zone, Di is the fault density within the fault zone at each fault zone development point; Pmax is the maximum fault throw of the fault zone, Pi is the fault throw of the fault zone at each fault zone development point; the characteristic value of low tectonic deformation intensity is S∈(0,0.01], the characteristic value of medium tectonic deformation intensity is S∈(0.01,0.1], and the characteristic value of strong tectonic deformation intensity is S∈(0.1,1].

[0036] Beneficial effects of the present invention:

[0037] The method of the present invention imports seismic data and stratigraphic data into 3D modeling software to generate a 3D stereo model. By processing and extracting the 3D seismic information, a high-definition top view of low-order faults in the target stratum of the work area is obtained. The high-definition top view of the low-order faults is then interpreted and combined with the spatial coordinates of the 3D model to obtain the width, vertical fault throw and fracture density of the fault zone in the target stratum. Finally, the three structural parameter values are integrated to quantitatively evaluate the structural deformation intensity of the fault zone.

[0038] The method of the present invention can effectively identify multi-scale faults developed in deep underground target layers, effectively improving the accuracy of identifying fault zones and defining their widths. During the extraction of three-dimensional seismic information, the three-dimensional fault information is vectorized and extracted to achieve the effect of batch data processing. At the same time, the method of the present invention is multi-scale when batch processing and extracting data, which effectively saves costs and improves accuracy. Finally, the method of the present invention achieves a quantitative evaluation of the structural deformation intensity of the fault zone by integrating three structural parameters: the width of the fault zone, the vertical fault throw, and the fracture density within the zone. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 This is the display effect diagram after importing data in step 2 of Example 2 of this application;

[0041] Figure 2 This is a rendering of the three-dimensional stratum model established in step 3 of Example 2 of this application;

[0042] Figure 3 This is a rendering of the high-definition top view captured in step 3 of Example 2 of this application;

[0043] Figure 4 This is the display effect diagram after the image in step 4 of Example 2 of this application is imported into 3D Move;

[0044] Figure 5 This is the effect diagram of the low-order fracture network obtained after interpretation in step 4 of Example 2 of this application;

[0045] Figure 6 This is the cross-sectional rendering generated in step 4 of Example 2 of this application;

[0046] Figure 7 This is the projection effect diagram generated in step 4 of Example 2 of this application;

[0047] Figure 8 This is the distance-fracture cumulative frequency scatter plot drawn in step 5 of Example 2 of this application;

[0048] Figure 9 This is a planar distribution diagram of multiple measurement lines in step 5 of Example 2 of this application;

[0049] Figure 10 This is the planar distribution map of the 18 fault zone development points in step five of Example 2 of this application. DETAILED DESCRIPTION

[0050] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] Example 1

[0052] The present application provides a method for quantitatively evaluating the structural deformation intensity of a fault zone by integrating multiple structural parameters based on seismic information. Specifically, the method comprises the following steps:

[0053] A. Data Preparation

[0054] (1) 3D seismic data of the work area (SEGY format);

[0055] (2) Target stratum data of the work area (ASCII code data format).

[0056] B. Data import

[0057] Import the data prepared in step A into Petrel software:

[0058] (1) Import the 3D seismic data of the work area into Petrel.

[0059] (2) Import the target stratum data of the work area into Petrel.

[0060] C. Data Processing

[0061] (1) Processing 3D seismic data using seismic ant tracking technology in Petrel software;

[0062] (2) Use Petrel to build a three-dimensional model of the target formation;

[0063] (3) Identification of low-order faults in the target stratum: Based on the ant body tracking results of the 3D seismic volume, the RMS amplitude algorithm in the Surface Attribute analysis technology under the Seismic Interpretation module in Petrel is used to superimpose the data volume of the 3D seismic volume attribute analysis results with the 3D model of the target stratum to identify low-order faults in the target stratum and capture a high-definition bird's-eye view.

[0064] D. Fracture network interpretation and information extraction

[0065] (1) Fracture network interpretation: Based on the result graph in C(3), perform low-order fracture network interpretation in 3D Move. The specific operations are as follows:

[0066] ① Import the high-definition top view of low-order fractures into 3D Move;

[0067] ②Use the Create lines function under the Model Building module in 3D Move to draw and interpret the fracture network and obtain numerical low-order fracture network data.

