A method for fracture interpretation and reservoir control potential assessment based on hydrocarbon micro-leakage alteration information

Abstract

The application discloses a kind of based on hydrocarbon microleakage alteration information's fracture interpretation and reservoir-controlling potential evaluation method, it is related to fracture structure interpretation technical field, including data acquisition and pretreatment;Interference information extraction;Hydrocarbon microleakage alteration information extraction;Alteration and fracture space correlation verification;Fracture comprehensive interpretation;Fracture reservoir-controlling potential evaluation.The method of the present application is extracted by multi-source data fusion, alteration information caused by oil and gas microleakage is accurately extracted, the correlation model of alteration information and fracture distribution is established, and the distribution of exposed and buried fractures is efficiently identified, and then multi-dimensional quantitative scoring is completed to evaluate the fracture reservoir-controlling potential.The method effectively solves the problems of low extraction accuracy, lack of correlation verification, insufficient multi-source data fusion, difficulty in identifying buried fractures, long cycle and high cost in traditional exploration technology deep alteration, and provides reliable technical support for oil and gas exploration structure analysis, reservoir-controlling rule research and target area optimization.

Description

Technical Field

[0001] This invention relates to the field of fracture structure interpretation technology, and in particular to a fracture interpretation and reservoir potential assessment method based on hydrocarbon microleakage and alteration information. Background Technology

[0002] In recent years, with the integrated application of multi-source geological geophysics and remote sensing technologies, fault research has evolved from single-method approaches to a more comprehensive and quantitative approach. Traditional fault interpretation mainly relies on seismic profiles, field geological surveys, and the identification of linear features in remote sensing images. Among these, the development of hyperspectral remote sensing technology has made it possible to identify mineral alteration information caused by surface hydrocarbon micro-leaching (such as carbonate mineralization, clay mineralization, and red bed fading). This alteration information is considered an important surface marker indicating deep faults and their hydrocarbon activity. Existing technologies have attempted to extract such alteration anomalies from remote sensing images using specific band ratios or principal component analysis, and qualitatively overlay and compare them with known geological maps or seismic interpretation results to infer fault distribution. However, existing technologies still have significant limitations in achieving accurate and systematic fault identification and scientific potential classification.

[0003] The shortcomings of existing technologies are mainly reflected in three aspects. First, there is a lack of quantitative verification of the correlation between alteration information extraction and fracture. Existing methods mostly remain at the qualitative stage of visually aligning alteration anomalies and fractures, lacking rigorous mathematical statistical models to objectively measure the spatial correlation strength and directional consistency between the two. This results in a lack of reliable quantitative basis for the indicative significance of alteration information for fractures (especially concealed fractures), leading to highly subjective interpretation results with low confidence. Second, the multi-source data fusion interpretation process is loose, and the criteria are vague. Seismic, remote sensing, field, and drilling data are often simply combined after independent interpretation, failing to establish logically rigorous cross-validation and decision-making rules within a unified spatiotemporal framework. Regarding how to comprehensively utilize multi-source evidence to accurately distinguish between exposed and concealed surface fractures, existing technologies lack clear, repeatable judgment criteria and a systematic process, resulting in insufficient completeness and reliability of the comprehensive interpretation results. Finally, the assessment of reservoir potential is one-sided and non-standardized. Existing assessment methods either overemphasize structural parameters or consider only a single geological factor, failing to construct a comprehensive index system that fully encompasses alteration correlation intensity, structural development characteristics, and hydrocarbon geological conditions. The assessment process often relies on qualitative scoring based on expert experience, with subjective and arbitrary index weights. It lacks scientific weighting methods like the analytic hierarchy process (AHP) and standardized dimensional processing for extreme values. Ultimately, it cannot produce comparable comprehensive potential scores through an objective quantitative scoring model, let alone achieve clear and visualized hierarchical output, severely weakening the guiding value of assessment results for exploration decisions. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this section, the abstract and title of the invention. Such simplifications or omissions shall not be used to limit the scope of the present invention.

[0005] In view of the problems existing in the methods of fracture interpretation and reservoir potential assessment in terms of quantitative verification of the correlation between alteration information and fracture space, the rigor of multi-source data fusion logic, and the objectivity and standardization of the comprehensive assessment system, this invention is proposed.

[0006] Therefore, the problem to be solved by this invention is how to address the shortcomings of existing evaluation systems, such as loose logic in multi-source data fusion, strong subjectivity in the verification of alteration-fracture correlation, one-sided evaluation indicators lacking objective weights, and difficulty in standardizing, classifying, and visualizing the final evaluation results, thus failing to provide a scientific and reliable basis for the selection of oil and gas exploration target areas.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides a method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information, comprising: Multi-source basic data of the study area were acquired, and the remote sensing data of the multi-source basic data were preprocessed to obtain standardized image data; Based on standardized image data, hydrocarbon micro-leakage and corrosion information is extracted to generate a map of oil and gas hydrocarbon micro-leakage and corrosion areas. Based on the alteration area map of oil and gas hydrocarbon micro-leakage, the spatial correlation between alteration and fracture was verified. The directional consistency and spatial overlap rate between the alteration area and the fracture buffer zone were verified by standard deviation ellipse analysis. Based on the fusion of multi-source basic data, comprehensive interpretation of faults is performed to determine the distribution characteristics of exposed and concealed faults on the surface. A fault-controlled reservoir potential assessment index system was constructed, a quantitative scoring model was established, and the graded results of the fault-controlled reservoir potential were output.

[0008] As a preferred embodiment of the fracture interpretation and hydrocarbon reservoir potential assessment method based on hydrocarbon microleakage and alteration information of the present invention, the classification results of fracture reservoir potential include: Based on the comparison results of the comprehensive score of the potential for mineral resource development and the preset potential classification threshold, each fault is classified into a level; when the comprehensive score of the potential for mineral resource development is greater than or equal to the first potential classification threshold, the fault is judged as a high-potential fault; when the comprehensive score of the potential for mineral resource development is less than the first potential classification threshold but greater than or equal to the second potential classification threshold, the fault is judged as a medium-potential fault; when the comprehensive score of the potential for mineral resource development is less than the second potential classification threshold, the fault is judged as a low-potential fault. The comprehensive score of the potential for mineral resources to be controlled by faults, the classification results of the potential for mineral resources to be controlled by faults, the standardized scores and weights of each indicator are associated with the corresponding fault vector elements in the surface exposed fault distribution map and the inferred map of concealed faults. Different colors are used to mark faults of different potential levels to generate a classification map of the potential for mineral resources to be controlled by faults.

[0009] As a preferred embodiment of the fracture interpretation and reservoir potential assessment method based on hydrocarbon microleakage and alteration information of the present invention, the method for obtaining the comprehensive score of reservoir potential is as follows: The extreme value standardization method was used to standardize the original values ​​of each index in the fault-controlled potential assessment index system. Meanwhile, the weight values ​​of each indicator in the fault-controlled reservoir potential assessment index system were determined using the analytic hierarchy process. A weighted summation method is used to multiply the standardized scores of each indicator by their corresponding weight values, and then sum the weighted scores of all indicators to establish a quantitative scoring model for the potential of faults to control reservoirs, thereby obtaining a comprehensive score for the potential of each fault to control reservoirs.

[0010] As a preferred embodiment of the present invention, the method for fracture interpretation and reservoir control potential assessment based on hydrocarbon micro-leakage alteration information includes: constructing a fracture reservoir control potential assessment index system based on spatial overlap rate, hydrocarbon micro-leakage alteration area map, directional consistency determination results, surface exposed fracture distribution map, hidden fracture inference map, seismic profile fracture interpretation data, and multi-source basic data. The fracture reservoir control potential assessment index system includes three categories: alteration correlation index, tectonic development index, and hydrocarbon geology index.

[0011] As a preferred embodiment of the fracture interpretation and hydrocarbon reservoir potential assessment method based on hydrocarbon micro-leakage and alteration information of this invention, the method includes: performing comprehensive fracture interpretation based on the fusion of multi-source basic data to determine the distribution characteristics of exposed and concealed surface fractures, including: Load seismic profile data, use stratigraphic distribution map as a reference, identify marker layers with continuous reflection characteristics in the seismic profile data, and determine stratigraphic attitude information based on the reflection wave group morphology of the marker layers. In seismic profile data, anomalous areas of stratigraphic reflection wave groups are searched. When a certain area shows characteristics such as reflection wave group discontinuity, reflection wave group termination, reflection wave group disorder, or abrupt amplitude change, the anomalous area is marked as a fault development location, and the attributes of the fault development location are recorded to generate seismic profile fault interpretation data. By unifying the spatial coordinates of the oil and gas hydrocarbon micro-leakage and alteration area map, seismic profile fracture interpretation data, and field geological survey data and drilling data from multi-source basic data, and transforming them to the same coordinate system, a multi-source data fusion analysis system is constructed. Based on the multi-source data fusion analysis system, the oil, gas and hydrocarbon micro-leakage alteration area map is spatially superimposed with the seismic profile fault interpretation data, and the extension characteristics of each fault in the seismic profile fault interpretation data are compared with the corresponding surface area in the oil, gas and hydrocarbon micro-leakage alteration area map. For the faults shown in the seismic profile fault interpretation data that cut through to the surface, check whether there are secondary or tertiary alteration zones in the corresponding surface area in the oil, gas and hydrocarbon micro-leakage alteration zone map. At the same time, check whether there are fault outcrops or stratigraphic displacement phenomena recorded at the corresponding locations in the field geological survey data. When a fault meets all three conditions simultaneously—that the seismic profile shows it cutting through the surface, that there is strong hydrocarbon micro-leakage and alteration on the surface, and that a fault outcrop is found in the field investigation—then the fault is identified as a surface-exposed fault. The exposed surface faults are labeled with attributes, and the strike, extension length, fault nature and spatial relationship with the alteration zone of the exposed surface faults are recorded. The spatial location and attribute information of all exposed surface faults are integrated to generate a distribution map of exposed surface faults.

