Fractured-vuggy reservoir orientation daughter feature fusion characterization method and device

Abstract

The invention provides a fractured-vuggy reservoir orientation daughter feature fusion characterization method and device. According to the method, through azimuth seismic attribute screening, azimuth main feature parameters are extracted, finally feature extraction results of different azimuths are fused, and the continuity and the signal-to-noise ratio of fracture characterization can be remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of integrated characterization of sub - body features in different azimuths of fracture - cave reservoirs, and more particularly, to a method and device for integrated characterization of sub - body features in different azimuths of fracture - cave reservoirs. Background Art

[0002] Fractures and caves are a special formation structure, commonly found in the oblique updip area of fault - block piedmont - derived basins and tectonic hinge zones. They can provide good accumulation spaces and migration channels for oil and gas, and are important favorable areas rich in oil and gas resources. Large - scale fracture - cave oil and gas fields have developed in many basins in China, such as the Sichuan Basin, Ordos Basin, and Songliao Basin. With the continuous deepening of the understanding of fracture - cave formation and the progress of exploration technology means, the number of discovered fracture - cave oil and gas fields shows an increasing trend year by year.

[0003] In fracture - cave oil and gas exploration, the interpretation and understanding of seismic data have always been at the core. In recent years, seismic data acquisition and processing technologies in the azimuth offset domain and azimuth angle domain have made great progress and have been commercially applied in oil fields for the first time. By controlling the offset or deflection angle of the ray path, these technologies can effectively improve seismic resolution and significantly improve the detection effect of complex geological bodies such as fault - block zones. However, these advanced data acquisition means also place higher requirements on subsequent interpretation and understanding.

[0004] The current seismic data interpretation process and technical system are mainly based on traditional zero - offset comprehensive seismic data. The wave - field propagation characteristics and signal characteristics of azimuth - divided and wide - azimuth seismic data are quite different from those of conventional data in many aspects. Directly applying the conventional interpretation process to it, the effect is often greatly limited. This results in the fact that in actual oil - field exploration and development, we cannot effectively identify a large amount of azimuth - divided seismic data collected, and the geological information contained therein has not been fully explored and utilized.

[0005] Especially in the well - location siting demonstration and subsequent fine - description stage, it is always necessary to rely on the comparison and analysis of the interpretation results of seismic data and the actual drilling situation to further improve the success rate of the next - step exploration. However, the direct application of current azimuth - divided data is seriously insufficient, making it impossible for us to establish an effective corresponding relationship and unable to make accurate and reliable predictions and evaluations. This directly leads to the blindness of well - location design. Although the data volume is huge, the actual drilling encounter effect cannot be ensured.

[0006] Generally speaking, the azimuthal data itself provides the possibility of higher resolution and richer information. However, without supporting technical means, we cannot effectively utilize these advanced data. Moreover, due to the uncertainty of the interpretation results, it may even mislead the actual drilling operations. Therefore, there is an urgent need to establish a supporting interpretation and recognition technology for the azimuthal data volume to achieve the effective transformation from data to information and then to knowledge, so that it can effectively serve the prediction and description of fracture-cavity oil and gas fields and clarify exploration. Summary of the Invention

[0007] In view of this, the present invention discloses a feature fusion characterization of azimuthal sub-volumes in a fracture-cavity reservoir, which can fully exploit the potential of azimuthal seismic data, effectively improve the continuity and signal-to-noise ratio of fracture characterization, and enhance the exploration and development effect.

[0008] According to one aspect of the present invention, a method for feature fusion characterization of azimuthal sub-volumes in a fracture-cavity reservoir is proposed. The method includes:

[0009] Step 1: Screen multiple azimuthal seismic data sub-volumes according to the dominant development azimuth of fracture-cavity reservoirs.

[0010] Step 2: Extract various fracture attribute information from the multiple azimuthal seismic data sub-volumes, and select some or all of the extracted various fracture attribute information as azimuthal seismic attribute data.

[0011] Step 3: Perform principal component analysis on each azimuthal seismic attribute data to extract azimuthal main feature parameters.

[0012] Step 4: Fuse the azimuthal main feature parameters of each azimuthal seismic attribute data to obtain the comprehensive structural information of the fracture-cavity reservoir.

[0013] In some embodiments, the range selection method for screening multiple azimuthal seismic data sub-volumes is 0 - 30°, 30 - 60°, 60 - 90°, 90 - 120°, 120 - 150°, 150 - 180° or 0 - 45°, 45 - 90°, 90 - 135°, 135 - 180°.

[0014] In some embodiments, extracting various fracture attribute information includes:

[0015] Extracting the various fracture attribute information by means of automatic fracture interpretation;

[0016] Or extracting the various fracture attribute information by means of coherence.

