阅读说明：本技术 基于构造背景的重力断裂影像识别方法 (Gravity fracture image identification method based on construction background ) 是由 冯国志 谷玉田 林会喜 谭绍泉 郭涛 尹克敏 王树华 李守济 张建华 杨国杰 于 2019-10-24 设计创作，主要内容包括：本发明提供一种基于构造背景的重力断裂影像识别方法,包括：步骤1,进行布格重力异常预处理,形成开展处理解释的基础资料；步骤2,进行重力差值趋势面场源分离,定量刻画目标地层的重力异常响应；步骤3,进行重力异常增强与处理转换,增强线性构造微弱信息,凸显小级别断裂线性影像；步骤4,联合多种处理转换成果建立窄化梯度带的非线性目标函数；步骤5,进行断裂线性影像综合分析,确定不同级别的断裂产状及组合样式。该基于构造背景的重力断裂影像识别方法提高了重力资料精细刻画断裂目标的有效性和实用性,提高了横向分辨能力,突出了断裂边界特征,可以更清晰的识别断裂构造格架。(The invention provides a gravity fracture image identification method based on a construction background, which comprises the following steps: step 1, performing Booth gravity anomaly preprocessing to form basic data for developing processing explanation; step 2, separating the gravity difference trend surface field sources, and quantitatively describing the gravity abnormal response of the target stratum; step 3, performing gravity anomaly enhancement and processing conversion, enhancing weak information of linear structure, and highlighting small-level fracture linear image; step 4, establishing a nonlinear objective function of the narrowed gradient band by combining a plurality of processing conversion results; and 5, comprehensively analyzing the fracture linear image, and determining fracture occurrence and combination patterns of different levels. The gravity fracture image identification method based on the construction background improves the effectiveness and the practicability of gravity data fine depiction of fracture targets, improves the transverse resolution capability, highlights fracture boundary characteristics and can more clearly identify fracture construction grillage.)

1. The gravity fracture image identification method based on the constructed background is characterized by comprising the following steps of:

step 1, performing Booth gravity anomaly preprocessing to form basic data for developing processing explanation;

step 2, separating the gravity difference trend surface field sources, and quantitatively describing the gravity abnormal response of the target stratum;

step 3, performing gravity anomaly enhancement and processing conversion, enhancing weak information of linear structure, and highlighting small-level fracture linear image;

step 4, establishing a nonlinear objective function of the narrowed gradient band by combining a plurality of processing conversion results;

and 5, comprehensively analyzing the fracture linear image, and determining fracture occurrence and combination patterns of different levels.

2. The gravity fracture image recognition method based on the construction background as claimed in claim 1, wherein in step 1, preprocessing the data of the grid-distribution gravity anomaly scatter points, including abnormal point elimination, adjustment and gridding, so that the gravity anomaly measurement point values are reasonably returned and grid-distribution gravity anomaly data for the next development processing interpretation is formed; the pretreatment of the Booth gravity anomaly specifically comprises the following steps:

1a) removing abnormal points: according to the geological background, abnormal distortion points of gravity measurement caused by errors of a measuring instrument are removed, and errors caused by the distortion points are removed;

2a) adjustment: when the data consists of a plurality of blocks, calculating the average value of the data of the overlapped part of each block of data, and leveling each block of data by using the average value difference to form unified spliced data;

3a) gridding: gridding the gravity scatter data by using a Krigin linear interpolation method, an inverse distance weighted interpolation method and a minimum curvature interpolation method, and preferably selecting grid data separated by a gravity data field source according to the comparison effect of the scatter data value and the grid data value;

4a) denoising, namely eliminating linear errors caused by measuring lines and small and disordered gravity anomalies caused by uneven density distribution near the ground surface by using a low-pass filter to form the original data of the Booth gravity anomalies processed in the next step.

3. The method for identifying gravity fracture images based on construction background as claimed in claim 2, wherein in step 3a, the meshing distance of the gravity data is set to be half of the distance between the actual measurement points of the gravity data.