[0068] (2) Collection of low-level fracture information: ① Use the Create Section function under the Model Building module to create a specific section according to requirements; ② Use the To Section function in the Project function under the Model Building module to project the fracture network data information within a certain distance on both sides of the established specific section to the section; ③ Select the fracture network data projected to the section and export its plane coordinate data (X, Y) in ASCII type data.

[0069] E. Quantitative evaluation of structural deformation intensity of fault zones

[0070] (1) Quantitative identification of fracture zone width

[0071] ① Use Notepad to open the ASCII data exported in step D and copy all the information into an Excel spreadsheet. Arrange the fracture data from small to large according to the spatial coordinate X or Y value and calculate the cumulative fracture frequency (Table 1):

[0072] Where (X, Y) is the plane coordinate of the fault development point, L is the distance between the fault development point and the statistical origin (X1, Y1), and T is the cumulative frequency of the fault;

[0073] Table 1

[0074]

[0075] ② Using the data L in Table 1 as the horizontal axis (X-axis) and the cumulative fault value T as the vertical axis (Y-axis), a distance-to-fault cumulative frequency scatter plot is drawn. The location where the scatter trend slope suddenly increases can be identified as the location where the fault zone develops (a sudden increase in the trend slope indicates a clear inflection point in the scatter trend). The distance span where the trend line slope increases is the width of the fault zone, recorded as W:

[0076]

[0077] Where W is the width of the fault zone, (Xm, Ym) and (Xn, Yn) are the plane coordinates of the fault data points on both sides of the slope increasing area.

[0078] (2) Quantitative reading of the vertical fault distance of the fault zone

[0079] Based on the plane coordinates (X and Y) of the fault zone development point obtained in step E(1), the spatial coordinates (X, Y, Z) of the upper and lower walls of the fault zone are read from the three-dimensional model of the target stratum in step C(2). The difference in the spatial coordinates Z between the upper and lower walls is the vertical throw of the fault zone, denoted as P. In this way, the vertical throws of multiple fault zones in step E(1) are obtained.

[0080] (3) Quantitative calculation of fracture density within the fault zone

[0081] Based on the statistical data of the cumulative frequency of fractures in step E(1), the fracture density D is calculated using the following formula:

[0082]

[0083] Where D is the fracture density, Tm and Tn are the cumulative fracture frequencies when counting the fractures on both sides of the fracture zone, and W is the width of the fracture zone. Thus, the fracture density within the multiple fracture zones in step 5 (1) is obtained.

[0084] (4) Quantitative evaluation of the structural deformation intensity of the fault zone

[0085] ① Repeat steps D(2) and E(1)(2)(3) to collect and calculate the fault zone data of multiple survey lines to obtain the structural parameter values of multiple fault zone development points (i.e., fault zone width, vertical fault throw, and fault density within the zone).

[0086] ② Based on the structural parameter values of the fault zone development point obtained in step E(4)①, quantitatively evaluate the structural deformation intensity characteristic value S of the fault zone:

[0087] S∈(0,1]; i=1,2,3,4,…;

[0088] Where S is the characteristic value of tectonic deformation intensity; Wmax is the maximum width of the fault zone, Wi is the width of the fault zone at each fault zone development point; Dmax is the maximum fault density within the fault zone, Di is the fault density within the fault zone at each fault zone development point; Pmax is the maximum fault throw of the fault zone, and Pi is the fault throw of the fault zone at each fault zone development point. The characteristic value for low tectonic deformation intensity is S∈(0,0.01], the characteristic value for medium tectonic deformation intensity is S∈(0.01,0.1], and the characteristic value for strong tectonic deformation intensity is S∈(0.1,1].

[0089] Example 2

[0090] Based on the method in Example 1, this application provides a specific embodiment of a method for implementing multi-tectonic parameter fusion based on seismic information to quantitatively evaluate the structural deformation intensity of a fault zone using data from the Luzhou area in southern Sichuan. The specific method is as follows:

[0091] 1. Data Preparation

[0092] ① 3D seismic data of Luzhou area in southern Sichuan (SEGY format);

[0093] ② Stratigraphic data of the Wufeng Formation in Luzhou area, southern Sichuan (ASCII format).

