Method for quantitatively evaluating structural deformation strength of fault zone based on seismic information

Abstract

The invention relates to a method for quantitatively evaluating the structural deformation strength of a fault zone based on seismic information. According to the method, the multi-scale fracture developed in the underground deep target layer can be effectively recognized, and the precision of recognizing the fault zone and limiting the width of the fault zone is effectively improved. In the extraction process of the three-dimensional seismic information, the three-dimensional fracture information is subjected to data vectorization and extraction, and the effect of batch data processing is achieved. Meanwhile, the method is multi-scale during batch processing and data extraction, so that the cost is effectively saved, and the precision is improved. Finally, the method achieves the quantitative evaluation of the deformation strength of the fault zone structure through the fusion of the three structure parameters of the width of the fault zone, the vertical fault displacement and the in-zone fracture density.

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] As an important structural feature in the earth's crust, the precise identification of the internal structure of the fault zone is of great significance for oil and gas exploration, earthquake prediction and engineering stability evaluation. In recent years, domestic and foreign scholars have developed a variety of fault zone structure identification methods through the integration of multidisciplinary technologies, such as geological profile method, remote sensing image analysis method, geophysical method and numerical simulation method.

[0003] The geological profile method mainly draws geological profiles through geological surveys to identify the morphology, scale, occurrence and other characteristics of the fault zone. Its advantage is that it is intuitive and can directly obtain field data, but it is difficult to carry out in some areas due to the limitations of topography and landforms, and the workload is large. The remote sensing image analysis method uses satellite images or aerial images to identify fault zones through image interpretation and ground feature classification. This method has a wide coverage and is suitable for areas where it is difficult to conduct field surveys, but due to resolution limitations, the ability to identify fine fault zones is weak, and the interpretation results are affected by image quality and interpretation level. Geophysical methods (such as seismic exploration, electromagnetic measurement, etc.) use physical detection methods to identify fault zones and determine the distribution of fault zones through features such as seismic wave propagation anomalies and electromagnetic field changes. This method can detect fault zones deep underground and obtain three-dimensional spatial information, but the equipment cost is high, the technical requirements are high, and the accuracy is limited by the geophysical technology itself. The numerical simulation method simulates the formation process of the fault zone by establishing a geological model to identify its distribution law and characteristics. This method can simulate the dynamic evolution of fault zones and predict the existence of unknown fault zones, but the model building process is complicated, requires a large amount of geological data support, and the simulation results depend on the accuracy of the model.

[0004] In addition, patents CN118732035A and CN110749924A respectively disclose methods for identifying fault zones by calculating coherence volumes and processing and analyzing fault enhancement data volumes on seismic information. However, it can only roughly identify the development location of the fault zone, and is still limited in limiting the width of the fault zone. Based on this, domestic and foreign scholars obtain fault information through field geological outcrop exploration, and then identify and analyze the width of the fault zone through mathematical statistical analysis (Genter et al., 1997; Berg and Skar, et al., 2005; Choi et al., 2016). Since the equal-width zone is used as the data sampling area in the data analysis process, its recognition accuracy is limited by the zone width, and it is only an analysis method for the visible fault zone on the surface. 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 formation data of the work area into the Petrel software respectively;

[0007] S2 builds a 3D model of the target stratum in the Petrel software, and uses seismic ant volume tracking technology to perform 3D seismic volume attribute analysis on the 3D seismic data; then the 3D seismic volume attribute analysis result data volume is superimposed with the 3D model of the target stratum to identify the low-order faults of the target stratum and capture a high-definition top 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 used Notepad to open the exported ASCII data and copied all the information to an Excel table. The fracture data were arranged from small to large according to the spatial coordinate values, and the cumulative fracture frequency was calculated. A scatter plot of distance-cumulative fracture frequency was 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 body 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 body with the target stratum 3D model.

[0012] On the basis of the above scheme, in step S3, the specific method of interpretation is: using the Create lines function under the ModelBuilding module in 3D Move, the fracture network is drawn and interpreted 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:

[0014] ①Use the Create Section function under the Model Building module to create specific sections according to requirements;

[0015] ②Use To Section 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 to the section and export it as ASCII type data.