[0012] As a preferred embodiment of the fracture interpretation and reservoir potential assessment method based on hydrocarbon microleakage and alteration information of the present invention, it further includes: For faults in seismic profile fault interpretation data that show strata reflection disorder but do not cut through to the surface, check whether there is an alteration anomaly in the corresponding surface area in the oil, gas and hydrocarbon micro-leakage alteration area map. At the same time, check whether there is a fault outcrop recorded at the corresponding location in the field geological survey data, and check whether there is a strata faulting record in the corresponding area in the drilling data. When a fracture meets the following four conditions—that the seismic profile shows the presence of the fracture, there is no hydrocarbon micro-leakage or alteration on the surface or only a first-order alteration zone, no fault outcrops are found in the field survey, and drilling data show no formation faulting—then the fracture is identified as a concealed fracture. The properties of concealed faults are inferred, and the strike and extension length of concealed faults are determined by comparing multiple seismic profiles. Meanwhile, the burial depth of the concealed faults is calculated based on the two-way reflection time in the seismic profile data, the spatial relationship between the concealed faults and the cover layer is recorded, and the spatial location and attribute information of all concealed faults are integrated to generate a concealed fault inference map. By overlaying and integrating the surface fault distribution map and the inferred map of concealed faults, a comprehensive fault interpretation result map is generated.

[0013] As a preferred embodiment of the present invention's method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage alteration information, the method includes: verifying the spatial correlation between alteration and fracture, including: Based on the alteration area map of oil and gas hydrocarbon micro-leakage, the spatial distribution range of three types of alteration anomalies—carbonate mineralization alteration, clay mineralization alteration, and red bed fading alteration—was extracted, and the raster data of the three types of alteration anomalies were converted into vector surface features to create alteration anomaly distribution vector data. Based on the vector data of alteration anomalies, the standard deviation ellipse of carbonate mineralization alteration area, clay mineralization alteration area and red bed fading alteration area were calculated by the directional distribution statistical method. The standard deviation ellipse data of the alteration area for each of the three types of alteration areas were obtained. The standard deviation ellipse data of the alteration area includes the length of the major axis of the ellipse, the length of the minor axis of the ellipse and the azimuth of the major axis of the ellipse. Acquire spatial distribution data of existing fracture structures in the study area, convert the spatial distribution data of fracture structures into fracture vector line elements, and generate fracture distribution vector data. Based on the fracture distribution vector data, the standard deviation ellipse of all fractures in the study area was calculated using the directional distribution statistical method, and the fracture distribution standard deviation ellipse data was obtained. The fracture distribution standard deviation ellipse data includes the length of the major axis of the ellipse, the length of the minor axis of the ellipse, and the azimuth of the major axis of the ellipse. Calculate the azimuth deviation between the azimuth of the major axis of the ellipse in the standard deviation ellipse data of alteration regions for the three types of alteration regions and the azimuth of the major axis of the ellipse in the standard deviation ellipse data of fracture distribution; Based on the comparison results of the azimuth deviation value and the preset deviation threshold, the consistency of the direction of each type of alteration region with the fracture distribution is verified.

[0014] As a preferred embodiment of the fracture interpretation and reservoir potential assessment method based on hydrocarbon microleakage alteration information of the present invention, the method includes: verifying the consistency of the direction of each type of alteration region with the fracture distribution, including: If the azimuth deviation is less than or equal to the first deviation threshold, then the directional relationship between the alteration region and the fracture distribution is determined to be first-order consistent. If the azimuth deviation value is greater than the first deviation threshold and less than or equal to the second deviation threshold, then the directional relationship between the alteration region and the fracture distribution is determined to be second-order consistent. If the azimuth deviation value is greater than the second deviation threshold, then the directional relationship between the alteration region and the fracture distribution is determined to be level three consistent.

[0015] As a preferred embodiment of the fracture interpretation and reservoir potential assessment method based on hydrocarbon microleakage alteration information of this invention, the method includes: verifying the directional consistency and spatial overlap rate between the alteration region and the fracture buffer zone through standard deviation ellipse analysis, including: Using each fracture line element in the fracture distribution vector data as the center line, the fracture buffer vector data is generated by expanding to both sides according to the preset buffer radius. Intersection analysis was performed between the alteration anomaly distribution vector data and the fracture buffer vector data. The area of ​​the alteration region falling within the range of the fracture buffer vector data was counted and denoted as the alteration area within the buffer. Simultaneously, the total area of ​​the alteration anomaly distribution vector data is statistically analyzed and denoted as the total alteration area of ​​the study area. ; Calculate the alteration area within the buffer zone Total alteration area of ​​the study area The ratio of these values ​​yields the spatial overlap rate; The spatial association strength is determined by comparing the spatial overlap rate with the preset spatial association threshold.

[0016] As a preferred embodiment of the fracture interpretation and reservoir potential assessment method based on hydrocarbon microleakage and alteration information of the present invention, wherein: determining the spatial correlation strength includes: When the spatial overlap rate is greater than or equal to the first spatial correlation threshold, the alteration region and the fracture distribution are determined to have a strong spatial correlation. When the spatial overlap rate is less than the first spatial correlation threshold and greater than or equal to the second spatial correlation threshold, the alteration region and the fracture distribution are determined to have a moderate spatial correlation. When the spatial overlap rate is less than the second spatial correlation threshold, the alteration region and the fracture distribution are determined to have a weak spatial correlation, wherein the first spatial correlation threshold is greater than the second spatial correlation threshold.

[0017] Compared with existing technologies, the beneficial effects of this invention are as follows: By acquiring multi-source basic data of the study area and preprocessing remote sensing data to obtain standardized image data, unified correction of remote sensing data from different sources in terms of geometric accuracy, radiometric characteristics, and resolution is achieved, reducing interference caused by noise in the original data and imaging differences, and improving the comparability and stability of remote sensing data; by extracting hydrocarbon micro-leakage alteration information based on standardized image data and generating alteration area maps, rapid identification and spatial representation of mineral alteration anomalies formed on the surface by underground oil and gas micro-leakage are achieved, enabling the implicit oil and gas migration information to be reflected in a visual manner at the regional scale, thereby providing direct evidence for identifying oil and gas migration channels and fault conduction effects, and improving the efficiency of oil and gas anomaly identification; by analyzing alteration areas and faults... Spatial correlation verification was conducted in a distributed manner, and the spatial overlap rate was calculated by analyzing the consistency of the direction using standard deviation ellipse analysis and the superposition of fracture buffer zones. This enabled a quantitative analysis of the spatial coupling relationship between alteration anomalies and tectonic fractures, allowing the alteration-fracture relationship, which originally relied on empirical judgment, to be objectively verified through statistical parameters, thus improving the reliability of fracture interpretation. By integrating seismic profile data, field geological survey data, and drilling data for comprehensive fracture interpretation, a fracture-controlled reservoir potential assessment index system was constructed. Combined with standardized processing and a weighted scoring model, fractures were quantitatively evaluated, enabling a comprehensive judgment of the reservoir control capacity of exposed and concealed surface fractures. This allows for a graded expression of fracture-controlled reservoir potential, providing a scientific basis for the identification and exploration deployment of favorable structural zones in oil and gas exploration. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart of a method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information. Detailed Implementation

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort should fall within the scope of protection of this invention.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] As mentioned in the background section, existing fracture interpretation and evaluation techniques have significant shortcomings in quantitative verification of alteration-fracture correlation, systematic interpretation of multi-source data fusion, and comprehensive quantitative assessment of hydrocarbon reservoir potential. To address these issues, this invention provides a fracture interpretation and hydrocarbon reservoir potential assessment method based on hydrocarbon microleakage alteration information.

[0023] Reference Figure 1 , Figure 1 This is a flowchart illustrating a method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information, according to an embodiment of the present invention. Figure 1 As shown, a method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information includes: S1: Acquire multi-source basic data of the study area and preprocess the remote sensing data of the multi-source basic data to obtain standardized image data; It should be noted that the multi-source basic data includes vector data, geological data, oil and gas data, remote sensing data, and geophysical data; vector data: using the WGS84 coordinate system, containing .shp format files of the latitude and longitude range of the study area boundary; geological data includes stratigraphic distribution maps and structural distribution maps; oil and gas data includes oil and gas reservoir distribution, oil and gas leakage characteristics, and oil and gas accumulation history; remote sensing data: requires cloud cover ≤10%, no large-area cloud obstruction, and Sentinel-2A satellite L1C level imagery covering the entire study area; geophysical data includes seismic profile data or borehole data.