[0094] 2. Data Import

[0095] Import data into Petrel software:

[0096] (1) Import the 3D seismic data (SEGY format) of the Luzhou area in southern Sichuan into the Petrel software:

[0097] The specific method is as follows: right-click the Input workspace, select import file, select SEGYseismic data as the file type, select the 3D seismic data of the Luzhou area in southern Sichuan and open it, and set the parameters in the Input data window as follows: select 3D seismic for Type, select Seismic (default) for Template, select Elevation depth for Domain, leave other parameters as default, and finally click OK.

[0098] (2) Import the stratigraphic data (ASCII format) of the Wufeng Formation in the Luzhou area of southern Sichuan into the Petrel software:

[0099] The specific method is as follows: right-click the Input workspace, select import file, select General lines / points as the file type, select the Wufeng Formation stratigraphic data in the Luzhou area of southern Sichuan and open it, and set the parameters of the Import lines / points window as follows: set Number of header line to 1, check Read as point, and leave other parameters as default. Finally, click OK.

[0100] The final three-dimensional display window of the work area is as follows Figure 1 As shown, the 3D display window displays the imported 3D seismic data and the 3D stratigraphic data of the Wufeng Formation.

[0101] 3. Data Processing

[0102] (1) Processing 3D seismic data using seismic ant tracking technology in Petrel software:

[0103] In the top bar of the Petrel software, click Seismic Interpretation to enter the seismic interpretation module. Click Volume attributes in this module and perform the following operations in the pop-up window:

[0104] ① Select Structural smoothing as the Attribute, and add the Luzhou area earthquake data LU201_202 to the Input workspace. Click OK to output the LU201_202 [structural smoothing] data volume.

[0105] ②Change Attribute to Chaos, add the data body LU201_202[structural smoothing] to the input workspace, and finally output the LU201_202[structural smoothing][Chaos] data body;

[0106] ③Change Attribute to 3D Edge Enhancement, and add the data volume LU201_202[structuralsmoothing][Chaos] to the input workspace, and finally output the LU201_202[structural smoothing][Chaos][3D Edge Enhancement] data volume;

[0107] ④Change Attribute to Ant tracking and add the data body LU201_202[structuralsmoothing][Chaos][3D Edge Enhancement] to the Input workspace. Finally, output the LU201_202[structural smoothing][Chaos][3D Edge Enhancement][Ant tracking] data body.

[0108] Other parameters in the process are default.

[0109] (2) Use Petrel software to establish a three-dimensional stratigraphic model of the Wufeng Formation:

[0110] In the top bar of the Petrel software, click Structural Modeling to enter the structural modeling module. Click Make surface in this module and perform the following operations in the pop-up window:

[0111] Add the stratigraphic data of the Wufeng Formation in Luzhou, southern Sichuan (ASCII format) to the Input workspace, name the result surface "surface" (or any other full English name), select "Automatic (from input data / boundary)" for Grid size and position, and leave other parameters as default. Click OK to output the 3D stratigraphic model of the Wufeng Formation named "surface" (e.g. Figure 2 shown).

[0112] (3) Identification of low-order faults in the Wufeng Formation:

[0113] Based on the ant body tracking results of 3D seismic volume, the low-order faults of the Wufeng Formation are identified. The specific steps are as follows:

[0114] In the Petrel top bar, click Seismic Interpretation to enter the Seismic Interpretation module. Click Surface attributes in the Attributes function under this module and perform the following operations in the pop-up window:

[0115] Select the RMS amplitude processing method, add the result data volume LU201_202[structuralsmoothing][Chaos][3D Edge Enhancement][Ant tracking] from step 3 (1) to the Input workspace, and add the Wufeng Formation 3D stratigraphic model surface created in step 3 (2) to the Add to surface workspace. All other parameters are default, click OK to output the RMS amplitude sub-layer of the surface, and the low-order faults are displayed in blue. Capture the high-definition top view and save it as Fault.jpg (e.g. Figure 3 shown).

[0116] 4. Interpretation of the Wufeng Formation Fault Network and Information Extraction in the Luzhou Area of Southern Sichuan

[0117] (1) Interpretation of low-order faults in the Wufeng Formation:

[0118] Based on the result Fault.jpg ( Figure 3 ), and interpret the low-order fracture network in 3D Move. The specific operations are as follows:

[0119] ① Click Model Building in the top bar of 3D Move to enter the modeling module, click Image in the Create Shapes function, then select Horizontal Referenced for Image Type and Top Left and Bottom Right for Define Location Using. Adjust the East (X) and North (Y) in Top Left and Bottom Right to make the work area size match the Luzhou area in southern Sichuan. Click Create Image, select Fault.jpg in the pop-up window and import it. The result is as follows Figure 4 shown.

