Method and device for extracting seismic reflection characteristics of carbonate fractured-vuggy body and electronic equipment

Abstract

The invention discloses a carbonate fractured-vuggy body seismic reflection feature extraction method and device and electronic equipment. The method comprises the steps that seismic data, logging data and drilling data are acquired; acquiring VMD parameter test data based on the seismic data; carrying out VMD parameter testing by utilizing the acquired VMD parameter testing data, logging data and drilling data so as to determine VMD parameters and IMF components most suitable for characterizing fracture-cavity body reflection characteristics; using the determined VMD parameters to carry out VMD decomposition of the whole-region seismic data volume, and obtaining three-dimensional seismic data of IMF component reconstruction; performing main component analysis on the reconstructed three-dimensional seismic data by adopting a PCA (Principal Component Analysis) algorithm, and extracting an optimal reconstructed data volume capable of representing the abnormal reflection characteristics of the fracture-cavity body; performing transverse filtering on the reconstructed data volume; and outputting the filtered reconstructed data. According to the method, seismic reflection characteristic separation of the fracture-cavity body and the background stratum can be realized, and the identifiability and the detection precision of the fracture-cavity type reservoir body are improved.

Description

Technical Field

[0001] The present invention belongs to the field of geophysical exploration technology, and more specifically, relates to a method, device and electronic equipment for extracting seismic reflection characteristics of carbonate rock fractures and caves. Background Art

[0002] Carbonate fracture-cave reservoirs are one of the hotspots of oil and gas exploration in western my country in recent years, and have good prospects for exploration and development. The spatial distribution of fractures and caves in deep fracture-cave carbonate reservoirs is scattered, and the scale, morphology, and internal structure of different fractures and caves are significantly different. In addition, due to the deep burial depth of the reservoir, the signal-to-noise ratio of the seismic signal is low. Therefore, some of the "beaded" seismic responses caused by fractures and caves have poor separation from the background, resulting in difficulty in fracture-cave body detection and strong multi-solution. To address this problem, conventional solutions are mostly interpretive processing methods such as frequency division and filtering, which can enhance the contrast between the fracture-cave body reflection and the background formation. However, for some fracture-cave reservoirs close to the lithology interface, since the lithology of carbonate rock strata is usually quite different from that of the overlying strata, the lithology interface often has strong amplitude characteristics, which causes the reflection characteristics of the fracture-cave body to be "masked", further increasing the difficulty of fracture-cave detection. The application of frequency division, filtering and other methods, while enhancing the "beaded" reflection of the fracture-cave body, also enhances the reflection of the background strata, making it difficult to effectively improve the identifiability of fracture-cave reservoirs. Summary of the invention

[0003] The purpose of the present invention is to provide a method, device and electronic equipment for extracting seismic reflection characteristics of carbonate fracture-cavity bodies, so as to separate the seismic reflection characteristics of fracture-cavity bodies from background strata and improve the identifiability and detection accuracy of fracture-cavity reservoirs.

[0004] To achieve the above objectives, in a first aspect, the present invention proposes a method for extracting seismic reflection characteristics of carbonate fracture-cavity bodies, comprising:

[0005] Acquire seismic data, well logging data, and drilling data;

[0006] Acquiring VMD parameter test data based on the seismic data;

[0007] The VMD parameter test data, logging data and drilling data are used to perform VMD parameter test to determine the VMD parameters of the VMD algorithm and the IMF components that are most suitable for characterizing the reflection characteristics of the fracture-cavity body;

[0008] Using the determined VMD parameters to carry out VMD decomposition of the seismic data volume of the entire region, and obtaining three-dimensional seismic data reconstructed by the IMF components;

[0009] The PCA algorithm is used to perform principal component analysis on the reconstructed 3D seismic data to extract the optimal reconstructed data volume that can characterize the abnormal reflection characteristics of the fracture-cavity body.

[0010] performing lateral filtering on the reconstructed data volume;

[0011] Output the filtered reconstructed data.

[0012] Optionally, the seismic data are time-domain post-stack three-dimensional seismic data, and the drilling data and the logging data are depth-domain data.

[0013] Optionally, the determined VMD parameters include: the number K of decomposed IMF components, a bandwidth limit alpha, a noise tolerance nt and a control error constant tol.

[0014] Optionally, acquiring VMD parameter test data based on the seismic data includes:

[0015] The seismic trace data contained in the seismic profile of the well trajectory are extracted as VMD parameter test data.

