A plane identification method for extrusion anticline deformation intensity

Abstract

A plane identification method for deformation intensity of extrusion anticline, the specific steps comprising: 1: obtaining the basic data of the study area, and establishing the isochronous stratigraphic framework; 2: determining the evaluation index representing the deformation intensity of the extrusion anticline, sampling along the seismic line in the study area for each index determined, and obtaining the measured values of each index at each sampling point; 3: performing standardization scoring processing on the obtained measured values of each index to obtain dimensionless scoring values G, A and U, and constructing a comprehensive deformation index; 4: establishing a function between the structural shortening amount S and the comprehensive deformation index Fd; 5: taking the coordinates of each sampling point and the corresponding Fd value as data points, performing gridding interpolation to obtain the continuous distribution data body of the Fd value of the entire study area, and generating a plane distribution map of the deformation intensity of the extrusion anticline; 6: drawing the boundaries of different deformation intensity partitions on the plane distribution map, and outputting a partition result map.

Description

Technical Field

[0001] This invention relates to the field of geological exploration and structural geological analysis technology, specifically to a planar identification method for the deformation strength of an anticline. Background Technology

[0002] Compressional anticlines are a common structural pattern formed by the compression, contraction, and folding deformation of strata under compressional tectonic settings. They are widely distributed in foreland thrust belts of orogenic belts and inversion tectonic zones within basins. The deformation intensity of compressional anticlines (i.e., the folding amplitude, shortening, and internal fracturing degree of the strata) directly determines their effectiveness as hydrocarbon traps—too weak deformation results in small trap size and limited reservoir space, while too strong deformation easily leads to the development of fracture systems that destroy the integrity of the trap. Simultaneously, deformation intensity also affects the degree of development of seismic geological hazards. Therefore, quantitatively identifying the planar distribution of deformation intensity in compressional anticlines is of great significance for the selection of hydrocarbon exploration targets, trap evaluation, and engineering geological stability assessment.

[0003] Currently, methods for characterizing the deformation intensity of compression anticlines mainly include methods for calculating tectonic shortening, methods for measuring the rate of change in the thickness of growing strata, and methods for analyzing fault-related folds. However, existing methods lack a comprehensive approach that can systematically identify and characterize the deformation intensity of compression anticlines on a plane by integrating multiple quantitative indicators. Most methods are limited to single-section analysis or qualitative description, making it difficult to achieve a continuous, quantitative, and visual representation of deformation intensity on a plane. Summary of the Invention

[0004] I. Technical problems to be solved This invention addresses the shortcomings of existing technologies by proposing a method that utilizes standardized scoring, constructs a comprehensive deformation index including coupling and nonlinear terms, and employs entropy weights. The method employs steps such as grey relational combination weighting and multivariate regression to achieve planar identification of deformation intensity and planar identification of extrusion anticline deformation intensity in different regions.

[0005] II. Specific Technical Solutions A planar identification method for the deformation strength of an extrusion anticline, comprising the following steps: Step 1: Acquire basic data for the study area, including two-dimensional or three-dimensional seismic data volumes, drilling data and well logging data for the study area, complete the interpretation of key stratigraphic interfaces and faults in the depth domain seismic profile, and establish an isochronous stratigraphic framework; Step 2: Determine the evaluation index characterizing the deformation intensity of the compression anticline. The evaluation index includes the rate of change of the thickness of the growing strata, the dip angle of the strata, and the uplift amplitude of the anticline. For each determined index, sampling is carried out along the seismic survey line in the study area to obtain the measured values ​​of each index at each sampling point. Step 3: Standardize and assign scores to the measured values ​​of each indicator to obtain dimensionless scores G, A, and U, and construct a comprehensive deformation index; Step 4: Determine the weights of each evaluation index using a combination of entropy weighting and grey relational analysis, and establish a functional relationship between the shortening amount S and the comprehensive deformation index Fd: S = a + b × Fd, where a and b are regression coefficients; other regression forms, such as the power function S = c × Fd, can also be used. d This equation links the dimensionless composite index with the actual measurable structural shortening, thus verifying the effectiveness of Fd and providing a quantitative tool for subsequent engineering predictions. It should be noted that the regression on structural shortening is only used to verify the correlation between the Fd index and actual deformation strength; subsequent deformation strength zoning will still directly use Fd without the need for additional regression S-values. Step 5: Using the coordinates of each sampling point and the corresponding Fd value as data points, perform grid interpolation within the study area using the interpolation method to obtain a continuous distribution data volume of Fd values ​​for the entire study area. Based on the distribution range of Fd values, set a color mapping table to generate a plane distribution map of the deformation intensity of the extrusion anticline. Step 6: Set the deformation intensity threshold according to the Fd value, divide the study area into strong deformation zone, medium deformation zone and weak deformation zone, delineate the boundaries of different deformation intensity zones on the planar distribution map, and output the partition result map.

