A method for enhancing high-angle fracture information

Abstract

The present invention relates to a high-angle fracture information enhancement method, which belongs to the technical field of oil and gas field exploration. The method first performs structural guidance filtering on three-dimensional seismic data of a target area, performs two-dimensional correlation analysis on the filtering results to calculate correlation coefficient arrays of seismic data bodies in different directions, then enhances high-angle signals of three different planes based on the correlation coefficient arrays, and calculates fracture indicator factor arrays corresponding to different directions, and finally fuses the three groups of high-angle fracture indicator factors to obtain a data body after high-angle fracture information enhancement. The method suppresses random noise and improves the prediction accuracy of high-angle fractures or crack zones.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas field exploration, and in particular to a high-angle fracture information enhancement method. Background Art

[0002] The discovery of effective reservoirs in the inner zone of buried hills has changed the previous understanding that effective reservoir sections are only distributed in the top weathering zone, enriched and improved the development pattern of buried hill fractures, and also explained the huge potential of the inner zone of buried hills, opening up new ideas for buried hill oil and gas exploration. Compared with the weathering zone, the number of low-angle fractures in the inner zone is reduced, and the proportion of high-angle fractures is increased, but the reservoirs in the inner zone are generally poor, while the reservoirs in the inner zone in areas with high-angle faults are generally well developed. How to accurately predict the high-angle fault information in the inner zone of buried hills has become one of the focuses in the field of oil and gas field exploration. At present, conventional high-angle fracture identification methods include body wave amplitude comparison method, resonance frequency method, linear time-frequency analysis method, etc., and conventional enhancement methods include wavelet threshold denoising algorithm, structure tensor algorithm, non-local mean filtering, etc.

[0003] However, conventional identification and enhancement methods have some defects. When processing low signal-to-noise ratio seismic data, the signal-to-noise ratio of seismic profile imaging can only be improved if the frequency band of the seismic data is consistent with the frequency band of the formation resonance response (Huang Dezhi, 2017). Linear time-frequency analysis is a convolution operation between the signal and other functions, which has information leakage problems and low precision (Zhang Hongmao, 2023). The classic wavelet threshold denoising algorithm uses a global threshold setting method, and the noise in the seismic data has obvious time and space transformation properties. The use of a global threshold denoising method is prone to over-killing or over-retention (Xu Zilong, 2021). At present, there are few studies on high-angle faults. For the high-angle reflection formed by large-scale fractures inside the buried hill, the enhanced information is reconstructed by enhancing the curve coefficients at the corresponding position in the curve domain (Zhang Zhijun, 2021). High-angle fractures usually develop around high-angle fractures. fk filtering and high-linear Radon transform can extract high-angle fractures from post-stack seismic data, but the resolution is low and there are illusions (Fan Yanen, 2022).

[0004] Based on sufficient research and actual data application, the present invention believes that the existing high-angle fracture signal recognition and enhancement technology has at least the following problems in fracture prediction:

[0005] (1) Limitations of single-direction identification: Conventional single-direction fault identification methods only consider a certain direction or specific attribute of seismic data, ignoring information in other directions or attributes, which may lead to the inability to fully utilize multi-source data and global information, affecting the comprehensiveness and integrity of the results. At the same time, conventional single-direction fault identification methods often rely on pre-set thresholds or rules to determine whether a fault exists or not. However, for different seismic data, the selection of thresholds and rules may lead to misjudgment or omission, resulting in inaccuracy and bias in the identification results.

[0006] (2) Limitations of improving resolution: Conventional signal enhancement methods often require operations such as signal filtering and noise reduction. These operations will limit the frequency range of the signal and may cause the loss of signal detail information, thereby affecting the resolution of the signal. Conventional methods cannot adapt to complex and changeable actual situations, thereby reducing the resolution and clarity of the signal. Summary of the invention

[0007] In order to solve the problem that the prior art cannot accurately identify high-angle faults in the inner zone, the present invention proposes a method for enhancing high-angle fault information. The method calculates the correlation coefficient array of seismic data bodies in different directions through a two-dimensional correlation algorithm, and then combines different methods to perform plane image and dip extension continuity enhancement processing for different plane data bodies, enhances the high-angle signal in the data body, and obtains three groups of high-angle fault indicator factor arrays. Finally, the three groups of high-angle fault indicator factor arrays are fused to obtain a data body with significantly enhanced high-angle information and clear fault boundaries, which can accurately identify high-angle cracks around high-angle faults, overcome the defects of the prior art, and obtain good results.

