Fault attribute graph description method and device, computer device and storage medium

Abstract

The invention relates to a method and device for depicting a fault attribute graph, a computer device and a storage medium, and relates to the technical field of seismic geological interpretation of petroleum and natural gas exploration areas, and the method for depicting the fault attribute graph comprises the steps: obtaining curvature attribute data volumes in seismic data volumes in different directions; curvature attribute values are extracted along a target layer according to the curvature attribute data volumes in different directions, and a curvature attribute value plane graph is generated; according to the curvature attribute value plane graphs of the different orientations, fault curvature attribute characteristic values of the different orientations are determined; normalizing the fault curvature attribute characteristic values in different directions to obtain normalized characteristic values; and carrying out superposition fusion on the curvature attribute data volumes in different orientations according to the normalized characteristic value, and drawing a fault attribute graph.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic geological interpretation of oil and gas exploration areas, and in particular to a method for depicting a fault attribute map, a device for depicting a fault attribute map, a computer device and a storage medium. Background Art

[0002] At present, the method of using seismic curvature attributes to identify faults has been widely used, and the ability to identify small faults using curvature attributes is significantly better than other seismic attributes such as coherence and dip. Although curvature attributes have excellent fault identification capabilities, for study areas where faults are extremely weak, the ability of curvature attributes to identify faults is not enough, and new technologies are urgently needed to enhance the ability of curvature attributes to identify faults. Summary of the invention

[0003] In view of this, the present invention provides a method for characterizing a fault attribute map, a device for characterizing a fault attribute map, a computer device, and a storage medium.

[0004] Specifically, the present invention is achieved through the following technical solutions:

[0005] According to a first aspect of the present invention, a method for characterizing a fault attribute map is provided, which includes: obtaining curvature attribute data volumes in seismic data volumes of different orientations; extracting curvature attribute values ​​along a target layer according to the curvature attribute data volumes of different orientations, and generating a curvature attribute value plane map; determining fault curvature attribute characteristic values ​​of different orientations according to the curvature attribute value plane map of different orientations; normalizing the fault curvature attribute characteristic values ​​of different orientations to obtain normalized characteristic values; and superimposing and fusing the curvature attribute data volumes of different orientations according to the normalized characteristic values ​​and drawing them into a fault attribute map.

[0006] The characterization method of the fault attribute map provided by the present invention specifically includes: since the seismic data bodies of different orientations have different recognition capabilities for faults of different orientations, and there are faults of different orientations in the study area, it is necessary to obtain the curvature attribute data bodies in the seismic data bodies of different orientations. Then, the curvature attribute values ​​are extracted along the target layer, and the extracted curvature attribute values ​​are displayed in the curvature attribute value plane map, and the critical value for the clearest display of the fault is found in the curvature attribute value plane map, and it is used as the fault curvature attribute characteristic value of the curvature attribute map; after finding the fault curvature attribute characteristic values ​​of the same target layer in different orientations, the fault curvature attribute characteristic values ​​of all orientations are normalized, that is, the fault curvature attribute characteristic values ​​of all orientations are unified to a certain characteristic value, and the characteristic value is used as the normalized characteristic value. Finally, the curvature attribute data bodies of different orientations are superimposed and fused according to the normalized characteristic value, and drawn into a fault attribute map. In the fused fault attribute map, large faults are enhanced and highlighted, while small and hidden faults are protected. Faults are portrayed more finely and the accuracy is greatly improved, thereby improving the ability of curvature attributes to identify faults.

[0007] The present invention is a method for finely characterizing faults based on three-dimensional seismic data using seismic curvature secondary attribute eigenvalue fusion technology, which solves the problem of low signal-to-noise ratio of seismic data, weak conventional attribute fault display, and difficulty in fine characterization of fault characteristics, thereby supporting oil and gas field exploration and development. The method specifically obtains curvature attribute value plane maps at different orientations, and then determines the fault curvature attribute eigenvalues ​​of the most obvious fault display in different curvature attribute value plane maps, and further, normalizes different fault curvature attribute eigenvalues ​​to obtain normalized eigenvalues, and then superimposes and fuses curvature attribute data bodies at different orientations according to the normalized eigenvalues, and draws a fault attribute map. Compared with conventional coherence, curvature and other attribute maps, the fused fault attribute map has greatly improved characterization accuracy, so that the larger faults in the study area are enhanced and highlighted, and it is easy to systematically comb the faults, small faults and hidden faults are protected, and the characterization of the faults is more refined. The faults displayed by the fused plane curvature attribute map are highly consistent with the seismic profile. Therefore, the present invention effectively improves the efficiency of fault interpretation and the ability to identify small faults.

[0008] In some embodiments, the step of determining fault curvature attribute characteristic values ​​at different orientations according to the curvature attribute value plane diagrams at different orientations includes: extracting instantaneous real amplitude attributes at different orientations along the target layer according to the curvature attribute value plane diagrams at different orientations.

