A method, device, equipment and medium for seismic migration data fusion

Abstract

The present application relates to the field of geophysical signal processing, and proposes a method, device, equipment and medium for seismic migration data fusion, wherein the method comprises: obtaining seismic migration data corresponding to a plurality of blocks respectively and selecting a reference block based on the characteristics of a target layer and a geological task; constructing an amplitude correction sequence, and performing energy correction on the seismic migration data based on the amplitude correction sequence; extracting relevant wavelets of the plurality of blocks respectively at the target layer and constructing target wavelets; calculating the frequency difference between the target wavelets and each relevant wavelet to construct a wavelet reconstruction factor, so as to perform frequency correction; and fusing the frequency-corrected seismic migration data of the overlapping area and the non-overlapping area between the plurality of blocks to obtain the fusion result of the seismic migration data. The scheme disclosed in the present application solves the problems of energy, frequency difference and boundary imaging difference encountered in the splicing processing of different three-dimensional block migration results.

Description

Technical Field

[0001] This invention relates to the field of geophysical signal processing, and in particular to a method, apparatus, device, and medium for seismic migration data fusion. Background Technology

[0002] In order to conduct detailed exploration of oil and gas exploration areas, 3D seismic acquisition is carried out in the exploration areas by year and by block. After the acquisition is completed in each year, a full-process seismic processing is carried out, including obtaining the pre-stack time migration and pre-stack depth migration results of individual blocks.

[0003] Furthermore, it is necessary to perform contiguous structural interpretation, reservoir inversion, and oil and gas prediction in oil and gas exploration areas, as well as pre-stack contiguous processing or post-stack data stitching of 3D data collected in different years. Among these, pre-stack contiguous processing involves a large amount of data, consumes a lot of computer data, and is slow to process, making it difficult to meet the requirements of regional oil and gas exploration in a timely manner; post-stack stitching, on the other hand, involves a smaller amount of data and is faster to process, making it one of the best technical methods.

[0004] Because the seismic processing procedures and parameters of data from different years and blocks are inherited, their waveform characteristics are relatively similar, which meets the requirements for post-stack splicing.

[0005] However, two differences in seismic migration results make it difficult to directly stitch the migration data together: differences in excitation and reception conditions, acquisition parameters, and systematic differences in seismic energy in different blocks result in certain differences in energy and frequency in the migration results of different blocks; differences in migration velocity, migration parameters, etc., result in certain imaging differences between different blocks, especially at the boundaries of the data, where reflection information in the direction of missing boundaries is often superimposed, resulting in significant imaging differences at the boundaries.

[0006] The above-mentioned problems in existing technologies prevent seismic migration data from being directly stitched together after stacking or from obtaining consistent continuous migration results. Summary of the Invention

[0007] In view of this, the present invention proposes a method, apparatus, device and medium for seismic migration data fusion, which solves the problem of energy, frequency and imaging differences in post-stack stitching results caused by differences in energy, frequency and boundary imaging between three-dimensional blocks, and obtains contiguous migration results with good consistency.

[0008] Based on the above objectives, embodiments of the present invention first provide a method for seismic migration data fusion, comprising: acquiring seismic migration data corresponding to several blocks respectively, and selecting one of the blocks as a reference block based on the characteristics of the target layer and the geological task; constructing an amplitude correction sequence based on the energy difference between the absolute amplitude of the reference block and the absolute amplitude of the non-reference blocks in the several blocks respectively, and performing energy correction on the seismic migration data based on the amplitude correction sequence; extracting the correlation wavelets of the several blocks in the target layer based on the energy-corrected seismic migration data, and constructing a target wavelet based on the correlation wavelet and the geological task; calculating the frequency difference between the target wavelet and each of the correlation wavelets, and obtaining a wavelet reconstruction factor reconstructed from the correlation wavelet onto the target wavelet based on the frequency difference, and performing frequency correction on the energy-corrected seismic migration data of the corresponding blocks based on the wavelet reconstruction factor; and fusing the frequency-corrected seismic migration data of the overlapping areas between the several blocks with the frequency-corrected seismic migration data of the non-overlapping areas between the several blocks to obtain the fusion result of the seismic migration data.

[0009] In some embodiments, the step of constructing an amplitude correction sequence based on the energy difference between the absolute amplitude of the reference block and the absolute amplitudes of the non-reference blocks in the plurality of blocks, and then performing energy correction on the seismic migration data based on the amplitude correction sequence, includes: performing layer flattening processing on the seismic migration data corresponding to the plurality of blocks based on the target layer, and extracting the absolute amplitudes of the plurality of blocks corresponding to the target layer according to a time window of a preset step size; calculating the energy difference between the absolute amplitude of the non-reference blocks and the absolute amplitude of the reference block; constructing an amplitude correction factor for the absolute amplitude of the non-reference blocks relative to the absolute amplitude of the reference block based on the energy difference; arranging the amplitude correction factor in chronological order and performing linear interpolation to obtain an amplitude correction sequence; and performing reverse layer flattening processing on the layer-flattened seismic migration data based on the amplitude correction sequence to perform energy correction on the seismic migration data.