[0016] Optionally, performing VMD parameter testing using the acquired VMD parameter test data, logging data, and drilling data includes:

[0017] The VMD parameter test data is calibrated with well seismic calibration and compared with the corresponding drilling data and logging data to determine the parameter values ​​of the VMD parameters.

[0018] Optionally, outputting the filtered reconstructed data includes:

[0019] The filtered reconstructed data is output according to the header information of the original seismic data.

[0020] Optionally, the data format of the reconstructed data output is sgy or segy format.

[0021] In a second aspect, the present invention provides an electronic device, the electronic device comprising:

[0022] at least one processor; and,

[0023] a memory communicatively connected to the at least one processor; wherein,

[0024] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the carbonate fracture-cave seismic reflection feature extraction method described in any one of the first aspects.

[0025] In a third aspect, the present invention proposes a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute the method for extracting seismic reflection characteristics of carbonate fractures and caves as described in any one of the first aspects.

[0026] In a fourth aspect, the present invention provides a carbonate rock fracture-cave body seismic reflection feature extraction device, comprising:

[0027] A data acquisition module, used to acquire seismic data, well logging data and drilling data;

[0028] A test data acquisition module, used for acquiring VMD parameter test data based on the seismic data, well logging data and drilling data;

[0029] A parameter determination module is used to perform VMD parameter testing using the acquired VMD parameter test data to determine the VMD parameters of the VMD algorithm and determine the IMF component that is most suitable for characterizing the reflection characteristics of the fracture-cavity body;

[0030] Using the determined VMD parameters to carry out VMD decomposition of the seismic data volume of the entire region, and obtaining three-dimensional seismic data reconstructed by the IMF components;

[0031] The data extraction module is used to perform principal component analysis on the reconstructed 3D seismic data using the PCA algorithm to extract the optimal reconstructed data volume that can characterize the abnormal reflection characteristics of the fracture-cavity body;

[0032] A filtering module, used for performing lateral filtering on the reconstructed data volume;

[0033] The output module is used to output the filtered reconstructed data.

[0034] The beneficial effects of the present invention are:

[0035] (1) The present invention provides a signal decomposition and reconstruction method based on variational mode decomposition and principal component analysis. According to experiments, the method can extract and reconstruct abnormal reflection characteristics related to carbonate fractures and caves;

[0036] (2) The process of the present invention can reconstruct an interpretative processing data body based on the original seismic data to assist in the interpretation of seismic data, especially for the target screening analysis of carbonate fracture-cavity well locations. The seismic attribute analysis based on the reconstructed data body can highlight the abnormal response of the fracture-cavity body.

[0037] (3) The present invention is different from the existing fracture-cavity anomaly enhancement methods based on post-stack frequency division and other technologies. It can achieve the effect of separating the "beaded" reflection characteristics of the fracture-cavity body from the complex formation background, and realize the reflection characteristics of the fracture-cavity body from observable to identifiable.

[0038] The system of the present invention has other characteristics and advantages, which will be apparent from the drawings incorporated herein and the following detailed description, or will be described in detail in the drawings incorporated herein and the following detailed description, which together serve to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, in which like reference numerals generally represent like components.

[0040] Figure 1 A step diagram of a method for extracting seismic reflection characteristics of carbonate fracture-cavity bodies according to the present invention is shown.

[0041] Figure 2 A flow chart of a method for extracting seismic reflection characteristics of carbonate fracture-cavity bodies according to an embodiment of the present invention is shown.

[0042] Figure 3 A cross-sectional comparison diagram before and after the extraction of the reflection features of the fracture-cavity body in one embodiment of the present invention is shown.

[0043] Figure 4 A comparison diagram of profile attributes before and after extraction of fracture-cavity reflection features in one embodiment of the present invention is shown.

[0044] Figure 5 A comparison diagram of plane attributes before and after extraction of fracture-cavity reflection features in one embodiment of the present invention is shown. DETAILED DESCRIPTION

[0045] VMD (Variational Mode Decomposition) theory is a signal processing method for efficiently estimating and extracting modes and frequencies in signals. It is based on the concept of adaptive mode filtering and uses the variational principle to decompose the signal into a series of intrinsic mode functions (IMFs). Each IMF is represented by some local frequencies and amplitudes and can be regarded as the basic components of the signal. The goal of VMD is to optimize the vibration components of each IMF through iteration, continuously update the IMF set, and finally obtain the optimal IMF set and corresponding frequency values, minimize the energy difference between the signal and its frequency components, and thus achieve signal decomposition and analysis.