[0009] In this embodiment, the step of determining the characteristic values ​​of the fault curvature attributes at different orientations according to the curvature attribute value plane diagrams at different orientations includes: extracting the instantaneous real amplitude attribute (IReAmp) along the target layer in the curvature attribute value plane diagrams at different orientations. The instantaneous real amplitude attribute is the time domain vibration amplitude of the seismic trace at the selected sampling point, and is the basic parameter of the amplitude attribute. The instantaneous real amplitude attribute reflects the fracture development of the stratum during this period. By extracting the instantaneous real amplitude attribute along the target layer from the curvature attribute value plane diagrams at different orientations, the fault development conditions at different orientations can be obtained.

[0010] In some embodiments, the step of determining the characteristic values ​​of fault curvature attributes in different orientations also includes: differentially amplifying the curvature attribute value range of the curvature attribute value plane graph; coloring the curvature attribute value plane graph; and determining that the curvature attribute value with a sudden color change is the characteristic value of the fault curvature attribute.

[0011] In this embodiment, since the curvature is the inverse of different circle radii and the value is too small, it is extremely difficult to determine the fault curvature attribute characteristic value, so it is necessary to perform differential amplification processing on the curvature attribute value range, wherein the curvature attribute value range can be normalized to 0-100 for differential amplification processing. Further, since the curvature reflects the bending degree of an arc, the greater the curvature, the more curved it is, so the curvature value at the fault often increases suddenly, which is manifested as a sudden change in color on the curvature attribute. Therefore, after performing differential amplification processing on the curvature attribute value range, the curvature attribute value plane map is color-adjusted, and the curvature attribute value corresponding to the sudden change in color is the most clear critical value for the fault display in the curvature attribute. Then the critical value is used as the fault curvature attribute characteristic value. By determining the fault curvature attribute characteristic value that shows the fault most clearly in the curvature attribute value plane map at different orientations, the fused fault attribute map can be clearly displayed for small faults, thereby enhancing the recognition ability of the curvature attribute for the fault.

[0012] In some embodiments, the step of normalizing the fault curvature attribute characteristic values ​​at different orientations to obtain a normalized characteristic value includes: determining the fault curvature attribute characteristic value with the most repetitions based on the fault curvature attribute characteristic values ​​at different orientations; and using the fault curvature attribute characteristic value with the most repetitions as the normalized characteristic value.

[0013] In this embodiment, the steps of normalizing the fault curvature attribute characteristic values ​​of different orientations to obtain the normalized characteristic value include: after obtaining multiple fault curvature attribute characteristic values, finding the fault curvature attribute characteristic value with the most repetitions among the multiple fault curvature attribute characteristic values, and the large number of repetitions indicates that the strata at the fault curvature attribute characteristic value in different orientations are all in a fractured state, so it is highly likely that the strata corresponding to the fault curvature attribute characteristic value in the entire seismic data is a fault, and therefore, the fault curvature attribute characteristic value with the most repetitions is used as the normalized characteristic value. Then, the curvature attribute data corresponding to the normalized characteristic value is obtained in the curvature attribute data body at different orientations, and the curvature attribute data at all orientations are merged to obtain a fault attribute map with a clear fault display.

[0014] According to the second aspect of the present invention, a characterization device for a fault attribute map is provided. The characterization device includes: an acquisition module, the acquisition module is used to acquire curvature attribute data bodies in seismic data bodies of different orientations; a generation module, the generation module is used to extract curvature attribute values ​​along the target layer according to the curvature attribute data bodies of different orientations, and generate a curvature attribute value plane map; a first determination module, the first determination module is used to determine the curvature attribute characteristic values ​​of the faults of different orientations according to the curvature attribute value plane maps of different orientations; a first processing module, the first processing module is used to normalize the curvature attribute characteristic values ​​of the faults of different orientations to obtain normalized characteristic values; a fusion module, the fusion module is used to superimpose and fuse the curvature attribute data bodies of different orientations according to the normalized characteristic values ​​and draw them into a fault attribute map.

[0015] The characterization device of the fault attribute map provided by the present invention mainly includes: an acquisition module, a generation module, a first determination module, a first processing module and a fusion module. Among them, since the seismic data bodies of different orientations have different abilities to identify faults of different orientations, and there are faults of different orientations in the study area, the acquisition module needs to obtain the curvature attribute data bodies in the seismic data bodies of different orientations. Then the generation module extracts the curvature attribute values ​​along the target layer, and displays the extracted curvature attribute values ​​in the curvature attribute value plane map. Further, the first determination module finds the critical value for the clearest display of the fault in the curvature attribute value plane map, and uses it as the fault curvature attribute characteristic value of the curvature attribute map; further, after finding the fault curvature attribute characteristic values ​​of the same target layer in different orientations, the first processing module normalizes the fault curvature attribute characteristic values ​​of all orientations, that is, the fault curvature attribute characteristic values ​​of all orientations are unified to a certain characteristic value, and the characteristic value is used as the normalized characteristic value. Finally, the fusion module superimposes and fuses the curvature attribute data volumes in different directions according to the normalized eigenvalues ​​and draws a fault attribute map. On the fused fault attribute map, large faults are enhanced and highlighted, small faults and hidden faults are protected, faults are depicted more finely, and the accuracy is greatly improved, thereby improving the ability of curvature attributes to identify faults.