[0017] Based on the above scheme, the specific method of 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 to an Excel table. 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 With 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] On the basis of the above scheme, the specific method for quantitatively identifying the width of the fault zone in step S4 is: according to the distance-fracture cumulative frequency scatter plot drawn, the distance span where the slope of the trend line increases is the width of the fault zone, 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 development point of the fault zone, 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 distance of the fault zone, denoted 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] Among them, D is the fault development density, Tm and Tn are the cumulative frequency values ​​of faults when they are counted on both sides of the fault zone, and W is the width of the fault zone.

[0031] On the basis of the above scheme, the specific method for quantitatively evaluating the structural deformation strength 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 width of the fault zone, the vertical fault throw and the 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 structural 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 distance of the fault zone, Pi is the fault distance of the fault zone at each fault zone development point; the characteristic value of low structural deformation intensity is S∈(0,0.01], the characteristic value of medium structural deformation intensity is S∈(0.01,0.1], and the characteristic value of strong structural 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 three-dimensional modeling software to generate a three-dimensional stereoscopic model, and obtains a high-definition top view of low-order faults in the target stratum of the work area by processing and extracting the three-dimensional seismic information; then, by interpreting the high-definition top view of the low-order faults and combining the spatial coordinates of the three-dimensional stereoscopic model, the width, vertical fault throw and fracture density of the fault zone in the target stratum are obtained, and 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, and effectively improve the accuracy of identifying fault zones and limiting the width of fault zones. In the process of extracting three-dimensional seismic information, the effect of batch processing of data is achieved by vectorizing and extracting three-dimensional fault information. 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 realizes the quantitative evaluation of the structural deformation intensity of the fault zone by integrating the three structural parameters of the width of the fault zone, the vertical fault distance 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

[0040] Figure 1 This is a diagram showing the effect of the data being imported 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 the present 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 a 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 a rendering of the low-order fracture network obtained after interpretation in step 4 of Example 2 of the present application;

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

[0046] Figure 7 The projection effect diagram generated in step 4 of Example 2 of the present application;

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

[0048] Fig. 9 It is a plan distribution diagram of multiple measurement lines in step 5 of Example 2 of this application;

[0049] Fig.10 This is the plan distribution diagram 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 described embodiments 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 creative work 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 the 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 overlay the 3D seismic volume attribute analysis result data 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), low-order fracture network interpretation is performed 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 fault information: ① Use the Create Section function in the Model Building module to create a specific section according to requirements; ② Use the To Section function in the Project function in 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 the structural deformation intensity of the fault zone

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

[0071] ① Use Notepad to open the ASCII data exported in step D, and copy all the information to an Excel table. 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 value of the fault T as the vertical axis (Y axis), a distance-fracture 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 (the trend slope suddenly increases, and an obvious turning point can be observed in the scatter trend), and the distance span where the trend line slope increases is the width of the fault zone development, 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 plates of the fault zone are read in the three-dimensional model of the target stratum in step C(2). The difference between the spatial coordinates Z of the upper and lower plates is the vertical fault throw of the fault zone, denoted as P. Thus, the vertical fault throws of multiple fault zones in step E(1) are obtained.

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

[0081] Based on the cumulative fracture frequency statistics 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 two 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] Among them, S is the characteristic value of structural 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 distance of the fault zone, Pi is the fault distance of the fault zone at each fault zone development point. The characteristic value of low structural deformation intensity is S∈(0,0.01], the characteristic value of medium structural deformation intensity is S∈(0.01,0.1], and the characteristic value of strong structural 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 realizing multi-structural parameter fusion based on seismic information to quantitatively evaluate the structural deformation strength of the 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 Luzhou area in southern Sichuan into 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 Luzhou area in southern Sichuan and open it, and set the parameters of the Input data window as follows: Select 3D seismic for Type, Seismic (default) for Template, Elevation depth for Domain, leave other parameters as default, and finally click OK.

[0098] (2) Import the stratigraphic data of the Wufeng Formation in Luzhou, southern Sichuan (ASCII format) 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 Luzhou area in 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, and 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 Wufeng Formation 3D stratigraphic data.

[0101] 3. Data Processing

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

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

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

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

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

[0107] ④Change Attribute to Ant tracking, and add the data body LU201_202[structuralsmoothing][Chaos][3D Edge Enhancement] to the Input workspace, and 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] Click Structural Modeling in the top bar of the Petrel software to enter the structural modeling module. Click Make surface in the 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 as 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 results of ant body tracking of 3D seismic volume, the low-order faults of Wufeng Formation are identified. The specific steps are as follows:

[0114] Click Seismic Interpretation in the top bar of Petrel to enter the structural 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] of step 3 (1) to the Input workspace, and add the surface of the Wufeng Formation 3D stratigraphic model established in step 3 (2) to the Add to surface workspace. Other parameters are set to 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 (such as Figure 3 shown).

