Stratum structure-oriented pre-stack texture attribute calculation method and system

Abstract

The invention provides a stratigraphic structure-oriented pre-stack texture attribute calculation method and system, and belongs to the technical field of oil-gas exploration. The method comprises the following steps: acquiring four-dimensional seismic data, and calculating a preliminary dip angle data volume corresponding to the four-dimensional seismic data; constructing a stratigraphic structure-oriented gradient structure tensor matrix GST according to the preliminary inclination angle data body, and calculating a first inclination angle data body based on the stratigraphic structure-oriented gradient structure tensor matrix GST; and according to the first inclination angle data body, constructing a stratigraphic structure-oriented gray-level co-occurrence matrix G, and based on the stratigraphic structure-oriented gray-level co-occurrence matrix G, calculating a texture feature attribute to obtain a texture feature attribute calculation result. According to the method and the system, the pre-stack seismic data is selected, the texture attributes are intuitively extracted according to the stratum structure characteristics, the physical characteristics are clearer, the structure characteristics of the pre-stack seismic data are better described, the stratum change details are more finely described, and the space continuity of a texture characteristic attribute calculation result is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration, and in particular to a stratum structure-oriented prestack texture attribute calculation method, a stratum structure-oriented prestack texture attribute calculation system, a machine-readable storage medium and an electronic device. Background Art

[0002] Texture is an inherent property of almost all surfaces, such as the texture of wood, the weave of fabric, the pattern of crops in the field, etc. It contains important information about the surface structure arrangement and its relationship with the surrounding environment. Since the texture attribute of an image seems to carry useful information for recognition purposes, the texture attribute is one of the most important attributes. In 1973, Haralick extracted texture attributes using gray-level co-occurrence matrix and analyzed them. In 1984, Love used texture features to convert seismic profiles into texture images and applied them to common structures. Texture attributes can be used to distinguish fill channels, stratigraphic heterogeneity, etc., can reflect the visual characteristics of homogeneous phenomena in images, and reflect the stratigraphic and sedimentary structural organization and arrangement attributes of underground strata and sediments that have slow or periodic changes.

[0003] There are many methods for extracting texture attributes, including statistical analysis, structural analysis, signal processing and modeling. The most commonly used one is the gray-level co-occurrence matrix method based on statistical analysis. The existing gray-level co-occurrence matrix method is not effective in extracting texture attributes in areas with obvious stratigraphic changes. At the same time, the calculation of texture attributes is mostly concentrated on post-stack seismic data, ignoring the orientation information and subtle geological structure information carried by pre-stack seismic data. Therefore, how to use pre-stack seismic data to accurately and intuitively extract texture attributes and describe the structural characteristics of pre-stack seismic data is an urgent problem to be solved. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a stratigraphic structure-guided prestack texture attribute calculation method and system to at least solve the above-mentioned problem of failing to accurately and intuitively extract texture attributes to describe the structural characteristics of prestack seismic data.

[0005] In order to achieve the above object, the present invention provides a first aspect of a stratum structure-guided prestack texture attribute calculation method, comprising:

[0006] Collecting four-dimensional seismic data u(x, y, t, d), and calculating a preliminary dip data volume corresponding to the four-dimensional seismic data u(x, y, t, d);

[0007] Constructing a formation structure-oriented gradient structure tensor matrix GST according to the preliminary dip data volume, and performing a first dip data volume calculation based on the formation structure-oriented gradient structure tensor matrix GST;

[0008] A stratum structure-oriented gray-level co-occurrence matrix G is constructed according to the first dip angle data volume, and texture feature attributes are calculated based on the stratum structure-oriented gray-level co-occurrence matrix G to obtain a texture feature attribute calculation result.

[0009] Optionally, the above-mentioned acquisition of four-dimensional seismic data u (x, y, t, d) and calculation of a preliminary dip data volume corresponding to the four-dimensional seismic data u (x, y, t, d) include:

[0010] Collecting four-dimensional seismic data u (x, y, t, d) to be analyzed from pre-stack seismic data;

[0011] Based on the four-dimensional seismic data u(x, y, t, d), the dip scanning method is used to obtain the preliminary dip data volume.

[0012] Optionally, the above-mentioned method of obtaining a preliminary dip data volume based on the four-dimensional seismic data u (x, y, t, d) by using a dip scanning method includes:

[0013] Based on the instantaneous frequency calculation formula, the instantaneous frequency ω(t) of the four-dimensional seismic data u(x, y, t, d) is obtained; wherein the instantaneous frequency calculation formula is:

[0014] represents the instantaneous phase, t represents the acquisition time corresponding to the four-dimensional seismic data, u(t) represents the four-dimensional seismic data, u H (t) represents the Hilbert transform data corresponding to the four-dimensional seismic data;

[0015] Based on the instantaneous wave number calculation formula, the instantaneous wave number k of the four-dimensional seismic data u (x, y, t, d) in the x direction of the survey line is obtained. x (t, x, y) and the instantaneous wave number k in the y direction of the survey line y (t, x, y); the instantaneous wave number calculation formula is:

[0016] Represents the instantaneous phase of 4D seismic data;

[0017] Based on the instantaneous frequency ω(t) of the four-dimensional seismic data u(x, y, t, d), the instantaneous wave number k in the x direction of the survey line x (t, x, y) and the instantaneous wave number k in the y direction of the survey line y (t, x, y), calculate the preliminary inclination data volume; where p(x, y, t, d) = k x (t, x, y) / ω(t), q(x, y, t, d)=k y (t, x, y) / ω(t), p(x, y, t, d) and q(x, y, t, d) are preliminary inclination data volumes.