[0017] In some embodiments, Step 4 specifically includes:

[0018] Summarize the azimuthal main feature parameters of each azimuthal seismic attribute data;

[0019] Combine the eigenvalues of the same principal component at different azimuths into an eigenvalue vector;

[0020] Normalize each eigenvalue vector to eliminate the influence of dimension;

[0021] Calculate the weight of each eigenvector;

[0022] Multiply the normalized eigenvalue vector by the weight to obtain a weighted fusion eigenvalue matrix;

[0023] Map the weighted fusion eigenvalue matrix to the prestack section spliced by the multiple azimuth seismic data sub-volumes to obtain the comprehensive structural information of the fracture-vuggy reservoir.

[0024] According to one aspect of the present invention, a fracture-vuggy reservoir azimuth sub-volume feature fusion characterization device is also proposed. The device includes:

[0025] An azimuth sub-volume screening unit for screening multiple azimuth seismic data sub-volumes according to the dominant development azimuth of the fracture-vuggy reservoir body;

[0026] An azimuth seismic attribute extraction unit for extracting various fracture attribute information on the multiple azimuth seismic data sub-volumes and selecting some or all of the extracted various fracture attribute information as azimuth seismic attribute data;

[0027] A principal component analysis unit for performing principal component analysis on each azimuth seismic attribute data to extract azimuth main feature parameters;

[0028] A multi-azimuth fusion unit for fusing the azimuth main feature parameters of each azimuth seismic attribute data to obtain the comprehensive structural information of the fracture-vuggy reservoir.

[0029] In some embodiments, the range selection method for screening multiple azimuth seismic data sub-volumes is 0-30°, 30-60°, 60-90°, 90-120°, 120-150°, 150-180° or 0-45°, 45-90°, 90-135°, 135-180°.

[0030] In some embodiments, in the azimuth seismic attribute extraction unit, the extraction of various fracture attribute information includes;

[0031] Extract the various fracture attribute information by means of automatic fracture interpretation;

[0032] Or extract the various fracture attribute information by means of coherence.

[0033] In some embodiments, the multi-azimuth fusion unit is specifically used for:

[0034] Summarize the azimuth main characteristic parameters of seismic attribute data in each azimuth;

[0035] Combine the eigenvalues of the same principal component at different azimuths into an eigenvalue vector;

[0036] Perform normalization processing on each eigenvalue vector to eliminate the influence of dimension;

[0037] Calculate the weight of each eigenvector;

[0038] Multiply the normalized eigenvalue vector by the weight to obtain a weighted fusion eigenvalue matrix;

[0039] Map the weighted fusion eigenvalue matrix to the prestack section spliced by the multiple azimuth seismic data sub-volumes to obtain the comprehensive structure information of the fracture-vuggy reservoir.

[0040] According to another aspect of the present invention, an electronic device is further provided, and the electronic device includes:

[0041] A memory storing executable instructions;

[0042] A processor that runs the executable instructions in the memory to implement the fracture-vuggy reservoir sub-azimuth sub-volume feature fusion characterization method described above.

[0043] According to another aspect of the present invention, a computer-readable storage medium is further provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the fracture-vuggy reservoir sub-azimuth sub-volume feature fusion characterization method described above is implemented.

[0044] According to the technical solution of the present invention, the fusion characterization technology based on sub-azimuth sub-volumes is used to realize the efficient use of azimuth seismic data. The present invention screens azimuth seismic attributes, extracts azimuth main characteristic parameters, and finally fuses the feature extraction results of different azimuths, which can significantly improve the continuity and signal-to-noise ratio of fracture characterization. Each aspect of this technical solution has at least the following advantages.

[0045] 1) Improve the prediction accuracy of fracture-vuggy oil and gas fields

[0046] The azimuth sub-volume feature fusion technology established by the present invention can significantly improve the ability to identify and depict the structure of complex fracture-vuggy reservoirs. Through the complementary fusion of features between sub-volumes, the utilization of regional geological information is greatly enhanced, and the description of key details is improved. This provides a more accurate and reliable geological prediction basis for subsequent drilling, helps to determine the comprehensive optimal well positions, and thus directly improves the drilling success rate.

[0047] 2) Reduce the risk of blind drilling

[0048] In the absence of effective interpretation means, azimuthal data often cannot be directly correlated with the actual geology, bringing great drilling risks. By establishing interpretation means adapted to the characteristics of azimuthal data, the present invention realizes the effective conversion of data into actual geological information, provides richer and more accurate support for well location design, effectively reduces the probability of blind drilling, and saves huge drilling costs.

[0049] 3) Tap the potential of data and improve data utilization efficiency

[0050] The present invention fully considers the differences in aspects such as wave field propagation of different azimuthal sub-bodies, can more fully tap and utilize the information contained in azimuthal data, and significantly improves the application efficiency of the data itself. This provides a solid basis for the understanding of the development of azimuthal technology.

[0051] 4) High cost-effectiveness and easy to promote and implement

[0052] The core of the present invention lies in the method and process, without relying on a large amount of additional resource investment. Establishing and implementing this process only requires the investment of software and manpower, with low cost and high efficiency. The improved interpretation and recognition effect directly corresponds to a substantial increase in the drilling success rate, bringing considerable economic benefits. At the same time, this technology is also very easy to promote and apply in the industry.