[0010] In some embodiments, the step of performing energy correction on the seismic migration data based on the amplitude correction sequence includes: multiplying the seismic migration data corresponding to the non-reference block after layer flattening by the amplitude correction sequence in the time domain and performing reverse layer flattening; determining whether the energy difference is within a preset energy range, and determining whether to reconstruct the amplitude correction factor and perform reconstruction or retention accordingly based on the determination result; and performing energy correction on the seismic migration data corresponding to the non-reference block in the target layer using the amplitude correction sequence corresponding to the energy difference within the preset energy difference range based on the reconstructed / retained amplitude correction factor.

[0011] In some embodiments, the step of extracting the correlation wavelets of the plurality of blocks in the target layer based on the energy-corrected seismic migration data, and constructing a target wavelet based on the correlation wavelets and the geological task, includes: performing layer flattening processing on the energy-corrected seismic migration data in the target layer and extracting the correlation wavelets corresponding to the plurality of blocks respectively; obtaining the effective frequency band range corresponding to the plurality of blocks based on the correlation wavelets corresponding to the plurality of blocks respectively, and obtaining a target frequency band range based on the effective frequency band range corresponding to the plurality of blocks respectively; and constructing the target wavelet corresponding to the target frequency band range based on the least squares error minimization method and the geological task.

[0012] In some embodiments, the step of calculating the frequency difference between the target wavelet and each of the correlated wavelets and obtaining the wavelet reconstruction factor of the correlated wavelet onto the target wavelet based on the frequency difference, and then performing frequency correction on the energy-corrected seismic migration data of the corresponding block based on the wavelet reconstruction factor, includes: constructing wavelet reconstruction factors of the correlated wavelets onto the target wavelet corresponding to the plurality of blocks based on a cross-correlation algorithm and the target frequency band range; performing frequency correction on the energy-corrected seismic migration data based on the wavelet reconstruction factor; determining whether the frequency-corrected seismic migration data satisfies the structural interpretation result of the target layer; and, in response to not satisfying the structural interpretation result of the target layer, returning to the step of reconstructing the wavelet reconstruction factor until the frequency-corrected seismic migration data satisfies the structural interpretation result of the target layer.

[0013] In some embodiments, the step of fusing the frequency-corrected seismic migration data of overlapping areas between the plurality of blocks with the frequency-corrected seismic migration data of non-overlapping areas between the plurality of blocks to obtain a fusion result of the seismic migration data includes: obtaining overlapping areas between the plurality of blocks; calculating the time difference of the overlapping areas based on a cross-correlation algorithm and performing smoothing processing; time-shifting the frequency-corrected seismic migration data based on the smoothed time difference to obtain the optimal position for stitching between the plurality of blocks, so as to obtain a time difference correction factor in the time domain of the frequency-corrected seismic migration data of the overlapping areas based on the optimal position; performing time difference correction on the frequency-corrected seismic migration data of the overlapping areas based on the time difference correction factor and fusing it with the frequency-corrected seismic migration data of non-overlapping areas between the plurality of blocks to obtain a fusion result of the seismic migration data.

[0014] In some embodiments, the step of obtaining the time difference correction factor in the time domain of the frequency-corrected seismic migration data of the overlapping area based on the optimal location includes: obtaining the time difference correction application degree factor corresponding to the overlapping area based on the optimal location; multiplying the time difference correction application degree factor with the smoothed time difference corresponding to the overlapping area to obtain the corresponding time difference correction factor.

[0015] In another aspect of this invention, a seismic migration data fusion apparatus is provided, comprising: a first module for acquiring seismic migration data corresponding to several blocks and selecting one of the blocks as a reference block based on the characteristics of the target layer and the geological task; a second module for constructing an amplitude correction sequence based on the energy difference between the absolute amplitude of the reference block and the absolute amplitude of the non-reference blocks in the several blocks, and performing energy correction on the seismic migration data based on the amplitude correction sequence; and a third module for extracting the correlation sub-data of the several blocks in the target layer based on the energy-corrected seismic migration data. The system comprises five modules: a first module for constructing a target wavelet based on the correlated wavelet and the geological task; a second module for calculating the frequency difference between the target wavelet and each of the correlated wavelets and obtaining the wavelet reconstruction factor of the correlated wavelet onto the target wavelet based on the frequency difference, and performing frequency correction on the energy-corrected seismic migration data of the corresponding block based on the wavelet reconstruction factor; and a third module for fusing the frequency-corrected seismic migration data of the overlapping areas between the blocks with the frequency-corrected seismic migration data of the non-overlapping areas between the blocks to obtain the fusion result of the seismic migration data.

[0016] In another aspect of the present invention, an electronic device is provided, including at least one processor; and a memory storing computer instructions executable on the processor, which, when executed by the processor, implement the steps of the above-described method.

[0017] In another aspect of the present invention, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the method steps described above.

[0018] This invention offers at least the following advantages: It proposes a method for seismic migration data fusion that resolves energy, frequency, and boundary imaging differences between 3D blocks, improves the energy, frequency, and boundary imaging differences in post-stack stitching results, and yields consistent, contiguous migration results without obvious stitching marks. Furthermore, the proposed seismic migration data fusion method can correct for energy, frequency, and time differences between processed data from different cycles, offering high operability and operational efficiency. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0020] Figure 1 The flowchart shown is a method for seismic migration data fusion provided in an embodiment of the present invention;

[0021] Figure 2 The diagram shown is another flowchart of a seismic migration data fusion method provided in an embodiment of the present invention;

[0022] Figure 3 The diagram shown illustrates the relative positions of four three-dimensional blocks according to an embodiment of the present invention.