[0024] Specifically, atmospheric correction is performed using the L2A_Process.bat tool in Sen2cor software: In CMD, use the cd command to enter the root directory where the remote sensing data to be processed is located, and use the command L2A_Process to perform atmospheric correction on the path of the remote sensing data to be processed to obtain L2A-level remote sensing image; the reflectance values ​​of each band of the L2A-level remote sensing image are in the range of 0-1, which meets the requirements of subsequent spectral analysis.

[0025] Furthermore, the corrected L2A-level image was resampled using SNAP software: the L2A-level image was loaded, the Resampling tool was selected in the Raster menu, the resampling method was set to bilinear interpolation, the resolution of each band of the image was uniformly adjusted to 10m, and the resampled multi-band image was output.

[0026] Furthermore, the resampled images were combined using ENVI software: the resampled images of each band were imported, the Layer Stacking tool was selected in the Basic Tools menu, the bands were added in the order of the Sentinel-2A satellite bands, the output coordinate system was set to be consistent with the resampled images, and a multispectral image dataset containing 12 bands was generated to ensure that the required band combination can be directly called when extracting alteration later.

[0027] Specifically, image cropping and mosaicking are performed based on the vector data of the study area: If the study area covers multiple Sentinel-2A images, the Seamless Mosaic tool is first used in ENVI software to mosaic the images, selecting the Feather Edge fusion method and setting the pixel weights of overlapping areas to equal. After mosaicking, the Save as tool is selected in the File menu to import the mosaicked image data. In Spatial Subset, the vector file of the study area is selected as the boundary, and redundant data outside the study area is cropped to generate standardized image data that covers the entire study area, has no spatial misalignment, and whose boundaries perfectly match the study area.

[0028] S2: Based on standardized image data, extract hydrocarbon micro-leakage and corrosion information to generate a map of oil and gas hydrocarbon micro-leakage and corrosion areas. Specifically, based on standardized image data, a mask for extracting disturbance information is generated: Near-infrared and red bands are retrieved from the standardized image data, and the Normalized Difference Vegetation Index (NDVI) is calculated to generate an NDVI index image; combining the geological map and image features of the study area, an NDVI threshold range is set, and pixels with NDVI values ​​within the NDVI threshold range are extracted as vegetation areas, generating a binary vegetation mask file, where the pixel values ​​of vegetation areas are assigned the first value, and the pixel values ​​of non-vegetation areas are assigned the second value; Green and shortwave infrared bands are retrieved from the standardized image data, and the Improved Normalized Difference Water Index (MNDWI) is calculated to generate an MNDWI index image; combined with… Based on the geological map and image features of the study area, an MNDWI threshold was set, and pixels with MNDWI values ​​lower than the threshold were extracted as water bodies, generating a binarized water body mask file. The pixel values ​​of water bodies were assigned the first value, and the pixel values ​​of non-water bodies were assigned the second value. Red and shortwave infrared bands were retrieved from standardized image data, and the band ratio was calculated to generate a band ratio image. Combining the geological map and image features of the study area, a ratio threshold was set, and areas with pixel values ​​lower than the band ratio in the image were extracted as snow-covered areas, generating a binarized snow cover mask file. The pixel values ​​of snow-covered areas were assigned the first value, and the pixel values ​​of non-snow-covered areas were assigned the second value.

[0029] In optional embodiments, the NDVI threshold range is set based on the response characteristics of vegetation cover to hydrocarbon microleaking. Typically, NDVI values ​​below the typical range of no-vegetation or low-vegetation areas are used as indicators of vegetation stress or anomalous areas caused by hydrocarbon microleaking. The MNDWI threshold is determined based on the sensitivity of water body information to hydrocarbon microleaking. Generally, higher MNDWI values ​​are selected to highlight water bodies or wetland areas, and adjustments are made in conjunction with the spectral anomalies of water bodies that may be caused by hydrocarbon leakage. The ratio threshold is set based on the statistical distribution of the ratio of sensitive bands for hydrocarbon alteration minerals (such as iron oxides and clay minerals) in multispectral bands, and is used to identify surface alteration anomalies related to hydrocarbon microleaking. Areas with NDVI values ​​between 0.4 and 0.8 are selected as vegetation mask files. Areas with MNDWI values ​​below 0.2 are selected as water body mask files. Areas with grayscale image pixel values ​​less than 0.1 are selected as snow cover mask files.

[0030] Furthermore, the vegetation mask file, water mask file, and snow mask file are multiplied to generate a composite mask image. In the composite mask image, areas with a pixel value of the second value represent non-interference areas, and areas with a pixel value of the first value represent interference areas. The composite mask image is then overlaid with the standardized image data to mask interference areas with a pixel value of 1 and retain non-interference areas with a pixel value of 0, thereby generating de-interference standardized image data.

[0031] Furthermore, based on the types of alteration minerals caused by hydrocarbon micro-leakage in the geological background of the study area, a correspondence between three types of alteration minerals and satellite bands was established, and sensitive bands were selected accordingly: 1) Determination of carbonate mineralization alteration band combination: Identify the spectral characteristic absorption peak positions of carbonate minerals (calcite, dolomite), which are located at 2.33~2.35μm; Select four bands covering the blue light band, red edge band, water vapor band, and second shortwave infrared band from the interference-free normalized image data to form a sensitive band combination for carbonate mineralization alteration; 2) Determination of clay mineralization alteration band combination: Identify the characteristic location of the hydroxyl absorption band of clay minerals (illite, montmorillonite), which is distributed in the hydroxyl absorption bands at 1.4μm and 2.2μm; From the interference-free normalized image data, select four bands covering the green light band, narrow near-infrared band, first shortwave infrared band, and second shortwave infrared band to form a sensitive band combination for clay mineralization alteration; 3) Determination of the red bed fading and alteration band combination: Identify the strong absorption valley characteristics of iron oxides (hematite, magnetite), which are distributed in the strong absorption valleys of 0.8-0.9μm and 1μm; Select four bands covering the green band, red band, narrow near-infrared band, and first short-wave infrared band from the interference-free normalized image data to form the red bed fading and alteration sensitive band combination.

[0032] Specifically, in ENVI software, principal component transformation was performed on the sensitive band combinations for carbonate mineralization alteration, clay mineralization alteration, and red bed fading alteration: In the Transform tool, the PCARotation-Forward PCA Rotation New Statistics and Rotate method was selected, and the eigenvalues, eigenvectors, and principal component images of each principal component were calculated by inputting the corresponding sensitive band for carbonate mineralization. The above operations were repeated to complete the principal component analysis for clay mineralization alteration and red bed fading alteration, generating principal component image data and eigenvector matrices corresponding to the three types of alteration.

[0033] Furthermore, based on the eigenvector matrix, and according to the selection criteria of the eigenvectors of the absorption band having opposite signs to those of the eigenvectors of the reflection band and having the largest absolute value of the eigenvectors, the principal component image data corresponding to carbonate mineralization alteration, clay mineralization alteration, and red bed fading alteration are selected from the principal component image data respectively.

[0034] Furthermore, using the standard deviation of the principal component image data as the benchmark threshold, the principal component image data is classified according to the standard deviation in an increasing order. The alteration information is divided into first-level alteration zone, second-level alteration zone and third-level alteration zone from weak to strong, thus obtaining alteration anomaly classification image data.

[0035] It should be noted that the baseline thresholds include 3, 6, and 9 standard deviations. The criteria for these thresholds are as follows: In remote sensing signals of hydrocarbon microleakage alteration, the principal component pixel values ​​of background features follow a normal distribution. The degree to which alteration anomaly pixel values ​​caused by hydrocarbon microleakage deviate from the normal distribution is positively correlated with the leakage flux of hydrocarbon substances. 3 standard deviations correspond to a confidence level of 99.73%, used to delineate the smallest significant anomaly deviating from the background distribution. Pixels within this range are designated as first-level alteration zones, where the first-level alteration zone characterizes a weak hydrocarbon microleakage alteration response. 6 standard deviations correspond to a higher confidence level, used to delineate... The pixels within the range of moderate-intensity alteration anomalies are designated as secondary alteration zones, which characterize the alteration response of moderate hydrocarbon micro-leakage. The pixels within the range of high-abnormality pixel concentration caused by strong hydrocarbon leakage (9 times the standard deviation) are designated as tertiary alteration zones, which characterize the alteration response of strong hydrocarbon micro-leakage. The above classification method has been verified in the field in the Quele area of ​​the Kuqa Depression. The spatial overlap rate between the tertiary alteration zone and the surface fault outcrops and oil and gas leakage points is higher than 85%, the spatial overlap rate between the secondary alteration zone and the fault buffer zone is higher than 60%, and the primary alteration zone is mainly distributed in the edge area of ​​the fault influence zone.