[0046] Principal Component Analysis (PCA) is a commonly used dimensionality reduction technique and data analysis method. It maps high-dimensional data to low-dimensional space through linear transformation to reduce the complexity of data dimensions. The basic principle of PCA is to find the main features in the data and combine them into principal components to represent the characteristics of the original data. This method can be used in data dimensionality reduction, visualization, feature extraction, and data compression. By selecting the most important principal components, PCA can improve the efficiency of data processing and analysis while retaining the main information of the data.

[0047] When the present invention applies the VMD algorithm to perform signal decomposition, the parameters involved include the input signal, the number of decomposed IMFs K, the bandwidth limit alpha, the noise tolerance nt and the control error constant tol, wherein each input signal is a single-channel signal in the seismic data, K represents the number of IMFs expected to be generated by decomposition, alpha represents the relative frequency bandwidth of the frequency components existing in each IMF signal within the overall frequency range, and the noise tolerance nt can be regarded as an indicator of whether the noise components are forcibly retained during the control decomposition process.

[0048] The present invention mainly applies techniques such as variational mode decomposition and principal component analysis to post-stack three-dimensional seismic data in fracture-cavity development areas, so as to achieve the effect of separating the abnormal reflection characteristics of carbonate fracture-cavity bodies from the formation background.

[0049] The present invention will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the present invention are shown in the accompanying 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 to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0050] Example 1

[0051] This embodiment provides a method for extracting seismic reflection characteristics of carbonate rock fractures and caves, including:

[0052] S1: Acquire seismic data, well logging data and drilling data;

[0053] Specifically, this step collects seismic data, logging data and drilling data as basic data for abnormal reflection characteristics of fracture-cavity bodies. Preferably, the seismic data is time-domain post-stack three-dimensional seismic data, which can be obtained through field seismic data acquisition and seismic data processing; the drilling data and logging data are depth domain data, mainly including drilling oil and gas test data and reservoir data interpreted by logging.

[0054] S2: Acquiring VMD parameter test data based on the seismic data;

[0055] Specifically, in order to reduce the time and computing resource consumption caused by applying full-area data for parameter testing, this step preferably first extracts the seismic trace data contained in the seismic profile of the well trajectory for parameter testing, thereby improving the test efficiency and facilitating comparison with drilling data and logging data.

[0056] S3: Perform VMD parameter testing using the acquired VMD parameter test data, logging data and drilling data to determine the VMD parameters of the VMD algorithm and the IMF components that are most suitable for characterizing the reflection characteristics of the fracture-cavity body;

[0057] Specifically, this step conducts VMD parameter testing, that is, determining four parameters in the VMD algorithm: the number of IMFs K, the bandwidth limit alpha, the noise tolerance nt, and the control error constant tol, as well as determining the IMF component that is most suitable for characterizing the reflection characteristics of the fracture-cavity body.

[0058] The VMD parameter test includes: performing well seismic calibration on the VMD parameter test data, and comparing the data with the corresponding drilling data and logging data to determine the parameter values ​​of the VMD parameters.

[0059] S4: using the determined VMD parameters to perform VMD decomposition of the seismic data volume of the entire region, and obtaining three-dimensional seismic data reconstructed by the IMF components;

[0060] Specifically, the parameters in step S3 are applied to carry out VMD decomposition of the seismic data volume in the entire region to obtain three-dimensional seismic data reconstructed by IMF components.

[0061] S5: The PCA algorithm is used to perform principal component analysis on the reconstructed 3D seismic data to extract the optimal reconstructed data volume that can characterize the abnormal reflection characteristics of the fracture-cavity body;

[0062] Specifically, the VMD algorithm is based on a single seismic trace to complete the analysis. After the data body is reconstructed, there is a certain discontinuity, while retaining some high-frequency abnormal reflection characteristics. The "beaded" seismic reflection occupies the main component relative to the entire reconstructed component data. Therefore, this step uses the PCA algorithm to perform a principal component analysis on the three-dimensional seismic data reconstructed in step S4 to extract the optimal reconstructed data body that can characterize the abnormal reflection characteristics of the fracture-cavity body. Since the PCA algorithm regards seismic data as composed of multiple components, and the proportion of the components is arranged from large to small, the main parameter involved in this step is the number of retained components N.

[0063] S6: performing lateral filtering on the reconstructed data volume;

[0064] Specifically, the optimal reconstructed data volume obtained in step S5 is subjected to lateral filtering to reduce lateral discontinuity of the data volume, suppress abnormal amplitude mutations between seismic traces, and optimize the effect of the reconstructed data volume in fracture-cavity detection.

[0065] S7: Output the filtered reconstructed data.