4. The gravity fracture image recognition method based on the construction background according to claim 1, wherein in step 2, a high-order difference trend surface analysis processing means is adopted to perform trend surface and difference analysis on the lattice gravity data, and quantitatively separate the gravity field; performing multiple times of trend surface fitting on the gravity anomaly by utilizing a high-order difference trend surface analysis technology to obtain multiple gravity trend surface anomalies, subtracting the original grid gravity anomaly from each time of trend surface anomaly to obtain a residual trend surface anomaly, and subtracting the different trend surface anomalies to obtain a difference trend surface anomaly; according to the fitting degree rate index of the difference value trend surface analysis and the regional geological background, different trend surfaces, residuals and difference value anomalies are selected and are subjected to statistical comparison analysis with the depths of all the stratums, and the gravity anomaly generated by the target stratum is selected according to the fitting degree, so that the quantitative separation of the gravity field is realized.

5. The gravity fracture image recognition method based on the construction background according to claim 1, wherein in step 3, a tilt angle processing method is adopted to enhance weak gravity anomaly information; and performing differentiation highlighting on the gravity abnormal features generated by the fracture by using the processing means of horizontal derivatives and horizontal total gradients in different directions, and analyzing the total features of the fractures in different trends.

6. The method for identifying gravity fracture images based on construction background as claimed in claim 5, wherein step 3 comprises:

1c) weak abnormal enhancement: carrying out derivative and inclination angle equalization filtering processing on the gravity anomaly, and enhancing the weak anomaly information of the gravity linearity to reflect the fracture with large burial depth or small density difference;

2c) and (3) qualitatively judging the fracture trend: carrying out horizontal derivative processing on the gravity anomaly in different directions, wherein the horizontal derivative processing is mainly carried out in the directions of 0 degrees, 45 degrees, 90 degrees and 135 degrees, the fracture trend is vertical to the processing direction, and the fracture position is the maximum or minimum position of the processed data;

3c) and (3) fracture position qualitative analysis: and finally, carrying out horizontal total gradient processing on the gravity anomaly, comprehensively depicting the gravity anomaly linear gradient band in each direction, and positioning the fracture position at the maximum position of the processed data.

7. The method for identifying gravity fracture images based on construction background as claimed in claim 1, wherein in step 4, various types of processing result data are optimized, a nonlinear objective function of a narrowing gradient band is established by combining various processing conversion results, the gradient linear abnormal band is converged, gravity gradient abnormality and background gravity field are fused, and fracture objective and fracture grade are highlighted.

8. The method for identifying gravity fracture images based on construction background as claimed in claim 7, wherein in step 4, a convergence factor is introduced to establish a nonlinear objective function of a narrowed gradient band in combination with a plurality of processing transformation results, and a linear abnormal band is further sharpened; and then, the gravity gradient abnormality and the background gravity field are fused, so that the fracture boundary characteristics are clearer, and the grade, the occurrence and the combination style of the fracture are highlighted.

9. The method for identifying gravity fracture images based on construction background as claimed in claim 8, wherein in step 4, the formula for calculating the nonlinear objective function of the narrowed gradient band is:

C＝A·X^m+B·Yⁿ，

x, Y is respectively gravity weak information enhancement abnormity and gravity gradient abnormity, A, B is a weight coefficient, m and n are focusing coefficients, the values of the weight coefficient and the focusing coefficients determine the highlighting and narrowing capabilities of gravity fracture linear abnormity, the calculation scheme is divided into two situations, ① is an area with other geophysical prospecting data, the maximum similarity of the gravity fracture linear abnormity C and other geophysical data plane fracture results is the target, a least square optimization algorithm is used for obtaining a coefficient value, the coefficient value is used as a reference value to be expanded to the whole area, ② is an area without other geophysical data, geological knowledge and similar geological structure area experience are used for reference, and the optimal gravity fracture linear abnormity C is obtained by optimizing the coefficient value.

10. The gravity fracture image recognition method based on the construction background according to claim 1, wherein in step 5, fracture occurrence and combination patterns of different levels are comprehensively analyzed according to gravity linear anomaly; and qualitatively describing the linear gradient abnormal characteristics of convergence by combining with the regional structure background, and comprehensively analyzing fracture trend, inclination and dip angle occurrence elements and combination patterns from a three-dimensional angle.