[0053] 5) Strong advancement and high technical level

[0054] The present invention fully combines the current advanced seismic data acquisition and imaging technologies, solves the technical problems commonly faced in the industry, and fully demonstrates strong forward-looking. The overall technical level and innovation points are relatively high, at the forefront of the industry's technical development, and are of great significance for promoting the improvement of regional exploration level.

[0055] The method and device of the present invention have other characteristics and advantages, which will be obvious in the accompanying drawings and subsequent specific embodiments incorporated herein, or will be described in detail in the accompanying drawings and subsequent specific embodiments incorporated herein. These accompanying drawings and specific embodiments are jointly used to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] By describing the exemplary embodiments of the present invention in more detail in conjunction with the accompanying drawings, the above and other objects, features, and advantages of the present invention will become more obvious. Among them, in the exemplary embodiments of the present invention, the same reference numerals generally represent the same components.

[0057] Figure 1 The flowchart of the method for fusing and characterizing the features of azimuthal sub-bodies in a fractured-vuggy reservoir according to an embodiment of the present invention is shown.

[0058] Figures 2(a) and (b) respectively show the fracture identification effects obtained by different azimuth range selection methods according to an embodiment of the present invention.

[0059] Figures 3(a) and (b) respectively show schematic diagrams of fracture attribute information extracted by different methods according to an embodiment of the present invention.

[0060] Figure 4 Shows the extraction map of azimuthal characteristic values.

[0061] Figure 5 (a) and (b) respectively show schematic diagrams of fracture characterization effects obtained according to the conventional full superposition method and according to an embodiment of the present invention. Detailed implementation manners

[0062] The preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present invention will be more thorough and complete, and can fully convey the scope of the present invention to those skilled in the art.

[0063] Example 1

[0064] Figure 1 Shows a flowchart of a method for fusing and characterizing sub-azimuth features of a fracture-vug reservoir according to an embodiment of the present invention. As shown in the figure, the method includes steps 1 to 4.

[0065] Step 1: Screen multiple azimuth seismic data subsets according to the dominant development azimuth of fracture-vug reservoirs.

[0066] The dominant development azimuth of fracture-vug reservoirs refers to the dominant tectonic movement direction that controls and affects the generation and development of fracture-vug type oil and gas reservoirs in a basin or oilfield.

[0067] The generation of fractures and vugs is closely related to regional tectonic movements and is generally formed in fracture systems under tensile stress. The direction of tectonic movement determines the distribution direction of fractures, thus directly controlling the directional distribution of fractures and vugs. In a basin or oilfield, due to differences in tectonic movements, one or several dominant directions will be formed, and the fracture-vug systems developed along these directions are the most developed.

[0068] These fracture-vug systems with strong development advantages are the most critical geological bodies that control and affect the overall distribution, volume level, and oil and gas storage effects of reservoirs.

[0069] Therefore, these directions are the preferred development orientations of the fracture-vug reservoirs in the basin. They represent the strongest tectonic compressive stress field within the region and are important parameters that determine and control the accumulation laws of fracture-vug oil and gas reservoirs. Determining these preferred development orientations is of great significance for guiding the prediction of fracture-vug oil and gas reservoirs within the region.

[0070] In step 1, based on existing geological research results, the preferred development orientations of the fracture-vug sandbody reservoirs within the target area can be determined. This is usually achieved through the analysis and judgment of the regional geological background and structure. Then, multiple azimuth angle intervals are set according to the determined preferred development orientations of the fracture-vug bodies. These azimuth angle intervals include the preferred development orientations within a certain angular range; and then, seismic data sub-volumes corresponding to the set azimuth angle intervals are extracted from the pre-stacked full azimuth angle domain seismic data volume.

[0071] In some embodiments, the selection methods for screening multiple azimuth angle seismic data sub-volumes are 0 - 30°, 30 - 60°, 60 - 90°, 90 - 120°, 120 - 150°, 150 - 180°. In some other embodiments, the selection methods for screening multiple azimuth angle seismic data sub-volumes are 0 - 45°, 45 - 90°, 90 - 135°, 135 - 180°.

[0072] Then, preprocessing such as high-density velocity analysis, residual static correction, and mapping migration can also be performed separately on the seismic data sub-volumes extracted for each azimuth angle interval to improve the signal-to-noise ratio. High-density prestack time migration can also be performed on the azimuth angle sub-volume seismic data after preprocessing to obtain multiple seismic profile images corresponding to different azimuth angles.

[0073] In summary, the purpose of step 1 is to extract seismic data sub-volumes corresponding to the preferred development orientations from the full azimuth seismic data volume, providing input for subsequent attribute analysis and interpretation.

[0074] Step 2, extract multiple fracture attribute information on the multiple azimuth angle seismic data sub-volumes, and select some or all of the extracted multiple fracture attribute information as azimuth angle seismic attribute data.

[0075] In some embodiments, the multiple fracture attribute information can be extracted by means of automatic fracture interpretation.