[0023] Figure 4 The diagram shown is a seismic profile after direct stitching of seismic migration results according to an embodiment of the present invention.

[0024] Figure 5 The diagram shown is a seismic plane diagram after direct stitching of seismic migration results according to an embodiment of the present invention.

[0025] Figure 6 The diagram shown is a schematic diagram of the related wavelets and the corresponding wavelet amplitude spectra of blocks 1, 2 and 3 provided in an embodiment of the present invention.

[0026] Figure 7 The diagram shown is a schematic diagram of a wavelet reconstruction factor and its amplitude spectrum provided in an embodiment of the present invention;

[0027] Figure 8 The diagram shown illustrates the time difference between region 2 and blocks 1 and 3 as provided in an embodiment of the present invention.

[0028] Figure 9 The diagram shown is a schematic diagram of the time difference application degree factor plane of the overlapping segment of the fused body of block 2 and blocks 1 and 3 provided in an embodiment of the present invention;

[0029] Figure 10 The diagram shown is a planar schematic of the amplitude properties after the offset result is stacked and fused according to an embodiment of the present invention.

[0030] Figure 11 The diagram shown is a schematic representation of a seismic migration data fusion apparatus according to an embodiment of the present invention;

[0031] Figure 12 The diagram shown is a schematic representation of an electronic device according to an embodiment of the present invention;

[0032] Figure 13 The diagram shown is a schematic representation of a computer-readable storage medium provided according to an embodiment of the present invention. Detailed Implementation

[0033] The following describes embodiments of the present invention. However, it should be understood that the disclosed embodiments are merely examples, and other embodiments may take various alternative forms.

[0034] Furthermore, it should be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or apparatus that comprises a list of elements may include not only those elements but also elements not expressly listed or inherent to such process, method, article, or apparatus.

[0035] One or more embodiments of this application will now be described with reference to the accompanying drawings.

[0036] Based on the above objectives, the first aspect of the present invention provides an embodiment of a method for seismic migration data fusion. Figure 1 The flowchart shown is a method for seismic migration data fusion provided by an embodiment of the present invention, as follows: Figure 1 As shown, a method for seismic migration data fusion includes:

[0037] S1. Obtain seismic migration data corresponding to several blocks respectively, and select one of the blocks as the reference block based on the target layer characteristics and geological task;

[0038] S2. Construct an amplitude correction sequence based on the energy difference between the absolute amplitude of the reference block and the absolute amplitude of the non-reference blocks in the plurality of blocks, and perform energy correction on the seismic migration data based on the amplitude correction sequence.

[0039] S3. Based on the energy-corrected seismic migration data, extract the correlation wavelets of the several blocks in the target layer, and construct the target wavelet based on the correlation wavelets and the geological task;

[0040] S4. Calculate the frequency difference between the target wavelet and each of the related wavelets and obtain the wavelet reconstruction factor of the related wavelets reconstructed onto the target wavelet based on the frequency difference, so as to perform frequency correction on the energy-corrected seismic migration data of the corresponding block based on the wavelet reconstruction factor.

[0041] S5. After time difference correction, the frequency-corrected seismic migration data of the overlapping areas between the several blocks is fused with the frequency-corrected seismic migration data of the non-overlapping areas between the several blocks to obtain the fusion result of the seismic migration data.

[0042] The above-mentioned seismic migration data fusion method addresses the differences in energy, frequency, and boundary imaging between 3D blocks, improving the energy, frequency, and boundary imaging differences in post-stack stitching results. This yields consistent, contiguous migration results without obvious stitching artifacts. Furthermore, the seismic migration data fusion method proposed in this invention can correct for energy, frequency, and time differences between processed data from different cycles, offering strong operability and high operational efficiency.

[0043] According to several embodiments of the present invention, the step of constructing an amplitude correction sequence based on the energy difference between the absolute amplitude of a reference block and the absolute amplitudes of non-reference blocks in several blocks, and then performing energy correction on seismic migration data based on the amplitude correction sequence includes: performing layer flattening processing on the seismic migration data corresponding to several blocks based on the target layer, and extracting the absolute amplitudes of several blocks corresponding to the target layer according to a time window of a preset step size; calculating the energy difference between the absolute amplitudes of non-reference blocks and the absolute amplitude of the reference block; constructing an amplitude correction factor for the absolute amplitude of non-reference blocks relative to the absolute amplitude of the reference block based on the energy difference; arranging the amplitude correction factor in chronological order and performing linear interpolation to obtain the amplitude correction sequence; and performing reverse layer flattening processing on the layer-flattened seismic migration data based on the amplitude correction sequence to perform energy correction on the seismic migration data.