[0120] ② Click Model Building in the top bar of 3D Move to enter the modeling module, click Fault in the Create lines function, then select No Snap in the Creation Mode window, check Sinuous, select AlongLength in Resampling, and leave the other parameters as default. Use the mouse to drag Fault.jpg ( Figure 4 ) is depicted and interpreted to obtain the numerical low-order fault network in Luzhou area of southern Sichuan ( Figure 5 ) data cloud and named it Fault.

[0121] (2) Quantitative information collection of low-order fractures

[0122] ① Click Model Building, Create Section, and Section in sequence to enter the window for generating a specific section perpendicular to the fault zone. Select Vertical Section for Principal Section Orientation. Generate the corresponding section (e.g. Figure 6 Then, click the Create Section button to generate the section and name it Section of fault zone.

[0123] ② Click Model Building, Project and To Section in sequence to enter the data projection function window. Select Project Data on Selected Section as the section of fault zone → Select AnyObjections → Set Project Data Within to 10m (this parameter depends on the size of the work area, and the value can be appropriately reduced for a small work area) → Select Normal to Section for Projection Method → Add the low-order fault network data cloud Fault in Objects to be Projected. Click Apply to project the low-order faults within 10m along the section direction and lateral direction of the Section of fault zone to the Section of fault zone section. The projection result is as follows: Figure 7 As shown, the red × is the data point projected onto the cross section.

[0124] ③ Select all the fault projection data points, right-click, and select ASCII in the Export As dialog box. The Data Export window will pop up, and you can export the (X, Y) coordinate data. Since the Y coordinate values for this survey line are the same, only the X coordinate data will be exported. Name the file X of fault.dat.

[0125] 5. Quantitative evaluation of the structural deformation intensity of the Wufeng Formation fault zone in the Luzhou area of southern Sichuan

[0126] (1) Quantitative identification of fracture zone width

[0127] ① Open the Xoffault.dat file with Notepad, copy all the data and paste it into Excel to generate the Xoffault.xlsx file (a total of 189 data points, only 24 data points are shown in Table 2 for demonstration purposes).

[0128] Among them, the distance L i =(X i -18516205) / 1000km; T is the cumulative value of the fracture frequency.

[0129] Table 2 Fracture sampling data table

[0130]

[0131]

[0132] ② With distance L as the X-axis and cumulative frequency of fractures T as the Y-axis, draw a distance-cumulative frequency scatter plot. The location where the slope suddenly changes can be identified as a fracture zone. Figure 8 As shown, the slope suddenly becomes larger ( Figure 8 The red dotted line in the figure shows the developed fault zones, and five fault zones can be identified here; Figure 8 The difference in distance between the sample points on both sides of the red dotted line is the width of the fault zone, denoted as W:

[0133]

[0134] Where W is the width of the fault zone, (Xm, Ym) and (Xn, Yn) are the plane coordinates of the sample points on both sides of the slope increasing area. Based on this, the widths of the five fault zones are obtained (as shown in Table 3)

[0135] Table 3 Statistics of fracture zone width

[0136] Fault zone number 1 2 3 4 5 Width / km 1.5 3.6 0.5 0.5 0.3

[0137] (2) Quantitative reading of the vertical fault distance of the fault zone

[0138] Based on the plane position coordinates of the fault zone identified in step 5 (1), the spatial coordinates (X, Y, Z) of the upper and lower plates of the fault zone are read from the three-dimensional geological model of the Wufeng Formation established in step 3 (2). The difference between the vertical coordinates Z of the upper and lower plates is the vertical fault throw of the fault zone, denoted as P. The vertical fault throws of the five fault zones in step 5 (1) are thus obtained (as shown in Table 4)

[0139] Table 4 Statistics of vertical fault distance

[0140] Fault zone number 1 2 3 4 5 Break distance / m 80.7 129.8 95.4 200 115.3

[0141] (3) Quantitative calculation of fracture density within the fault zone

[0142] Based on the cumulative fracture frequency statistics in step 5 (1), the fracture density D is calculated using the following formula:

[0143]

[0144] Where D is the fracture density, Tm and Tn are the cumulative fracture frequencies when counting the fractures on both sides of the fracture zone, and W is the fracture width. Based on this, the fracture density within the five fracture zones in step 5 (1) is obtained (as shown in Table 5).

