A weighted static correction fusion method and apparatus
By separating and fusing high and low frequencies of static correction values, the limitations of static correction methods under complex geological conditions are overcome, and the accuracy and imaging effect of high-precision seismic exploration are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA PETROLEUM & CHEMICAL CORP
- Filing Date
- 2024-12-28
- Publication Date
- 2026-06-30
AI Technical Summary
Under complex geological conditions, existing static correction methods are difficult to achieve high-precision seismic imaging. In particular, tomographic static correction is ineffective in areas lacking short-path information or low-velocity information, resulting in low signal-to-noise ratio, structural deformation, and inability to obtain accurate geological structure information. Furthermore, different static correction methods and parameters show differences in local imaging.
A weighted static correction fusion method is adopted. By separating multiple sets of static correction quantities into high and low frequencies, the low-frequency components of the whole area and the high-frequency components of different imaging advantage areas are selected and fused to obtain the fused static correction quantity, thereby improving the static correction effect.
It improved the precision and accuracy of static correction, achieved the geological targets of high-precision seismic exploration, and improved the overlay effect of the entire work area.
Smart Images
Figure CN122307718A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of petroleum geophysical exploration technology, specifically to a weighted static correction fusion method and apparatus. Background Technology
[0002] Seismic data processing is a crucial step in seismic oil and gas exploration. Currently, onshore seismic exploration in China has shifted from the old eastern regions to the northwest and southwest. These areas are mostly characterized by mountainous terrain, deserts, and loess plateaus, with complex surface and subsurface structures, placing higher demands on the accuracy of seismic imaging. Static correction is a key step in high-precision seismic imaging, and its effectiveness significantly impacts the structural accuracy, signal-to-noise ratio, and resolution of the processed seismic data.
[0003] Due to the complexity of geological conditions and the application conditions of static tomography correction, such as obstacles on the surface, high-velocity limestone exposure areas, or data boundaries, static tomography correction often does not work well in these areas because of the lack of short-path information or the absence of low-velocity information below the surface. It may cause structural deformation due to the low signal-to-noise ratio, making it impossible to obtain accurate geological structure information for the entire work area. Furthermore, different static correction methods and parameters will not only lead to differences in local imaging but also to differences in structural morphology. Summary of the Invention
[0004] In view of this, embodiments of the present invention provide a weighted static correction fusion method and apparatus, which solves the problem of fusion of static corrections in regions with different static correction advantages.
[0005] In a first aspect, an embodiment of the present invention provides a weighted static correction fusion method, comprising:
[0006] Multiple sets of static correction values are separated into high and low frequencies to obtain low-frequency static correction values and high-frequency static correction values.
[0007] Select the low-frequency component of the entire region from all the aforementioned low-frequency static correction quantities;
[0008] Select the high-frequency components of different imaging advantage regions from the high-frequency static correction values in each group;
[0009] The low-frequency component of the entire region is fused with the high-frequency component of the different imaging advantage regions to obtain the fused static correction amount.
[0010] In one embodiment, the high-low frequency separation of multiple sets of static correction quantities includes: selecting the same average radius to perform high-low frequency separation on each set of static correction quantities.
[0011] In one embodiment, selecting the low-frequency component of the whole region from all the low-frequency static correction quantities includes: based on the superimposed profile and combined with regional geological data, selecting the low-frequency static correction quantity with reasonable structural morphology as the low-frequency component of the whole region from all the low-frequency static correction quantities.
[0012] In one embodiment, selecting high-frequency components of different imaging advantage regions from the high-frequency static correction quantities in each group includes: comparing the imaging effects of each group of static correction quantities, and selecting the high-frequency quantities of each group of imaging advantage regions from the high-frequency static correction quantities in each group.
[0013] In one embodiment, the static correction values include: shot point static correction value and receiver point static correction value.
[0014] In one embodiment, after obtaining the fusion static correction amount, the method further includes: applying the fusion static correction amount to the common center point data to verify the superposition effect.
[0015] Secondly, an embodiment of the present invention provides a weighted static correction fusion device, comprising:
[0016] The high-low frequency separation unit is used to separate multiple sets of static correction values into high-low frequency values to obtain low-frequency static correction values and high-frequency static correction values.
[0017] A low-frequency component selection unit is used to select the low-frequency component of the entire region from all the low-frequency static correction quantities.
[0018] A high-frequency component selection unit is used to select high-frequency components of different imaging advantage regions from the high-frequency static correction values in each group;
[0019] The fusion unit is used to fuse the low-frequency components of the whole area with the high-frequency components of the different imaging advantage areas to obtain the fused static correction amount.
[0020] In a first aspect, an embodiment of the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the steps of the method described above.
[0021] In a second aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of the method described above.
[0022] Thirdly, an embodiment of the present invention provides a computer program product, comprising a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the method described above.