[0076] In some examples, the general process of obtaining the main and secondary fracture results through automatic fracture interpretation to extract multiple fracture attribute information is as follows:

[0077] 1) Implement automatic fracture interpretation of the screened multiple azimuth angle seismic data sub-volumes, mainly including dip interpretation and edge feature extraction interpretation, to obtain the automatic picking results of the fracture system reflecting the main trends and detailed structures of the regional fracture zones;

[0078] 2) Set a sampling window on the automatically picked fracture zone, sample at a certain distance interval to obtain fracture zone samples containing the fracture zone.

[0079] Calculate various seismic attributes of each fracture sample, mainly including attributes such as dispersion, coherence, directionality, and relative reflection intensity change, to form three-dimensional cube attribute data.

[0080] Perform directional filtering on the attribute cube, retain the attribute components consistent with the main fracture direction, eliminate the noise components perpendicular to the fracture strike, and enhance the continuity of the fracture sequence.

[0081] Select various attributes that can effectively describe the fracture information from the filtered attribute component results, which are the extracted multiple fracture attribute information.

[0082] Through the above process, finally obtain the seismic attribute expression results that can fully characterize the main fractures and secondary small fault blocks. These attributes reflect the geophysical responses of the fractures in multiple aspects such as density, filling property, and volume characteristics.

[0083] In some other embodiments, the multiple fracture attribute information can be extracted by a coherence method.

[0084] In some examples, the general process of obtaining the main and secondary fracture results by a coherence method to extract multiple fracture attribute information is as follows:

[0085] 1) Based on the structural coherence method, extract the features reflecting the discontinuity changes in the region.

[0086] 2) Through correlation analysis, determine the feature subset highly correlated with the actual fracture zone.

[0087] 3) Along the strike of the selected feature subset, set a sampling window with a certain width.

[0088] 4) Calculate various fracture attribute information within the sampling window.

[0089] The coherence method can accurately extract the range of the fracture zone, and the extracted fracture attribute information can reflect and quantify the detailed change characteristics of the fracture. It realizes the fine high-resolution characterization of the main fractures and complex small fault blocks.

[0090] In this step, first extract different types of fracture attribute information, such as coherence attribute, curvature attribute, etc., from each azimuth seismic data sub-volume, and then screen them. Retain the attributes that can well represent the fracture information, and screen out the attributes with large noise or redundant information. Thus, obtain the seismic attributes that can best represent the fracture information on each azimuth sub-volume, that is, the azimuth seismic attribute data.

[0091] Step 3: Perform principal component analysis on the seismic attribute data at each azimuth angle to extract the azimuth main feature parameters.

[0092] In some examples, the process of performing principal component analysis on the seismic attribute data at each azimuth angle to extract the azimuth main feature parameters may include:

[0093] 1) Collect and prepare the seismic attribute data in different azimuth angle intervals, such as three-dimensional cubes of multiple types of attributes such as dispersion, coherence, amplitude, etc.;

[0094] 2) Perform principal component analysis on each azimuth angle attribute data separately. The principal component analysis is transformed through orthogonal transformation to a lower-dimensional coordinate system that can better represent the original data information;

[0095] 3) Calculate the variable contribution rate on each principal component dimension, and select the number of principal components to be retained according to the contribution rate size. For example, the first few principal components with a cumulative contribution rate reaching 80% can be selected;

[0096] 4) These retained low-dimensional principal components are the azimuth main feature parameters, and their coordinate values are the main eigenvalue of the azimuth attribute data information.

[0097] These main eigenvalues can represent the main information components of the original attribute data corresponding to the azimuth angle, eliminating redundancy and noise in the data. Through the above process of principal component analysis, the main information features in the azimuth seismic attribute data can be effectively extracted, laying a foundation for subsequent feature fusion processing.

[0098] Step 4: Fuse the azimuth main feature parameters of the seismic attribute data at each azimuth angle to obtain the comprehensive structural information of the fracture-vuggy reservoir.

[0099] In some embodiments, this step specifically includes:

[0100] Summarize the azimuth main feature parameters of the seismic attribute data at each azimuth angle;

[0101] Combine the eigenvalues of the same principal component at different azimuth angles into an eigenvalue vector;

[0102] Perform normalization processing on each eigenvalue vector to eliminate the influence of dimensions;

[0103] Calculate the weight of each eigenvector;

[0104] Multiply the normalized eigenvalue vector by the weight to obtain a weighted fusion eigenvalue matrix;

[0105] Map the weighted fusion eigenvalue matrix to the pre-stack section spliced by the multiple azimuth angle seismic data sub-volumes to obtain the comprehensive structural information of the fracture-vuggy reservoir.

[0106] The main beneficial effects of integrating the azimuth main characteristic parameters of seismic attribute data in all azimuths to obtain the comprehensive structural information of the fracture-vuggy reservoir are as follows:

[0107] 1) Improve the signal-to-noise ratio

[0108] Through principal component analysis, the azimuth main characteristic parameters have eliminated the noise and redundant components in the attribute data of each azimuth. Fusing these characteristic parameters with high signal-to-noise ratio can greatly improve the reliability of the interpretation results.