[0018] Optionally, the above-mentioned construction of the formation structure-oriented gradient structure tensor matrix GST based on the preliminary dip angle data volume includes:

[0019] Acquire new four-dimensional seismic data u′(x, y, t, d) along the stratigraphic structure direction from the pre-stack seismic data;

[0020] Based on the new four-dimensional seismic data u′(x, y, t, d), a stratigraphic structure-oriented gradient structure tensor matrix GST is constructed.

[0021] Optionally, the above-mentioned acquisition of new four-dimensional seismic data u′(x, y, t, d) from the pre-stack seismic data along the stratigraphic structure direction includes:

[0022] According to the preliminary inclination data volume, construct the first rotation matrix R(p) and the second rotation matrix R(q);

[0023] Based on the first rotation matrix R(p) and the second rotation matrix R(q), determine a first calculation grid W′;

[0024] Based on the first computational grid W′, new four-dimensional seismic data u′ (x, y, t, d) are acquired in the pre-stack seismic data.

[0025] Optionally, the determining of the first calculation grid W′ based on the first rotation matrix R(p) and the second rotation matrix R(q) includes:

[0026] Based on the first rotation matrix R(p), the first grid is calculated; where W 1 =R(p)*W,W 1 is the first grid, W represents the initial calculation grid used to acquire four-dimensional seismic data;

[0027] Based on the second rotation matrix R(q), the second grid is calculated; where W 2 =R(q)*W,W 2 is the second grid;

[0028] Based on the first grid and the second grid, a first calculation grid W' is determined.

[0029] Optionally, the above-mentioned gradient structure tensor matrix GST based on formation structure guidance performs first dip angle data volume calculation, including:

[0030] Based on the matrix feature decomposition rule, the gradient structure tensor matrix GST is decomposed; the matrix decomposition formula is:

[0031] υ 1 ,υ 2 and 3are the three eigenvectors of the gradient structure tensor matrix GST, λ 1 , 2 and λ 3 are the three eigenvalues ​​of the gradient structure tensor matrix GST;

[0032] Sort the three eigenvalues ​​of the gradient structure tensor matrix GST and get the largest eigenvalue;

[0033] Based on the vector of the eigenvector corresponding to the maximum eigenvalue in the x direction, the vector in the y direction, and the vector in the t direction, a first inclination angle data volume is calculated.

[0034] Optionally, the gray-level co-occurrence matrix G guided by the stratigraphic structure is constructed according to the first dip angle data volume, including:

[0035] Acquire new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure from the pre-stack seismic data along the direction of the first dip data volume;

[0036] Grayscale conversion is performed on the new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure;

[0037] Based on the grayscale-converted four-dimensional seismic data u″(x, y, t, d), a stratigraphic structure-oriented grayscale co-occurrence matrix G is constructed;

[0038] Among them, the gray level co-occurrence matrix G is:

[0039]

[0040] represents the calculation direction of the gray-level co-occurrence matrix, G(i, j) represents the gray-level co-occurrence matrix, and i and j represent the positions in the gray-level co-occurrence matrix.

[0041] Optionally, the acquisition of new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure from the pre-stack seismic data along the direction of the first dip angle data volume comprises:

[0042] Constructing a third rotation matrix R(p′) and a fourth rotation matrix R(q′) according to the first tilt angle data volume;

[0043] Determine a second calculation grid W″ based on the third rotation matrix R(p′) and the fourth rotation matrix R(q′);

[0044] Based on the second computational grid W″, new four-dimensional seismic data u″(x, y, t, d) guided by the stratum structure are acquired in the pre-stack seismic data.

[0045] Optionally, the gray level co-occurrence matrix G based on the stratum structure orientation calculates the texture feature attribute, including:

[0046] Based on the stratum structure-oriented gray-level co-occurrence matrix G, the statistical probability p of the element G(i, j) in the gray-level co-occurrence matrix G is obtained. ij ;in, N represents the selected gray level;

[0047] Based on the statistical probability p of the element G(i, j) in the gray-level co-occurrence matrix G ij , calculate texture feature attributes.

[0048] Optionally, the above texture feature attribute includes energy value;

[0049] The energy value is calculated as follows:

[0050]

[0051] Among them, Energy represents the energy value.

[0052] Optionally, the above texture feature attributes include contrast;

[0053] The formula for calculating contrast is:

[0054]

[0055] Among them, Contrast represents contrast.

[0056] Optionally, the texture feature attributes include homogeneity;

[0057] The formula for calculating homogeneity is:

[0058]

[0059] Among them, Homogeneity means homogeneity.

[0060] Optionally, the texture feature attribute includes an entropy value;

[0061] The calculation formula of entropy value is:

[0062]

[0063] Among them, Entropy represents the entropy value.

[0064] Optionally, the above texture feature attributes include correlation;

[0065] The formula for calculating the correlation is:

[0066]

[0067] in, Correlation means correlation.

[0068] A second aspect of the present invention provides a stratum structure-guided prestack texture attribute calculation system, comprising:

[0069] A preliminary dip data volume calculation module is used to collect four-dimensional seismic data u (x, y, t, d) and calculate the preliminary dip data volume corresponding to the four-dimensional seismic data u (x, y, t, d);

[0070] A first dip data volume calculation module, used for constructing a formation structure-oriented gradient structure tensor matrix GST according to the preliminary dip data volume, and performing first dip data volume calculation based on the formation structure-oriented gradient structure tensor matrix GST;

[0071] The texture feature attribute calculation module is used to construct a stratum structure-oriented grayscale co-occurrence matrix G according to the first dip angle data volume, and calculate the texture feature attributes based on the stratum structure-oriented grayscale co-occurrence matrix G to obtain the texture feature attribute calculation result.