[0016] In some embodiments, the first determination module includes: an extraction module, the extraction module being used to extract instantaneous real amplitude attributes at different orientations along the target layer according to the curvature attribute value plane graphs at different orientations.

[0017] In this embodiment, the first determination module includes an extraction module. The extraction module is used to extract instantaneous real amplitude attributes (Insta nta neous Amplitude, IReAmp) along the target layer in the curvature attribute value plane diagrams at different orientations. The instantaneous real amplitude attribute is the time domain vibration amplitude of the seismic trace at the selected sampling point, which is a basic parameter of the amplitude attribute. The instantaneous real amplitude attribute reflects the fracture development of the stratum during this period. By extracting the instantaneous real amplitude attribute along the target layer from the curvature attribute value plane diagrams at different orientations, the fault development conditions at different orientations can be obtained.

[0018] In some embodiments, the first determination module also includes: a second processing module, the second processing module is used to perform differential amplification processing on the curvature attribute value range of the curvature attribute value plane diagram; a color adjustment module, the color adjustment module is used to perform color adjustment processing on the curvature attribute value plane diagram; a second determination module, the second determination module is used to determine that the curvature attribute value with a sudden change in color is a fault curvature attribute characteristic value.

[0019] In this embodiment, since the curvature is the inverse of different circle radii and the value is too small, it is extremely difficult to determine the fault curvature attribute characteristic value. Therefore, the second processing module is required to perform differential amplification processing on the curvature attribute value range, wherein the curvature attribute value range can be normalized to 0-100 for differential amplification processing. Further, since the curvature reflects the bending degree of an arc, the greater the curvature, the more curved it is. Therefore, the curvature value at the fault often increases suddenly, which is manifested as a sudden change in color on the curvature attribute. Therefore, after performing differential amplification processing on the curvature attribute value range, the curvature attribute value plane map is color-adjusted using the color adjustment module. The curvature attribute value corresponding to the sudden change in color is the critical value of the curvature attribute for the clearest display of the fault. Then the second determination module uses the critical value as the fault curvature attribute characteristic value. By determining the fault curvature attribute characteristic value that shows the fault most clearly in the curvature attribute value plane map at different orientations, the fused fault attribute map can be clearly displayed for small faults, thereby enhancing the recognition ability of the curvature attribute for the fault.

[0020] In some embodiments, the first processing module includes: a third determination module, the third determination module is used to determine the fault curvature attribute characteristic value with the most repetitions based on the fault curvature attribute characteristic values ​​in different orientations; and a fourth determination module, the fourth determination module is used to use the fault curvature attribute characteristic value with the most repetitions as a normalized characteristic value.

[0021] In this embodiment, the first processing module includes a third determination module and a fourth determination module. After obtaining multiple fault curvature attribute characteristic values, the third determination module finds the fault curvature attribute characteristic value with the most repetitions among the multiple fault curvature attribute characteristic values. The large number of repetitions indicates that the strata at the fault curvature attribute characteristic value in different orientations are all in a fractured state. Then, it is highly likely that the strata corresponding to the fault curvature attribute characteristic value in the entire seismic data is a fault. Therefore, the fourth determination module uses the fault curvature attribute characteristic value with the most repetitions as a normalized characteristic value. Then, the curvature attribute data corresponding to the normalized characteristic value is obtained in the curvature attribute data body at different orientations, and the curvature attribute data at all orientations are merged to obtain a fault attribute map with a clear fault display.

[0022] According to a third aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for characterizing a fault attribute map in the first aspect or any possible implementation of the first aspect are implemented.

[0023] According to a fourth aspect of the present invention, there is provided a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for characterizing a fault attribute map in the first aspect or any possible implementation of the first aspect.

[0024] The technical solution provided by the present invention brings at least the following beneficial effects:

[0025] The present invention provides a method for finely characterizing faults based on three-dimensional seismic data using seismic curvature secondary attribute eigenvalue fusion technology, which solves the problem of low signal-to-noise ratio of seismic data, weak display of conventional attribute faults, and difficulty in finely characterizing fault characteristics, thereby supporting the exploration and development of oil and gas fields, strengthening and highlighting large faults, protecting small faults and hidden faults, making fault characterization more refined and greatly improving accuracy. At the same time, the present invention also greatly improves the efficiency of fault interpretation, which is of great significance for areas where fault development is weak and fault zones contribute more to oil and gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0028] Figure 1 A schematic diagram of a flow chart of a method for depicting a fault attribute map provided by an embodiment of the present invention;

[0029] Figure 2 A schematic flow chart of the steps of determining fault curvature attribute characteristic values ​​at different orientations in the method for depicting a fault attribute map provided by an embodiment of the present invention;

[0030] Figure 3 A schematic flow chart of the step of normalizing fault curvature attribute characteristic values ​​at different orientations to obtain normalized characteristic values ​​in a method for depicting a fault attribute map provided in an embodiment of the present invention;

[0031] Figure 4 A schematic flow chart of a method for depicting a fault attribute map provided in a specific embodiment of the present invention;