Technical Field

The invention relates to the technical field of area structure fracture identification, in particular to a gravity fracture image identification method based on a structure background.

Background

The fracture research has very important significance in the aspects of ore finding, water finding, oil and gas finding, hydraulic engineering construction and the like, and because the fracture is a channel of mineral liquid, the formation and occurrence positions of ore bodies are controlled. The fracture can also destroy the formed ore body, and the continuation of the ore body can be inferred only according to the fracture property. Fractures are important pathways for hydrocarbon migration enrichment, and exploration of hydrocarbons must pinpoint the fracture structure. When the engineering construction is carried out, the fault condition of the foundation must be known in detail so as to determine a better engineering base and ensure the stability of the engineering.

In addition to direct identification of surface fractures according to geological investigation, deep fracture identification is mainly applied to various geophysical prospecting technologies at present, including various exploration means such as gravity, magnetic force, electrical method, earthquake and the like, for example, a high-density electrical method is used for identifying shallow fractures in engineering construction, and data in-phase axis changes are used for identifying fractures in an earthquake exploration method.

The qualitative and quantitative interpretation of fractures based on various anomalous features in the gravitational field is one of the important aspects of geologic structure research using gravity data. The method for identifying the fracture by adopting the gravity anomaly has various technologies, and the commonly used data processing method comprises a horizontal direction derivative, continuation, filtering, a horizontal total gradient and the like, and the methods have commonality in principle, mainly comprise the steps of processing and converting data to highlight a fracture target gravity anomaly step band, comprehensively determining fracture positions of different scales by using extreme value positions or zero value positions, and further comprehensively dividing a fracture system and researching fracture grades, conditions and combination patterns. However, the conventional methods have some technical defects, such as unobvious fracture boundary characteristics, often wide gradient band range, low transverse resolution, and inaccurate fracture position and trend identification; in addition, since only the abnormal step band is processed, the properties of different levels of fracture in the area cannot be described in detail, and thus the accuracy of identifying the fracture by the gravity data is not high. Therefore, a new gravity fracture image identification method based on a construction background is invented, and the technical problems are solved.

Disclosure of Invention

The invention aims to provide a gravity fracture image recognition method based on a structure background, which can finely depict the occurrence and combination patterns of fractures of different levels and improve the recognition of regional geological structures.

The object of the invention can be achieved by the following technical measures: the gravity fracture image identification method based on the constructed background comprises the following steps: step 1, performing Booth gravity anomaly preprocessing to form basic data for developing processing explanation; step 2, separating the gravity difference trend surface field sources, and quantitatively describing the gravity abnormal response of the target stratum; step 3, performing gravity anomaly enhancement and processing conversion, enhancing weak information of linear structure, and highlighting small-level fracture linear image; step 4, establishing a nonlinear objective function of the narrowed gradient band by combining a plurality of processing conversion results; and 5, comprehensively analyzing the fracture linear image, and determining fracture occurrence and combination patterns of different levels.

The object of the invention can also be achieved by the following technical measures:

in step 1, preprocessing the scattered point data of the abnormal grid gravity, including abnormal point elimination, adjustment and gridding, so that the abnormal gravity measurement point value is reasonably returned and gridded abnormal grid gravity data for the next development and interpretation is formed; the pretreatment of the Booth gravity anomaly specifically comprises the following steps:

1a) removing abnormal points: according to the geological background, abnormal distortion points of gravity measurement caused by errors of a measuring instrument are removed, and errors caused by the distortion points are removed;

2a) adjustment: when the data consists of a plurality of blocks, calculating the average value of the data of the overlapped part of each block of data, and leveling each block of data by using the average value difference to form unified spliced data;

3a) gridding: gridding the gravity scatter data by using a Krigin linear interpolation method, an inverse distance weighted interpolation method and a minimum curvature interpolation method, and preferably selecting grid data separated by a gravity data field source according to the comparison effect of the scatter data value and the grid data value;

4a) denoising, namely eliminating linear errors caused by measuring lines and small and disordered gravity anomalies caused by uneven density distribution near the ground surface by using a low-pass filter to form the original data of the Booth gravity anomalies processed in the next step.