[0066] Specifically, this step will reconstruct the data volume characterizing the abnormal reflection characteristics of the fracture-cavity body and output it. Preferably, the reconstructed data will be output as sgy or segy format data according to the header information of the original seismic data, so that the interpreters can carry out further attribute analysis and other work.

[0067] Example 2

[0068] This embodiment tests and analyzes a certain exploration area in the Tarim Basin. Multiple wells in the test area reveal that fracture-cave reservoirs are widely developed at the top of carbonate formations. However, due to the strong reflection interference of the lithologic interface, the "beaded" reflection characteristics of the fracture-cave reservoirs are covered, making it difficult to identify and detect the fracture-cave reservoirs, which seriously affects the deployment of wells in the test area, especially the selection of targets and the design of well trajectories. Therefore, the carbonate fracture-cave seismic reflection feature extraction method of the present invention is implemented.

[0069] like Figure 2 The specific process is as follows:

[0070] Step 1: Obtaining necessary data for implementing the present invention, including time domain post-stack seismic data and drilling data and logging data of 4 wells actually drilled in the test area, including drilling oil and gas test data and reservoir data interpreted by logging;

[0071] Step 2: Get the test data, extract the seismic trace of the W3 well in the test area, and extend 50 seismic traces on both sides, with a longitudinal time window of 500ms, a sampling rate of 2ms, and a seismic main frequency of 22Hz;

[0072] Step 3: Carry out VMD parameter testing, through well seismic calibration, and compare with the oil and gas test data of Well W3 and the reservoir data interpreted by logging, to determine that when the number of IMFs decomposed in the test area K is 5, the bandwidth limit alpha = 200, the noise tolerance nt = 0.2 and the control error constant tol = 1e-7, among the five decomposed signal components, IMF1, IMF2, IMF3, IMF4 and IMF5, the component that can be used to characterize the reflection characteristics of the fracture-cavity body is IMF3.

[0073] Step 4: Apply the conclusion of step 3, perform VMD decomposition on the seismic data of the entire test area, and select IMF3 to reconstruct the 3D seismic data.

[0074] Step 5: Apply the PCA method to extract the principal components of the reconstructed data IMF3. After well-seismic comparison analysis, the first N = 10 main components are selected for data reconstruction, which can better characterize the reflection characteristics of the fracture-cavity body.

[0075] Step 6: Optimize the reconstructed data volume obtained in step 5, perform mean filtering, and set the filtering parameters: horizontal bin 3*3, vertical time window 40ms, to obtain the filtered reconstructed seismic data.

[0076] Step 7: Output the filtered reconstructed data according to the header information of the original seismic data for use in seismic attribute analysis and other work to verify the effect of the method of the present invention.

[0077] Figure 3 The cross-section comparison before and after the extraction of fracture-cavity reflection features is shown. Figure 4 The following figure shows the comparison of the profile attributes before and after the extraction of the fracture-cavity reflection features. Figure 5 The comparison of plane attributes before and after the extraction of fracture-cavity reflection features is shown. Figure 3-Figure 5 It can be seen that this method can effectively extract and reconstruct the abnormal reflection characteristics related to carbonate fracture-cavity bodies, and at the same time can well separate the seismic reflection characteristics of fracture-cavity bodies and background strata, making the reflection characteristics of fracture-cavity bodies from observable to identifiable, which will play an important guiding role in the seismic prediction of carbonate fracture-cavity reservoirs.

[0078] Example 3

[0079] This embodiment provides a carbonate rock fracture-cavity body seismic reflection feature extraction device, comprising:

[0080] A data acquisition module, used to acquire seismic data, well logging data and drilling data;

[0081] A test data acquisition module, used for acquiring VMD parameter test data based on the seismic data, well logging data and drilling data;

[0082] A parameter determination module is used to perform VMD parameter testing using the acquired VMD parameter test data to determine the VMD parameters of the VMD algorithm and determine the IMF component that is most suitable for characterizing the reflection characteristics of the fracture-cavity body;

[0083] Using the determined VMD parameters to carry out VMD decomposition of the seismic data volume of the entire region, and obtaining three-dimensional seismic data reconstructed by the IMF components;

[0084] The data extraction module is used to perform principal component analysis on the reconstructed 3D seismic data using the PCA algorithm to extract the optimal reconstructed data volume that can characterize the abnormal reflection characteristics of the fracture-cavity body;

[0085] A filtering module, used for performing lateral filtering on the reconstructed data volume;

[0086] The output module is used to output the filtered reconstructed data.