[0032] Figure 5 A flowchart for confirming fault curvature attribute characteristic values ​​at different orientations in a specific embodiment of the present invention;

[0033] Figure 6 is a normalized eigenvalue plane diagram of different orientations in a specific embodiment of the present invention;

[0034] Figure 7is a fault attribute map in a specific embodiment of the present invention;

[0035] Figure 8 A comparison diagram of a fault attribute map and a conventional coherent curvature attribute map in a specific embodiment of the present invention;

[0036] Fig. 9 A comparison diagram of a fault attribute map and a bottom layer cross-section display map in a specific embodiment of the present invention;

[0037] Fig.10 A schematic block diagram of a device for depicting a fault attribute map provided by an embodiment of the present invention;

[0038] Fig.11 A schematic block diagram of a first determination module in a device for depicting a fault attribute map provided by an embodiment of the present invention;

[0039] Fig.12 A schematic block diagram of a first processing module in a device for depicting a fault attribute map provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Figure 1 A schematic flow chart of a method for depicting a fault attribute map provided by an embodiment of the present invention. The method may include the following steps:

[0042] S102: Obtaining curvature attribute data volumes in seismic data volumes at different orientations;

[0043] S104: extracting curvature attribute values ​​along the target layer according to the curvature attribute data bodies at different orientations, and generating a curvature attribute value plane map; S106: determining fault curvature attribute characteristic values ​​at different orientations according to the curvature attribute value plane maps at different orientations;

[0044] S108: normalizing the fault curvature attribute characteristic values ​​at different orientations to obtain normalized characteristic values;

[0045] S110: Superimpose and fuse the curvature attribute data bodies of different orientations according to the normalized eigenvalues ​​and draw them into a fault attribute map. The characterization method of the fault attribute map provided by the present invention specifically includes: since the seismic data bodies of different orientations have different recognition capabilities for faults of different orientations, and there are faults of different orientations in the study area, it is necessary to obtain the curvature attribute data bodies in the seismic data bodies of different orientations. Then, the curvature attribute values ​​are extracted along the target layer, and the extracted curvature attribute values ​​are displayed in the curvature attribute value plane map, and the critical value for the clearest display of the fault is found in the curvature attribute value plane map, which is used as the fault curvature attribute characteristic value of the curvature attribute map; after finding the fault curvature attribute characteristic values ​​of the same target layer in different orientations, the fault curvature attribute characteristic values ​​of all orientations are normalized, that is, the fault curvature attribute characteristic values ​​of all orientations are unified to a certain characteristic value, and the characteristic value is used as the normalized characteristic value. Finally, the curvature attribute data bodies of different orientations are superimposed and fused according to the normalized characteristic value, and drawn into a fault attribute map. In the fused fault attribute map, large faults are enhanced and highlighted, while small and hidden faults are protected. Faults are portrayed more finely and the accuracy is greatly improved, thereby improving the ability of curvature attributes to identify faults.

[0046] The present invention is a method for finely characterizing faults based on three-dimensional seismic data using seismic curvature secondary attribute eigenvalue fusion technology, which solves the problem of low signal-to-noise ratio of seismic data, weak conventional attribute fault display, and difficulty in fine characterization of fault characteristics, thereby supporting oil and gas field exploration and development. The method specifically obtains curvature attribute value plane maps at different orientations, and then determines the fault curvature attribute eigenvalues ​​with the most obvious fault display in different curvature attribute maps, and further, normalizes different fault curvature attribute eigenvalues ​​to obtain normalized eigenvalues, and then superimposes and fuses curvature attribute data bodies at different orientations according to the normalized eigenvalues, and draws a fault attribute map. Compared with conventional coherence, curvature and other attribute maps, the fused fault attribute map has greatly improved characterization accuracy, so that the larger faults in the study area are enhanced and highlighted, and it is easy to systematically comb the faults, small faults and hidden faults are protected, and the characterization of the faults is more refined. The faults displayed by the fused plane curvature attribute map are highly consistent with the seismic profile. Therefore, the present invention effectively improves the efficiency of fault interpretation and the ability to identify small faults.

[0047] Furthermore, the step of determining fault curvature attribute characteristic values ​​at different orientations according to the curvature attribute value plane diagrams at different orientations includes: extracting instantaneous real amplitude attributes at different orientations along the target layer according to the curvature attribute value plane diagrams at different orientations.

[0048] In this embodiment, the step of determining the characteristic values ​​of the fault curvature attributes at different orientations according to the curvature attribute value plane diagrams at different orientations includes: extracting the instantaneous real amplitude attribute (IReAmp) along the target layer in the curvature attribute value plane diagrams at different orientations. The instantaneous real amplitude attribute is the time domain vibration amplitude of the seismic trace at the selected sampling point, and is the basic parameter of the amplitude attribute. The instantaneous real amplitude attribute reflects the fracture development of the stratum during this period. By extracting the instantaneous real amplitude attribute along the target layer from the curvature attribute value plane diagrams at different orientations, the fault development conditions at different orientations can be obtained.