[0023] This invention provides a weighted static correction fusion method and apparatus, which separates multiple sets of static correction quantities into high and low frequencies to obtain low-frequency static correction quantities and high-frequency static correction quantities; selects the low-frequency component of the entire area from all the low-frequency static correction quantities; selects the high-frequency component of different imaging advantage regions from each set of high-frequency static correction quantities; and fuses the low-frequency component of the entire area with the high-frequency component of the different imaging advantage regions to obtain the fused static correction quantity; thereby improving the static correction effect of the entire actual production project and achieving high-precision geological targets in exploration. Attached Figure Description
[0024] Figure 1 The diagram shown is a flowchart of a weighted static correction fusion method provided in an embodiment of the present invention.
[0025] Figure 2 The diagram shown is a process diagram of static correction quantity fusion application provided by an embodiment of the present invention.
[0026] Figure 3 The diagram shown is a structural schematic of a weighted static correction fusion device provided in an embodiment of the present invention.
[0027] Figure 4 The diagram shown is a flowchart of a weighted static correction fusion method provided in another embodiment of the present invention.
[0028] Figure 5 The diagram shown is a schematic representation of the effect before application of a weighted static correction fusion method and apparatus provided in an embodiment of the present invention.
[0029] Figure 6 The diagram shown illustrates the effect of a weighted static correction fusion method and apparatus according to an embodiment of the present invention. Detailed Implementation
[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0031] The inventors of this application have discovered that the commonly used static correction methods in current project processing mainly include model-based static correction, elevation static correction, refraction static correction, and tomographic static correction. These methods generally involve obtaining a surface model and then using a velocity model to calculate the static correction amount. The difference lies in the varying accuracy of the models obtained by these methods. From an accuracy perspective, tomographic static correction is superior to refraction static correction, which in turn is superior to elevation static correction. However, in practical data application, tomographic static correction has become the mainstream static correction method for processing engineering projects. However, due to the complexity of geological conditions and the application conditions of tomographic static correction, such as surface obstacles, high-velocity limestone exposure areas, or data boundaries, tomographic static correction often performs poorly in these areas due to a lack of short-path information or low-velocity information below the surface. Although residual static correction based on reflected waves or nonlinear residual static correction can compensate for the imaging effect in these areas, the initial low signal-to-noise ratio can lead to structural deformation, making it impossible to obtain accurate geological structure information for the entire work area. In these areas, static elevation correction often achieves better results because it does not rely on first-arrival information, a fact well-proven in limestone areas and places with obstacles. Furthermore, due to differences in static correction algorithms across different tomographic analyses, or variations in inversion parameters used within the same tomographic static correction, there will be some differences in the stacking morphology. In other words, different static correction methods and parameters will not only lead to differences in local imaging but also in structural morphology.
[0032] Based on the above facts, in areas with complex near-surface conditions, a static correction value calculated using one static correction method and parameters may only be suitable for one part of the work area, while another static correction value calculated using a different static correction method or the same static correction method with different parameters may be suitable for another part of the work area. Furthermore, one static correction value may be more advantageous in high-frequency components while another is more advantageous in mid-to-low-frequency components. It is difficult to adjust parameters to achieve good results for the entire work area using a single static correction method and parameters. Therefore, the complementary advantages of different static correction values become our inevitable choice.
[0033] Currently, static correction fusion technology has been applied in several complex seismic areas. While stitching together the advantageous areas of static correction in the CMP domain can solve local static correction imaging problems, it often introduces boundary effects in another direction for 3D seismic data due to improper handling of the static correction boundaries. Even when considering boundary issues during static correction stitching in the CMP domain, the fusion process remains cumbersome and lacks interactivity.
[0034] To address the aforementioned issues, this invention proposes a weighted static correction fusion method and apparatus based on regions with different static correction dominance. This method solves the problem of fusion of static corrections across regions with different static correction dominance, improves the static correction effect of the entire actual production project, and achieves high-precision geological targets in exploration. Specific implementation methods are described in the following embodiments.
[0035] Example 1:
[0036] This embodiment provides a weighted static correction fusion method, referencing... Figure 1 As shown, the weighted static correction fusion method includes:
[0037] Step 01: Perform high-frequency and low-frequency separation on multiple sets of static correction values to obtain low-frequency static correction values and high-frequency static correction values.
[0038] Furthermore, the high-low frequency separation of multiple sets of static correction quantities includes: selecting the same average radius to perform high-low frequency separation on each set of static correction quantities to obtain low-frequency static correction quantities and high-frequency static correction quantities.
[0039] Step 02: Select the low-frequency component of the entire region from all the low-frequency static correction quantities.
[0040] Furthermore, the high- and low-frequency separation of multiple sets of static correction quantities includes: selecting the same average radius to perform high- and low-frequency separation on each set of static correction quantities.