[0109] 2) More continuous structural description

[0110] The attributes in different azimuths reflect different structural information. Feature fusion can make this information complementary, significantly improve the continuity expression of the boundaries of geological bodies such as fault zones, and is more conducive to the accurate description of oil and gas reservoirs.

[0111] 3) Make more efficient use of the advantages of azimuth data

[0112] Feature fusion fully combines the advantages of data in different azimuths, such as improving the accuracy of reservoir description and enhancing the recognition of thin layers and structural details, and can more effectively play the specialty of azimuth technology in detailed description.

[0113] 4) Provide a more reliable basis for drilling

[0114] Comprehensively using multi-azimuth features can significantly improve the prediction and recognition ability of key geological bodies, provide a richer and more accurate geological basis for determining the drill point location, etc., and directly improve the drilling efficiency.

[0115] 5) Better support subsequent fine description

[0116] The feature fusion result can reflect richer and more reliable geological information within the region, and is a more scientific and reliable basis for carrying out fine description and improving the recovery rate.

[0117] Generally speaking, the azimuth feature fusion of multiple azimuths can further explore and improve the data value, and provide strong support for the discovery and efficient development of fracture-vuggy oil and gas fields.

[0118] According to the method for characterizing the fracture-vuggy reservoir by azimuth sub-body feature fusion in this embodiment, the fusion characterization technology based on azimuth sub-bodies is used to realize the efficient use of azimuth seismic data. In this embodiment, through azimuth seismic attribute screening, azimuth main characteristic parameters are extracted, and finally the feature extraction results in different azimuths are fused, which can significantly improve the continuity and signal-to-noise ratio of fracture characterization.

[0119] Example 2

[0120] According to an embodiment of the present invention, a device for fusing and characterizing sub - body features in different azimuths of a fracture - cave reservoir is provided. The device includes:

[0121] An azimuth sub - body screening unit for screening multiple azimuth - angle seismic data sub - bodies according to the dominant development azimuth of fracture - cave reservoirs.

[0122] An azimuth - angle seismic attribute extraction unit for extracting various fracture attribute information on the multiple azimuth - angle seismic data sub - bodies and selecting some or all of the extracted various fracture attribute information as azimuth - angle seismic attribute data.

[0123] A principal component analysis unit for performing principal component analysis on each azimuth - angle seismic attribute data to extract azimuth main feature parameters.

[0124] A multi - azimuth fusion unit for fusing the azimuth main feature parameters of each azimuth - angle seismic attribute data to obtain the comprehensive structural information of the fracture - cave reservoir.

[0125] In some embodiments, the range selection method for screening multiple azimuth - angle seismic data sub - bodies is 0 - 30°, 30 - 60°, 60 - 90°, 90 - 120°, 120 - 150°, 150 - 180° or 0 - 45°, 45 - 90°, 90 - 135°, 135 - 180°.

[0126] In some embodiments, in the azimuth - angle seismic attribute extraction unit, extracting various fracture attribute information includes:

[0127] Extracting the various fracture attribute information by means of automatic fracture interpretation;

[0128] Or extracting the various fracture attribute information by means of coherence.

[0129] In some embodiments, the multi - azimuth fusion unit is specifically used for:

[0130] Summarizing the azimuth main feature parameters of each azimuth - angle seismic attribute data;

[0131] Combining the eigenvalues of the same principal component of different azimuths into an eigenvalue vector;

[0132] Performing normalization processing on each eigenvalue vector to eliminate the influence of dimension;

[0133] Calculating the weight of each eigenvector;

[0134] Multiplying the normalized eigenvalue vector by the weight to obtain a weighted - fused eigenvalue matrix;

[0135] Map the weighted fusion eigenvalue matrix to the prestack section spliced by the multiple azimuth seismic data sub-volumes to obtain the comprehensive structural information of the fracture-vug reservoir.

[0136] According to the fracture-vug reservoir sub-azimuth volume feature fusion characterization device of this embodiment, the technology of fusion characterization based on sub-azimuth volumes is used to realize the efficient use of azimuth seismic data. Through azimuth seismic attribute screening, azimuth main feature parameters are extracted in this embodiment, and finally the feature extraction results of different azimuths are fused, which can significantly improve the continuity and signal-to-noise ratio of fracture characterization.

[0137] For other detailed descriptions and advantages of this embodiment, reference can be made to the corresponding descriptions in the foregoing embodiments, which will not be elaborated herein.

[0138] Example 3

[0139] According to another aspect of the present invention, an electronic device is further provided. The electronic device includes:

[0140] A memory storing executable instructions:

[0141] A processor that runs the executable instructions in the memory to implement the fracture-vug reservoir sub-azimuth volume feature fusion characterization method according to the present invention.