[0072] In a third aspect of the present invention, a machine-readable storage medium is provided, on which instructions are stored, and when the instructions are executed by a processor, the processor is configured to execute the above-mentioned stratigraphic structure-guided prestack texture attribute calculation method.

[0073] In a fourth aspect of the present invention, an electronic device is provided. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned stratigraphic structure-guided prestack texture attribute calculation method is implemented.

[0074] Through the above technical scheme, a stratigraphic structure-oriented pre-stack texture attribute calculation method and system are provided. Pre-stack seismic data are selected, four-dimensional seismic data u (x, y, t, d) is collected from the pre-stack seismic data, and the preliminary dip data volume corresponding to the four-dimensional seismic data u (x, y, t, d) is calculated. Compared with post-stack seismic data, pre-stack seismic data contains richer stratigraphic and sedimentary information, and there are subtle differences between different azimuths or offsets. According to the preliminary dip data volume, a stratigraphic structure-oriented gradient structure tensor matrix GST is constructed, and the first dip data volume is calculated based on the stratigraphic structure-oriented gradient structure tensor matrix GST, which improves the dip calculation accuracy in the area where the stratigraphic changes sharply, thereby improving the texture attribute calculation accuracy. According to the first dip data volume, a stratigraphic structure-oriented grayscale co-occurrence matrix G is constructed, and the texture feature attributes are calculated based on the stratigraphic structure-oriented grayscale co-occurrence matrix G, and the texture feature attribute calculation results are obtained, which can improve the signal resolution and continuity along the layer direction. The method and system intuitively extract texture attributes based on the formation structural characteristics, with clearer physical properties, and thus better describe the structural characteristics of prestack seismic data, thereby more finely describing the details of formation changes and improving the spatial continuity of the calculation results of texture feature attributes.

[0075] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0077] Figure 1 It is a flow chart of a stratigraphic structure-oriented prestack texture attribute calculation method provided by one embodiment of the present invention;

[0078] Figure 2 It is a flow chart of another stratigraphic structure-guided prestack texture attribute calculation method provided by one embodiment of the present invention;

[0079] Figure 3 It is a schematic diagram of layer-by-layer amplitude slices of four-dimensional pre-stack seismic data provided by one embodiment of the present invention;

[0080] Figure 4 is a schematic diagram of a calculated layer-by-layer texture attribute slice provided by an embodiment of the present invention;

[0081] Figure 5 It is a block diagram of a stratum structure-oriented pre-stack texture attribute calculation system provided by one embodiment of the present invention;

[0082] Figure 6 It is a schematic diagram of the structure of an electronic device provided by a preferred embodiment of the present invention.

[0083] Description of Reference Numerals

[0084] 10 - electronic device, 100 - processor, 101 - memory, 102 - computer program. DETAILED DESCRIPTION

[0085] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0086] Figure 1 is a flow chart of a method for calculating prestack texture attributes guided by stratum structure provided by an embodiment of the present invention. Figure 2 FIG. 1 is a flow chart of another method for calculating prestack texture attributes guided by stratum structure provided by an embodiment of the present invention. Figure 1 and Figure 2 As shown, an embodiment of the present invention provides a stratigraphic structure-guided prestack texture attribute calculation method, comprising:

[0087] S110: collecting four-dimensional seismic data u (x, y, t, d), and calculating a preliminary dip data volume corresponding to the four-dimensional seismic data u (x, y, t, d);

[0088] In some implementations of the present embodiment, the above-mentioned acquisition of four-dimensional seismic data u(x, y, t, d) and calculation of the preliminary dip data body corresponding to the four-dimensional seismic data u(x, y, t, d) include: acquiring the four-dimensional seismic data u(x, y, t, d) to be analyzed from pre-stack seismic data; and obtaining the preliminary dip data body based on the four-dimensional seismic data u(x, y, t, d) by using the dip scanning method.

[0089] Among them, in the four-dimensional seismic data u (x, y, t, d), x represents xline, y represents inline, t represents time, and d represents direction.

[0090] In some implementations of this embodiment, the above-mentioned method of obtaining a preliminary dip data volume based on the four-dimensional seismic data u(x, y, t, d) by using the dip scanning method includes: obtaining the instantaneous frequency ω(t) of the four-dimensional seismic data u(x, y, t, d) based on the instantaneous frequency calculation formula; wherein the instantaneous frequency calculation formula is: represents the instantaneous phase, t represents the acquisition time corresponding to the four-dimensional seismic data, u(t) represents the four-dimensional seismic data, u H(t) represents the Hilbert transform data corresponding to the four-dimensional seismic data; based on the instantaneous wave number calculation formula, the instantaneous wave number k of the four-dimensional seismic data u(x, y, t, d) in the x direction of the survey line is obtained x (t, x, y) and the instantaneous wave number k in the y direction of the survey line y (t, x, y); the instantaneous wave number calculation formula is: represents the instantaneous phase of the four-dimensional seismic data; based on the instantaneous frequency ω(t) of the four-dimensional seismic data u(x, y, t, d), the instantaneous wave number k in the x direction of the survey line x (t, x, y) and the instantaneous wave number k in the y direction of the survey line y (t, x, y), calculate the preliminary inclination data volume; where p(x, y, t, d) = k x (t, x, y) / ω(t), q(x, y, t, d)=k y (t, x, y) / ω(t), p(x, y, t, d) and q(x, y, t, d) are preliminary inclination data volumes.