In step 3a, the gravity data gridding interval is set to be one half of the actual gravity data point interval.

In step 2, a high-order difference trend surface analysis processing means is adopted to carry out trend surface and difference analysis on the lattice gravity data, and a gravity field is quantitatively separated; performing multiple times of trend surface fitting on the gravity anomaly by utilizing a high-order difference trend surface analysis technology to obtain multiple gravity trend surface anomalies, subtracting the original grid gravity anomaly from each time of trend surface anomaly to obtain a residual trend surface anomaly, and subtracting the different trend surface anomalies to obtain a difference trend surface anomaly; according to the fitting degree rate index of the difference value trend surface analysis and the regional geological background, different trend surfaces, residuals and difference value anomalies are selected and are subjected to statistical comparison analysis with the depths of all the stratums, and the gravity anomaly generated by the target stratum is selected according to the fitting degree, so that the quantitative separation of the gravity field is realized.

In step 3, enhancing weak gravity anomaly information by adopting an inclination angle processing method; and performing differentiation highlighting on the gravity abnormal features generated by the fracture by using the processing means of horizontal derivatives and horizontal total gradients in different directions, and analyzing the total features of the fractures in different trends.

The step 3 comprises the following steps:

1c) weak abnormal enhancement: carrying out derivative and inclination angle equalization filtering processing on the gravity anomaly, and enhancing the weak anomaly information of the gravity linearity to reflect the fracture with large burial depth or small density difference;

2c) and (3) qualitatively judging the fracture trend: carrying out horizontal derivative processing on the gravity anomaly in different directions, wherein the horizontal derivative processing is mainly carried out in the directions of 0 degrees, 45 degrees, 90 degrees and 135 degrees, the fracture trend is vertical to the processing direction, and the fracture position is the maximum or minimum position of the processed data;

3c) and (3) fracture position qualitative analysis: and finally, carrying out horizontal total gradient processing on the gravity anomaly, comprehensively depicting the gravity anomaly linear gradient band in each direction, and positioning the fracture position at the maximum position of the processed data.

In step 4, various processing result data are optimized, a nonlinear target function of a narrowing gradient zone is established by combining various processing conversion results, a gradient linear abnormal zone is converged, gravity gradient abnormality and a background gravity field are fused, and a fracture target and a fracture grade are highlighted.

In step 4, firstly combining a plurality of processing conversion results, introducing a convergence factor to establish a nonlinear target function of a narrowed gradient band, and further sharpening a linear abnormal band; and then, the gravity gradient abnormality and the background gravity field are fused, so that the fracture boundary characteristics are clearer, and the grade, the occurrence and the combination style of the fracture are highlighted.

In step 4, the calculation formula of the established nonlinear objective function of the narrowing gradient band is as follows:

C＝A·X^m+B·Yⁿ，

x, Y is respectively gravity weak information enhancement abnormity and gravity gradient abnormity, A, B is a weight coefficient, m and n are focusing coefficients, the values of the weight coefficient and the focusing coefficients determine the highlighting and narrowing capabilities of gravity fracture linear abnormity, the calculation scheme is divided into two situations, ① is an area with other geophysical prospecting data, the maximum similarity of the gravity fracture linear abnormity C and other geophysical data plane fracture results is the target, a least square optimization algorithm is used for obtaining a coefficient value, the coefficient value is used as a reference value to be expanded to the whole area, ② is an area without other geophysical data, geological knowledge and similar geological structure area experience are used for reference, and the optimal gravity fracture linear abnormity C is obtained by optimizing the coefficient value.

In step 5, comprehensively analyzing fracture occurrence and combination patterns of different levels according to the gravity linear abnormity; and qualitatively describing the linear gradient abnormal characteristics of convergence by combining with the regional structure background, and comprehensively analyzing fracture trend, inclination and dip angle occurrence elements and combination patterns from a three-dimensional angle.