[0049] Figure 2 A flow chart of the steps of determining fault curvature attribute characteristic values ​​at different orientations in the method for depicting a fault attribute map provided in an embodiment of the present invention, wherein the steps may further include the following steps:

[0050] S202: performing differential amplification processing on the curvature attribute value range of the curvature attribute value plane graph;

[0051] S204: performing color adjustment on the curvature attribute value plane graph;

[0052] S206: Determine the curvature attribute value where the color suddenly changes as the fault curvature attribute characteristic value.

[0053] In this embodiment, since the curvature is the inverse of different circle radii and the value is too small, it is extremely difficult to determine the fault curvature attribute characteristic value, so it is necessary to perform differential amplification processing on the curvature attribute value range, wherein the curvature attribute value range can be normalized to 0-100 for differential amplification processing. Further, since the curvature reflects the bending degree of an arc, the greater the curvature, the more curved it is, so the curvature value at the fault often increases suddenly, which is manifested as a sudden change in color on the curvature attribute. Therefore, after performing differential amplification processing on the curvature attribute value range, the curvature attribute value plane map is color-adjusted, and the curvature attribute value corresponding to the sudden change in color is the most clear critical value for the fault display in the curvature attribute. Then the critical value is used as the fault curvature attribute characteristic value. By determining the fault curvature attribute characteristic value that shows the fault most clearly in the curvature attribute value plane map at different orientations, the fused fault attribute map can be clearly displayed for small faults, thereby enhancing the recognition ability of the curvature attribute for the fault.

[0054] Figure 3 A schematic flow chart of the steps of normalizing fault curvature attribute characteristic values ​​at different orientations to obtain normalized characteristic values ​​in the method for depicting a fault attribute map provided in an embodiment of the present invention, wherein the steps may include the following steps:

[0055] S302: determining the fault curvature attribute characteristic value with the largest number of repetitions according to the fault curvature attribute characteristic values ​​at different orientations;

[0056] S304: taking the fault curvature attribute eigenvalue with the largest number of repetitions as the normalized eigenvalue.

[0057] In this embodiment, the steps of normalizing the fault curvature attribute characteristic values ​​of different orientations to obtain the normalized characteristic value include: after obtaining multiple fault curvature attribute characteristic values, finding the fault curvature attribute characteristic value with the most repetitions among the multiple fault curvature attribute characteristic values, and the large number of repetitions indicates that the strata at the fault curvature attribute characteristic value in different orientations are all in a fractured state, so it is highly likely that the strata corresponding to the fault curvature attribute characteristic value in the entire seismic data is a fault, and therefore, the fault curvature attribute characteristic value with the most repetitions is used as the normalized characteristic value. Then, the curvature attribute data corresponding to the normalized characteristic value is obtained in the curvature attribute data body at different orientations, and the curvature attribute data at all orientations are merged to obtain a fault attribute map with a clear fault display.

[0058] Figure 4 A schematic flow chart of a method for depicting a fault attribute map provided in a specific embodiment of the present invention may include the following steps:

[0059] S402: Obtaining curvature attributes of seismic data at different orientations;

[0060] S404: extracting curvature instantaneous real amplitude attributes along the layer;

[0061] S406: Finding fault curvature attribute characteristic values ​​at different orientations;

[0062] S408: normalizing the characteristic values ​​of fault curvature attributes in different orientations;

[0063] S410: Fusing curvature attributes of different orientations.

[0064] In this embodiment, firstly, since the seismic data bodies of different orientations have different recognition capabilities for faults of different orientations, and there are also faults of different orientations in the study area, it is necessary to extract curvature attributes from seismic data of different orientations, which are generally divided into 6 orientations, namely 0-30 degree orientation, 30-60 degree orientation, 60-90 degree orientation, 90-120 degree orientation, 120-150 degree orientation, and 150-180 degree orientation. Further, on the orientation curvature attribute map obtained in the previous step, the instantaneous real amplitude attribute is extracted along the target layer; further, since the curvature is the inverse of the radius of different circles, the value is too small, so the characteristic value of the fault curvature attribute is extremely difficult to determine, so it is necessary to normalize the secondary attribute value range to 0-100 for difference amplification processing, and determine the characteristic value of the fault curvature attribute by color adjustment. The principle of finding the characteristic value of the fault curvature attribute is: since the curvature attribute value will suddenly increase at the fault, the characteristic value found by the color mutation is the critical value of the curvature attribute for the clearest display of the fault. Further, repeat the above two steps. Find the characteristic value of the fault curvature attribute of the same target layer of seismic data in different azimuths, and unify the characteristic values ​​of the fault curvature attribute of all azimuths to a certain characteristic value, namely the normalized characteristic value. Finally, the data bodies of each azimuth after the characteristic value is normalized are superimposed and fused along the secondary attribute value of the layer curvature. As a result, on the fused fault attribute map, larger faults are enhanced and highlighted, small faults and hidden faults are protected, the faults are more delicately portrayed and the accuracy is greatly improved.

[0065] In a specific embodiment of the present application, for example, in the center of a basin, the faults are weakly developed, but from the wells that have been drilled, it can be seen that the faults play an important role in the enrichment and accumulation of oil and gas. Therefore, it is of great significance to carry out detailed characterization of small faults.