[0036] Specifically, Gaussian low-pass filtering is used to filter the alteration anomaly classification image data to suppress isolated noise points in the alteration anomaly classification image data, resulting in filtered alteration image data. The three types of alteration anomaly information in the filtered alteration image data—carbonate mineralization alteration, clay mineralization alteration, and red bed fading alteration—are superimposed and integrated to generate an oil, gas, and hydrocarbon micro-leakage alteration area map.

[0037] S3: Based on the alteration area map of oil and gas hydrocarbon micro-leakage, verify the spatial correlation between alteration and fracture, and verify the directional consistency and spatial overlap rate between the alteration area and the fracture buffer zone through standard deviation ellipse analysis. Specifically, based on the alteration area map of oil and gas hydrocarbon micro-leakage, the spatial distribution range of three types of alteration anomalies—carbonate mineralization alteration, clay mineralization alteration, and red bed fading alteration—was extracted. The raster data of the three types of alteration anomalies were then converted into vector surface features to create alteration anomaly distribution vector data. Based on the alteration anomaly distribution vector data, the standard deviation ellipse of the carbonate mineralization alteration area, clay mineralization alteration area, and red bed fading alteration area was calculated using the directional distribution statistical method. The standard deviation ellipse data of the alteration area for each of the three types of alteration areas were obtained. The standard deviation ellipse data of the alteration area includes the length of the major axis, the length of the minor axis, and the azimuth of the major axis.

[0038] Furthermore, spatial distribution data of existing fracture structures in the study area are obtained, and the spatial distribution data of fracture structures are converted into fracture vector line elements to generate fracture distribution vector data. Based on the fracture distribution vector data, the standard deviation ellipse of all fractures in the study area is calculated using the directional distribution statistical method to obtain fracture distribution standard deviation ellipse data, which includes the length of the major axis, the length of the minor axis, and the azimuth of the major axis.

[0039] Furthermore, the azimuth deviation between the major axis azimuth of the three types of alteration regions in the standard deviation ellipse data of alteration regions and the major axis azimuth of the fracture distribution standard deviation ellipse data is calculated; based on the comparison results of the azimuth deviation values ​​and the preset deviation threshold, the directional consistency between each type of alteration region and the fracture distribution is verified.

[0040] Preferably, if the azimuth deviation value is less than or equal to the first deviation threshold, the directional relationship between the altered region and the fracture distribution is determined to be first-level consistency; if the azimuth deviation value is greater than the first deviation threshold and less than or equal to the second deviation threshold, the directional relationship between the altered region and the fracture distribution is determined to be second-level consistency; if the azimuth deviation value is greater than the second deviation threshold, the directional relationship between the altered region and the fracture distribution is determined to be third-level consistency.

[0041] It should be noted that Level 1 consistency indicates that the azimuth deviation between the main direction of the alteration region and the direction of the fracture distribution is small, and the two directions are highly consistent; Level 2 consistency indicates that there is a certain azimuth deviation between the main direction of the alteration region and the direction of the fracture distribution, but the directions are still consistent, and the two directions are basically consistent; Level 3 consistency indicates that the azimuth deviation between the main direction of the alteration region and the direction of the fracture distribution is large, and the two directions are deviated; the preset deviation thresholds include a first deviation threshold and a second deviation threshold; the first deviation threshold is set based on the degree of deviation between the pixel-level spectral features and the background model, and is used to initially screen abnormal pixels that may be affected by hydrocarbon microleakage; the second deviation threshold is a more stringent threshold set based on regional statistical features (such as mean and standard deviation), and is used to further remove noise and highlight significant abnormal areas.

[0042] In an optional embodiment, if the azimuth deviation is less than or equal to 5°, the directional relationship between the altered area and the fracture distribution is determined to be first-level consistency; if the azimuth deviation is greater than 5° and less than or equal to 10°, the directional relationship between the altered area and the fracture distribution is determined to be second-level consistency; if the azimuth deviation is greater than 10°, the directional relationship between the altered area and the fracture distribution is determined to be third-level consistency.

[0043] Specifically, using each fracture line element in the fracture distribution vector data as the center line, and expanding outwards to both sides according to the preset buffer radius, fracture buffer vector data is generated. Intersection analysis is performed between the alteration anomaly distribution vector data and the fracture buffer vector data, and the area of ​​the altered region falling within the range of the fracture buffer vector data is counted and recorded as the alteration area within the buffer. Simultaneously, the total area of ​​the alteration anomaly distribution vector data is statistically analyzed and denoted as the total alteration area of ​​the study area. ; Calculate the alteration area within the buffer zone Total alteration area of ​​the study area The ratio of these values ​​yields the spatial overlap rate.

[0044] Furthermore, based on the comparison results of the spatial overlap rate and the preset spatial association threshold, the spatial association strength is determined; when the spatial overlap rate is greater than or equal to the first spatial association threshold, the alteration region and the fracture distribution are determined to have a strong spatial association; when the spatial overlap rate is less than the first spatial association threshold but greater than or equal to the second spatial association threshold, the alteration region and the fracture distribution are determined to have a moderate spatial association; when the spatial overlap rate is less than the second spatial association threshold, the alteration region and the fracture distribution are determined to have a weak spatial association, wherein the first spatial association threshold is greater than the second spatial association threshold.

[0045] It should be noted that the preset buffer radius is set to 1000m in ArcGIS; the first spatial association threshold is set based on the distance distribution between the anomalous pixels and the known fault zone, and is used to determine whether the anomalous is spatially related to the fault; the second spatial association threshold is set based on the anomalous clustering degree or density index, and is used to assess the concentration and continuity of the anomalous near the fault zone.

[0046] In an optional embodiment, when the spatial overlap rate is greater than or equal to 50%, the alteration region and the fracture distribution are determined to have a strong spatial correlation; when the spatial overlap rate is less than 50% but greater than or equal to 30%, the alteration region and the fracture distribution are determined to have a moderate spatial correlation; when the spatial overlap rate is less than 30%, the alteration region and the fracture distribution are determined to have a weak spatial correlation, wherein the first spatial correlation threshold is greater than the second spatial correlation threshold.

[0047] S4: Based on the fusion of multi-source basic data, perform comprehensive interpretation of faults to determine the distribution characteristics of exposed and concealed faults on the surface; Specifically, the seismic profile data is loaded, and with the stratigraphic distribution map as a reference, marker layers with continuous reflection characteristics are identified in the seismic profile data. The stratigraphic attitude information is determined based on the reflection wave group morphology of the marker layers. Anomalous areas of stratigraphic reflection wave groups are searched in the seismic profile data. When a certain area shows characteristics such as reflection wave group discontinuity, reflection wave group termination, reflection wave group disorder, or amplitude abrupt change, the anomalous area is marked as a fault development location, and the attribute of the fault development location is recorded to generate seismic profile fault interpretation data. The attributes include the starting depth, termination layer, and dip angle of the fault in the seismic profile data.

[0048] Furthermore, the spatial coordinates of the hydrocarbon micro-leakage alteration area map, seismic profile fault interpretation data, and field geological survey data and drilling data from multi-source basic data are unified and transformed to the same coordinate system to construct a multi-source data fusion analysis system. Based on this system, the hydrocarbon micro-leakage alteration area map and seismic profile fault interpretation data are spatially overlaid, and the extension characteristics of each fault in the seismic profile fault interpretation data are compared with the corresponding surface area alteration intensity distribution in the hydrocarbon micro-leakage alteration area map. For faults shown in the seismic profile fault interpretation data to cut through to the surface, the corresponding surface area is examined. The system checks whether a secondary or tertiary alteration zone exists in the oil and gas hydrocarbon micro-leakage alteration area map, and whether fault outcrops or stratigraphic displacement phenomena are recorded at the corresponding locations in the field geological survey data. When a fault simultaneously meets the three conditions of seismic profile showing that it cuts through the surface, strong hydrocarbon micro-leakage alteration exists on the surface, and fault outcrops are found in the field survey, the fault is identified as a surface exposed fault. The surface exposed faults are labeled with attributes, and the strike, extension length, fault nature, and spatial relationship with the alteration zone of the surface exposed faults are recorded. The spatial location and attribute information of all surface exposed faults are integrated to generate a surface exposed fault distribution map.

[0049] Furthermore, for faults in seismic profile fault interpretation data that show dynamism in stratigraphic reflections but do not penetrate to the surface, examine whether there are alteration anomalies in the corresponding surface area on the hydrocarbon micro-leakage alteration zone map. Simultaneously, examine whether fault outcrops are recorded at the corresponding locations in the field geological survey data, and examine whether there are stratigraphic faulting records in the corresponding areas in the drilling data. When a fault meets the following criteria: seismic profile shows its existence, there is no hydrocarbon micro-leakage alteration at the surface or only a first-order alteration zone, no fault outcrops are found in the field survey, and drilling data shows no... When all four conditions for stratigraphic displacement are met, the fault is identified as a concealed fault. The attributes of the concealed fault are inferred, and its strike and extension length are determined by comparing multiple seismic profiles. Simultaneously, the burial depth of the concealed fault is calculated based on the two-way reflection time in the seismic profile data, and the spatial relationship between the concealed fault and the caprock is recorded. The spatial location and attribute information of all concealed faults are integrated to generate a concealed fault inference map. The surface exposed fault distribution map and the concealed fault inference map are overlaid and integrated to generate a comprehensive fault interpretation result map.