[0145] Table 5 Statistics of fault development density within the fault zone

[0146] Fault zone number 1 2 3 4 5 Density / (individuals / km) 16 27 11 12 12

[0147] (4) Quantitative evaluation of the structural deformation intensity of the fault zone

[0148] ① Repeat steps 4 (2) and 5 (1) (2) (3) to measure the 7 lines of the Wufeng Formation in Luzhou area of southern Sichuan ( Figure 9 ) fault zone data were collected and calculated to obtain the structural parameter values of 40 fault zone development points in the Wufeng Formation in Luzhou area of southern Sichuan. Here, 19 fault point data are selected for display (the locations of the fault points are shown in Figure 10 The structural parameters are the width of the fault zone W, the vertical fault throw P, and the development density D (as shown in Table 6).

[0149] Table 6 Structural parameter values of the development points of the Wufeng Formation fault zone in Luzhou area, southern Sichuan

[0150] Breakpoint number Width / km Frequency / number Break distance / m 2 3.6 27 129.8 3 0.5 11 95.4 4 0.5 12 200 6 1.5 21 145.8 7 0.7 10 247.2 8 2.4 34 170.5 15 0.1 4 203 18 0.1 8 52.7 19 0.6 15 51.4 23 0.3 7 71.8 24 0.4 13 27.8 25 0.3 9 69.8 26 1.6 18 152.5 30 0.2 6 71 33 0.7 20 27.2 38 0.2 8 63.3 39 0.2 8 44.8 40 0.3 9 73.2

[0151] ② Based on the structural parameter values of the fault zone development points obtained in step 5 (4) ① above, quantitatively evaluate the structural deformation intensity characteristic values S of the 18 fault zone development points:

[0152] S∈(0,1]; i=1,2,3,4,…;

[0153] Where S is the characteristic value of tectonic deformation intensity; Wmax is the maximum width of the fault zone, and Wi is the width of the fault zone at each fault zone development point; Dmax is the maximum fracture density within the fault zone, and Di is the fracture density within the fault zone at each fault zone development point; Pmax is the maximum fault throw of the fault zone, and Pi is the fault throw of each fault zone development point. The calculation results are shown in Table 7. The characteristic value for low tectonic deformation intensity is S∈(0,0.01], the characteristic value for medium tectonic deformation intensity is S∈(0.01,0.1], and the characteristic value for strong tectonic deformation intensity is S∈(0.1,1].

[0154] Table 7 Structural parameter values and structural deformation intensity characteristic values of the Wufeng Formation fault zone development points in the Luzhou area

[0155] Breakpoint number Width / km Frequency / number Break distance / m Deformation strength characteristic value 2 3.6 27 129.8 0.4170 3 0.5 11 95.4 0.0173 4 0.5 12 200 0.0397 6 1.5 21 145.8 0.1518 7 0.7 10 247.2 0.0572 8 2.4 34 170.5 0.4598 15 0.1 4 203 0.0027 18 0.1 8 52.7 0.0014 19 0.6 15 51.4 0.0153 23 0.3 7 71.8 0.0050 24 0.4 13 27.8 0.0048 25 0.3 9 69.8 0.0062 26 1.6 18 152.5 0.1452 30 0.2 6 71 0.0028 33 0.7 20 27.2 0.0126 38 0.2 8 63.3 0.0033 39 0.2 8 44.8 0.0024 40 0.3 9 73.2 0.0065