[0066] Figure 5 FIG. 1 is a flow chart for confirming fault curvature attribute characteristic values ​​at different orientations in a specific embodiment of the present invention, wherein the orientation data are 0-30 degree orientation data and 30-60 degree orientation data. Figure 5 Figure a and Figure 5 As shown in Figure b, the accuracy of using curvature attribute isochronous slices to depict small faults is not enough. Extracting instantaneous real amplitude attributes along the layer on the curvature attribute map to display small faults is better, but Figure 5 Figure c and Figure 5 As shown in Figure d, the instantaneous real amplitude attribute value is too small, and the fault characteristic value is difficult to determine. Furthermore, since the curvature reflects the bending degree of an arc, the greater the curvature, the more curved it is. Therefore, the curvature value at the fault often increases suddenly, which is manifested as a sudden change in color in the curvature attribute. The sudden change in color value is the characteristic value of the fault curvature attribute. In order to more conveniently find the characteristic value of the fault curvature attribute, Figure 5 Figure c in Figure 5 The curvature attribute value range of the layer in the d figure is normalized to 0-100 for difference amplification, and the characteristic value of the fault curvature is determined by color adjustment, such as Figure 5 The e graph and Figure 5 As shown in Figure g, the minimum curvature of the 0-30 degree azimuth data along the layer changes suddenly at 40 degrees, as shown in Figure g. Figure 5 The f graph and Figure 5 In the h figure, the minimum curvature of the layer data at the azimuth of 30 degrees to 60 degrees suddenly changes at 38, so the fault curvature attribute characteristic value of the azimuth data at 0 degrees to 30 degrees is 40, and the fault curvature attribute characteristic value of the azimuth data at 30 degrees to 60 degrees is 38. The fault curvature characteristic attribute values ​​of the azimuth data at 0 degrees to 30 degrees, 30 degrees to 60 degrees, 60 degrees to 90 degrees, 90 degrees to 120 degrees, 120 degrees to 150 degrees, and 150 degrees to 180 degrees are respectively confirmed by the above fault curvature attribute characteristic value confirmation method, thereby obtaining Table 1.

[0067] Table 1

[0068]

[0069] It can be seen from Table 1 that the fault curvature attribute characteristic value of the azimuth of 0-30 degrees is 40, the fault curvature attribute characteristic value of the azimuth of 30-60 degrees is 38, the fault curvature attribute characteristic value of the azimuth of 60-90 degrees is 39, the fault curvature attribute characteristic value of the azimuth of 90-120 degrees is 40, the fault curvature attribute characteristic value of the azimuth of 120-150 degrees is 37, and the fault curvature attribute characteristic value of the azimuth of 150-180 degrees is 40. Further, it can be seen from Table 1 that the value with the most repetitions in the fault curvature attribute characteristic values ​​of each azimuth is 40, so the fault curvature attribute characteristic values ​​of each azimuth are normalized to obtain a normalized characteristic value, and its normalized characteristic value is 40.

[0070] Further, Figure 6 The normalized eigenvalue plane graphs at different orientations in a specific embodiment of the present invention are obtained by using the normalized eigenvalues ​​in the curvature attribute graphs at different orientations.

[0071] Further, Figure 7 is a fault attribute map in a specific embodiment of the present invention; the final fault attribute map of the present invention is obtained by superimposing and fusing curvature attribute data volumes in different directions according to normalized eigenvalues, wherein: Figure 7 Figure a in the figure is the superposition of normalized eigenvalue plane graphs at different orientations; Figure 7 Figure b in the figure is a fusion image after the normalized eigenvalue plane images in different orientations are fused.

[0072] Figure 8is a comparison diagram of a fault attribute map and a conventional coherent curvature attribute map in a specific embodiment of the present invention. Figure 8 The graph a in the figure is the coherent attribute graph. Figure 8 Figure b in the figure is the curvature attribute diagram. Figure 8 Figure c in the figure is a fault attribute map obtained by the present invention. By comparison, it can be seen that the fault attribute map of the present invention has greatly improved the accuracy of description compared with conventional coherence, curvature and other attribute maps, so that the larger faults in the study area are enhanced and highlighted, and the systematic combing of faults is facilitated, while the tiny faults and hidden faults are protected, and the description of faults is more refined.

[0073] Fig. 9 This is a comparison diagram of a fault attribute map and a stratigraphic cross-section display map in a specific embodiment of the present invention. Fig. 9 Figure a in the figure is the fault attribute map. Fig. 9 Figure b in the figure is a stratigraphic cross-section diagram. Fig. 9 It can be seen that the faults displayed in the fault attribute map of the present invention are highly consistent with the faults in the stratigraphic profile display map. Therefore, the present invention effectively improves the efficiency of fault interpretation and improves the ability to identify small faults.