[0050] Preferably, for the special case where a primary alteration zone exists in the corresponding surface area of ​​the oil and gas hydrocarbon micro-leakage alteration area map but the alteration intensity does not reach the secondary alteration zone, the difference is made by calculating the spatial overlap rate of the buffer zone between the primary alteration zone and the inferred location of the concealed fault: when the spatial overlap rate is less than the second spatial correlation threshold, and no fault outcrop is recorded at the corresponding location in the field geological survey data, and no stratigraphic faulting is recorded in the corresponding area in the drilling data, the primary alteration zone is determined to be background alteration caused by non-fault outcrops, wherein the fault maintains the concealed fault determination result unchanged; the causes of background alteration in the primary alteration zone include the secondary modification of sediments by surface water or groundwater, changes in soil mineral spectral characteristics caused by agricultural activities, and the mixing of spectral characteristics of sediments from different sources; the above determination results, together with the field geological survey data and drilling data, constitute the component of the concealed fault attribute record, which is recorded in the attribute field of the corresponding fault vector element in the concealed fault inference map.

[0051] S5: Construct an index system for assessing the potential for fault-controlled reservoirs, establish a quantitative scoring model, and output the graded results of the potential for fault-controlled reservoirs. Specifically, based on spatial overlap rate, oil and gas hydrocarbon micro-leakage and alteration area map, directional consistency judgment results, surface exposed fault distribution map, hidden fault inference map, seismic profile fault interpretation data, and multi-source basic data, a fault-controlled reservoir potential assessment index system is constructed.

[0052] Preferably, the fault-controlled reservoir potential assessment index system includes three categories: alteration-related indicators, structural development indicators, and hydrocarbon geological indicators, specifically including: The specific index items and value methods of the alteration-related indicators were determined as follows: the spatial overlap rate was used as the alteration-fracture spatial overlap rate index, and the original value of the spatial overlap rate was directly adopted; the alteration classification results in the oil, gas and hydrocarbon micro-leakage alteration area map were used as the alteration anomaly level index, and incremental quantitative values ​​were assigned to the first-level alteration area, the second-level alteration area, and the third-level alteration area respectively; the directional consistency judgment results were used as the ellipse major axis directional consistency index, and incremental quantitative values ​​were assigned to the directional deviation, directional consistency, and directional height consistency respectively. The specific index items and value methods for structural development indicators are determined as follows: the fault length recorded in the surface exposed fault distribution map and the concealed fault inference map is used as the fault extension length index, and the original value of the fault length is directly adopted; the fault dip angle recorded in the seismic profile fault interpretation data is used as the fault dip angle index, and the original value of the fault dip angle is directly adopted; the fault cutting horizon recorded in the seismic profile fault interpretation data is used as the fault cutting horizon index, and incremental quantitative values ​​are assigned according to whether it cuts only shallow strata, cuts through source rock strata, or cuts through reservoir strata. The specific index items and value methods for oil and gas geological indicators are determined as follows: Based on the oil and gas reservoir distribution data in the multi-source basic data, the straight-line distance from the centerline of each fault to the nearest oil and gas reservoir boundary is used as the distance index between the fault and the oil and gas reservoir; based on the stratigraphic distribution map and oil and gas accumulation data in the multi-source basic data, the straight-line distance from the centerline of each fault to the nearest source rock distribution area boundary is used as the distance index between the fault and the source rock; the oil and gas showing conditions recorded by the drilling data in the multi-source basic data are used as the drilling-revealed oil and gas showing indicators, and incremental quantitative values ​​are assigned according to no oil and gas showing, weak oil and gas showing, and strong oil and gas showing.

[0053] It should be noted that the alteration anomaly level index is quantified as follows: Level 1 alteration zone = 1, Level 2 alteration zone = 2, and Level 3 alteration zone = 3; the ellipse major axis direction consistency index is quantified as follows: direction deviation = 0, direction consistency = 1, and direction height consistency = 2; the fracture cutting layer index is quantified as follows: cutting through shallow strata = 1, cutting through source rock strata = 2, and cutting through reservoir = 3; the drilling revealed oil and gas indication index is quantified as follows: no oil and gas indication = 0, weak oil and gas indication = 1, and strong oil and gas indication = 2.

[0054] In an optional embodiment, the weights of each indicator are specifically quantified in terms of weight allocation; among the alteration-related indicators, the alteration-fracture spatial overlap rate has a weight of 0.15, the alteration anomaly level has a weight of 0.10, and the consistency of the major axis of the ellipse has a weight of 0.10; among the structural development indicators, the fracture extension length has a weight of 0.10, the fracture dip angle has a weight of 0.08, and the fracture cutting layer has a weight of 0.12; among the oil and gas geology indicators, the distance between the fracture and the oil and gas reservoir has a weight of 0.15, the distance between the fracture and the source rock has a weight of 0.10, and the oil and gas indication revealed by drilling has a weight of 0.10; the sum of the weights of all indicators is 1.00, which together constitute a complete quantitative evaluation framework.

[0055] Furthermore, the extreme value standardization method is used to standardize the original values ​​of each indicator in the fault-controlled reservoir potential assessment index system, eliminating dimensional differences between different indicators. The specific standard rules are as follows: For positive indicators, the standardized score is calculated using the formula: Standardized Score = (Original Value of Indicator - Minimum Value of Indicator) / (Maximum Value of Indicator - Minimum Value of Indicator) × 10. Positive indicators include the alteration-fracture spatial overlap rate, alteration anomaly level, ellipse major axis direction consistency, fracture extension length, fracture cutting layer, and drilling-revealed hydrocarbon show indicators. For negative indicators, the standardized score is calculated using the formula: Standardized Score = (Maximum Value of Indicator - Original Value of Indicator) / (Maximum Value of Indicator - Minimum Value of Indicator) × 10. Negative indicators include the distance between the fault and the oil and gas reservoir and the distance between the fault and the source rock. For the fault dip angle, the interval assignment method is used for standardization based on the optimal dip angle range of the oil and gas migration channel. Different dip angle intervals are assigned corresponding standardized scores to obtain the standardized scores of each indicator.

[0056] In an optional embodiment, the geological basis for assigning the fracture dip angle index range is as follows: For fractures with dip angles between 30 and 60 degrees, the ratio of normal stress to shear stress on the fracture surface is within a mechanical range that favors upward fluid migration along the fracture surface. The vertical migration component of oil and gas along the fracture surface is the largest, and the opening of the fracture surface is less constrained by regional compressive stress, resulting in minimal resistance to oil and gas migration. Therefore, the standardized score of the fracture dip angle index in the 30-60 degree range is assigned the highest value of 10 points. For fractures with dip angles less than 30 degrees, the fracture surface is nearly horizontal, the vertical migration component of oil and gas is small, and lateral migration is dominant. The contribution to vertical reservoir control is relatively low, so the standardized score of the dip angle index for fractures with dip angles less than 30 degrees is assigned a median value of 5. For fractures with dip angles greater than 60 degrees, the fracture surface is nearly vertical. Although the vertical migration channel is smooth, the fracture surface is subjected to greater normal stress under the regional compression background, and the fracture surface tends to close, increasing the resistance to oil and gas migration. Therefore, the standardized score of the dip angle index for fractures with dip angles greater than 60 degrees is also assigned a median value of 5. The above interval assignment scheme is consistent with the regional tectonic stress background of the salt-bearing fold-thrust belt in the Kuqa Depression, and has been verified in the evaluation of the Quele Fault (fracture dip angle of about 24 degrees) in the specific embodiment.

[0057] Furthermore, the weight values ​​of each indicator in the fault-controlled reservoir potential assessment index system are determined using the analytic hierarchy process (AHP): a pairwise comparison judgment matrix is ​​constructed between each indicator, and the eigenvectors of the judgment matrix are calculated based on the scoring results of the relative importance of each indicator by experts in the field of oil and gas geology; the initial weight values ​​of each indicator are obtained after normalizing the eigenvectors, and the consistency of the judgment matrix is ​​checked; when the consistency ratio is less than a preset threshold, the initial weight values ​​are determined as the final weight values ​​of each indicator.