[0044] According to several embodiments of the present invention, the step of energy correction of seismic migration data based on amplitude correction sequence includes: multiplying the seismic migration data corresponding to the non-reference block after layer flattening by the amplitude correction sequence in the time domain and performing reverse layer flattening; determining whether the energy difference is within a preset energy range, and determining whether to reconstruct the amplitude correction factor and reconstruct or retain it accordingly based on the determination result; and performing energy correction on the seismic migration data corresponding to the non-reference block in the target layer based on the reconstructed / retained amplitude correction factor and the amplitude correction sequence corresponding to the energy difference within the preset energy difference range.

[0045] According to several embodiments of the present invention, the step of extracting correlation wavelets of several blocks in the target layer based on energy-corrected seismic migration data, and constructing target wavelets based on correlation wavelets and geological tasks includes: performing layer flattening processing on the energy-corrected seismic migration data in the target layer and extracting correlation wavelets corresponding to several blocks respectively; obtaining the effective frequency band range corresponding to several blocks based on the correlation wavelets corresponding to several blocks respectively, and obtaining the target frequency band range based on the effective frequency band range corresponding to several blocks respectively; and constructing the target wavelet corresponding to the target frequency band range based on the least squares error minimization method and geological tasks.

[0046] According to several embodiments of the present invention, the step of calculating the frequency difference between the target wavelet and each correlated wavelet and obtaining the wavelet reconstruction factor of the correlated wavelet reconstructed onto the target wavelet based on the frequency difference, and then performing frequency correction on the energy-corrected seismic migration data of the corresponding block based on the wavelet reconstruction factor includes: constructing wavelet reconstruction factors of the correlated wavelet reconstructed onto the target wavelet for several blocks based on a cross-correlation algorithm and the target frequency band; performing frequency correction on the energy-corrected seismic migration data based on the wavelet reconstruction factor; determining whether the frequency-corrected seismic migration data satisfies the structural interpretation results of the target layer; and, in response to not satisfying the structural interpretation results of the target layer, returning to the step of reconstructing the wavelet reconstruction factor until the frequency-corrected seismic migration data satisfies the structural interpretation results of the target layer.

[0047] According to several embodiments of the present invention, the steps of fusing frequency-corrected seismic migration data of overlapping areas between several blocks with frequency-corrected seismic migration data of non-overlapping areas between several blocks to obtain a fused seismic migration data result include: obtaining overlapping areas between several blocks; calculating the time difference of the overlapping areas based on a cross-correlation algorithm and performing smoothing processing; time-shifting the frequency-corrected seismic migration data based on the smoothed time difference to obtain the optimal position for stitching between several blocks, and obtaining the time difference correction factor of the frequency-corrected seismic migration data of the overlapping areas in the time domain based on the optimal position; performing time difference correction on the frequency-corrected seismic migration data of the overlapping areas based on the time difference correction factor and fusing it with the frequency-corrected seismic migration data of non-overlapping areas between several blocks to obtain a fused seismic migration data result.

[0048] According to several embodiments of the present invention, the step of obtaining the time difference correction factor of the frequency-corrected seismic migration data of the overlapping area in the time domain based on the optimal location includes: obtaining the time difference correction application degree factor corresponding to the overlapping area based on the optimal location; multiplying the time difference correction application degree factor with the smoothed time difference corresponding to the overlapping area to obtain the corresponding time difference correction factor.

[0049] In one embodiment of the present invention, such as Figure 2 As shown, Figure 2 The diagram illustrates another flowchart of a seismic migration data fusion method provided by an embodiment of the present invention. For several blocks, the structural interpretation results of the target layer for each block are loaded, and the results are quality controlled. Taking a time window size of 200ms as an example, the absolute amplitude of each block is extracted in the target layer with a 200ms time window. The energy difference of the absolute amplitude between blocks is analyzed. Using the amplitude energy of a certain block as the reference block, the amplitude correction factors for the remaining non-reference blocks are obtained. Simultaneously, the seismic migration data corresponding to several blocks are subjected to layer flattening in the target layer. The layer-flattened seismic migration data is then subjected to reverse layer flattening to obtain amplitude-corrected seismic migration data. It is determined whether the energy difference is within a preset energy range. Based on the determination result, it is confirmed whether to reconstruct the amplitude correction factor. If it is not within the preset energy range, the amplitude correction factor needs to be reconstructed according to the previous steps. Based on the newly constructed amplitude correction factor, the seismic migration data is again amplitude-corrected until the energy difference is within the preset energy range, thus completing the energy correction of the seismic migration data.

[0050] Furthermore, the steps for frequency correction of the energy-corrected seismic migration data are as follows:

[0051] First, the energy-corrected seismic migration data is flattened at the target layer to obtain the correlated wavelets of each block. Frequency characteristic analysis is performed on the correlated wavelets corresponding to each block to obtain the effective bandwidth range of each block. Combined with the frequency-division scanning data of each block, the effective frequency band range of each region is analyzed to obtain the target frequency band range of the target wavelet. Further, the amplitude spectra of the correlated wavelets of each block are synthesized into a target wavelet within the target frequency band using the principle of minimizing least squares error, resulting in the target wavelet with the smallest error compared to the correlated wavelets of each block. For the target wavelet, its amplitude spectrum needs to be compared and analyzed with the correlated wavelets of each block to obtain the differences between the target wavelet and the correlated wavelets of each block, i.e., to confirm whether the frequency, phase, and waveform characteristics of the target wavelet meet the requirements of subsequent interpretation. If they do not meet the interpretation requirements, the target wavelet needs to be reconstructed according to the aforementioned steps. Preferably, if the waveform and frequency characteristics of a certain block can be used as regional standard characteristics, the correlated wavelet of that block can be selected as the target wavelet. After obtaining the target wavelet, it is necessary to construct the wavelet reconstruction factor of the relevant wavelets of each block to the target wavelet in the target frequency band using the cross-correlation algorithm in the time domain. The amplitude spectrum of the wavelet reconstruction factor is analyzed, and its rationality is analyzed. The result data is obtained in the frequency domain or time domain through the reconstruction factor, that is, the frequency correction is performed on the energy-corrected seismic migration data.