[0074] Fig.10 A schematic block diagram of a device for depicting a fault attribute map provided by an embodiment of the present invention. The device 10 for depicting a fault attribute map includes:

[0075] An acquisition module 102 is used to acquire curvature attribute data volumes in seismic data volumes at different orientations;

[0076] A generating module 104 is used to extract curvature attribute values ​​along the target layer according to the curvature attribute data bodies in different directions, and generate a curvature attribute value plane map;

[0077] A first determination module 106, configured to determine fault curvature attribute characteristic values ​​at different orientations according to the curvature attribute value plane graphs at different orientations;

[0078] The first processing module 108 is used to normalize the fault curvature attribute characteristic values ​​at different orientations to obtain normalized characteristic values;

[0079] The fusion module 110 is used to superimpose and fuse the curvature attribute data volumes in different directions according to the normalized eigenvalues ​​and draw a fault attribute map.

[0080] The characterization device 10 of the fault attribute map provided by the present invention mainly includes: an acquisition module 102, a generation module 104, a first determination module 106, a first processing module 108 and a fusion module 110. Among them, since the seismic data bodies of different orientations have different recognition capabilities for faults of different orientations, and there are faults of different orientations in the study area, the acquisition module 102 needs to obtain the curvature attribute data bodies of the seismic data bodies of different orientations. Then the generation module 104 extracts the curvature attribute value along the target layer, and displays the extracted curvature attribute value in the curvature attribute value plane map. Further, the first determination module 106 finds the critical value for the clearest display of the fault in the curvature attribute value plane map, and uses it as the fault curvature attribute characteristic value of the curvature attribute map; further, after finding the fault curvature attribute characteristic value of the same target layer in different orientations, the first processing module 106 normalizes the fault curvature attribute characteristic values ​​of all orientations, that is, the fault curvature attribute characteristic values ​​of all orientations are unified to a certain characteristic value, and the characteristic value is used as the normalized characteristic value. Furthermore, the final fusion module 110 superimposes and fuses the curvature attribute data bodies of different directions according to the normalized eigenvalues, and draws a fault attribute map. On the fused fault attribute map, large faults are enhanced and highlighted, small faults and hidden faults are protected, and faults are more finely portrayed with greatly improved accuracy, thereby improving the ability of curvature attributes to identify faults.

[0081] Furthermore, the first determination module 106 includes: an extraction module, configured to extract instantaneous real amplitude attributes at different orientations along the target layer according to the curvature attribute value plane graphs at different orientations.

[0082] In this embodiment, the first determination module 106 includes an extraction module. The extraction module is used to extract instantaneous real amplitude attributes (Insta nta neous Amplitude, IReAmp) along the target layer in the curvature attribute value plane diagrams of different orientations. The instantaneous real amplitude attribute is the time domain vibration amplitude of the seismic trace at the selected sampling point, which is a basic parameter of the amplitude attribute. The instantaneous real amplitude attribute reflects the fracture development of the stratum during this period. By extracting the instantaneous real amplitude attribute along the target layer from the curvature attribute value plane diagrams of different orientations, the fault development conditions at different orientations can be obtained.

[0083] Fig.11 A schematic block diagram of a first determination module in a device for depicting a fault attribute map provided by an embodiment of the present invention. The first determination module 106 includes:

[0084] The second processing module 1062 is used to perform differential amplification processing on the curvature attribute value range of the curvature attribute value plane graph;

[0085] A color adjustment module 1064 is used to perform color adjustment on the curvature attribute value plane graph;

[0086] The second determining module 1066 is used to determine that the curvature attribute value of the color mutation is a fault curvature attribute characteristic value.

[0087] In this embodiment, since the curvature is the inverse of different circle radii and the value is too small, it is extremely difficult to determine the fault curvature attribute characteristic value, so the second processing module 1062 is required to perform differential amplification processing on the curvature attribute value range, wherein the curvature attribute value range can be normalized to 0-100 for differential amplification processing. Further, since the curvature reflects the bending degree of an arc, the greater the curvature, the more curved it is, so the curvature value at the fault often increases suddenly, which is manifested as a sudden change in color on the curvature attribute. Therefore, after performing differential amplification processing on the curvature attribute value range, the color adjustment module 1064 is used to perform color adjustment processing on the curvature attribute value plane map, and the curvature attribute value corresponding to the sudden change in color is the critical value of the curvature attribute for the clearest display of the fault. Then the second determination module 1066 uses the critical value as the fault curvature attribute characteristic value. By determining the fault curvature attribute characteristic value that shows the fault most clearly in the curvature attribute value plane map at different orientations, the fused fault attribute map can clearly display small faults, thereby enhancing the curvature attribute's ability to identify faults.

[0088] Fig.12 A schematic block diagram of a first processing module in a device for depicting a fault attribute map provided in an embodiment of the present invention. The first processing module 108 includes:

[0089] The third determination module 1082 is used to determine the fault curvature attribute characteristic value with the largest number of repetitions according to the fault curvature attribute characteristic values ​​at different orientations;

[0090] The fourth determination module 1084 is configured to use the fault curvature attribute characteristic value with the largest number of repetitions as a normalized characteristic value.