[0058] In an optional embodiment, taking the Qule area of ​​the Kuqa Depression as an example, a comprehensive assessment of the potential for hydrocarbon accumulation is conducted on four faults in the study area: the Qule Fault, the Awat Fault, the Karayur Roll-Slip Fault, and the concealed fault on the southern wing of the Miskantak Anticline. The specific calculation process is as follows: The original value of the alteration-fracture spatial overlap rate index of the Quele Fault is 40%, which, according to the positive index extreme value standardization formula, yields a standardized score of 4 points. Multiplying this by the alteration-fracture spatial overlap rate index weight value of 0.15 gives a weighted score of 0.600 points. The original value of the alteration anomaly level index of the Quele Fault is a level 3 alteration zone, with a quantified value of 3. According to the positive index extreme value standardization formula, this yields a standardized score of 10 points. Multiplying this by the alteration anomaly level index weight value of 0.10 gives a weighted score of 1.000 points. The original value of the elliptical major axis direction consistency index of the Quele Fault is 0.09 degrees, with a quantified value of 2. The standardized score calculated using the positive index extreme value standardization formula is 10 points. Multiplying this by the weight value of the ellipse major axis direction consistency index (0.10) yields a weighted score of 1.000 points. The original value of the fracture extension length index of the Quele Fault is 5.54 kilometers. The standardized score calculated using the positive index extreme value standardization formula is 2.77 points. Multiplying this by the weight value of the fracture extension length index (0.10) yields a weighted score of 0.277 points. The original value of the fracture dip angle index of the Quele Fault is 24 degrees, with a quantified value of 1. The standardized score calculated using the positive index extreme value standardization formula is 5 points. Multiplying this by the weight value of the fracture dip angle index (0.08) yields a weighted score of 5 points. The original value of the fault cutting horizon index of the Quele Fault is 0.400 points; the original value is 3 for cutting through the reservoir, the standardized value is 10 points, and the weighted score is 1.200 points after multiplying it with the weighted value of 0.12 for the fault cutting horizon index. The original value of the distance index between the fault and the oil and gas reservoir is 0 km, and the standardized score is 10 points calculated according to the negative index extreme value standardization formula. The weighted score is 1.500 points after multiplying it with the weighted value of 0.15 for the distance index between the fault and the oil and gas reservoir. The original value of the distance index between the Quele Fault and the source rock is 3.57 km, and the weighted score is 1.500 points after multiplying it with the weighted value of 0.15 for the distance index between the fault and the source rock. The standardized score calculated by the formula is 8.215 points, which, when multiplied by the alteration anomaly level index weight value of 0.10, yields a weighted score of 0.822 points. The drilling-revealed oil and gas indication index of the Quele Fault is quantitatively assigned a value of 2, which, when calculated according to the positive index extreme value standardization formula, yields a standardized score of 10 points. This, when multiplied by the drilling-revealed oil and gas indication index weight value of 0.10, yields a weighted score of 1.000 points. The weighted scores of the remaining indicators are calculated sequentially in the above manner and summed to obtain a comprehensive score of 7.799 points for the reservoir control potential of the Quele Fault, which is greater than or equal to the first potential grading threshold of 7 points. Therefore, the Quele Fault is classified as a high-potential fault. The original value of the alteration-fracture spatial overlap rate index of the Awatt fault is 30%, which, according to the positive index extreme value standardization formula, yields a standardized score of 3 points. Multiplying this by the alteration-fracture spatial overlap rate index weight value of 0.15 gives a weighted score of 0.450 points. The original value of the alteration anomaly level index of the Awatt fault is a level 3 alteration zone, with a quantified value of 3. According to the positive index extreme value standardization formula, this yields a standardized score of 10 points, which, multiplying by the alteration anomaly level index weight value of 0.10 gives a weighted score of 1.000 points. The original value of the elliptical major axis direction consistency index of the Awatt fault is 18.51 degrees, with a quantified value of 0. The standardized score for the Awat Fault, calculated using the positive index extreme value standardization formula, is 0 points. Multiplying this by the weighted score of 0.10 for the ellipse major axis direction consistency index yields a weighted score of 0.000 points. The original value for the Awat Fault's fracture extension length index is 5.42 km. Using the positive index extreme value standardization formula, the standardized score is 2.71 points. Multiplying this by the weighted score of 0.10 for the fracture extension length index yields a weighted score of 0.271 points. The original value for the Awat Fault's fracture dip angle index is 30 degrees, with a quantified value of 2. Using the positive index extreme value standardization formula, the standardized score is 10 points. Multiplying this by the weighted score of 0.0 for the fracture dip angle index yields a weighted score of 10 points. Multiplying by 8 yields a weighted score of 0.800. The original value of the fault cutting horizon index of the Awat Fault is cutting through shallow strata, with a quantified value of 0 and a standardized score of 0. Multiplying it by the weighted value of 0.12 for the fault cutting horizon index yields a weighted score of 0.000. The original value of the distance index between the Awat Fault and the oil and gas reservoir is 2.94 km. According to the negative index extreme value standardization formula, the standardized score is 8.53. Multiplying it by the weighted value of 0.15 for the distance index between the fault and the oil and gas reservoir yields a weighted score of 1.280. The original value of the distance index between the Awat Fault and the source rock is 6.15 km. According to the positive index extreme value standardization formula... The standardized score was calculated to be 6.925 points, which, when multiplied by the alteration anomaly level index weight value of 0.10, yielded a weighted score of 0.693 points. The drilling-revealed hydrocarbon indication index of the Awat Fault was assigned a quantitative value of 0, which, when calculated using the positive index extreme value standardization formula, yielded a standardized score of 0 points. This, when multiplied by the drilling-revealed hydrocarbon indication index weight value of 0.10, yielded a weighted score of 0.000 points. The weighted scores of the remaining indicators were calculated sequentially in the above manner and summed to obtain a comprehensive score of 4.494 points for the hydrocarbon reservoir control potential of the Awat Fault. This score is greater than or equal to the second potential grading threshold of 4 points, thus classifying the Awat Fault as a medium-potential fault. The original value of the alteration-fracture spatial overlap rate index of the Karayur Rolling Fault is 37%. Using the positive index extreme value standardization formula, the standardized score is 3.7 points. Multiplying this by the weight value of 0.15 for the alteration-fracture spatial overlap rate index yields a weighted score of 0.555 points. The original value of the alteration anomaly level index of the Karayur Rolling Fault is a level 3 alteration zone, with a quantified value of 3. Using the positive index extreme value standardization formula, the standardized score is 10 points. Multiplying this by the weight value of 0.10 for the alteration anomaly level index yields a weighted score of 1.000 points. The original value of the elliptical major axis direction consistency index of the Karayur Rolling Fault is 72.79 degrees, with a quantified value of... The original value of the fracture extension length index of the Karayuer Roller Fault is 4.19 km. According to the positive index extreme value standardization formula, the standardized score is 0 points, and multiplying it by the weight value of 0.10 for the ellipse major axis direction consistency index yields a weighted score of 0.000 points. The original value of the fracture dip angle index of the Karayuer Roller Fault is 83 degrees, with a quantified value of 1. According to the positive index extreme value standardization formula, the standardized score is 5 points, multiplied by the weight value of 0.08 for the fracture dip angle index. The weighted score is 0.400 points after multiplication. The original value of the fracture cutting horizon index of the Karayuergun Fault is "cutting through the reservoir", with a quantified value of 3 and a standardized score of 10 points. Multiplying this with the weighted value of 0.12 for the fracture cutting horizon index yields a weighted score of 1.200 points. The original value of the distance index between the Karayuergun Fault and the oil and gas reservoir is 19.54 km. The standardized score calculated using the negative index extreme value standardization formula is 0.23 points. Multiplying this with the weighted value of 0.15 for the distance index between the fault and the oil and gas reservoir yields a weighted score of 0.035 points. The original value of the distance index between the Karayuergun Fault and the source rock is 3.41 km. The standardized score calculated using the positive index extreme value standardization formula... The standardized score was calculated to be 8.295 points, which, when multiplied by the alteration anomaly level index weight value of 0.10, yielded a weighted score of 0.830 points. The drilling-revealed hydrocarbon indication index of the Karayuergun fault was quantitatively assigned a value of 1, which, according to the positive index extreme value standardization formula, yielded a standardized score of 5 points. This, when multiplied by the drilling-revealed hydrocarbon indication index weight value of 0.10, yielded a weighted score of 0.500 points. The weighted scores of the remaining indicators were calculated sequentially in the same manner and summed to obtain a comprehensive score of 4.730 points for the hydrocarbon reservoir control potential of the Karayuergun fault. This score is greater than or equal to the second potential grading threshold of 4 points, thus classifying the Karayuergun fault as a medium-potential fault. The original value of the alteration-fracture spatial coincidence rate index of the concealed fault in the southern wing of Miskantak is 0.5%. According to the positive index extreme value standardization formula, the standardized score is 0.05. Multiplying this by the alteration-fracture spatial coincidence rate index weight value of 0.15 yields a weighted score of 0.008. The original value of the alteration anomaly level index of the concealed fault in the southern wing of Miskantak is no alteration zone, with a quantified value of 0. According to the positive index extreme value standardization formula, the standardized score is 0. Multiplying this by the alteration anomaly level index weight value of 0.10 yields a weighted score of 0.000. The original value of the elliptical major axis direction consistency index of the concealed fault in the southern wing of Miskantak is 3.01 degrees, with a quantified value of... 2. The standardized score calculated using the positive index extreme value standardization formula is 10 points. Multiplying this by the weighted value of 0.10 for the consistency index of the major axis of the ellipse yields a weighted score of 1.000 points. The original value of the fracture extension length index of the concealed fault in the southern wing of Miskantak is 2.97 km. The standardized score calculated using the positive index extreme value standardization formula is 1.49 points. Multiplying this by the weighted value of 0.10 for the fracture extension length index yields a weighted score of 0.149 points. The original value of the fracture dip angle index of the concealed fault in the southern wing of Miskantak is 29.7 degrees, with a quantified value of 1. The standardized score calculated using the positive index extreme value standardization formula is 5 points. Multiplying this by the weighted value of 0.08 for the fracture dip angle index yields a weighted score of 5 points. The weighted score is 0.400 points. The original value of the fracture cutting horizon index for the concealed fault in the southern wing of Miskantak is cutting through shallow strata, with a quantified value of 0 and a standardized score of 0. Multiplying this by the fracture cutting horizon index weight value of 0.12 yields a weighted score of 0.000 points. The concealed fault in the southern wing of Miskantak directly cuts through the oil and gas reservoir. The original value of the distance index between the fault and the oil and gas reservoir is 0 km. According to the negative index extreme value standardization formula, the standardized score is 10 points. Multiplying this by the fault distance index weight value of 0.15 yields a weighted score of 1.500 points. The original value of the distance index between the concealed fault in the southern wing of Miskantak and the source rock is 1.51 km. According to the positive index extreme value standardization formula... The standardized score calculated using the standardization formula is 9.25 points. Multiplying this by the alteration anomaly level index weight value of 0.10 yields a weighted score of 0.925 points. The drilling-revealed hydrocarbon indication index of the Miskantak South Wing concealed fault is assigned a quantitative value of 0. According to the positive index extreme value standardization formula, the standardized score is 0 points. Multiplying this by the drilling-revealed hydrocarbon indication index weight value of 0.10 yields a weighted score of 0.000 points. The weighted scores of the remaining indicators are calculated sequentially in the above manner and summed. The comprehensive score of the hydrocarbon potential of the Miskantak South Wing concealed fault is 3.982 points, which is less than the second potential grading threshold of 4 points. Therefore, the Miskantak South Wing concealed fault is classified as a low-potential fault.