The invention discloses a gravity fracture image identification method based on a structural background in a new area with low exploration degree or when seismic data are less and the requirement of area exploration work is difficult to meet. The technical scheme adopted by the invention is as follows: preprocessing the gravity potential field data to form basic data for developing processing explanation; separating the gravity high-order difference trend surface field sources, and quantitatively describing the gravity abnormal response of different target stratums; enhancing and processing conversion of gravity anomaly, and highlighting small-level fracture linear images; establishing a nonlinear target function of a narrowed gradient zone, converging a gradient linear abnormal zone, fusing gravity gradient abnormality and a background gravity field, and highlighting a fracture target and a fracture grade; and comprehensively analyzing the fracture linear image, and identifying fracture occurrence and combination patterns of different levels. The invention adopts the gravity potential field difference trend surface to realize the fine separation of field sources, and the gradient convergence highlights the fracture target, thereby further finely depicting the fracture occurrence factors and the combination patterns of different levels. The gravity fracture image identification method based on the construction background improves the effectiveness and the practicability of gravity data fine depiction of fracture targets, improves the transverse resolution capability, highlights fracture boundary characteristics and can more clearly identify fracture construction grillage.

Drawings

FIG. 1 is a flowchart of an embodiment of a method for identifying gravity fracture images based on a constructed background according to the present invention;

FIG. 2 is a diagram illustrating a Bruger gravity anomaly in ZZ zone according to an embodiment of the present invention;

FIG. 3 is a diagram of 5 times trend surface anomaly in ZZ region due to gravity anomaly according to an embodiment of the present invention;

FIG. 4 is a diagram illustrating the 5-fold trend surface exception handling transformation for ZZ region gravity anomaly in accordance with an embodiment of the present invention;

FIG. 5 is a graph showing gravity fracture images of 5-fold trend surface of ZZ zone in an embodiment of the present invention.

Detailed Description

In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.

As shown in fig. 1, fig. 1 is a flowchart of a gravity fracture image recognition method based on a structural background according to the present invention.

Step 101, preprocessing the abnormal grid gravity to form basic data of data processing.

Preprocessing scatter data of abnormal grid gravity, including abnormal point elimination, adjustment and gridding, so that a gravity abnormal measurement value is reasonably returned and gridded abnormal grid gravity data of a next development and interpretation is formed;

the pretreatment of the Booth gravity anomaly comprises the following specific steps:

1) removing abnormal points: according to the geological background, abnormal distortion points (single points) of gravity measurement caused by errors of a measuring instrument are eliminated, and errors caused by the distortion points are eliminated;

2) adjustment: when the data consists of a plurality of blocks, calculating the average value of the data of the overlapped part of each block of data, and leveling each block of data by using the average value difference to form unified spliced data;

3) gridding: gridding the gravity scatter data by using a Krigin linear interpolation method, an inverse distance weighted interpolation method, a minimum curvature interpolation method and other methods, and preferably selecting grid data separated by a gravity data field source according to the comparison effect of the scatter data value and the grid data value; the gravity data gridding interval is generally set to be one half of the actual gravity data point interval.

4) Denoising, namely eliminating linear errors caused by measuring lines and small and disordered gravity anomalies caused by uneven density distribution near the ground surface by using a low-pass filter to form the original data of the Booth gravity anomalies processed in the next step.

102, separating gravity difference trend surface field sources, and quantitatively describing the gravity anomaly response of a target stratum; and performing trend surface and difference analysis on the lattice distribution gravity data by adopting a high-order difference trend surface analysis processing means, and quantitatively separating the gravity field. Performing multiple times of trend surface fitting on the gravity anomaly by utilizing a high-order difference trend surface analysis technology to obtain multiple gravity trend surface anomalies, subtracting the original grid gravity anomaly from each time of trend surface anomaly to obtain a residual trend surface anomaly, and subtracting the different trend surface anomalies to obtain a difference trend surface anomaly; according to the fitting degree rate index of the difference value trend surface analysis and the regional geological background, different trend surfaces, residuals and difference value anomalies are selected and are subjected to statistical comparison analysis with the depths of all the stratums, and the gravity anomaly generated by the target stratum is selected according to the fitting degree, so that the quantitative separation of the gravity field is realized.