[0006] As a preferred option: In step three, the comprehensive deformation index is specifically: Where λ1-λ5 are coupling coefficients, satisfying λ1+λ2+λ3+λ4+λ5=1; p, q, and r are nonlinear exponents, all greater than or equal to 1; The standardized scoring process involves assigning scores of 2, 4, 6, 8, and 10 to the measured values ​​of each indicator according to preset grading intervals. The larger the measured value, the higher the corresponding score.

[0007] Geological significance of each item: Independent items , , These represent the individual contributions of stratigraphic development, stratigraphic dip angle, and uplift amplitude to deformation intensity. The square term (p=q=r=2) is introduced to simulate the "accelerated growth" characteristic of deformation intensity—geological facts show that when a certain index exceeds a certain threshold, the deformation intensity increases sharply, and linear models cannot characterize this critical effect.

[0008] Coupling terms The synergistic effect of growth strata development and dip angle. When high growth rate and high dip angle occur simultaneously, it often indicates strong syntectonic deformation, and their combined effect is greater than the sum of their independent contributions (positive coupling).

[0009] Coupling terms When high dip angles and high uplift amplitudes coexist, reflecting the strong uplift and rotation of fault-related folds, the deformation intensity will increase superlinearly.

[0010] By using nonlinear exponents and coupling terms, the comprehensive index more closely reflects the physical nature of anticline deformation, outperforming conventional linear weighted models. It should be noted that, in practical implementation, the inclusion of coupling terms can be chosen based on the geological characteristics of the study area; the scope of protection of this invention includes both cases with and without coupling terms.

[0011] As a preferred option: In step four, the weights of each evaluation index are determined by a combination of the entropy weight method and the grey relational analysis method. The specific steps are as follows: 4.1 Construct the original data matrix based on the assigned scores G, A, and U for each sampling point, and calculate the objective weight w of each indicator using the entropy weight method. e = (w e,g , w e,a, w e,u ); 4.2 Using the actual value of the shortening amount as the reference sequence and the assigned scores of each indicator as the comparison sequence, calculate the grey relational degree of each indicator, and obtain the relational degree weight w after normalization. grey = (w grey,g , w grey,a , w grey,u ); 4.3 Calculate the combined weights using the multiplicative composition formula: , i = g, a, u.

[0012] As a preferred option, the functional relationship in step four is obtained by performing linear regression on the measured sample data of the study area using SPSS software.

[0013] As a preferred method, the interpolation method in step five is either Kriging interpolation or inverse distance weighted interpolation.

[0014] As a preferred embodiment, in step six, the method for setting the deformation intensity threshold is as follows: based on the cumulative frequency curve of the Fd value in the study area, the quantile values ​​corresponding to 30% and 70% of the cumulative frequency are taken as the boundary threshold T2 between the weak deformation zone and the medium deformation zone, and the boundary threshold T1 between the medium deformation zone and the strong deformation zone, respectively, and T1>T2.

[0015] The beneficial effects of this invention are as follows: 1. The nonlinear comprehensive index better aligns with geological patterns: For the first time, a square term and a coupling term are introduced in the evaluation of the deformation strength of compression anticlines. This allows for the characterization of the synergistic amplification effect and accelerated growth characteristics between indices, improving the accuracy of the evaluation. Even in specific embodiments of this invention where the coupling term is not used (λ4=λ5=0), the square term itself is superior to linear superposition.

[0016] 2. Objective and repeatable combined weighting: The combined use of entropy weight and grey relational analysis is based entirely on data to calculate weights, eliminating subjective factors and making the method universally applicable.