[0156] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information, characterized in that: The steps include: S1 imports the 3D seismic data and target stratum data of the work area into Petrel software respectively; S2 builds a 3D model of the target stratum in Petrel software and uses seismic ant tracking technology to perform 3D seismic volume attribute analysis on the 3D seismic data. The 3D seismic volume attribute analysis result data volume is then superimposed with the 3D model of the target stratum to identify low-order faults in the target stratum and capture a high-definition bird's-eye view. S3 imports the high-definition top view obtained in step S2 into 3D Move software and interprets the low-order fracture network; collects low-order fracture information data, and exports ASCII type data; S4 opens the exported ASCII data with Notepad and copies all the information into an Excel spreadsheet. The fracture data are arranged from small to large according to the spatial coordinate values, and the cumulative fracture frequency is calculated. A scatter plot of distance-cumulative fracture frequency is drawn. Combined with the three-dimensional model of the target stratum, the width of the fault zone is quantitatively identified, the vertical fault throw of the fault zone is quantitatively read, the fault density within the fault zone is quantitatively calculated, and the structural deformation intensity of the fault zone is quantitatively evaluated; The specific method for quantitatively evaluating the structural deformation intensity of the fault zone is: ① Collect and calculate the fault zone data of multiple survey lines to obtain the structural parameter values of multiple fault zone development points, namely the fault zone width, vertical fault throw and fault density within the zone; ② Based on the structural parameter values of the fault zone development points, quantitatively evaluate the characteristic value S of the structural deformation intensity of the fault zone: , S∈(0, 1]; i = 1, 2, 3, 4, …; Where S is the characteristic value of tectonic deformation intensity; Wmax is the maximum width of the fault zone, Wi is the width of the fault zone at each fault zone development point; Dmax is the maximum fault density within the fault zone, Di is the fault density within the fault zone at each fault zone development point; Pmax is the maximum fault throw of the fault zone, Pi is the fault throw of the fault zone at each fault zone development point; the characteristic value of low tectonic deformation intensity is S∈(0,0.01], the characteristic value of medium tectonic deformation intensity is S∈(0.01, 0.1], and the characteristic value of strong tectonic deformation intensity is S∈(0.1,1].

2. The method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information according to claim 1, characterized in that: In step S2, the specific method of superimposing the 3D seismic attribute analysis result data volume with the target stratum 3D model is to use the RMS amplitude algorithm in the Surface Attribute analysis technology under the Seismic Interpretation module in Petrel to superimpose the 3D seismic attribute analysis result data volume with the target stratum 3D model.

3. The method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information according to claim 1, characterized in that: In step S3, the specific interpretation method is: using the Createlines function under the Model Building module in 3D Move to draw and interpret the fracture network to obtain numerical low-order fracture network data.

4. The method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information according to claim 1, characterized in that: In step S3, the specific method for collecting low-order fracture information data is: ①Use the Create Section function in the Model Building module to create a specific section according to your needs; ②Use the To Section function in the Project function under the Model Building module to project the fracture network data information within a certain distance on both sides of the established specific section to the section; ③ Select the fracture network data projected onto the section and export it as ASCII data.

5. The method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information according to claim 1, characterized in that: The specific method for drawing the distance-fracture cumulative frequency scatter plot in step S4 is: ① Use Notepad to open the ASCII data exported in step D and copy all the information into an Excel spreadsheet. Arrange the fracture data from small to large according to the spatial coordinate X or Y value and calculate the cumulative fracture frequency. ② Using data L as the horizontal axis (X-axis) and the cumulative value of faults T as the vertical axis (Y-axis), draw a distance-fracture cumulative frequency scatter plot. The location where the slope of the scatter trend suddenly increases can be identified as the location where the fault zone develops; Where (X, Y) is the plane coordinate of the fault development point, L is the distance between the fault development point and the statistical origin (X1, Y1), and T is the cumulative frequency of the fault; Li= ; Ti=i; (Xi, Yi) is the coordinate of the fault development position, where i is 1, 2, 3,… 6. The method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information according to claim 5, characterized in that: The specific method for quantitatively identifying the width of the fault zone in step S4 is as follows: based on the distance-fracture cumulative frequency scatter plot, the distance span where the slope of the trend line increases is the width of the fault zone, which is recorded as W: Where W is the width of the fault zone, (Xm, Ym) and (Xn, Yn) are the plane coordinates of the fault data points on both sides of the slope increasing area.

7. The method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information according to claim 6, characterized in that: The specific method for quantitatively reading the vertical fault distance of the fault zone in step S4 is: Based on the plane coordinates of the fault zone development point, the spatial coordinates (X, Y, Z) of the upper and lower walls of the fault zone are read from the three-dimensional model of the target stratum obtained in step S2. The difference between the spatial coordinates Z of the upper and lower walls is the vertical fault throw of the fault zone, which is recorded as P.

8. The method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information according to claim 7, characterized in that: The specific method for quantitatively calculating the fracture density within the fracture zone in step S4 is: Based on the obtained cumulative fracture frequency, the fracture density D is calculated. The specific formula is: Where D is the fault density, Tm and Tn are the cumulative fault frequencies when counting on both sides of the fault zone, and W is the width of the fault zone.

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