[0091] Specifically, firstly, the four-dimensional seismic data u(x, y, t, d) to be analyzed is collected from the pre-stack seismic data. Then, the inclination scanning method is used to obtain the preliminary inclination data volume. The specific process of using the inclination scanning method to obtain the preliminary inclination data volume is as follows: first, starting from the definition of instantaneous frequency ω: in: represents the instantaneous phase, u(t) represents the four-dimensional seismic data, and u H (t) is its Hilbert transform; the instantaneous frequency is calculated using the time-frequency representation method, Rewrite as Where: p z (t, f) is the time-frequency representation of the signal spectrum. Get the instantaneous wave number k of the four-dimensional seismic data u (x, y, t, d) in the x direction of the survey line x (t, x, y), according to Get the instantaneous wave number k of the four-dimensional seismic data u (x, y, t, d) in the y direction of the survey line y Finally, the preliminary inclination data volume p(x, y, t, d) is calculated as p(x, y, t, d) = k x (t, x, y) / ω(t), the preliminary inclination data volume q(x, y, t, d) is q(x, y, t, d)=k y (t, x, y) / ω(t), where p(x, y, t, d) represents the apparent dip angle of the four-dimensional seismic data u(x, y, t, d) in the x direction of the survey line, and q(x, y, t, d) represents the apparent dip angle of the four-dimensional seismic data u(x, y, t, d) in the y direction of the lateral line.

[0092] S120: constructing a formation structure-oriented gradient structure tensor matrix GST according to the preliminary dip data volume, and performing first dip data volume calculation based on the formation structure-oriented gradient structure tensor matrix GST;

[0093] In some implementations of the present embodiment, the above-mentioned construction of the stratigraphic structure-oriented gradient structure tensor matrix GST based on the preliminary dip data volume includes: collecting new four-dimensional seismic data u′(x, y, t, d) along the stratigraphic structure direction from the pre-stack seismic data; and constructing the stratigraphic structure-oriented gradient structure tensor matrix GST based on the new four-dimensional seismic data u′(x, y, t, d).

[0094] In some implementations of the present embodiment, the above-mentioned acquisition of new four-dimensional seismic data u′(x, y, t, d) from pre-stack seismic data along the stratigraphic structure direction includes: constructing a first rotation matrix R(p) and a second rotation matrix R(q) based on a preliminary dip data volume; determining a first computational grid W′ based on the first rotation matrix R(p) and the second rotation matrix R(q); and acquiring new four-dimensional seismic data u′(x, y, t, d) in the pre-stack seismic data based on the first computational grid W′.

[0095] In some implementations of this embodiment, the above-mentioned determining the first calculation grid W′ based on the first rotation matrix R(p) and the second rotation matrix R(q) includes: calculating the first grid based on the first rotation matrix R(p); wherein W 1 =R(p)*W,W 1 is the first grid, W represents the initial calculation grid used to collect four-dimensional seismic data; based on the second rotation matrix R(q), the second grid is calculated; where W 2 =R(q)*W,W 2 is the second grid; based on the first grid and the second grid, a first calculation grid W′ is determined.

[0096] Specifically, based on the pre-stack seismic data, new four-dimensional seismic data u′(x, y, t, d) are first selected along the stratigraphic structure direction. The specific process of selecting the new four-dimensional seismic data u′(x, y, t, d) is as follows: First, according to the preliminary dip data volume p(x, y, t, d) and q(x, y, t, d), the first rotation matrix R(p) and the second rotation matrix R(q) are respectively constructed. Among them, taking the rotation around the x-axis as an example, p represents the value of the preliminary inclination data volume p (x, y, t, d) at the center point of the calculation grid W. According to the formula W 1 =R(p)*W to get the first grid. According to the formula W 2=R(q)*W to get the second grid. Update the stratigraphic structure-oriented gradient structure tensor matrix calculation grid, i.e., the first calculation grid W′, according to the first grid and the second grid. Use the first calculation grid W′ to reselect new four-dimensional seismic data u′(x, y, t, d) from the prestack seismic data. Thus, the selection of new four-dimensional seismic data u′(x, y, t, d) is completed. Then, for the stratigraphic structure-oriented four-dimensional seismic data u′(x, y, t, d), the first calculation grid W′ is used to reselect new four-dimensional seismic data u′(x, y, t, d). i Construct the gradient structure tensor matrix GST(x, y, t, d i ), achieving the purpose of constructing the formation structure-oriented gradient structure tensor matrix GST.

[0097] Among them, the specific process of using the first calculation grid W′ to reselect new four-dimensional seismic data u′(x, y, t, d) in the pre-stack seismic data is: first, move along the x direction according to the moving distance of the first grid, and then move along the y direction according to the moving distance of the second grid, and use the pre-stack seismic data circled by the first calculation grid W′ after the final move as the new four-dimensional seismic data u′(x, y, t, d).

[0098] Among them, d i Direction represents the i-th direction in d, for example u(x, y, t, d i ) is the data of the i-th direction of u(x, y, t, d).

[0099] In the above implementation process, before using the first calculation grid W′ to select new four-dimensional seismic data u′(x, y, t, d), the method can also use an interpolation method to make the prestack seismic data more dense to obtain dense prestack seismic data.