[0052] Furthermore, overlapping areas between several blocks are identified. The time difference between each block is calculated using a cross-correlation algorithm, and the planar distribution characteristics of the time difference are analyzed. Based on these planar characteristics, an appropriate smoothing factor is selected to smooth the time difference, effectively eliminating high-frequency variations. The smoothed time difference is then compared with the frequency-corrected seismic migration data after time shifting to obtain the optimal location of the stitching point. Using this optimal location as a reference, data is gradually transitioned to the uncorrected data on both sides. A transition scheme is used to obtain a time difference correction application degree factor at the overlapping points. This factor is multiplied by the time difference value to obtain the final time difference correction factor. The time difference correction factor is applied to each block, and comparative analyses are performed on overlapping areas and overlapping / non-overlapping segments to ensure that the corrected time difference is within 1–2 ms.

[0053] The fusion steps for overlapping and non-overlapping segments include: multiplying the time difference correction application degree positive factor by the corresponding overlapping segments and then adding them together to obtain the data fusion results for the overlapping segments; merging the non-overlapping segment data with the overlapping segment data and reordering them to obtain the fused result data; and performing quality control analysis on the splicing points of the result data, the boundary between overlapping and non-overlapping segments, and other locations, and extracting the frequency, amplitude, and other attributes of the target layer of the seismic data for planar quality control.

[0054] The following is another embodiment provided by the present invention, taking a three-dimensional block of four blocks as an example. Figure 3 The diagram shown illustrates the relative positions of four three-dimensional blocks provided in an embodiment of the present invention. Figure 3 As shown, it includes: block 1, block 2, block 3 and block 4. Block 1, block 2 and block 3 are adjacent, while block 4 is not adjacent to block 1, block 2 and block 3. The same color indicates the pre-stack full-processing result according to the unified process, and the arrow direction indicates the plane position of the profile.

[0055] Based on the above four three-dimensional blocks, an amplitude correction sequence is constructed. The specific steps include: quality control of the structural interpretation results of the four three-dimensional target layers and loading them into the seismic migration data volume of each block. (1) Extract the absolute value amplitude corresponding to each three-dimensional block in a time window of 200ms above and below the target layer, and analyze the energy difference of the absolute value amplitude between each block. In this embodiment, the average absolute value amplitude of the target layer of blocks 1 to 4 is 1600, 1100, 1400, and 1700, respectively. Based on the amplitude energy of block 1, an amplitude correction factor is constructed to adjust the amplitude of blocks 2 to 4 to the same energy as that of block 1. (2) The target layer is shifted upward and downward in 100ms increments, and an amplitude correction factor is calculated according to the process in (1). (3) The amplitude correction factor of each block is used to construct an amplitude correction sequence according to the time series, and linear interpolation is used between the data points.

[0056] Furthermore, the pre-stack migration results of blocks 2-3 are flattened at the target layer, multiplied in the time domain by the amplitude correction sequence, and then subjected to reverse layer flattening to obtain amplitude-corrected seismic migration data. The profile and planar properties of the corrected results are quality controlled. If the allowable energy difference is not met, the aforementioned steps are repeated to reconstruct the amplitude correction sequence until the amplitude-energy difference is within the preset allowable range. This example only shows the effect after all fusion processing is performed. Figure 4 The diagram shown is a seismic profile obtained by directly stitching together seismic migration results according to an embodiment of the present invention. Figure 5 The diagram shown is a seismic plane diagram after direct stitching of seismic migration results provided in an embodiment of the present invention, where the arrows indicate the locations of the stitching points, such as... Figure 4 and Figure 5 As shown, there is no significant energy difference between blocks in both cross-sectional and planar properties.