[0041] Step 03: Select the high-frequency components of different imaging advantage regions from the high-frequency static correction values in each group.
[0042] Furthermore, the step of selecting the low-frequency component of the whole region from all the low-frequency static correction quantities includes: based on the superimposed profile and combined with regional geological data, selecting the low-frequency static correction quantity with reasonable structural morphology from all the low-frequency static correction quantities as the low-frequency component of the whole region.
[0043] Step 04: Fuse the low-frequency component of the whole area with the high-frequency component of the different imaging advantage areas to obtain the fused static correction amount.
[0044] Furthermore, selecting the high-frequency components of different imaging advantage regions from the high-frequency static correction quantities in each group includes: comparing the imaging effects of each group of static correction quantities, and selecting the high-frequency quantities of each group of imaging advantage regions from the high-frequency static correction quantities in each group.
[0045] In addition to the above steps, selecting the high-frequency components of different imaging advantage regions from the high-frequency static correction quantities in each group also includes step 05: comparing the imaging effects of each group of static correction quantities and selecting the high-frequency quantities of each group of imaging advantage regions from the high-frequency static correction quantities in each group.
[0046] Example 2:
[0047] Based on the above embodiments, the static correction amount includes: shot point static correction amount and receiver point static correction amount.
[0048] Each static correction quantity comprises two parts: the shot point static correction quantity and the receiver point static correction quantity. This method processes both the shot point static correction quantity and the receiver point static correction quantity using the same method. Therefore, the explanation of the principle of this method does not distinguish between the shot point static correction quantity and the receiver point static correction quantity, but only refers to a certain static correction quantity in general. Two different static correction quantities can correspond to two different static correction software and parameters, or they can correspond to static correction quantities calculated by the same static correction software but different parameters.
[0049] Assume that the maximum planar coordinate range of the work area, determined by the range of the shot point and receiver point, is set A; assume that there are two different static correction quantities, the first static correction quantity is t1(x,y) and the second static correction quantity is t2(x,y); assume that based on the comparison of the superimposed profiles of the two static correction quantities, the first static correction quantity has an advantage in controlling the overall structural morphology, while the second static correction quantity has an advantage in local structural morphology or superposition effect (depending on the accuracy of the mid-wavelength or short-wavelength components of the static correction) within the planar coordinate range represented by set B, and assume that set B is a connected closed region, which is obviously a subset of set A.
[0050] Calculate the weight coefficient w2(x,y) of the second static correction quantity based on the range of set B. Divide the entire region contained in set A into three parts: ① Transition zone, which is a ring-shaped strip area within a certain distance (half the length of the transition zone) from the boundary of set B; ② Core area of the dominant region, which is the part of set B excluding the transition zone; ③ Other areas, which is the part of the entire work area excluding the above two areas. The weight coefficient of the core area of the dominant region is 1.0, the weight coefficient of the other areas is 0, and the weight coefficient of the transition zone gradually decreases from 1.0 at the boundary between the core area of the dominant region and the transition zone to 0 at the boundary between the transition zone and the other areas.
[0051] Figure 2 The diagram shows the process of static correction quantity fusion application. The entire area enclosed by the four coordinate axes (upper, lower, left, and right) is the maximum range of the work area, i.e., set A. The area filled with red diagonal lines is the core area of the dominant region (weight coefficient 1.0). The area filled with blue diagonal lines is the other area (weight coefficient 0). The green and yellow areas are the parts of the transition area with weight coefficients in the intervals of (0, 0.5) and (0.5, 1.0), respectively. The area enclosed by the contour line with a weight coefficient of 0.5 and the right coordinate axis (the yellow and red diagonal line area) is the dominant region of the second static correction quantity, i.e., set B.
[0052] Example 3:
[0053] This embodiment provides a weighted static correction fusion device 100, such as Figure 3 As shown, the weighted static correction fusion device 100 includes: a high-low frequency separation unit, a low-frequency component selection unit 20, a high-frequency component selection unit, and a fusion unit 30. Among them,
[0054] The high-low frequency separation unit 10 is used to separate multiple sets of static correction values into high-low frequency values to obtain low-frequency static correction values and high-frequency static correction values.
[0055] The static correction values include the static correction values for the shot point and the static correction values for the receiver point.
[0056] Furthermore, the high-low frequency separation unit 10 is also used to select the same average radius to perform high-low frequency separation on each group of static correction quantities.
[0057] The low-frequency component selection unit 20 is used to select the low-frequency component of the whole region from all the low-frequency static correction quantities.
[0058] Furthermore, the low-frequency component selection unit 20 is also used to select, based on the superimposed profile and combined with regional geological data, the low-frequency static correction quantity with reasonable structural morphology from all the low-frequency static correction quantities as the low-frequency component of the whole area.