[0100] In some implementations of this embodiment, the above-mentioned formation structure-guided gradient structure tensor matrix GST performs first dip angle data volume calculation, including: performing matrix decomposition on the gradient structure tensor matrix GST based on a matrix characteristic decomposition rule; wherein the matrix decomposition formula is: υ 1 ,υ 2 and 3 are the three eigenvectors of the gradient structure tensor matrix GST, λ 1 , 2 and λ 3 are three eigenvalues ​​of the gradient structure tensor matrix GST; the three eigenvalues ​​of the gradient structure tensor matrix GST are sorted to obtain the maximum eigenvalue; based on the vector of the eigenvector corresponding to the maximum eigenvalue in the x direction, the vector in the y direction, and the vector in the t direction, the first inclination data body is calculated.

[0101] Specifically, based on the formation structure-guided gradient structure tensor matrix GST, a high-precision dip data volume is calculated to obtain a first dip data volume. The process of calculating the first dip data volume is as follows: first, the gradient structure tensor matrix GST is matrix decomposed to obtain three eigenvalues ​​of the gradient structure tensor matrix GST, and the three eigenvalues ​​of the gradient structure tensor matrix GST are sorted to obtain the maximum eigenvalue. The eigenvector υ of the obtained maximum eigenvalue is used 1 (x, y, t, d i ) is the vector υ in the x direction 1x (x, y, t, d i ), vector υ in the y direction 1y (x, y, t, d i ) and the vector υ in the t direction 1t (x, y, t, d i ), calculate d i The inclination data volume p′(x, y, t, d i ) and q′(x, y, t, d i ):in, The inclination data volume p′(x, y, t, d i ) and q′(x, y, t, d i ) is the first inclination data volume.

[0102] S130: constructing a stratum structure-oriented gray-level co-occurrence matrix G according to the first dip angle data volume, and calculating texture feature attributes based on the stratum structure-oriented gray-level co-occurrence matrix G to obtain a texture feature attribute calculation result.

[0103] In some implementations of this embodiment, the above-mentioned construction of the stratigraphic structure-oriented grayscale co-occurrence matrix G according to the first dip data body includes: acquiring new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure from the prestack seismic data along the direction of the first dip data body; grayscale conversion of the new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure; based on the grayscale converted four-dimensional seismic data u″(x, y, t, d), constructing the stratigraphic structure-oriented grayscale co-occurrence matrix G; wherein the grayscale co-occurrence matrix G is: represents the calculation direction of the gray-level co-occurrence matrix, G(i, j) represents the gray-level co-occurrence matrix, and i and j represent the positions in the gray-level co-occurrence matrix.

[0104] In some implementations of the present embodiment, the above-mentioned acquisition of new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure from the pre-stack seismic data along the direction of the first dip data body includes: constructing a third rotation matrix R(p′) and a fourth rotation matrix R(q′) according to the first dip data body; determining a second computational grid W″ based on the third rotation matrix R(p′) and the fourth rotation matrix R(q′); and acquiring new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure in the pre-stack seismic data based on the second computational grid W″.

[0105] Specifically, the four-dimensional seismic data u′(x, y, t, d) are first updated along the direction of the first dip angle data body to obtain new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure. The process of obtaining the new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure is as follows: First, according to the first dip angle data body p′(x, y, t, d i ) and q′(x, y, t, d i ), respectively construct the third rotation matrix R(p′) and the fourth rotation matrix R(q′). According to the formula W 3 =R(p′)*W 1 Get the third grid, according to the formula W 4 =R(q′)*W 1 Get the fourth grid. Update the stratigraphic structure-oriented gradient structure tensor matrix calculation grid based on the third grid and the fourth grid to get the second calculation grid W″. Use the second calculation grid W″ to reselect new stratigraphic structure-oriented four-dimensional seismic data u″(x, y, t, d) in the prestack seismic data (the prestack seismic data can be dense prestack seismic data). Thereby, the selection of new stratigraphic structure-oriented four-dimensional seismic data u″(x, y, t, d) is completed. Then, grayscale conversion is performed on the new four-dimensional seismic data u″(x, y, t, d) selected according to the stratigraphic structure direction, and the grayscale level is designated as N. Based on the grayscale-converted four-dimensional seismic data u″(x, y, t, d), a stratigraphic structure-oriented grayscale co-occurrence matrix G is constructed. Thereby, the purpose of constructing the stratigraphic structure-oriented grayscale co-occurrence matrix G based on the first dip data body is achieved.

[0106] In some implementations of this embodiment, the gray level co-occurrence matrix G based on the stratigraphic structure guide calculates the texture feature attribute, including: based on the stratigraphic structure guide gray level co-occurrence matrix G, obtaining the statistical probability p of the element G(i, j) in the gray level co-occurrence matrix G ij ;in, N represents the selected gray level; based on the statistical probability p of the element G(i, j) in the gray level co-occurrence matrix G ij , calculate texture feature attributes.

[0107] Specifically, according to the statistical probability p of the element G(i, j) in the gray level co-occurrence matrix G guided by the stratigraphic structure ij , calculate the texture feature attributes guided by the stratum structure, so as to achieve the purpose of intuitively extracting texture attributes based on the stratum structure characteristics.

[0108] In the above implementation process, the method uses prestack seismic data, uses the stratigraphic structure-guided gradient structure tensor matrix to extract high-precision dip and azimuth information, and intuitively extracts texture attributes based on stratigraphic structure characteristics. The physical characteristics are clearer, and thus the structural characteristics of prestack seismic data are better described, thereby more finely describing the details of stratigraphic changes and improving the spatial continuity of the texture feature attribute calculation results. Based on the grayscale co-occurrence matrix, this method adds stratigraphic structure information and uses prestack seismic data for texture attribute calculation, which has the following advantages:

[0109] 1. This method uses pre-stack seismic data to analyze geological bodies. Compared with post-stack seismic data, pre-stack seismic data contains richer stratigraphic and sedimentary information, and has subtle differences between different azimuths or offsets.