[0057] Furthermore, a wavelet reconstruction factor is constructed based on the energy-corrected seismic migration data, and frequency correction is performed on the energy-corrected seismic migration data based on the wavelet reconstruction factor. The specific steps for constructing the wavelet reconstruction factor based on the energy-corrected seismic migration data include: (1) performing layer flattening processing on the seismic data of block 1 and the energy-corrected blocks 2, 3, and 4 at the target layer. In this embodiment, the correlation wavelet of the target layer is extracted using a 200ms time window through cross-correlation wavelet extraction technology. Figure 6 The diagram shown is a schematic diagram of the relevant wavelets and their corresponding amplitude spectra of blocks 1, 2 and 3 provided in the embodiment of the present invention; (2) The relevant wavelets are subjected to frequency feature analysis to obtain the effective bandwidth range of each block. Combined with the frequency division scanning data of each block, the effective frequency band range of the three blocks is determined. In this embodiment, block 1: 7-58Hz, block 2: 5-59Hz, block 3: 5-60Hz. Then, the relevant wavelet of block 1 is used to determine the effective frequency band range of the target wavelet (5-55Hz); (3) The features of block 1 can be selected as the basis for splicing. The relevant wavelet of block 1 is used as the target wavelet. In the time domain, the cross-correlation algorithm is used to construct the wavelet reconstruction factor of the relevant wavelets of blocks 2 and 3 to the target wavelet in the frequency band range of 5-55Hz. Figure 7 The diagram shown is a schematic diagram of the wavelet reconstruction factor and its amplitude spectrum provided in an embodiment of the present invention. After analysis of its amplitude spectrum, its characteristics are largely consistent with the characteristics of the wavelets related to blocks 2 and 3 and the wavelets related to block 1.

[0058] Furthermore, the wavelet reconstruction factor is applied and quality controlled. Specifically, the offset results of blocks 2 and 3 after energy correction are applied to the frequency domain or time domain to obtain result data whose frequency and energy characteristics are consistent with those of block 1. The frequency, phase, and waveform characteristics of the seismic wavelet reconstructed profile are quality controlled to determine whether they meet the interpretation requirements. If they do not meet the requirements, the reconstruction factor needs to be extracted again according to the aforementioned steps.

[0059] Since there are intersecting cases when splicing multiple 3D blocks, in practical applications, the time difference of the two blocks is first corrected and fused before being spliced ​​with the next block. In this embodiment, according to the processing order of block 1 to block 3 to block 2 to block 4, block 2 is spliced ​​with the fused body of blocks 1 and 3. Specifically, (1) the overlapping segments of block 2 and the fused body of blocks 1 and 3 are selected by matching coordinates or line points. (2) the average travel time of the target layer of the entire splicing area is calculated. Using the travel time plus or minus 2 seconds as a time window, the overlapping segments of block 2 and the fused body of blocks 1 and 3 are cross-correlated to calculate the time difference between overlapping segments. The time difference is smoothed with an appropriate smoothing factor to remove high-frequency changes in the time difference. The smoothed time difference is then analyzed to determine that the changes in planar features are relatively reasonable and to achieve quality control of the smoothing radius. Figure 8 The diagram shown illustrates the time difference between region 2 and blocks 1 and 3 as provided in an embodiment of the present invention. (3) Figure 9 The diagram shown is a planar schematic of the time difference application degree factor for the overlapping segments of Block 2 and the fusion body of Blocks 1 and 3 provided in this embodiment of the invention. The black lines represent the positions of the splicing points. Based on the splicing points, the data gradually transitions to the uncorrected time difference data on both sides to obtain the time difference correction application degree factor at the overlapping points. (4) Multiply the smoothed time difference value by the time difference correction application factor to obtain the time difference correction factor and apply it to the seismic data of Block 2. (5) Multiply the time difference correction application degree factor by the overlapping segment of Block 2 to obtain the data to be fused for the overlapping segment of the fusion body of Block 2. Subtract the time difference correction application factor from 1 and multiply it by the fusion body of Blocks 1 and 3 to obtain the data to be fused for the overlapping segment of the fusion body of Blocks 1 and 3. Add the two data to be fused to obtain the fusion result of the overlapping segment. (6) Merge the data of the non-overlapping segment with the data of the overlapping segment and reorder them to obtain the fused result data.

[0060] Preferably, quality control analysis is performed on the splicing points, overlapping and non-overlapping segments, and other locations of the fused data volume to ensure that the corrected time difference is within 1-2 ms and that there are no obvious abrupt changes in waveform characteristics (refer to...). Figure 4 and Figure 5 The frequency, amplitude, and other attributes of the target layer in the seismic data are extracted for planar quality control. Figure 10 The diagram shown is a planar schematic of the amplitude attributes after the migration results are stacked and fused according to an embodiment of the present invention. It can be seen that the frequency and energy of the fused seismic data volume are evenly distributed on the plane, with no abrupt changes or anomalies.

[0061] A second aspect of the present invention provides an apparatus for seismic migration data fusion. Figure 11 A schematic diagram of a seismic migration data fusion apparatus provided in an embodiment of the present invention is shown, as follows: Figure 11As shown, it includes: a first module 011, used to acquire seismic migration data corresponding to several blocks and select one of the blocks as a reference block based on the characteristics of the target layer and the geological task; a second module 012, used to construct an amplitude correction sequence based on the energy difference between the absolute amplitude of the reference block and the absolute amplitude of the non-reference blocks in the several blocks, and to perform energy correction on the seismic migration data based on the amplitude correction sequence; a third module 013, used to extract the correlation wavelets of the several blocks in the target layer based on the energy-corrected seismic migration data, and to perform energy correction on the seismic migration data based on the correlation wavelets and The geological task constructs a target wavelet; the fourth module 014 is used to calculate the frequency difference between the target wavelet and each of the related wavelets and obtain the wavelet reconstruction factor of the related wavelets reconstructed onto the target wavelet based on the frequency difference, so as to perform frequency correction on the energy-corrected seismic migration data of the corresponding block based on the wavelet reconstruction factor; the fifth module 015 is used to perform time difference correction on the frequency-corrected seismic migration data of the overlapping areas between the several blocks and fuse it with the frequency-corrected seismic migration data of the non-overlapping areas between the several blocks to obtain the fusion result of the seismic migration data.