[0091] In this embodiment, the first processing module 108 includes a third determination module 1082 and a fourth determination module 1084. After obtaining multiple fault curvature attribute characteristic values, the third determination module 182 finds the fault curvature attribute characteristic value with the most repetitions among the multiple fault curvature attribute characteristic values. The large number of repetitions indicates that the strata at the fault curvature attribute characteristic value in different orientations are all in a fractured state. Then, it is highly likely that the strata corresponding to the fault curvature attribute characteristic value in the entire seismic data is a fault. Therefore, the fourth determination module 1084 uses the fault curvature attribute characteristic value with the most repetitions as a normalized characteristic value. Then, the curvature attribute data corresponding to the normalized characteristic value is obtained in the curvature attribute data body at different orientations, and the curvature attribute data at all orientations are merged to obtain a fault attribute map with a clear fault display.

[0092] According to a third aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for characterizing a fault attribute map in the first aspect or any possible implementation of the first aspect are implemented.

[0093] According to a fourth aspect of the present invention, there is provided a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for characterizing a fault attribute map in the first aspect or any possible implementation of the first aspect.

[0094] Although this specification includes many specific implementation details, these should not be interpreted as limiting the scope of any invention or the scope of protection claimed, but are mainly used to describe the features of the specific embodiments of specific inventions. Certain features described in multiple embodiments in this specification may also be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment may also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although features may work in certain combinations as described above and even initially claim protection, one or more features from the claimed combination may be removed from the combination in some cases, and the claimed combination may point to a sub-combination or a variation of a sub-combination.

[0095] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or requiring that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

[0096] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

[0097] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article 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, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0098] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. The present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for describing a fault attribute map, characterized in that: The method comprises: Obtaining curvature attribute data volumes in seismic data volumes at different orientations; Extracting curvature attribute values ​​along the target layer according to the curvature attribute data bodies in different directions, and generating a curvature attribute value plane map; Determining fault curvature attribute characteristic values ​​at different orientations according to the curvature attribute value plane diagrams at different orientations; Normalizing the fault curvature attribute characteristic values ​​at different orientations to obtain normalized characteristic values; The curvature attribute data volumes in different directions are superimposed and fused according to the normalized eigenvalues ​​and drawn into a fault attribute map.

2. The method for describing a fault attribute map according to claim 1, characterized in that: The step of determining fault curvature attribute characteristic values ​​at different orientations according to the curvature attribute value plane diagrams at different orientations comprises: According to the curvature attribute value plane diagrams at different orientations, instantaneous real amplitude attributes at different orientations are extracted along the target layer.

3. The method for describing a fault attribute map according to claim 1, characterized in that: The step of determining characteristic values ​​of fault curvature attributes in different orientations further includes: Performing differential amplification processing on the curvature attribute value range of the curvature attribute value plane graph; Performing color adjustment on the curvature attribute value plane map; The curvature attribute value at which the color suddenly changes is determined as the fault curvature attribute characteristic value.

4. The method for describing a fault attribute map according to claim 1, characterized in that: The step of normalizing the fault curvature attribute characteristic values ​​at different orientations to obtain normalized characteristic values ​​comprises: Determining the fault curvature attribute characteristic value with the greatest number of repetitions according to the fault curvature attribute characteristic values ​​at different orientations; The fault curvature attribute characteristic value with the largest number of repetitions is used as the normalized characteristic value.

5. A device for depicting a fault attribute map, characterized in that: The device comprises: An acquisition module, the acquisition module is used to acquire curvature attribute data volumes in seismic data volumes at different orientations; A generating module, the generating module is used to extract curvature attribute values ​​along the target layer according to the curvature attribute data bodies in different directions, and generate a curvature attribute value plane map; A first determination module, the first determination module is used to determine the fault curvature attribute characteristic values ​​at different orientations according to the curvature attribute value plane diagrams at different orientations; A first processing module, the first processing module is used to normalize the fault curvature attribute characteristic values ​​at different orientations to obtain normalized characteristic values; A fusion module is used to superimpose and fuse the curvature attribute data volumes in different directions according to the normalized eigenvalues ​​and draw a fault attribute map.

6. The device for depicting a fault attribute map according to claim 5, characterized in that: The first determining module comprises: An extraction module is used to extract instantaneous real amplitude attributes at different directions along the target layer according to the curvature attribute value plane diagram at different directions.

7. The device for depicting a fault attribute map according to claim 5, characterized in that: The first determining module also includes: A second processing module, the second processing module is used to perform differential amplification processing on the curvature attribute value range of the curvature attribute value plane graph; A color adjustment module, the color adjustment module is used to perform color adjustment processing on the curvature attribute value plane map; The second determining module is used to determine that the curvature attribute value plane graph with a sudden color change is a fault curvature attribute characteristic value.

8. The device for depicting a fault attribute map according to claim 5, characterized in that: The first processing module comprises: A third determination module, the third determination module is used to determine the fault curvature attribute characteristic value with the largest number of repetitions according to the fault curvature attribute characteristic values ​​at different orientations; A fourth determining module is used to use the fault curvature attribute characteristic value with the largest number of repetitions as the normalized characteristic value.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for describing a fault attribute map according to any one of claims 1 to 4 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for describing a fault attribute map according to any one of claims 1 to 4 are implemented.

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