[0110] 2. Based on traditional dip scanning, this method adds stratigraphic structural information and uses the preliminary dip data volume obtained by preliminary calculation to constrain the gradient structure tensor matrix guided by the stratigraphic structure, thereby improving the dip calculation accuracy in areas where the stratigraphic structure changes dramatically, so as to obtain high-precision dip guided by the stratigraphic structure, namely the first dip data volume, thereby improving the calculation accuracy of texture attributes.

[0111] 3. In the process of constructing the grayscale co-occurrence matrix, this method uses high-precision inclination as the stratigraphic structure-guided constraint to construct a stratigraphic structure-guided grayscale co-occurrence matrix. The prestack seismic texture attribute calculation is realized based on the stratigraphic structure-guided grayscale co-occurrence matrix, which can improve the signal resolution and continuity along the layer direction.

[0112] The implementation effect of this method can be found in Figure 3 and Figure 4 , Figure 3 is a schematic diagram of layer-by-layer amplitude slices of four-dimensional prestack seismic data provided by an embodiment of the present invention. Figure 4 It is a schematic diagram of a calculated layer-by-layer texture attribute slice provided by an embodiment of the present invention.

[0113] In some implementations of this embodiment, the above-mentioned texture feature attribute includes an energy value; the calculation formula of the energy value is: Among them, Energy represents the energy value.

[0114] Specifically, energy is defined as the sum of squares of the grayscale co-occurrence matrix element values. The energy value reflects the uniformity of the grayscale distribution and the coarseness of the texture of the image. The energy value is larger in images with uniform grayscale distribution and regular changes. When all elements in the grayscale co-occurrence matrix G are equal, the energy value is low; when some values ​​in the grayscale co-occurrence matrix G are large and other values ​​are small, the energy value is large; when the elements in the grayscale co-occurrence matrix G are concentrated, the energy value is large.

[0115] In some implementations of this embodiment, the above texture feature attribute includes contrast; the calculation formula of contrast is: Among them, Contrast represents contrast.

[0116] Specifically, contrast reflects the contrast of the degree of change in a certain location and its area in the direction of the stratigraphic structure. The deeper the texture grooves, the greater the contrast and the clearer the visual effect; conversely, the smaller the contrast, the shallower the grooves and the blurred the effect. The larger the element value away from the diagonal in the gray-level co-occurrence matrix G, the greater the contrast value.

[0117] In some implementations of this embodiment, the above texture feature attributes include homogeneity; the calculation formula of homogeneity is: Among them, Homogenity means homogeneity.

[0118] Specifically, homogeneity reflects the uniformity of texture changes along the direction of the stratigraphic structure. A large value of homogeneity indicates that there is a lack of change between different regions of the image texture, and the local area is very uniform. When the diagonal elements in the gray-level co-occurrence matrix G have large values, the homogeneity value is large. Therefore, it can be used to quantify the continuity of reflections and reflect the degree of change of the strata. The more consistent the degree of change of the geological body, the greater the homogeneity value.

[0119] In some implementations of this embodiment, the texture feature attribute includes an entropy value; the entropy value is calculated as follows: Among them, Entropy represents the entropy value.

[0120] Specifically, the entropy value reflects the randomness of the degree of texture change along the direction of the stratigraphic structure. When all elements in the gray-level co-occurrence matrix G have the greatest randomness or all values ​​are almost equal, the entropy value is large. That is, the more complex the degree of change of the geological body, the greater the entropy value.

[0121] In some implementations of this embodiment, the above texture feature attributes include correlation; the calculation formula of the correlation is: in, Correlation means correlation.

[0122] Specifically, correlation reflects the similarity between neighboring pixels in the horizontal and vertical directions.

[0123] Figure 5 FIG. 1 is a block diagram of a stratum structure-oriented prestack texture attribute calculation system provided by an embodiment of the present invention. Figure 5 As shown, an embodiment of the present invention provides a stratum structure-guided prestack texture attribute calculation system, comprising:

[0124] A preliminary dip data volume calculation module is used to collect four-dimensional seismic data u (x, y, t, d) and calculate the preliminary dip data volume corresponding to the four-dimensional seismic data u (x, y, t, d);

[0125] A first dip data volume calculation module, used for constructing a formation structure-oriented gradient structure tensor matrix GST according to the preliminary dip data volume, and performing first dip data volume calculation based on the formation structure-oriented gradient structure tensor matrix GST;

[0126] The texture feature attribute calculation module is used to construct a stratum structure-oriented grayscale co-occurrence matrix G according to the first dip angle data volume, and calculate the texture feature attributes based on the stratum structure-oriented grayscale co-occurrence matrix G to obtain the texture feature attribute calculation result.

[0127] Specifically, the system uses pre-stack seismic data and a stratigraphic structure-guided gradient structure tensor matrix to extract high-precision dip and azimuth information, intuitively extracts texture attributes based on stratigraphic structure characteristics, and makes physical properties clearer, thereby better describing the structural characteristics of pre-stack seismic data, thereby more finely describing stratigraphic change details and improving the spatial continuity of texture feature attribute calculation results.

[0128] An embodiment of the present invention further provides a machine-readable storage medium having instructions stored thereon, which, when executed by the processor 100, configures the processor 100 to execute the above-mentioned stratigraphic structure-guided prestack texture attribute calculation method.

[0129] Machine-readable storage media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0130] An embodiment of the present invention also provides an electronic device 10, which includes a memory 101, a processor 100, and a computer program 102 stored in the memory 101 and executable on the processor 100. When the processor 100 executes the computer program 102, the above-mentioned stratigraphic structure-guided prestack texture attribute calculation method is implemented.