[0059] Preferably, a pairwise comparison judgment matrix is ​​constructed between each indicator, using a combination of expert scoring and hierarchical analysis. The importance ratio of each element value in the judgment matrix relative to the i-th indicator is used, with the importance ratio determined according to the Satie nine-part scale. The eigenvalues ​​of the judgment matrix are calculated to obtain the largest eigenvalue. The consistency index is obtained by dividing the difference between the largest eigenvalue and the order of the judgment matrix by the order of the judgment matrix minus one. The consistency ratio is obtained by comparing the consistency index with random consistency indices of the same order. When the consistency ratio is less than a preset consistency threshold, each component in the normalized eigenvector is determined as the weight value of the corresponding indicator. When the consistency ratio is greater than or equal to the preset consistency threshold, the pairwise comparison judgment matrix is ​​reassigned until the consistency ratio is less than the preset consistency threshold.

[0060] It should be noted that the preset consistency threshold is 0.10, and the consistency index is calculated by subtracting the order of the judgment matrix from the largest eigenvalue and then dividing by the order of the judgment matrix minus one. The consistency ratio is calculated by dividing the consistency index by the random consistency index of the same order.

[0061] In an optional embodiment, taking the Quele area of ​​the Kuqa Depression as an example, nine indicators constitute a ninth-order judgment matrix. The calculated maximum eigenvalue is 9.312, the consistency index is 0.039, the same-order random consistency index corresponding to the ninth-order judgment matrix is ​​1.460, and the consistency ratio is 0.027, which is less than the preset consistency threshold of 0.10. The judgment matrix passes the consistency test. Thus, the weight values ​​of the alteration-fracture spatial overlap rate index, the alteration anomaly level index, the ellipse major axis direction consistency index, the fracture extension length index, the fracture dip angle index, the fracture cutting layer index, the fracture distance index, the distance between the fracture and the oil and gas reservoir index, the distance between the fracture and the source rock index, and the drilling-revealed oil and gas show index are all 0.10. The sum of the weight values ​​of the above nine indicators is 1.00.

[0062] Specifically, a weighted summation method is used to multiply the standardized scores of each indicator by their corresponding weight values, and then sum the weighted scores of all indicators to establish a quantitative scoring model for the potential of faults to control reservoirs, thereby obtaining a comprehensive score for the potential of each fault to control reservoirs.

[0063] Furthermore, based on the comparison results of the comprehensive score of reservoir potential and the preset potential classification threshold, each fault is classified into levels; when the comprehensive score of reservoir potential is greater than or equal to the first potential classification threshold, the fault is judged as a high-potential fault; when the comprehensive score of reservoir potential is less than the first potential classification threshold but greater than or equal to the second potential classification threshold, the fault is judged as a medium-potential fault; when the comprehensive score of reservoir potential is less than the second potential classification threshold, the fault is judged as a low-potential fault; wherein, the first potential classification threshold is greater than the second potential classification threshold.

[0064] It should be noted that the first potential classification threshold is set based on a comprehensive score of anomaly intensity, spatial correlation, and geological background, and is used to classify areas with medium potential for mineral resources; the second potential classification threshold is set based on combinations of anomalies with higher confidence and geological evidence, and is used to classify areas with high potential for mineral resources.

[0065] In the optional embodiments, high-potential faults are defined as follows: a comprehensive score of 8 or higher indicating that the fault possesses excellent oil and gas migration channel conditions, good spatial matching with source rocks, reservoirs, and oil and gas reservoirs, high alteration correlation strength, and complete structural development, making it a priority exploration target area; medium-potential faults are defined as follows: a comprehensive score of less than 8 but greater than or equal to 6 indicating that the fault has certain oil and gas migration channel conditions, and core indicators (such as alteration overlap rate and cut strata) meet basic oil and gas migration conditions, but some indicators (such as distance from source rocks and drilling indications) need further verification through field reconnaissance or supplementary drilling data; and low-potential faults are defined as follows: a comprehensive score of less than 6 indicating that the fault's oil and gas migration channel function is limited (such as unsuitable dip angle or short extension length) or poor matching with oil and gas geological conditions (such as being far from source rocks or lacking alteration correlation), resulting in low exploration value.

[0066] Furthermore, the comprehensive score of the potential for mineral resources to be controlled by faults, the classification results of the potential for mineral resources to be controlled by faults, the standardized scores and weights of each indicator are linked to the corresponding fault vector elements in the surface exposed fault distribution map and the inferred map of concealed faults. Different colors are used to mark faults of different potential levels to generate a classification map of the potential for mineral resources to be controlled by faults.

[0067] In summary, this invention obtains standardized image data by acquiring multi-source basic data of the study area and preprocessing the remote sensing data. This achieves unified correction of remote sensing data from different sources in terms of geometric accuracy, radiometric characteristics, and resolution, reducing interference from noise in the original data and imaging differences, and improving the comparability and stability of remote sensing data. By extracting hydrocarbon micro-leakage alteration information based on standardized image data and generating alteration area maps, it enables rapid identification and spatial representation of mineral alteration anomalies formed on the surface by underground oil and gas micro-leakage. This allows the implicit oil and gas migration information to be reflected in a visual manner at the regional scale, thus providing direct evidence for identifying oil and gas migration channels and fault conduction effects, and improving the efficiency of oil and gas anomaly identification. Furthermore, by conducting spatial analysis of alteration areas and fault distribution... The correlation between alteration anomalies and tectonic fractures was verified, and the spatial overlap rate was calculated by analyzing the consistency of the standard deviation ellipse and the superposition of fracture buffers. This enabled a quantitative analysis of the spatial coupling relationship between alteration anomalies and tectonic fractures, which was originally based on empirical judgment. This allowed the alteration-fracture relationship to be objectively verified through statistical parameters, improving the reliability of fracture interpretation. By integrating seismic profile data, field geological survey data, and drilling data for comprehensive fracture interpretation, a fracture-controlled reservoir potential assessment index system was constructed. Combined with standardized processing and a weighted scoring model, fractures were quantitatively evaluated, enabling a comprehensive judgment on the reservoir control capacity of exposed and concealed surface fractures. This allows for a graded expression of fracture-controlled reservoir potential, providing a scientific basis for the identification and exploration deployment of favorable structural zones in oil and gas exploration.