[0008] The specific technical solutions are as follows:

[0009] (1) Input the 3D seismic data array S of the target area, which includes the line number (X direction), channel number (Y direction) and time sampling point number (Z direction);

[0010] (2) Perform structural guidance filtering on the three-dimensional seismic data array S, and record the filtered array as SP;

[0011] (3) Calculate the correlation coefficient arrays of array SP in three ways: along the XOY plane, along the XOZ plane, and along the YOZ plane. The three correlation coefficient arrays are SC_XOY, SC_XOZ, and SC_YOZ.

[0012] (4) For the correlation coefficient array SC_XOY, perform fault plane continuity enhancement processing on the XOY plane, and record the processed array as the fracture indicator factor array SE_XOY corresponding to the XOY plane;

[0013] (5) For the correlation coefficient array SC_XOZ, the dip extension continuity enhancement processing is performed, and the processed array is recorded as the fracture indicator factor array SE_XOZ corresponding to the XOZ plane;

[0014] (6) Using the same method as step (5), calculate the fracture indicator factor array SE_YOZ corresponding to the YOZ plane for the correlation coefficient array SC_YOZ;

[0015] (7) The three fracture indicator factor arrays SE_XOY, SE_XOZ and SE_YOZ are fused to obtain a fracture indicator factor array SN.

[0016] Compared with the prior art, the present invention can achieve the following positive technical effects:

[0017] (1) Accuracy of high-angle information extraction: Seismic signals may have different characteristics and information in different directions and angles. When calculating the correlation coefficient array of a single data body to extract high-angle signals, it may not be possible to obtain comprehensive information. The present invention calculates the correlation coefficient array along the XOY plane, along the XOZ plane, and along the YOZ plane, performs image plane continuity enhancement processing on the XOY plane, and performs dip extension continuity enhancement processing on the XOZ plane and the YOZ plane to obtain three sets of high-angle fracture indicator factor arrays and merge them. Compared with the conventional method of calculating a single data body, more comprehensive information can be obtained, revealing its spatial distribution and morphological characteristics, laying a foundation for accurate prediction of high-angle cracks in the later stage.

[0018] (2) Improving the resolution of high-angle fault signals: By acquiring seismic data from multiple directions and fusing the data, the signal-to-noise ratio of the seismic data can be significantly improved. By analyzing the seismic signals in different directions, the azimuth of the high-angle fault can be determined. The data acquired in different directions may be subject to different interferences and noises, but after fusion, these interferences can be weakened or eliminated, and the high-angle fault signal can be enhanced, making the target signal clearer. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a technical flow chart of the present invention;

[0020] Figure 2 It is the cross section of 3D seismic data of the target area;

[0021] Figure 3 To construct a profile of the guided filtering results;

[0022] Figure 4 Seismic profiles before and after enhancement of randomly extracted high-angle signals. Figure 4 -(a) is a cross-sectional view without high-angle signal enhancement. Figure 4 -(b) is the cross-sectional view after high-angle signal enhancement; DETAILED DESCRIPTION

[0023] Example 1

[0024] A high-angle fracture information enhancement method, comprising the steps of:

[0025] Step 1: Input the 3D seismic data S(x,y,t) of the target area, where x represents the line number, y represents the channel number, and t represents the number of time sampling points;

[0026] Step 2: Use a construction-guided filtering method to perform construction-guided filtering on the array S(x, y, t). The construction-guided filtering method used in the present invention is a public method, which is the method of the paper "Application of Construction-Guided Filtering Technology in Fault Identification" published by Zhao Fengquan et al. in 2018. The array after filtering is denoted as SP(x, y, t);

[0027] Step 3: Calculate the correlation coefficient array of array SP(x,y,t) in three ways:

[0028] Step 3-1: Calculate along the XOY plane to obtain the correlation coefficient array SC_XOY(x,y,t).

[0029]

[0030] Where x i represents the i-th number in the X direction, y i represents the i-th number in the Y direction, represents the average value in the X direction, represents the average value in the Y direction, N represents the length of the calculation window, which is set to 5 in the present invention;

[0031] Step 3-2: Use the same method as step 3-1 to calculate along the XOZ plane and along the YOZ plane to obtain the correlation coefficient arrays SC_XOZ(x,y,t) and SC_YOZ(x,y,t);

[0032] Step 4: for the correlation coefficient array SC_XOY(x, y, t), perform image plane continuity enhancement processing on the XOY plane. The image plane continuity enhancement processing method adopted in the present invention is a public method, which is the method of the paper “Anisotropic diffusion in image processing” published by Weickert J in 1998. The processed array is recorded as the fracture indicator factor array SE_XOY(x, y, t) corresponding to the XOY plane.

