Frequency-division compression method and apparatus for pre-stack seismic data, and device and storage medium

Abstract

A frequency-division compression method for pre-stack seismic data. The method comprises: acquiring pre-stack seismic data (S1); performing a Hartley transform on the pre-stack seismic data, so as to obtain transformed seismic data (S2); dividing the transformed seismic data into low-frequency data and high-frequency data (S3), wherein the low-frequency data comprises at least one low-frequency transform coefficient group, and the high-frequency data comprises at least one high-frequency transform coefficient group; and respectively performing compression coding at different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group, so as to obtain compressed data (S4), wherein the compression coding level of the low-frequency transform coefficient group is greater than the compression coding level of the high-frequency transform coefficient group. Further provided is a frequency-division compression apparatus for pre-stack seismic data. High-level coding is performed on a low-frequency portion, in which the main energy of seismic data is concentrated, so as to ensure a signal-to-noise ratio, and low-level coding is performed on a high-frequency portion, so as to increase a compression ratio.

Description

Prestack seismic data frequency division compression method, device, equipment and storage medium Technical Field

[0001] The present invention relates to the field of oil and gas exploration, to seismic data acquisition and signal processing technology, and in particular to a pre-stack seismic data frequency division compression method, a pre-stack seismic data frequency division compression device, a computer device and a computer-readable storage medium. Background Art

[0002] With the rapid development of oil geophysical exploration technology and the increasingly high requirements for exploration accuracy, seismic exploration instruments are also moving towards multi-dimensional, multi-component, multi-parameter and high-resolution. The amount of seismic exploration data has increased exponentially. Faced with the current situation of real-time recovery of massive data and channel bandwidth transmission constraints, how to improve the real-time transmission capability of massive data in seismic exploration systems is a major bottleneck issue restricting production efficiency.

[0003] Seismic data compression and reconstruction techniques offer an effective solution to this problem. Seismic data compression is a key technology for the transmission and storage of massive amounts of seismic data. Data compression can reduce the amount of data at the source, improving real-time data processing speed and saving storage space.

[0004] Seismic exploration data compression methods can be divided into two categories according to whether there is information loss or not: lossless compression and lossy compression. Lossless compression can ensure that the decompressed data is exactly the same as the original data, and is particularly suitable for compressing seismic data that needs further processing after decompression. However, its compression efficiency is low, and the compression ratio is generally less than 2. Lossy compression can achieve high compression while allowing a small amount of information loss. The compression ratio is higher, but there are problems such as information loss.

[0005] How to compress data as much as possible while ensuring information integrity is still a problem that needs to be solved.

[0006] Summary of the Invention

[0007] The purpose of the embodiment of the present invention is to provide a pre-stack seismic data frequency division compression method, device, equipment and storage medium. The method uses Hartley transform to distinguish the high-frequency part and the low-frequency part in the pre-stack seismic data, and then performs different levels of compression encoding on the low-frequency part and the high-frequency part respectively. The low-frequency part that concentrates the main energy of the seismic data is encoded with a high level of encoding to ensure the signal-to-noise ratio of the compressed data, and the high-frequency part is encoded with a low level of encoding to improve the compression ratio of the data.

[0008] In order to achieve the above object, the present invention provides a method for frequency division and compression of pre-stack seismic data in a first aspect, the method comprising:

[0009] Acquire pre-stack seismic data;

[0010] Perform Hartley transform on pre-stack seismic data to obtain transformed seismic data;

[0011] Dividing the transformed seismic data into low-frequency data and high-frequency data; the low-frequency data includes at least one low-frequency transformation coefficient group, and the high-frequency data includes at least one high-frequency transformation coefficient group;

[0012] performing compression coding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group, respectively, to obtain compressed data, wherein the compression coding level of the low-frequency transform coefficient group is greater than the compression coding level of the high-frequency transform coefficient group, and the compressed data includes target coding symbol groups at each level and auxiliary scanning data at each level;

[0013] The compression coding includes:

[0014] In the main scanning phase, the transform coefficient group is subjected to a step-by-step coding scan to obtain initial coding symbol groups at each level, where each level of coding corresponds to a threshold value. The initial coding symbol groups include important coding symbols and minor coding symbols. The minor coding symbols following the last important coding symbol in each level of the initial coding symbol groups are deleted to obtain target coding symbol groups at each level.

[0015] determining significant transform coefficients in the transform coefficient group based on significant coding symbols in the primary coding symbol group;

[0016] In the auxiliary scanning stage, each important transform coefficient in the transform coefficient group is quantized level by level according to the threshold value corresponding to each level of coding, and auxiliary scanning data of each level is output.