[0062] A third aspect of the present invention provides an electronic device, Figure 12 The diagram shown is a schematic representation of an electronic device provided in an embodiment of the present invention. For example... Figure 12 As shown, an electronic device provided by an embodiment of the present invention includes the following modules: at least one processor 021; and a memory 022, the memory 022 storing computer instructions 023 that can be executed on the processor 021, the computer instructions 023 implementing the steps of the method described above when executed by the processor 021.

[0063] The present invention also provides a computer-readable storage medium. Figure 13 The diagram shown is a structural schematic of a computer-readable storage medium provided in an embodiment of the present invention. Figure 13 As shown, computer-readable storage medium 031 stores a computer program 032 that, when executed by a processor, performs the steps of the method described above. The method performed is the same as described above.

[0064] Finally, it should be noted that those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program for setting system parameters can be stored in a computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. The storage medium for the program can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. The above computer program embodiments can achieve the same or similar effects as any of the corresponding foregoing method embodiments.

[0065] Furthermore, the method disclosed in the embodiments of the present invention can also be implemented as a computer program executed by a processor, which may be stored in a computer-readable storage medium. When the computer program is executed by the processor, it performs the functions defined in the method disclosed in the embodiments of the present invention.

[0066] Furthermore, the above-described method steps and system units can also be implemented using a controller and a computer-readable storage medium for storing a computer program that enables the controller to perform the functions of the above-described steps or units.

[0067] Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the functionality of various illustrative components, blocks, modules, circuits, and steps has been generally described. Whether this functionality is implemented as software or as hardware depends on the specific application and the design constraints imposed on the system as a whole. Those skilled in the art can implement the functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the embodiments disclosed herein.

[0068] In one or more exemplary designs, functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functionality may be stored as one or more instructions or code on or transmitted via a computer-readable medium. Computer-readable media include computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one location to another. Storage media may be any available medium accessible to a general-purpose or special-purpose computer. By way of example, and not limitation, computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disc storage devices, disk storage devices or other magnetic storage devices, or any other medium that may be used to carry or store the required program code in the form of instructions or data structures and is accessible to a general-purpose or special-purpose computer or a general-purpose or special-purpose processor. Furthermore, any connection may be appropriately referred to as computer-readable media. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the aforementioned coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are all included in the definition of media. As used herein, disks and optical discs include compact discs (CDs), laser discs, optical discs, digital multifunction discs (DVDs), floppy disks, and Blu-ray discs, wherein disks typically reproduce data magnetically, while optical discs reproduce data optically using lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0069] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.

[0070] It should be understood that, as used herein, the singular form “a” is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, “and / or” refers to any and all possible combinations of one or more of the associated listed items.

[0071] The embodiment numbers disclosed in the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0072] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0073] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A method of seismic migration data fusion, characterized in that, include: Seismic migration data corresponding to several blocks are obtained, and one of the blocks is selected as the reference block based on the target layer characteristics and geological task; An amplitude correction sequence is constructed based on the energy difference between the absolute amplitude of the reference block and the absolute amplitude of the non-reference blocks in the plurality of blocks, respectively, to perform energy correction on the seismic migration data. This includes: performing layer flattening on the seismic migration data corresponding to the plurality of blocks based on the target layer, and extracting the absolute amplitude of the plurality of blocks corresponding to the target layer according to a preset step size time window; calculating the energy difference between the absolute amplitude of the non-reference blocks and the absolute amplitude of the reference block; constructing an amplitude correction factor for the absolute amplitude of the non-reference blocks relative to the absolute amplitude of the reference block based on the energy difference; arranging the amplitude correction factor in chronological order and performing linear interpolation to obtain the amplitude correction sequence; and performing reverse layer flattening on the layer-flattened seismic migration data based on the amplitude correction sequence to perform energy correction on the seismic migration data. Based on the energy-corrected seismic migration data, the correlation wavelets of the several blocks in the target layer are extracted respectively, and the target wavelets are constructed based on the correlation wavelets and the geological task; Calculate the frequency difference between the target wavelet and each of the related wavelets, and obtain the wavelet reconstruction factor of the related wavelets reconstructed onto the target wavelet based on the frequency difference, so as to perform frequency correction on the energy-corrected seismic migration data of the corresponding block based on the wavelet reconstruction factor; The frequency-corrected seismic migration data of the overlapping areas between the several blocks is time-difference corrected and then fused with the frequency-corrected seismic migration data of the non-overlapping areas between the several blocks to obtain the fused seismic migration data.

2. The method of claim 1, wherein, The step of performing energy correction on the seismic migration data based on the amplitude correction sequence includes: The seismic migration data corresponding to the non-benchmark block after the layer flattening process is multiplied in the time domain by the amplitude correction sequence and the reverse layer flattening process. Determine whether the energy difference is within a preset energy difference range, and based on the determination result, determine whether to reconstruct the amplitude correction factor and perform reconstruction or retention accordingly; Based on the reconstructed / preserved amplitude correction factor, the seismic migration data of the non-reference block corresponding to the target layer are energy corrected by the amplitude correction sequence corresponding to the energy difference within the preset energy difference range.