[0017] 3. Decoupling of Method and Data: This patent presents a complete evaluation process (scoring → nonlinear combination → combined weighting → construction of a comprehensive index → ​​regression verification → planar interpolation → partitioning), rather than specific numerical values. In specific embodiments, λ, thresholds, etc., can be recalculated for new study areas using the same process without affecting the scope of patent protection.

[0018] 4. Computer-based implementation: All steps are algorithmized and can be embedded in geological evaluation software to achieve automated processing, which has practical industrial application value.

[0019] 5. Achieved a leap from profile to plane: The generated deformation intensity plane distribution map and zoning results provide an intuitive and effective tool for evaluating oil and gas exploration traps and assessing engineering geological stability. Attached Figure Description

[0020] Figure 1 This is a diagram showing the relationship between the rate of change of the thickness of the growing strata and the amount of tectonic shortening in this invention.

[0021] Figure 2 This is a diagram showing the relationship between stratigraphic dip angle and tectonic shortening in this invention.

[0022] Figure 3 This is a diagram showing the relationship between the anticline uplift amplitude and the structural shortening in this invention.

[0023] Figure 4 This is a graph showing the relationship between the actual structural shortening amount and the regression structural shortening amount based on Fd in this invention.

[0024] Figure 5 This is a planar partition diagram of the extrusion anticline deformation strength based on Fd in this invention. Detailed Implementation

[0025] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby providing a clearer and more explicit definition of the scope of protection of the present invention.

[0026] like Figures 1 to 5As shown: This embodiment takes the compressional anticline structure of Block A in southern Sichuan as the research object, and uses the method of the present invention to perform planar identification of the deformation strength of the anticline.

[0027] Step S1: Obtain basic data for the study area Using two-dimensional seismic data volumes, drilling data, and well logging data of the study area, we completed the interpretation of key stratigraphic interfaces and faults in the depth domain seismic profile and established an isochronous stratigraphic framework.

[0028] Step S2: Determine evaluation indicators and collect data The evaluation indicators were determined to be the rate of change of stratigraphic thickness (%), stratigraphic dip angle (°), and anticline uplift amplitude (km). Sampling was carried out along multiple survey lines in the study area, and the measured values ​​of each indicator were obtained at 19 sampling points (survey lines L1-L19), as shown in Table 1.

[0029] Scatter plots were created by comparing the measured changes in the thickness of the growing strata, the dip angle of the strata, and the amplitude of the anticline uplift with the corresponding actual tectonic shortening for each survey line (see [reference]). Figure 1 , Figure 2 , Figure 3 As can be seen from the figure, all indicators are significantly positively correlated with the actual structural shrinkage, indicating that the three selected indicators can reasonably reflect the deformation strength of the extrusion anticline.

[0030] Table 1. Statistics of Influence Parameters of Different Survey Lines on the Compression Anticline in Block A of Southern Sichuan Step S3: Standardized Scoring and Construction of Comprehensive Deformation Index (3.1) Standardized scoring: According to the scoring criteria shown in Table 2, the measured values ​​of each indicator are mapped to the scoring values ​​(2, 4, 6, 8, 10) to obtain G, A, and U.

[0031] Table 2 Single-factor scoring criteria (3.2) Construct the comprehensive deformation index Fd. In this embodiment, λ1=0.15, λ2=0.25, λ3=0.60, λ4=λ5=0 (i.e., coupling terms are not considered for now), p=q=r=2. Then: The Fd values ​​for each sampling point were calculated, and the results are shown in Table 3.

[0032] Table 3. Comprehensive Deformation Index Fd and Deformation Intensity Zones for Each Survey Line *Note: Fd=0.784 of L9 is slightly lower than the threshold of 0.785, so it is judged as a medium deformation zone. Its actual structural shortening is 5.43 km (the largest in the entire work area), which is a reasonable fluctuation at the boundary. It can be adjusted to a strong deformation zone by fine-tuning the threshold (such as taking 0.78), but this will not affect the effectiveness of the method.

[0033] Step S4: Combined weighting and regression modeling 4.1 Entropy Weight-Grey Relational Analysis Combination Weighting: Based on the scores of G, A, and U at 19 sampling points, the objective weight w is calculated using the entropy weight method. e =(0.120,0.235,0.645); The grey relational weight is calculated as w, using the actual shortening amount as the reference sequence. grey =(0.195,0.263,0.542). After multiplication and synthesis, the combined weights are obtained as w = (0.153, 0.249,0.598). This weight allocation shows that the anticline uplift amplitude (weight 0.598) has the greatest impact on the deformation intensity, which is highly consistent with geological understanding.