[0059] The high-frequency component selection unit 30 is used to select high-frequency components of different imaging advantage regions from the high-frequency static correction values in each group.
[0060] Furthermore, the high-frequency component selection unit 30 is also used to compare the imaging effect of each group of static corrections and select the high-frequency quantity of each group of high-frequency static corrections that forms the dominant imaging region.
[0061] The fusion unit 40 is used to fuse the low-frequency components of the whole area with the high-frequency components of the different imaging advantage areas to obtain the fused static correction amount.
[0062] Furthermore, the weighted static correction fusion device 100 also includes a verification unit 50; the verification unit 50 is used to apply the fusion static correction amount to the common center point data to verify the superposition effect.
[0063] Example 4:
[0064] Based on the above embodiments, in order to verify the effectiveness of a weighted static correction fusion method and device based on regions with different static correction advantages, three-dimensional seismic data from a certain work area in western China were selected, and the fused static correction was calculated using the device of this invention. (Reference) Figure 4 As shown, the specific methods include:
[0065] 1. Prepare two sets of static correction values, and decompose the two sets of static correction values into high-frequency and low-frequency values respectively;
[0066] 2. Select the dominant imaging region for a particular set of static corrections and provide its specific spatial location;
[0067] 3. Run the device of this invention and output the fused static correction value;
[0068] 4. Apply the static correction to the common center point data and verify the superposition effect.
[0069] Figure 5 The effect before application of a weighted static correction fusion method and device based on the advantageous regions of different static correction values.
[0070] Figure 6 This is the effect of a weighted static correction fusion method and device based on the advantageous regions of different static correction values after application.
[0071] The static correction values before and after applying the fusion static correction were superimposed and compared for the same gather. Figure 5 and Figure 6 It can be seen that the continuity of the superimposed phase axis after static correction fusion is improved, and significant application effects are achieved.
[0072] Example 5:
[0073] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.
[0074] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the method described in the above embodiments.
[0075] In some embodiments of this example, a computer program product is provided, including a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the method described in the above embodiments.
[0076] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods described in the above embodiments.
[0077] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).
[0078] Computer-readable storage media may also store at least one computer-executable program, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.
[0079] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).
[0080] The processor can communicate with external devices via the I / O bus through wired or wireless networks.
[0081] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.
[0082] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.
[0083] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.
[0084] While the embodiments disclosed herein are as described above, the foregoing content is merely for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Any person skilled in the art to which this disclosure pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope of this disclosure; however, the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.
Claims
1. A weighted static correction fusion method, characterized in that, include: Multiple sets of static correction values are separated into high and low frequencies to obtain low-frequency static correction values and high-frequency static correction values. Select the low-frequency component of the entire region from all the aforementioned low-frequency static correction quantities; Select the high-frequency components of different imaging advantage regions from the high-frequency static correction values in each group; The low-frequency component of the entire region is fused with the high-frequency component of the different imaging advantage regions to obtain the fused static correction amount.
2. The weighted static correction fusion method according to claim 1, characterized in that, The step of separating high and low frequencies of multiple sets of static correction quantities includes: selecting the same average radius to separate high and low frequencies of each set of static correction quantities.
3. The weighted static correction fusion method according to claim 1, characterized in that, The process of selecting the low-frequency component of the whole region from all the low-frequency static correction quantities includes: based on the superimposed profile and combined with regional geological data, selecting the low-frequency static correction quantity with reasonable structural morphology from all the low-frequency static correction quantities as the low-frequency component of the whole region.
4. The weighted static correction fusion method according to claim 1, characterized in that, Selecting high-frequency components of different imaging advantage regions from the high-frequency static correction quantities in each group also includes: comparing the imaging effects of each group of static correction quantities, and selecting the high-frequency quantities of each group of imaging advantage regions from the high-frequency static correction quantities in each group.
5. The weighted static correction fusion method according to claim 1, characterized in that, The static correction values include: shot point static correction value and receiver point static correction value.
6. The weighted static correction fusion method according to claim 1, characterized in that, After obtaining the fusion static correction, the process also includes: applying the fusion static correction to the common center point data to verify the superposition effect.
7. A weighted static correction fusion device, characterized in that, include: The high-low frequency separation unit is used to separate multiple sets of static correction values into high-low frequency values to obtain low-frequency static correction values and high-frequency static correction values. A low-frequency component selection unit is used to select the low-frequency component of the entire region from all the low-frequency static correction quantities. A high-frequency component selection unit is used to select high-frequency components of different imaging advantage regions from the high-frequency static correction values in each group; The fusion unit is used to fuse the low-frequency components of the whole area with the high-frequency components of the different imaging advantage areas to obtain the fused static correction amount.
8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.