[0142] The method includes the following steps:

[0143] Step 1, screen multiple azimuth seismic data sub-volumes according to the dominant development azimuth of fracture-vug reservoirs;

[0144] Step 2, extract multiple fracture attribute information on the multiple azimuth seismic data sub-volumes, and select some or all of the extracted multiple fracture attribute information as azimuth seismic attribute data;

[0145] Step 3, perform principal component analysis on each azimuth seismic attribute data to extract azimuth main feature parameters;

[0146] Step 4, fuse the azimuth main feature parameters of each azimuth seismic attribute data to obtain the comprehensive structural information of the fracture-vug reservoir.

[0147] In some embodiments, the range selection method for screening multiple azimuth seismic data sub-volumes is 0-30°, 30-60°, 60-90°, 90-120°, 120-150°, 150-180° or 0-45°, 45-90°, 90-135°, 135-180°.

[0148] In some embodiments, extracting multiple fracture attribute information includes;

[0149] Extract the multiple fracture attribute information by means of automatic fracture interpretation;

[0150] Or extract the multiple fracture attribute information by means of coherence.

[0151] In some embodiments, step 4 specifically includes:

[0152] Summarize the azimuth main characteristic parameters of the seismic attribute data at each azimuth angle;

[0153] Combine the eigenvalues of the same principal component at different azimuth angles into an eigenvalue vector;

[0154] Perform normalization processing on each eigenvalue vector to eliminate the influence of dimension;

[0155] Calculate the weight of each eigenvector;

[0156] Multiply the normalized eigenvalue vector by the weight to obtain a weighted fusion eigenvalue matrix;

[0157] Map the weighted fusion eigenvalue matrix to the pre-stack section spliced by the multiple azimuth seismic data sub-volumes to obtain the comprehensive structural information of the fracture-vuggy reservoir.

[0158] Specifically, the memory may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0159] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform the desired functions. In an embodiment of the present invention, the processor is used to run the computer-readable instructions stored in the memory.

[0160] According to the fracture-vuggy reservoir azimuth sub-volume feature fusion characterization scheme of this embodiment, the fusion characterization technology based on azimuth sub-volumes is used to realize the efficient use of azimuth seismic data. This embodiment extracts the azimuth main characteristic parameters through azimuth seismic attribute screening, and finally fuses the feature extraction results of different azimuths, which can significantly improve the continuity and signal-to-noise ratio of fracture characterization.

[0161] For the detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details will not be repeated here.

[0162] Example 4

[0163] According to another aspect of the present invention, there is also provided a computer-readable storage medium storing a computer program, which when executed by a processor implements the method for fusing and characterizing the features of sub-bodies in different azimuths of a fracture-vug reservoir according to the present invention.

[0164] The method includes the following steps:

[0165] Step 1: Screen multiple azimuth seismic data sub-bodies according to the dominant development azimuth of the fracture-vug reservoir body;

[0166] Step 2: Extract various fracture attribute information from the multiple azimuth seismic data sub-bodies, and select some or all of the extracted various fracture attribute information as azimuth seismic attribute data;

[0167] Step 3: Perform principal component analysis on each azimuth seismic attribute data to extract azimuth main feature parameters;

[0168] Step 4: Fuse the azimuth main feature parameters of each azimuth seismic attribute data to obtain the comprehensive structural information of the fracture-vug reservoir.

[0169] In some embodiments, the range selection method for screening multiple azimuth seismic data sub-bodies is 0-30°, 30-60°, 60-90°, 90-120°, 120-150°, 150-180° or 0-45°, 45-90°, 90-135°, 135-180°.

[0170] In some embodiments, extracting various fracture attribute information includes;

[0171] Extracting the various fracture attribute information by means of automatic fracture interpretation;

[0172] Or extracting the various fracture attribute information by means of coherence.

[0173] In some embodiments, Step 4 specifically includes:

[0174] Summarize the azimuth main feature parameters of each azimuth seismic attribute data;

[0175] Combine the eigenvalues of the same principal component in different azimuths into an eigenvalue vector;

[0176] Perform normalization processing on each eigenvalue vector to eliminate the influence of dimension;

[0177] Calculate the weight of each eigenvector;

[0178] Multiply the normalized eigenvalue vector by the weight to obtain a weighted fusion eigenvalue matrix;

[0179] Map the eigenvalue matrix after weighted fusion to the prestack section stitched by the multiple azimuth seismic data sub-volumes to obtain the comprehensive structural information of the fracture-vug reservoir.

[0180] According to the computer-readable storage medium of the embodiment of the present invention, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are run by a processor, all or part of the steps of the methods of the various embodiments of the present invention described above are executed.

[0181] The above-mentioned computer-readable storage medium includes but is not limited to: optical storage media (such as CD-ROMs and DVDs), magneto-optical storage media (such as MOs), magnetic storage media (such as magnetic tapes or external hard drives), media with built-in rewritable non-volatile memories (such as memory cards), and media with built-in ROMs (such as ROM cartridges).

[0182] Those skilled in the art should understand that, in order to solve the technical problem of how to obtain good user experience effects, known structures such as communication buses and interfaces may also be included in this embodiment, and these known structures should also be included in the protection scope of the present invention.