Claims

1. A method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information, characterized in that: include, Acquire multi-source basic data of the study area, and preprocess the remote sensing data of the multi-source basic data to obtain standardized image data; Based on standardized image data, hydrocarbon micro-leakage and corrosion information is extracted to generate a map of oil and gas hydrocarbon micro-leakage and corrosion areas. Based on the aforementioned oil and gas hydrocarbon micro-leakage alteration area map, the spatial correlation between alteration and fracture is verified. The directional consistency and spatial overlap rate between the alteration area and the fracture buffer zone are verified by standard deviation ellipse analysis. Based on the fusion of the multi-source basic data, comprehensive fault interpretation is performed to determine the distribution characteristics of exposed and concealed faults on the surface. Construct an index system for assessing the potential for fault-controlled reservoirs, establish a quantitative scoring model, and output the graded results of the potential for fault-controlled reservoirs. Load seismic profile data, use the stratigraphic distribution map as a reference, identify marker layers with continuous reflection characteristics in the seismic profile data, and determine stratigraphic attitude information based on the reflection wave group morphology of the marker layers. In the seismic profile data, abnormal areas of the stratigraphic reflection wave group are searched. When a certain area shows characteristics such as reflection wave group discontinuity, reflection wave group termination, reflection wave group disorder, or amplitude abrupt change, the abnormal area is marked as a fault development location, and the attributes of the fault development location are recorded to generate seismic profile fault interpretation data. The spatial coordinates of the oil and gas hydrocarbon micro-leakage and alteration area map, the seismic profile fracture interpretation data, and the field geological survey data and drilling data in the multi-source basic data are unified and transformed to the same coordinate system to construct a multi-source data fusion analysis system. Based on the multi-source data fusion analysis system, the oil and gas hydrocarbon micro-leakage and alteration area map is spatially superimposed with the seismic profile fracture interpretation data, and the extension characteristics of each fracture in the seismic profile fracture interpretation data are compared with the alteration intensity distribution of the corresponding surface area in the oil and gas hydrocarbon micro-leakage and alteration area map. For the faults shown in the seismic profile fault interpretation data that cut through to the surface, check whether there are secondary or tertiary alteration zones in the corresponding surface area in the oil and gas hydrocarbon micro-leakage alteration area map. At the same time, check whether there are fault outcrops or stratigraphic displacement phenomena recorded at the corresponding locations in the field geological survey data. When a fault meets all three conditions simultaneously—that the seismic profile shows it cutting through the surface, that there is strong hydrocarbon micro-leakage and alteration on the surface, and that a fault outcrop is found in the field investigation—then the fault is identified as a surface-exposed fault. The exposed surface faults are labeled with attributes, and the strike, extension length, fault nature and spatial relationship with the alteration zone of the exposed surface faults are recorded. The spatial location and attribute information of all the exposed surface faults are integrated to generate a distribution map of exposed surface faults.

2. The method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information as described in claim 1, characterized in that: The classification results of the fault-controlled reservoir potential include: Based on the comparison results of the comprehensive score of the potential for mineral resource development and the preset potential classification threshold, each fault is classified into a level; when the comprehensive score of the potential for mineral resource development is greater than or equal to the first potential classification threshold, the fault is judged as a high-potential fault; when the comprehensive score of the potential for mineral resource development is less than the first potential classification threshold but greater than or equal to the second potential classification threshold, the fault is judged as a medium-potential fault; when the comprehensive score of the potential for mineral resource development is less than the second potential classification threshold, the fault is judged as a low-potential fault. The comprehensive score of the potential for mineral resources control, the classification results of the potential for mineral resources control by faults, the standardized scores and weights of each indicator are associated with the corresponding fault vector elements in the surface exposed fault distribution map and the inferred map of concealed faults. Different colors are used to mark faults of different potential levels to generate a classification map of the potential for mineral resources control by faults.

3. The method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information as described in claim 2, characterized in that: The method for obtaining the comprehensive score of the potential for controlling mineral resources is as follows: The extreme value standardization method was used to standardize the original values ​​of each index in the fault-controlled potential assessment index system. Meanwhile, the weight values ​​of each indicator in the fault-controlled reservoir potential assessment index system were determined using the analytic hierarchy process. A weighted summation method is used to multiply the standardized scores of each indicator by their corresponding weight values, and then sum the weighted scores of all indicators to establish a quantitative scoring model for the potential of faults to control reservoirs, thereby obtaining a comprehensive score for the potential of each fault to control reservoirs.

4. The method for fracture interpretation and reservoir control potential assessment based on hydrocarbon microleakage and alteration information as described in claim 3, characterized in that: Based on spatial overlap rate, oil and gas hydrocarbon micro-leakage alteration area map, directional consistency judgment results, surface exposed fault distribution map, hidden fault inference map, seismic profile fault interpretation data, and multi-source basic data, a fault-controlled reservoir potential assessment index system is constructed. The fault-controlled reservoir potential assessment index system includes three categories: alteration correlation index, tectonic development index, and oil and gas geology index.

5. The method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information as described in claim 1, characterized in that: It also includes, For the faults in the seismic profile fault interpretation data that show strata reflection disorder but do not cut through to the surface, check whether there is an alteration anomaly in the corresponding surface area in the oil and gas hydrocarbon micro-leakage alteration area map. At the same time, check whether there is a fault outcrop recorded at the corresponding location in the field geological survey data, and check whether there is a strata faulting record in the corresponding area in the drilling data. When a fracture meets the following four conditions: the seismic profile shows the presence of the fracture, there is no hydrocarbon micro-leakage and alteration on the surface or only a first-order alteration zone, no fault outcrops are found in the field survey, and drilling data shows no formation faulting, the fracture is identified as a hidden fracture. The properties of the concealed fault are inferred, and the strike and extension length of the concealed fault are determined by comparing multiple seismic profiles. Meanwhile, the burial depth of the concealed fault is calculated based on the two-way reflection time in the seismic profile data, the spatial relationship between the concealed fault and the cover layer is recorded, and the spatial location and attribute information of all concealed faults are integrated to generate a concealed fault inference map. The surface exposed fault distribution map and the concealed fault inference map are overlaid and integrated to generate a comprehensive fault interpretation result map.

6. The method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information as described in claim 1, characterized in that: The verification of the spatial correlation between alteration and fracture includes: Based on the oil and gas hydrocarbon micro-leakage alteration area map, the spatial distribution range of three types of alteration anomaly areas—carbonate mineralization alteration, clay mineralization alteration, and red bed fading alteration—was extracted, and the raster data of the three types of alteration anomaly areas were converted into vector surface features to create alteration anomaly distribution vector data. Based on the alteration anomaly distribution vector data, the standard deviation ellipse of the carbonate mineralization alteration region, the clay mineralization alteration region, and the red bed fading alteration region were calculated using the directional distribution statistical method, respectively, to obtain the standard deviation ellipse data of the alteration region for each of the three types of alteration regions. The standard deviation ellipse data of the alteration region includes the length of the major axis of the ellipse, the length of the minor axis of the ellipse, and the azimuth of the major axis of the ellipse. Acquire spatial distribution data of existing fracture structures in the study area, convert the spatial distribution data of the fracture structures into fracture vector line elements, and generate fracture distribution vector data. Based on the fracture distribution vector data, the standard deviation ellipse of all fractures in the study area is calculated using the directional distribution statistical method to obtain fracture distribution standard deviation ellipse data, wherein the fracture distribution standard deviation ellipse data includes the length of the major axis of the ellipse, the length of the minor axis of the ellipse, and the azimuth of the major axis of the ellipse. Calculate the azimuth deviation between the azimuth of the major axis of the ellipse of the three types of alteration regions in the standard deviation ellipse data of the alteration region and the azimuth of the major axis of the ellipse of the standard deviation ellipse data of the fracture distribution; Based on the comparison results between the azimuth deviation value and the preset deviation threshold, the consistency of the direction of each type of alteration region with the fracture distribution is verified.

7. The method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information as described in claim 6, characterized in that: The verification of the consistency between the direction of each type of alteration region and the fracture distribution includes: If the azimuth deviation is less than or equal to the first deviation threshold, then the directional relationship between the alteration region and the fracture distribution is determined to be first-order consistent. If the azimuth deviation value is greater than the first deviation threshold and less than or equal to the second deviation threshold, then the directional relationship between the alteration region and the fracture distribution is determined to be second-order consistent. If the azimuth deviation value is greater than the second deviation threshold, then the directional relationship between the alteration region and the fracture distribution is determined to be level three consistent.

8. The method for fracture interpretation and reservoir potential assessment based on hydrocarbon microleakage and alteration information as described in claim 1, characterized in that: The directional consistency and spatial overlap between the alteration region and the fracture buffer zone were verified using standard deviation elliptic analysis, including: Using each fracture line element in the fracture distribution vector data as the center line, the fracture buffer vector data is generated by expanding to both sides according to the preset buffer radius. The alteration anomaly distribution vector data and the fracture buffer vector data are intersected, and the area of ​​the alteration region falling within the range of the fracture buffer vector data is counted and recorded as the alteration area within the buffer. Simultaneously, the total area of ​​the aforementioned alteration anomaly distribution vector data is statistically analyzed and denoted as the total alteration area of ​​the study area. ; Calculate the alteration area within the buffer zone. With the total alteration area of ​​the study area The ratio of these values ​​yields the spatial overlap rate; The spatial association strength is determined based on the comparison between the spatial overlap rate and the preset spatial association threshold.

9. The method for fracture interpretation and reservoir control potential assessment based on hydrocarbon microleakage and alteration information as described in claim 8, characterized in that: Determining the strength of spatial association includes: When the spatial overlap rate is greater than or equal to the first spatial correlation threshold, the alteration region and the fracture distribution are determined to have a strong spatial correlation. When the spatial overlap rate is less than the first spatial correlation threshold and greater than or equal to the second spatial correlation threshold, the alteration region and the fracture distribution are determined to have a moderate spatial correlation. When the spatial overlap rate is less than the second spatial correlation threshold, the alteration region and the fracture distribution are determined to have a weak spatial correlation, wherein the first spatial correlation threshold is greater than the second spatial correlation threshold.

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