[0116] 4. Interpretation of the Wufeng Formation Fault Network and Its Information Extraction in Luzhou, 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; select Top Left and Bottom Right for Define Location Using; adjust 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 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 turn to enter the function window for generating a specific section perpendicular to the fault zone. Select Vertical Section for Principal Section Orientation. Generate the corresponding section (such as 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. Project Data on Selected Section Select 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 in 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 where the fracture is projected onto the cross section.

[0124] ③ Select all the fault projection data points, right-click and select the ASCII type in Export As, a data export window pops up, and the (X, Y) coordinate data is exported. Since the Y coordinate value of this survey line is the same, only the X coordinate data needs to be exported, and the file is named X of fault.dat.

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

[0126] (1) Quantitative identification of fault 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, Table 2 only shows 24 data points for demonstration).

[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 Take distance L as the X-axis and cumulative frequency of faults T as the Y-axis. Draw a distance-cumulative frequency scatter plot. The location where the slope suddenly changes can be identified as the fault zone. Figure 8 As shown, the slope suddenly increases ( Figure 8 The red dotted line in the figure shows the developed fault zones, and 5 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 increase 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 in 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 the fracture density within the fault zone

[0142] Based on the cumulative frequency statistics of fractures 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 the fractures are counted on both sides of the fracture zone, and W is the width of the fracture zone. 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 density within the fault zone

[0146] Fault zone number 1 2 3 4 5 Density / (unit / 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 ( Fig. 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 Fig.10 Purple numbers and dots in the middle), and the structural parameter types are fault zone width W, vertical fault throw P and 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] Among them, S is the characteristic value of structural 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 distance of the fault zone, Pi is the fault distance of the fault zone at each fault zone development point. The calculation results are shown in Table 7, where the characteristic value of low structural deformation intensity is S∈(0,0.01], the characteristic value of medium structural deformation intensity is S∈(0.01,0.1], and the characteristic value of strong structural 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 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 only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope 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 formation data of the work area into the Petrel software respectively; S2 builds a 3D model of the target stratum in the Petrel software, and uses seismic ant volume tracking technology to perform 3D seismic volume attribute analysis on the 3D seismic data; then the 3D seismic volume attribute analysis result data volume is superimposed with the 3D model of the target stratum to identify the low-order faults of the target stratum and capture a high-definition top 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 used Notepad to open the exported ASCII data and copied all the information to an Excel table. The fracture data were arranged from small to large according to the spatial coordinate values, and the cumulative fracture frequency was calculated. A scatter plot of distance-cumulative fracture frequency was 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.

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, a specific method for superimposing the three-dimensional seismic body attribute analysis result data body with the target stratum three-dimensional model is to use the RMS amplitude algorithm in the Surface Attribute analysis technology under the Seismic Interpretation module in Petrel to superimpose the three-dimensional seismic body attribute analysis result data body with the target stratum three-dimensional 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 method of interpretation is: using the Createlines function under the Model Building module in 3D Move, the fracture network is drawn and interpreted 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 sequence fracture information data is: ①Use the Create Section function under the Model Building module to create specific sections according to requirements; ②Use To Section 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 it as ASCII type 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 of 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 to an Excel table. Arrange the fracture data from small to large according to the spatial coordinate X or Y value, and calculate the cumulative fracture frequency; ② With 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; 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; 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: according to the distance-fracture cumulative frequency scatter plot drawn, 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 development point of the fault zone, 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 distance of the fault zone, denoted 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: Among them, D is the fault development density, Tm and Tn are the cumulative frequency values ​​of faults when they are counted on both sides of the fault zone, and W is the width of the fault zone.

9. The method for quantitatively evaluating the structural deformation intensity of a fault zone based on seismic information according to claim 8, characterized in that: The specific method for quantitatively evaluating the structural deformation strength of the fault zone in step S4 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 width of the fault zone, the vertical fault throw and the 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,…; Among them, S is the characteristic value of structural 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 distance of the fault zone, Pi is the fault distance of the fault zone at each fault zone development point; the characteristic value of low structural deformation intensity is S∈(0,0.01], the characteristic value of medium structural deformation intensity is S∈(0.01,0.1], and the characteristic value of strong structural deformation intensity is S∈(0.1,1].

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