[0034] 4.2 Establishing a linear regression between Fd and the constructed shortening amount S: With Fd as the independent variable and the actual constructed shortening amount as the dependent variable, the regression equation is obtained: S = 1.44 + 3.45 × Fd Correlation coefficient R 2 =0.66, indicating that Fd is significantly positively correlated with the amount of tectonic shortening, verifying the effectiveness of Fd as a comprehensive index of deformation strength (see Table 4). Figure 4 It should be noted that the regression shortening amount here is only used to verify the correlation between the Fd exponent and the actual deformation strength. Subsequent deformation strength zoning will still directly use Fd, without the need to use the regression S value.

[0035] Table 4. Shortening of each survey line and regression data (based on Fd) Step S5: Planar interpolation and generation of deformation strength planar diagram Using the coordinates of each sampling point and its corresponding Fd value as data points, Kriging interpolation was performed to perform gridded interpolation, resulting in a continuous distribution data volume of Fd values ​​across the entire study area. A color mapping table was set based on the Fd value range (0-1.000) (dark red representing high Fd, blue representing low Fd), generating a planar distribution map of the extrusion anticline deformation intensity. Figure 5 ).

[0036] Step S6: Deformation strength plane partitioning and automatic identification Based on the cumulative frequency curve of the Fd value, the 30th quantile is taken as the boundary threshold between the weak deformation zone and the moderate deformation zone, T2 = 0.340, and the 70th quantile is taken as the boundary threshold between the moderate deformation zone and the strong deformation zone, T1 = 0.785. The zoning criteria are as follows: Strong deformation zone: Fd≥0.785 Medium deformation region: 0.340≤Fd<0.785 Weak deformation zone: Fd < 0.340 The deformation zoning results for each survey line are shown in the last column of Table 3. The boundaries of different deformation intensity zones are automatically drawn on the planar distribution map, and the zoning result map is output. Figure 5 ).

[0037] Method stability verification To verify the robustness of this method in terms of parameter selection, the coupling coefficients λ1, λ2, and λ3 were varied by 10% (i.e., λ1∈[0.135,0.165], λ2∈[0.225,0.275], λ3∈[0.54,0.66]), while maintaining λ1+λ2+λ3=1, and keeping λ1:λ2=3:5, λ1:λ3=1:4, and λ2:λ3=5:12. The Fd values ​​and deformation zones of each survey line were recalculated. Representative survey lines in the strong deformation zone, boundary zone, and weak deformation zone (L5, L6, L7, L9, L13, L19) were selected, and their Fd values ​​and zone results under different parameter combinations are shown in Table 5.

[0038] Table 5 Comparison of Fd values ​​and deformation zones for key survey lines under different coupling coefficients Note: (1) The original Fd of L9 is 0.784, which is slightly lower than the threshold of 0.785, and belongs to the boundary point. (2) When λ3=0.66, λ2=0.275, and λ1=0.165, the Fd value of L9 exceeds 0.785, and it becomes a strong deformation zone. The actual structural shortening of this survey line is the largest in the entire work area (5.43 km), and it should belong to the strong deformation zone. Therefore, this change is reasonable.

[0039] Overall conclusion: The core region of the strongly deformable zone (L5-L8, L14, etc.) remains stable under all parameter combinations; only the boundary points L9 and L13 exhibit fluctuations between adjacent zones under some parameter combinations, which is consistent with the objective ambiguity of geological zoning. Independently adjusting λ1, λ2, and λ3 yields consistent results, indicating that this method is insensitive to the value of the coupling coefficient and possesses good stability and versatility.

[0040] Results Verification: Comparison of the zoning results in Table 3 with geological observations shows that areas of strong deformation are mainly distributed in the core of the anticline (L5-L8, L13, L14, etc.), exhibiting strong folding and dense faulting on seismic profiles; areas of weak deformation are located on the flanks of the anticline (L2, L3, L17-L19, etc.), with gently sloping strata and no obvious structural features. The zoning results are consistent with the actual situation, proving the feasibility and accuracy of this method.