3. The method of claim 1, wherein, The step of extracting the correlation wavelets of the several blocks in the target layer based on the energy-corrected seismic migration data, and constructing the target wavelet based on the correlation wavelets and the geological task, includes: After performing layer flattening on the target layer, the energy-corrected seismic migration data is used to extract the corresponding wavelets for each of the several blocks. Based on the relevant wavelets corresponding to the aforementioned blocks, the effective frequency band range corresponding to the aforementioned blocks is obtained, and the target frequency band range is obtained based on the effective frequency band range corresponding to the aforementioned blocks. The target wavelet corresponding to the target frequency band range is constructed based on the least squares error minimization method and the geological task described above.

4. The method of claim 3, wherein, The step of calculating the frequency difference between the target wavelet and each of the related wavelets and obtaining the wavelet reconstruction factor of the related wavelets onto the target wavelet based on the frequency difference, and then performing frequency correction on the energy-corrected seismic migration data of the corresponding block based on the wavelet reconstruction factor, includes: Based on the cross-correlation algorithm and the target frequency band range, the wavelet reconstruction factors corresponding to the correlation wavelets of the several blocks are constructed to reconstruct the target wavelet; Frequency correction is performed on the energy-corrected seismic migration data based on the wavelet reconstruction factor; Determine whether the frequency-corrected seismic migration data meets the structural interpretation results of the target layer; In response to a failure to meet the structural interpretation results of the target layer, the process returns to the step of reconstructing the wavelet reconstruction factor until the frequency-corrected seismic migration data meets the structural interpretation results of the target layer.

5. The method of claim 1, wherein, The step of fusing the frequency-corrected seismic migration data of the overlapping areas between the several blocks with the frequency-corrected seismic migration data of the non-overlapping areas between the several blocks to obtain the fused seismic migration data includes: Obtain the overlapping areas between the aforementioned blocks; The time difference of the overlapping region is calculated based on the cross-correlation algorithm and then smoothed. The optimal position for stitching together the frequency-corrected seismic migration data is obtained by time-shifting the smoothed time difference, and the time difference correction factor of the frequency-corrected seismic migration data of the overlapping area in the time domain is obtained based on the optimal position. Based on the time difference correction factor, the frequency-corrected seismic migration data of the overlapping area is corrected for time difference, and the frequency-corrected seismic migration data of the non-overlapping areas between the several blocks are fused to obtain the fusion result of the seismic migration data.

6. The method of claim 5, wherein, The step of obtaining the time difference correction factor in the time domain of the frequency-corrected seismic migration data of the overlapping area based on the optimal location includes: Based on the optimal location, obtain the time difference correction application degree factor corresponding to the overlapping area; The time difference correction application degree factor is multiplied by the smoothed time difference corresponding to the overlapping region to obtain the corresponding time difference correction factor.

7. An apparatus for seismic migration data fusion, characterized in that, include: The first module is used to acquire seismic migration data corresponding to several blocks and select one of the blocks as the reference block based on the target layer characteristics and geological tasks. The second module is used to construct an amplitude correction sequence based on the energy difference between the absolute amplitude of the reference block and the absolute amplitude of the non-reference blocks in the plurality of blocks, so as to perform energy correction on the seismic migration data based on the amplitude correction sequence. The third module is used to extract the correlation wavelets of the several blocks in the target layer based on the energy-corrected seismic migration data, so as to construct the target wavelet based on the correlation wavelets and the geological task; a fourth module configured to calculate a frequency difference between the target wavelet and each of the correlation wavelets, and obtain a wavelet reconstruction factor of reconstructing the correlation wavelet onto the target wavelet based on the frequency difference, so as to perform frequency correction on the energy-corrected seismic migration data of the corresponding blocks based on the wavelet reconstruction factor; a fifth module configured to perform time difference correction on the frequency-corrected seismic migration data of the overlapping area between the blocks, and fuse the frequency-corrected seismic migration data of the non-overlapping area between the blocks, to obtain a fusion result of the seismic migration data; the second module is further configured to perform layer flattening on the seismic migration data corresponding to the blocks respectively based on the target layer, and extract absolute value amplitudes of the blocks respectively corresponding to the target layer according to a preset time window step; calculate an energy difference between the absolute value amplitudes of the non-reference blocks and the absolute value amplitudes of the reference blocks; construct an amplitude correction factor of the absolute value amplitudes of the non-reference blocks relative to the absolute value amplitudes of the reference blocks based on the energy difference, arrange the amplitude correction factor in time sequence and perform linear interpolation to obtain an amplitude correction sequence, and perform inverse layer flattening on the layer-flattened seismic migration data based on the amplitude correction sequence, so as to perform energy correction on the seismic migration data.

8. An electronic device, comprising: comprise: at least one processor; and a memory storing computer instructions executable on the processor, the computer instructions being executed by the processor to implement the steps of the method of any one of claims 1-6. 9.A computer readable storage medium storing computer programs executable by a processor to implement the steps of the method of any one of claims 1-6.

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