[0183] According to the fracture-vug reservoir sub-azimuth sub-volume feature fusion characterization solution of this embodiment, the fusion characterization technology based on sub-azimuth sub-volumes is used to realize the efficient use of azimuth seismic data. In this embodiment, azimuth seismic attributes are screened to extract azimuth main feature parameters, and finally the feature extraction results of different azimuths are fused, which can significantly improve the continuity and signal-to-noise ratio of fracture characterization.

[0184] For the detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details are not repeated herein.

[0185] Example 5

[0186] This embodiment illustrates the process and beneficial effects of the present invention with a specific application.

[0187] To solve the problem that it is difficult to make full use of the azimuth angle seismic data of fracture-vug bodies, the present invention fully excavates the structural information of reservoirs and fracture cracks contained in azimuth sub-volumes, retains the effective information in different azimuth sub-volumes by means of eigenvalue extraction, and summarizes the information of azimuth sub-volumes through information fusion, providing new ideas and solutions for the fine study of fracture-vug body reservoirs.

[0188] First, the azimuth angle ranges for azimuth angle superposition can be screened, and there are two ways to select the ranges. The first is the azimuth angle gather sorting method of 0-30°, 30-60°, 60-90°, 90-120°, 120-150°, and 150-180°. The second is the azimuth angle gather sorting method of 0-45°, 45-90°, 90-135°, and 135-180°. The three figures in Fig. 2(a) show the fracture identification effects extracted from the azimuth sub-bodies based on 0-30°, 90-120°, and 0-180° from left to right in sequence. The three figures in Fig. 2(a) show the fracture identification effects extracted from the azimuth sub-bodies based on 0-45°, 90-135°, and 0-180° from left to right in sequence. It can be seen that in this embodiment, compared with the first one, the second azimuth angle gather sorting method is better in the continuity of the main fractures and the resolution of the secondary fractures. Therefore, the second azimuth gather sorting method is selected.

[0189] Secondly, the fracture attribute extraction methods are screened. Fig. 3(a) shows the results of obtaining the main and secondary fractures through automatic fracture interpretation, and Fig. 3(b) shows the results of obtaining the main and secondary fractures through the coherence method. It can be seen that in this embodiment, the results obtained by the coherence method are better than those obtained by the automatic fracture interpretation method, and perform better in terms of resolution and signal-to-noise ratio. Therefore, the coherence method is selected to extract fracture attribute information.

[0190] Eigenvalue extraction is performed on the attribute extraction results of 0-45°, 45-90°, 90-135°, and 135-180°. PC0, PC1, PC2, and PC3 respectively represent the eigenvector solutions of this component obtained by solving each classification. The eigenvalue column is the eigenvalues of the four azimuth sub-bodies, and the last row represents the proportion of this eigenvalue in the fusion result, as Figure 4 shown.

[0191] Finally, the obtained eigenvalues are written in matrix form and then displayed, and compared with the conventional full superposition results. Figure 5 (a) shows the fracture characterization effect of the conventional full superposition results, Figure 5 (b) shows the fracture characterization effect of the azimuth sub-body feature fusion according to the present invention. The three green frames in each figure are the comparison differences with the full superposition results. It can be seen that compared with the conventional full superposition results, the fracture characterization effect of the azimuth sub-body feature fusion according to the present invention has significant improvements in fracture continuity, signal-to-noise ratio, and resolution, providing a reliable data volume for the subsequent fine characterization of the reservoir body.

[0192] For other detailed descriptions of this exemplary embodiment, reference can be made to the corresponding descriptions in the foregoing embodiments, which will not be elaborated here.

[0193] All aspects of this technical solution have at least the following advantages.

[0194] 1) Improve the prediction accuracy of fractured-vuggy oil and gas fields

[0195] In summary, the azimuth sub-volume feature fusion technology established by the present invention can significantly improve the ability to identify and depict the structure of complex fractured-vuggy reservoirs. Through the complementary fusion of features between sub-volumes, the utilization of regional geological information is greatly enhanced, and the depiction of key details is improved. This provides a more accurate and reliable geological prediction basis for subsequent drilling, helps to clarify the comprehensive optimal well positions, and thus directly improves the drilling success rate.

[0196] 2) Reduce the risk of blind drilling

[0197] In the absence of effective interpretation means, the azimuthal data often cannot directly correspond to the actual geology, bringing great drilling risks. The present invention realizes the effective conversion from data to actual geological information by establishing interpretation means adapted to the characteristics of azimuthal data, provides richer and more accurate support for well location design, effectively reduces the probability of blind drilling, and saves huge drilling costs.

[0198] 3) Tap the data potential and improve the data utilization efficiency

[0199] The present invention fully considers the differences in wave field propagation and other aspects of different azimuth sub-volumes, can more fully tap and utilize the information contained in the azimuthal data, and significantly improves the application efficiency of the data itself. This provides a solid basis for the development of azimuthal technology in terms of interpretation and understanding.