[0131] like Figure 6 FIG. 1 is a schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 6 As shown, the electronic device 10 of this embodiment includes: a processor 100, a memory 101, and a computer program 102 stored in the memory 101 and executable on the processor 100. When the processor 100 executes the computer program 102, the steps in the above method embodiment are implemented. Alternatively, when the processor 100 executes the computer program 102, the functions of each module / unit in the above device embodiment are implemented.

[0132] Exemplarily, the computer program 102 may be divided into one or more modules / units, one or more modules / units are stored in the memory 101, and are executed by the processor 100 to complete the present invention. One or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 102 in the electronic device 10. For example, the computer program 102 may be divided into a preliminary inclination data volume calculation module, a first inclination data volume calculation module, and a texture feature attribute calculation module.

[0133] The electronic device 10 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 10 may include, but is not limited to, a processor 100 and a memory 101. Those skilled in the art will appreciate that Figure 6 It is only an example of the electronic device 10 and does not constitute a limitation of the electronic device 10. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0134] The processor 100 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0135] The memory 101 may be an internal storage unit of the electronic device 10, such as a hard disk or memory of the electronic device 10. The memory 101 may also be an external storage device of the electronic device 10, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 10. Further, the memory 101 may also include both an internal storage unit of the electronic device 10 and an external storage device. The memory 101 is used to store computer programs and other programs and data required by the electronic device 10. The memory 101 may also be used to temporarily store data that has been output or is to be output.

[0136] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0137] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program 102 products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program 102 product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0138] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program 102 products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by the computer program 102 instructions. These computer program 102 instructions can be provided to a processor 100 of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor 100 of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0139] These computer program 102 instructions may also be stored in a computer readable memory 101 that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory 101 produce an article of manufacture including an instruction device that implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0140] These computer program 102 instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0141] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0142] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A stratigraphic structure-guided prestack texture attribute calculation method. It is characterized in that include: Collecting four-dimensional seismic data u(x, y, t, d), and calculating a preliminary dip data volume corresponding to the four-dimensional seismic data u(x, y, t, d); Constructing a formation structure-oriented gradient structure tensor matrix GST according to the preliminary dip data volume, and performing a first dip data volume calculation based on the formation structure-oriented gradient structure tensor matrix GST; A stratum structure-oriented gray-level co-occurrence matrix G is constructed according to the first dip angle data volume, and texture feature attributes are calculated based on the stratum structure-oriented gray-level co-occurrence matrix G to obtain a texture feature attribute calculation result.

2. The method for calculating prestack texture attributes guided by stratigraphic structure according to claim 1, It is characterized in that The collecting of four-dimensional seismic data u(x, y, t, d) and calculating the preliminary dip data volume corresponding to the four-dimensional seismic data u(x, y, t, d) include: Collecting four-dimensional seismic data u (x, y, t, d) to be analyzed from pre-stack seismic data; Based on the four-dimensional seismic data u(x, y, t, d), the dip scanning method is used to obtain the preliminary dip data volume.

3. The stratigraphic structure-guided prestack texture attribute calculation method according to claim 2, It is characterized in that The method of obtaining a preliminary dip data volume based on the four-dimensional seismic data u (x, y, t, d) by using a dip scanning method includes: Based on the instantaneous frequency calculation formula, the instantaneous frequency ω(t) of the four-dimensional seismic data u(x, y, t, d) is obtained; wherein the instantaneous frequency calculation formula is: represents the instantaneous phase, t represents the acquisition time corresponding to the four-dimensional seismic data, u(t) represents the four-dimensional seismic data, u H (t) represents the Hilbert transform data corresponding to the four-dimensional seismic data; Based on the instantaneous wave number calculation formula, the instantaneous wave number k of the four-dimensional seismic data u (x, y, t, d) in the x direction of the survey line is obtained. x (t, x, y) and the instantaneous wave number k in the y direction of the survey line y (t, x, y); the instantaneous wave number calculation formula is: Represents the instantaneous phase of 4D seismic data; Based on the instantaneous frequency ω(t) of the four-dimensional seismic data u(x, y, t, d), the instantaneous wave number k in the x direction of the survey line x (t, x, y) and the instantaneous wave number k in the y direction of the survey line y (t, x, y), calculate the preliminary inclination data volume; where p(x, y, t, d) = k x (t, x, y) / ω(t), q(x, y, t, d)=k y (t, x, y) / ω(t), p(x, y, t, d) and q(x, y, t, d) are preliminary inclination data volumes.

4. The method for calculating prestack texture attributes guided by stratigraphic structure according to claim 1, It is characterized in that The step of constructing a formation structure-oriented gradient structure tensor matrix GST according to the preliminary dip angle data volume comprises: Acquire new four-dimensional seismic data u′(x, y, t, d) along the stratigraphic structure direction from the pre-stack seismic data; Based on the new four-dimensional seismic data u′(x, y, t, d), a stratigraphic structure-oriented gradient structure tensor matrix GST is constructed.

5. The method for calculating prestack texture attributes guided by stratum structure according to claim 4, It is characterized in that The method of acquiring new four-dimensional seismic data u′(x, y, t, d) from the pre-stack seismic data along the stratum structure direction includes: According to the preliminary inclination data volume, construct the first rotation matrix R(p) and the second rotation matrix R(q); Based on the first rotation matrix R(p) and the second rotation matrix R(q), determine a first calculation grid W′; Based on the first computational grid W′, new four-dimensional seismic data u′(x, y, t, d) are acquired in the pre-stack seismic data.