[0033] Step 5: For the correlation coefficient array SC_XOZ(x,y,t), perform the trend extension continuity enhancement process.

[0034] Sx=epx(x,y,t) ,Sz(x,y,t)=e pt(x,y,t) ,

[0035] Where P x (x,y,t) is the inclination array of the array SC_XOZ(x,y,t) in the x direction, P t (x,y,t) is the inclination array of the array SC_XOZ(x,y,t) in the t direction, and SE_XOZ(x,y,t) is the fracture indicator factor array corresponding to the XOZ plane;

[0036] Step 6: Using the same method as step 5, calculate the correlation coefficient array SC_YOZ(x,y,t) and the fracture indicator factor array SE_YOZ(x,y,t) corresponding to the YOZ plane;

[0037] Step 7: Merge the three break indicator arrays SE_XOY(x,y,t), SE_XOZ(x,y,t) and SE_YOZ(x,y,t),

[0038] a(x,y,t)=SE_XOY(x,y,t)+SE_XOZ(x,y,t)+SE_YOZ(x,y,t),

[0039] b(x,y,t)=SE_XOY(x,y,t) 2 +SE_XOZ(x,y,t) 2 +SE_YOZ(x,y,t) 2 ,

[0040]

[0041] Where SN(x,y,t) is the array of high-angle fracture indicator factors.

[0042] Example 2

[0043] Figure 2 and Figure 3 They are the 3D seismic data of the target layer section in a certain study area in Bohai Sea and the cross-section diagram of the structural guidance filtering result. The time range of the target layer section is 3000-5000ms. Figure 4 From the seismic profiles before and after the randomly extracted high-angle signal enhancement of the target layer segment, after the application of the present invention, the high-angle fault signal is accurately extracted, the horizontal and low-angle fault signals are eliminated, the target fault is well retained, and the high-angle fault enhancement effect is significant, laying the foundation for the subsequent accurate prediction of high-angle cracks in the inner zone.

[0044] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A high-angle fracture information enhancement method, characterized in that: Including the following steps: Step 1: Input 3D seismic data of the target area S(x,y,t) ,in x Indicates the line number, y Indicates the road number, t Indicates the number of time sampling points; Step 2: Use the guided filtering method to construct the array S(x,y,t) Perform construction-guided filtering, and record the filtered array as SP(x,y,t) ; Step 3: Calculate the array in three ways SP(x,y,t) An array of correlation coefficients: Step 3-1: Along XOY Plane calculation to get the correlation coefficient array SC_XOY(x,y,t) , ， In the formula express X Direction Number, express Y Direction Number, express X The average value of the direction, express Y The average value of the direction, N represents the calculation window length, N is set to 5; Step 3-2: Use the same method as step 3-1, along XOZ Plane and along Y OZ Plane calculation to get the correlation coefficient array SC_XOZ(x,y,t) and SC_YOZ(x,y,t) ; Step 4: For the correlation coefficient array SC_XOY(x,y,t) ,Do XOY The image plane continuity enhancement processing on the plane, the processed array is recorded as XOY Array of fracture indicator factors corresponding to the plane SE_XOY(x,y,t) ; Step 5: For the correlation coefficient array SC_XOZ(x,y,t) , do the tendency extension continuity enhancement processing, ， ， ， In the formula P x (x,y,t) is an array SC_XOZ(x,y,t) exist x An array of inclination angles of the direction, P t (x,y,t) is an array SC_XOZ(x, y,t) exist t An array of inclination angles of the direction, SE_XOZ(x,y,t) for XOZ The fracture indicator factor array corresponding to the plane; Step 6: Use the same method as step 5 to calculate the correlation coefficient array SC_YOZ(x,y,t) ,calculate YOZ Array of fracture indicator factors corresponding to the plane SE_YOZ(x,y,t) ; Step 7: Merge the three break indicator arrays SE_XOY(x,y,t), SE_XOZ(x,y,t) and SE_YOZ(x,y,t) , ， ， ， In the formula SN(x,y,t) is an array of high-angle fracture indication factors.

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