[0200] 4) High cost-effectiveness and easy to promote and implement

[0201] The core of the present invention lies in the method and process, without relying on a large amount of additional resource investment. Establishing and implementing this process only requires the investment of software and manpower, with low cost and high efficiency. The improved interpretation and recognition effect directly corresponds to a significant increase in the drilling success rate, which can bring considerable economic benefits. At the same time, this technology is also very easy to promote and apply in the industry.

[0202] 5) Strong advancement and high technical level

[0203] The present invention fully combines the current advanced seismic data acquisition and imaging technologies, solves the technical problems commonly faced in the industry, and fully demonstrates strong forward-looking. The overall technical level and innovation points are relatively high, being at the forefront of the industry's technical development, and are of great significance for promoting the improvement of regional exploration level.

[0204] The above has described the embodiments of the present invention. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, the practical application, or the technical improvement of the technology in the market, or to enable other ordinary technicians in the art to understand the embodiments disclosed herein.

Claims

1. A method for fusing and characterizing the features of sub-bodies in different azimuths of a fracture-vug reservoir, characterized in that, the method comprises: Step 1, screening sub-bodies of seismic data at multiple azimuth angles according to the dominant development azimuth of fracture-vug reservoirs; Step 2, extracting various fracture attribute information from the sub-bodies of seismic data at multiple azimuth angles, and selecting some or all of the extracted various fracture attribute information as azimuth seismic attribute data; Step 3, performing principal component analysis on the azimuth seismic attribute data of each azimuth angle to extract azimuth main feature parameters; Step 4, fusing the azimuth main feature parameters of the azimuth seismic attribute data of each azimuth angle to obtain the comprehensive structural information of the fracture-vug reservoir.

2. The method according to claim 1, characterized in that, the range selection method for screening sub-bodies of seismic data at multiple azimuth angles is 0-30°, 30-60°, 60-90°, 90-120°, 120-150°, 150-180° or 0-45°, 45-90°, 90-135°, 135-180°.

3. The method according to claim 1, characterized in that, extracting various fracture attribute information includes; extracting the various fracture attribute information by means of automatic fracture interpretation; or extracting the various fracture attribute information by means of coherence.

4. The method according to claim 1, characterized in that, Step 4 specifically comprises: summarizing the azimuth main feature parameters of the azimuth seismic attribute data of each azimuth angle; combining the eigenvalues of the same principal component of different azimuth angles into an eigenvalue vector; performing normalization processing on each eigenvalue vector to eliminate the influence of dimension; calculating the weight of each eigenvector; multiplying the normalized eigenvalue vector by the weight to obtain a weighted fusion eigenvalue matrix; mapping the weighted fusion eigenvalue matrix to the pre-stack section spliced by the sub-bodies of seismic data at multiple azimuth angles to obtain the comprehensive structural information of the fracture-vug reservoir.

5. A device for fusing and characterizing the features of sub-bodies in different azimuths of a fracture-vug reservoir, characterized in that, the device comprises: An azimuth sub-body screening unit for screening sub-bodies of seismic data at multiple azimuth angles according to the dominant development azimuth of fracture-vug reservoirs; An azimuth seismic attribute extraction unit for extracting various fracture attribute information from the sub-bodies of seismic data at multiple azimuth angles, and selecting some or all of the extracted various fracture attribute information as azimuth seismic attribute data; A principal component analysis unit for performing principal component analysis on the azimuth seismic attribute data of each azimuth angle to extract azimuth main feature parameters; A multi-azimuth fusion unit for fusing the azimuth main feature parameters of the azimuth seismic attribute data of each azimuth angle to obtain the comprehensive structural information of the fracture-vug reservoir.

6. The device according to claim 5, characterized in that, the range selection method for screening sub-bodies of seismic data at multiple azimuth angles is 0-30°, 30-60°, 60-90°, 90-120°, 120-150°, 150-180° or 0-45°, 45-90°, 90-135°, 135-180°.

7. The device according to claim 5, characterized in that, In the azimuth seismic attribute extraction unit, multiple fracture attribute information is extracted, including: extracting the multiple fracture attribute information by means of automatic fracture interpretation; or extracting the multiple fracture attribute information by means of coherence.

8. The method according to claim 5, wherein, the multi-azimuth fusion unit is specifically configured to: summarize the azimuth main feature parameters of the seismic attribute data of each azimuth; combine the eigenvalues of the same principal component of different azimuths into an eigenvalue vector; perform normalization processing on each eigenvalue vector to eliminate the influence of dimension; calculate the weight of each eigenvector; multiply the normalized eigenvalue vector by the weight to obtain a weighted fusion eigenvalue matrix; map the weighted fusion eigenvalue matrix to the prestack section spliced by the multiple azimuth seismic data sub-bodies to obtain the comprehensive structural information of the fracture-vuggy reservoir.

9. An electronic device, wherein, the electronic device includes: a memory storing executable instructions; a processor that runs the executable instructions in the memory to implement the method according to any one of claims 1-4.

10. A computer-readable storage medium storing a computer program, which when executed by a processor implements the method according to any one of claims 1-4.

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