6. The method for calculating prestack texture attributes guided by stratum structure according to claim 5, It is characterized in that The determining of the first calculation grid W′ based on the first rotation matrix R(p) and the second rotation matrix R(q) comprises: Based on the first rotation matrix R(p), the first grid is calculated; where W 1 =R(p)*W,W 1 is the first grid, W represents the initial calculation grid used to acquire four-dimensional seismic data; Based on the second rotation matrix R(q), the second grid is calculated; where W 2 =R(q)*W,W 2 is the second grid; Based on the first grid and the second grid, a first calculation grid W' is determined.

7. The stratigraphic structure-guided prestack texture attribute calculation method according to claim 1, It is characterized in that The first dip angle data volume calculation based on the formation structure-guided gradient structure tensor matrix GST includes: Based on the matrix feature decomposition rule, the gradient structure tensor matrix GST is decomposed; the matrix decomposition formula is: υ 1 ,υ 2 and 3 are the three eigenvectors of the gradient structure tensor matrix GST, λ 1 , 2 and λ 3 are the three eigenvalues ​​of the gradient structure tensor matrix GST; Sort the three eigenvalues ​​of the gradient structure tensor matrix GST and get the largest eigenvalue; Based on the vector of the eigenvector corresponding to the maximum eigenvalue in the x direction, the vector in the y direction, and the vector in the t direction, a first inclination angle data volume is calculated.

8. The method for calculating prestack texture attributes guided by stratum structure according to claim 1, It is characterized in that The step of constructing a stratum structure-oriented gray-level co-occurrence matrix G according to the first dip angle data volume comprises: Acquire new four-dimensional seismic data u″(x, y, t, d) guided by the stratigraphic structure from the pre-stack seismic data along the direction of the first dip data volume; Grayscale conversion of new four-dimensional seismic data u″(x, y, t, d) guided by stratum structure; Based on the grayscale-converted four-dimensional seismic data u″(x, y, t, d), a stratigraphic structure-oriented grayscale co-occurrence matrix G is constructed; Among them, the gray level co-occurrence matrix G is: represents the calculation direction of the gray-level co-occurrence matrix, G(i, j) represents the gray-level co-occurrence matrix, and i and j represent the positions in the gray-level co-occurrence matrix.

9. The method for calculating prestack texture attributes guided by stratum structure according to claim 8, It is characterized in that The method of acquiring new four-dimensional seismic data u″(x, y, t, d) guided by the stratum structure from the pre-stack seismic data along the direction of the first dip angle data volume comprises: Constructing a third rotation matrix R(p′) and a fourth rotation matrix R(q′) according to the first tilt angle data volume; Determine a second calculation grid W″ based on the third rotation matrix R(p′) and the fourth rotation matrix R(q′); Based on the second computational grid W″, new four-dimensional seismic data u″ (x, y, t, d) guided by the stratum structure are acquired in the pre-stack seismic data.

10. The method for calculating prestack texture attributes guided by stratum structure according to claim 8, It is characterized in that The gray level co-occurrence matrix G based on the stratum structure orientation calculates the texture feature attributes, including: Based on the stratum structure-oriented gray-level co-occurrence matrix G, the statistical probability p of the element G(i,j) in the gray-level co-occurrence matrix G is obtained. ij ;in, N represents the selected gray level; Based on the statistical probability p of the element G(i,j) in the gray-level co-occurrence matrix G ij , calculate texture feature attributes.

11. The method for calculating prestack texture attributes guided by stratum structure according to claim 10, It is characterized in that The texture feature attribute includes an energy value; The energy value is calculated as follows: Among them, Energy represents the energy value.

12. The method for calculating prestack texture attributes guided by stratum structure according to claim 10, It is characterized in that The texture feature attributes include contrast; The calculation formula of the contrast ratio is: Among them, Contrast represents contrast.

13. The method for calculating prestack texture attributes guided by stratum structure according to claim 10, It is characterized in that The texture feature attributes include homogeneity; The calculation formula of the homogeneity is: Among them, Homogeneity means homogeneity.

14. The method for calculating prestack texture attributes guided by stratum structure according to claim 10, It is characterized in that The texture feature attribute includes an entropy value; The calculation formula of the entropy value is: Among them, Entropy represents the entropy value.

15. The method for calculating prestack texture attributes guided by stratum structure according to claim 10, It is characterized in that The texture feature attributes include correlation; The calculation formula of the correlation is: in, Correlation means correlation.

16. A stratigraphic structure-guided prestack texture attribute calculation system. It is characterized in that include: A preliminary dip data volume calculation module is used to collect four-dimensional seismic data u (x, y, t, d) and calculate the preliminary dip data volume corresponding to the four-dimensional seismic data u (x, y, t, d); A first dip data volume calculation module, used for constructing a formation structure-oriented gradient structure tensor matrix GST according to the preliminary dip data volume, and performing first dip data volume calculation based on the formation structure-oriented gradient structure tensor matrix GST; The texture feature attribute calculation module is used to construct a stratum structure-oriented grayscale co-occurrence matrix G according to the first dip angle data volume, and calculate the texture feature attributes based on the stratum structure-oriented grayscale co-occurrence matrix G to obtain the texture feature attribute calculation result.

17. A machine-readable storage medium having stored thereon instructions, It is characterized in that When the instruction is executed by a processor, the processor is configured to execute the stratigraphic structure-guided prestack texture attribute calculation method as claimed in any one of claims 1 to 15.

18. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the method for calculating prestack texture attributes guided by the formation structure as described in any one of claims 1 to 15 is implemented.

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