[0041] This embodiment constructs a nonlinear comprehensive deformation index and uses entropy weight-grey relational combination weighting to effectively identify and quantitatively characterize the deformation intensity of compression anticlines. This overcomes the shortcomings of single profile analysis or qualitative evaluation, reduces the risk of trap evaluation in oil and gas exploration, and reduces a large amount of manual profile interpretation work. This has positive significance for plane identification of deformation intensity of compression anticlines, selection of oil and gas exploration traps, and assessment of engineering geological stability.

[0042] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims.

Claims

1. A planar identification method for the deformation strength of an extrusion anticlinal, characterized in that, The specific steps include: Step 1: Acquire basic data for the study area, including two-dimensional or three-dimensional seismic data volumes, drilling data and well logging data for the study area, complete the interpretation of key stratigraphic interfaces and faults in the depth domain seismic profile, and establish an isochronous stratigraphic framework; Step 2: Determine the evaluation index characterizing the deformation intensity of the compression anticline. The evaluation index includes the rate of change of the thickness of the growing strata, the dip angle of the strata, and the uplift amplitude of the anticline. For each determined index, sampling is carried out along the seismic survey line in the study area to obtain the measured values ​​of each index at each sampling point. Step 3: Standardize and assign scores to the measured values ​​of each indicator to obtain dimensionless scores G, A, and U, and construct a comprehensive deformation index; Step 4: Use a combination of entropy weight method and grey relational analysis to determine the weight of each evaluation index, and establish a functional relationship between the shortening amount S and the comprehensive deformation index Fd: S=a+b×Fd, where a and b are regression coefficients; Step 5: Using the coordinates of each sampling point and the corresponding Fd value as data points, perform grid interpolation within the study area using the interpolation method to obtain a continuous distribution data volume of Fd values ​​for the entire study area. Based on the distribution range of Fd values, set a color mapping table to generate a plane distribution map of the deformation intensity of the extrusion anticline. Step 6: Set the deformation intensity threshold according to the Fd value, divide the study area into strong deformation zone, medium deformation zone and weak deformation zone, delineate the boundaries of different deformation intensity zones on the planar distribution map, and output the partition result map.

2. The planar identification method for extrusion anticlinal deformation strength according to claim 1, characterized in that: In step three, the comprehensive deformation index is specifically as follows: Where λ1-λ5 are coupling coefficients, satisfying λ1+λ2+λ3+λ4+λ5=1; p, q, and r are nonlinear exponents, all greater than or equal to 1; The standardized scoring process involves assigning scores of 2, 4, 6, 8, and 10 to the measured values ​​of each indicator according to preset grading intervals. The larger the measured value, the higher the corresponding score.

3. The planar identification method for extrusion anticlinal deformation strength according to claim 1, characterized in that: In step four, the weights of each evaluation index are determined using a combination of the entropy weight method and the grey relational analysis method. The specific steps are as follows: 4.1 Construct the original data matrix based on the assigned scores G, A, and U for each sampling point, and calculate the objective weight w of each indicator using the entropy weight method. e =(w e,g, w e,a , w e,u ); 4.2 Using the actual value of the shortening amount as the reference sequence and the assigned scores of each indicator as the comparison sequence, calculate the grey relational degree of each indicator, and obtain the relational degree weight w after normalization. grey = (w grey,g , w grey,a , w grey,u ); 4.3 Calculate the combined weights using the multiplicative composition formula: , i = g, a, u.

4. The planar identification method for the extrusion anticlinal deformation strength according to claim 1, characterized in that: The functional relationship in step four was obtained by performing linear regression on the measured sample data of the study area using SPSS software.

5. The planar identification method for the extrusion anticlinal deformation strength according to claim 1, characterized in that: The interpolation method in step five is either Kriging interpolation or inverse distance weighted interpolation.

6. The planar identification method for the extrusion anticlinal deformation strength according to claim 1, characterized in that: In step six, the method for setting the deformation intensity threshold is as follows: based on the cumulative frequency curve of the Fd value in the study area, the quantile values ​​corresponding to 30% and 70% of the cumulative frequency are taken as the boundary threshold T2 between the weak deformation zone and the medium deformation zone, and the boundary threshold T1 between the medium deformation zone and the strong deformation zone, respectively, and T1>T2.

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