The high-order difference trend surface analysis field source separation technology is characterized in that f (x, y) is a critical point (x, y) in a space omega (x, y) domain according to field theory and series theory₀,y₀) Separation into e pieces of f (x, y)_iThe degree of fitting of the mathematical model of (1) is C^q。

f(x,y)＝f_q(x,y)+r_q(x,y)

In the formula: f (x, y) is a gravity anomaly expression;

f_q(x, y) is a gravity anomaly trend surface expression, and q is a trend surface number;

r_q(x, y) is a gravity residual anomaly expression;

C^qis a fitting degree expression;

e is the number of assumed independent geological anomalous bodies;

k is a natural number less than q;

degree of fitting C^q(q is 1,2, L, infinity), a Taylor series expansion reflecting f (x, y) is changed along with the inflection point, and a gravity-magnetic function f (x, y) with independent parent distribution is fitted in a topological structure according to the grade_iThe inflection point of (a) or the extreme point of derivation thereof is a characteristic point of separation between the inter-stage and the intra-stage heavy magnetic field source.

Assume f (x, y) is decomposed into e independent parent distribution functions f (x, y) in a topology_iThe composite function formed by superposition has high enough measurement and calculation precision and sufficiently large sampling sample according to the given epsilon > 0 and the known sample f (x)_j，y_j) j is 1,2, L, N, the times q corresponding to e trend surface fitting degree curve extreme points can be selected according to the topology structure₁、q₂And k and q, carrying out step-by-step statistics according to a scale to deduce the gravity and magnetic trend surface abnormality of the underburden, the gravity and magnetic trend surface residual abnormality of the overburden and the gravity and magnetic difference value trend surface abnormality of the target stratum which are most related to the depth of the target stratum.

103, performing gravity anomaly enhancement and processing conversion, enhancing weak information of a linear structure, and highlighting a small-level fracture linear image;

processing methods such as an inclination angle and the like are adopted to enhance weak gravity anomaly information; and performing differentiation highlighting on the gravity abnormal features generated by the fracture by utilizing processing means such as horizontal derivatives, horizontal total gradients and the like in different directions, and analyzing the total features of the fractures in different trends. The method comprises the following steps:

1) weak abnormal enhancement: carrying out derivative, inclination angle and other balanced filtering processing on the gravity anomaly, and enhancing the weak anomaly information of the gravity linearity to reflect the fracture with large burial depth or small density difference;

the inclination angle processing mathematical model is as follows:

in the following steps: g_zz-an abnormal vertical component of gravity;

g_xz-a gravity anomaly x-direction component;

g_yz-a gravity anomaly y-direction component.

2) And (3) qualitatively judging the fracture trend: carrying out horizontal derivative processing on the gravity anomaly in different directions, wherein the horizontal derivative processing is mainly carried out in the directions of 0 degrees, 45 degrees, 90 degrees and 135 degrees, the fracture trend is vertical to the processing direction, and the fracture position is the maximum or minimum position of the processed data;

3) and (3) fracture position qualitative analysis: finally, carrying out horizontal total gradient processing on the gravity anomaly, comprehensively depicting gravity anomaly linear gradient zones in all directions, and positioning the fracture position at the maximum position of the processed data;

and step 104, combining a plurality of processing conversion exceptions to establish a nonlinear objective function of the narrowed gradient band.

Optimizing various processing result data, jointly establishing a nonlinear target function, converging a gradient linear abnormal zone, integrating a background gravity field, and highlighting a fracture target and a fracture grade; firstly, combining a plurality of processing conversion results, introducing a convergence factor to establish a nonlinear target function of a narrowed gradient band, and further sharpening a linear abnormal band; then, the gravity gradient abnormality and the background gravity field are fused, so that the fracture boundary characteristics are clearer, and the grade, the occurrence and the combination pattern of the fracture are highlighted;

the nonlinear function calculation formula of the narrowed linear abnormal band is as follows:

C＝A·X^m+B·Yⁿx, Y is gravity weak information enhanced anomaly and gravity gradient anomaly, A, B is weight coefficient, m and n are focusing coefficients, the values of the weight coefficient and the focusing coefficients determine the highlighting and narrowing capability of gravity fracture linear anomaly, the calculation scheme can be divided into two cases, namely, ① areas with other geophysical prospecting data, the maximum similarity of the gravity fracture linear anomaly C and other geophysical data plane fracture results is the target, a least square optimization algorithm is used for obtaining coefficient values, the coefficient values are used as reference values to be expanded to the whole area, ② areas without other geophysical data, and the reference areas can be used for referenceTexture recognition and similar geological structure regional experience, and optimal gravity fracture linear anomaly C is obtained by optimizing coefficient values.

And 105, comprehensively analyzing the fracture linear image, and identifying fracture occurrence and combination patterns of different levels.

And comprehensively analyzing fracture occurrence and combination patterns of different levels according to the gravity linear abnormity. And qualitatively describing the linear gradient abnormal characteristics of convergence by combining with the regional structure background, and comprehensively analyzing the occurrence factors such as fracture trend, inclination and dip angle and the combination pattern from a three-dimensional angle.

In one embodiment of the present invention, the method comprises the following steps:

first, the gravity potential field is preprocessed to form the basic data of data processing.

In this case, taking the 1:20 ten thousand gravity identification fracture in the ZZ area as an example, firstly, gridding the gravity data, wherein the grid spacing is 250 × 250m, and forming basic data for gravity data field source separation; then denoising the gravity data by using a low-pass filter, and reserving effective signals; fig. 2 is a diagram of gravity anomaly after low-pass filtering in the ZZ region, and it can be seen from the diagram that the anomaly curve is relatively smooth, and the filtering effect is relatively ideal.

And secondly, separating the gravity difference trend surface field sources, and quantitatively describing the gravity anomaly response of the target stratum.

And (4) carrying out 40 times of trend surface analysis on the filtered gravity anomaly, and determining the target stratum gravity response represented by the difference anomaly by combining the regional geological background. FIG. 3 is a map of the difference anomaly between 5 and 10 times of gravity in the area, the anomaly being determined by analysis of the combination to represent the response of the anomaly to gravity in the Jurassic formation in the area.

And thirdly, performing gravity anomaly enhancement and processing conversion to highlight the small-level fracture linear image.

Firstly, processing the difference value abnormality of gravity for 5-10 times, such as derivative, inclination angle and the like, and enhancing the information of the gravity weak abnormality; then carrying out gradient processing on the gravity anomaly, solving the anomaly of a horizontal total gradient derivative, and depicting a gravity anomaly linear gradient zone; and finally, determining the position of the fracture center of mass by using the characteristic value. FIG. 4 is a graph of the anomaly handling transformation of 5-10 times trend surface for gravity anomaly in the area, and it can be seen from FIG. 4 that weak anomaly information is enhanced and the linear gradient anomaly bands in the area are delineated by the horizontal total gradient derivative processing.

And fourthly, combining multiple processing conversion results, introducing a convergence factor to establish a nonlinear target function of a narrowed gradient band, further sharpening a linear abnormal band, and fusing gravity gradient abnormality and a background gravity field to enable fracture boundary characteristics to be clearer and highlight the fracture level. FIG. 5 is a graph of 5-10 difference convergence linear anomalies for the region, with extreme bands representing fracture spread characteristics and amplitudes representing fracture levels. As can be seen from FIG. 5, the fracture gradient linear band is converged and narrowed, and the fracture strike and grade are highlighted.

And fifthly, comprehensively analyzing the fracture linear images, and identifying fracture occurrence and combination patterns of different levels. And (3) carrying out 2-4 steps of treatment on the gravity anomaly of different order difference values, and precisely depicting fracture linear anomaly zones of different target stratums, so that fracture occurrence and combination patterns of different levels are comprehensively analyzed, and powerful geological basis can be provided for further geological comprehensive analysis.

The above-mentioned embodiments are further illustrative of the objects, technical solutions and advantages of the present invention, and it should be understood that the above-mentioned embodiments are only illustrative of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.