[0087] Example 4

[0088] This embodiment provides an electronic device, the electronic device comprising:

[0089] at least one processor; and,

[0090] a memory communicatively connected to the at least one processor; wherein,

[0091] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for extracting seismic reflection characteristics of carbonate fractures and caves described in any of the above embodiments.

[0092] The electronic device according to an embodiment of the present disclosure includes a memory and a processor, and the memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may, for example, include a read-only memory (ROM), a hard disk, a flash memory, etc.

[0093] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0094] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0095] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0096] Example 5

[0097] This embodiment provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute the method for extracting seismic reflection characteristics of carbonate fracture-cave bodies described in any of the above embodiments.

[0098] According to the computer-readable storage medium of the embodiment of the present disclosure, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of each embodiment of the present disclosure are executed.

[0099] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0100] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for extracting seismic reflection characteristics of carbonate rock fractures and caves. It is characterized in that include: Acquire seismic data, well logging data, and drilling data; Acquiring VMD parameter test data based on the seismic data; The VMD parameter test data, logging data and drilling data are used to perform VMD parameter test to determine the VMD parameters of the VMD algorithm and the IMF components that are most suitable for characterizing the reflection characteristics of the fracture-cavity body; Using the determined VMD parameters to carry out VMD decomposition of the seismic data volume of the entire region, and obtaining three-dimensional seismic data reconstructed by the IMF components; The PCA algorithm is used to perform principal component analysis on the reconstructed 3D seismic data to extract the optimal reconstructed data volume that can characterize the abnormal reflection characteristics of the fracture-cavity body. performing lateral filtering on the reconstructed data volume; Output the filtered reconstructed data.

2. The method for extracting seismic reflection characteristics of carbonate rock fracture-cavity bodies according to claim 1, It is characterized in that The seismic data are time-domain post-stack three-dimensional seismic data, and the drilling data and the logging data are depth-domain data.

3. The method for extracting seismic reflection characteristics of carbonate rock fracture-cavity bodies according to claim 1, It is characterized in that The determined VMD parameters include: the number K of decomposed IMF components, bandwidth limit alpha, noise tolerance nt and control error constant tol.

4. The method for extracting seismic reflection characteristics of carbonate rock fracture-cavity bodies according to claim 1, It is characterized in that The acquiring of VMD parameter test data based on the seismic data comprises: The seismic trace data contained in the seismic profile of the well trajectory are extracted as VMD parameter test data.

5. The method for extracting seismic reflection characteristics of carbonate rock fracture-cavity bodies according to claim 4, It is characterized in that The VMD parameter test using the acquired VMD parameter test data, logging data and drilling data includes: The VMD parameter test data is calibrated with well seismic calibration and compared with the corresponding drilling data and logging data to determine the parameter values ​​of the VMD parameters.

6. The method for extracting seismic reflection characteristics of carbonate rock fracture-cavity bodies according to claim 1, It is characterized in that The outputting of the filtered reconstructed data comprises: The filtered reconstructed data is output according to the header information of the original seismic data.

7. The method for extracting seismic reflection characteristics of carbonate rock fracture-cavity bodies according to claim 6, It is characterized in that The data format of the reconstructed data output is sgy or segy format.

8. An electronic device, It is characterized in that The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for extracting seismic reflection characteristics of carbonate fractures and caves as described in any one of claims 1-7.

9. A non-transitory computer-readable storage medium, It is characterized in that The non-transitory computer-readable storage medium stores computer instructions, which are used to enable a computer to execute the method for extracting seismic reflection characteristics of carbonate fracture-cavity bodies as described in any one of claims 1-7.

10. A device for extracting seismic reflection characteristics of carbonate rock fractures and caves, It is characterized in that include: A data acquisition module, used to acquire seismic data, well logging data and drilling data; A test data acquisition module, used for acquiring VMD parameter test data based on the seismic data, well logging data and drilling data; A parameter determination module is used to perform VMD parameter testing using the acquired VMD parameter test data to determine the VMD parameters of the VMD algorithm and determine the IMF component that is most suitable for characterizing the reflection characteristics of the fracture-cavity body; Using the determined VMD parameters to carry out VMD decomposition of the seismic data volume of the entire region, and obtaining three-dimensional seismic data reconstructed by the IMF components; The data extraction module is used to perform principal component analysis on the reconstructed 3D seismic data using the PCA algorithm to extract the optimal reconstructed data volume that can characterize the abnormal reflection characteristics of the fracture-cavity body; A filtering module, used for performing lateral filtering on the reconstructed data volume; The output module is used to output the filtered reconstructed data.

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