[0017] According to the above technical means, the high-frequency part and the low-frequency part in the pre-stack seismic data are distinguished by Hartley transform, and then the low-frequency part and the high-frequency part are compressed and coded at different levels respectively. The low-frequency part that concentrates the main energy of the seismic data is encoded at a high level to ensure the signal-to-noise ratio of the compressed data, and the high-frequency part is encoded at a low level to improve the compression ratio of the data. At the same time, in the compression coding process, the secondary coding symbols after the last important coding symbol are deleted, while ensuring the integrity of the data, the amount of data after compression coding is further reduced, saving data transmission resources.

[0018] In the embodiment of the present application, the transformed seismic data is divided into low-frequency data and high-frequency data, including:

[0019] The transformed seismic data are divided into low-frequency data and high-frequency data according to the acquisition parameters and data quality of the seismic data.

[0020] According to the above technical means, the transformed seismic data can be more accurately divided into low-frequency data and high-frequency data.

[0021] In an embodiment of the present application, the data quality includes the Nyquist frequency, and the sampling parameters include: a frequency sampling interval;

[0022] The transformed seismic data is divided into low-frequency data and high-frequency data according to the acquisition parameters and data quality of the seismic data, including:

[0023] The frequency range of low-frequency data and the frequency range of high-frequency data are determined by calculating the Nyquist frequency and the frequency sampling interval;

[0024] The transformed seismic data is divided into low-frequency data and high-frequency data according to the determined frequency range.

[0025] According to the above technical means, high-frequency data and low-frequency data are divided according to data acquisition parameters. The division method is more consistent with the actual data and is more conducive to ensuring the integrity of the data after subsequent compression.

[0026] In the embodiment of the present application, the frequency range of the low-frequency data satisfies the following relationship:

[0027] The frequency range of the high-frequency data satisfies the following relationship:

[0028] or

[0029] Among them, f1 is the low frequency, f2 is the high frequency, f max is the Nyquist frequency, and df is the frequency sampling interval.

[0030] According to the above technical means, the transformed data can be accurately divided into a high-frequency part and a low-frequency part.

[0031] In the embodiment of the present application, in the main scanning phase, the transform coefficient group is subjected to a level-by-level coding scan to obtain initial coding symbol groups at each level, including:

[0032] Determining a first threshold corresponding to a current level coding scan according to an iterative threshold function and a transform coefficient group;

[0033] comparing an absolute value of each transform coefficient in the transform coefficient group with the first threshold;

[0034] If the absolute value of the transform coefficient is greater than or equal to the first threshold, encoding the transform coefficient as a symbol P or a symbol N; wherein the symbol P corresponds to a significant transform coefficient with a positive value, and the symbol N corresponds to a significant transform coefficient with a negative value, and the symbol P and the symbol N are significant coding symbols;

[0035] If the absolute value of the transform coefficient is less than the first threshold, encoding the transform coefficient as symbol T or symbol Z or not encoding; wherein the symbol T and the symbol Z are secondary coding symbols;

[0036] According to the symbol P, the symbol N, the symbol T and the symbol Z, a current-level initial coding symbol group is obtained.

[0037] According to the above technical means, the transformation coefficient group is converted into an initial coding symbol group.

[0038] In the embodiment of the present application, in the auxiliary scanning stage, each important transform coefficient in the transform coefficient group is quantized level by level according to the threshold value corresponding to each level of coding, and auxiliary scanning data of each level is output, including:

[0039] Determining a threshold corresponding to a current level of encoding according to the iterative threshold function and the transform coefficient group;

[0040] Determine a quantization interval corresponding to the current level code according to a threshold corresponding to the current level code, wherein the quantization interval is divided into two sub-intervals;

[0041] Determine the current level quantization result of each important transform coefficient according to the quantization interval corresponding to the current level encoding;

[0042] According to the current-level quantization result of each important transform coefficient, the current-level auxiliary scanning data is output.

[0043] In the embodiment of the present application, determining the current-level quantization result of each important transform coefficient according to the quantization interval corresponding to the current-level encoding includes:

[0044] If the important transform coefficient belongs to the previous sub-interval of the quantization interval corresponding to the encoding, the quantization result is 0; if the important transform coefficient belongs to the next sub-interval of the quantization interval corresponding to the encoding, the quantization result is 1.

[0045] In the embodiment of the present application, after respectively performing compression encoding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group, the method further includes:

[0046] Decoding the compressed data in a corresponding level to obtain decoded data;

[0047] The decoded data are merged and then subjected to inverse Hartley transform to obtain reconstructed seismic data.

[0048] According to the above technical means, the compressed and encoded data is restored to obtain reconstructed seismic data.

[0049] A second aspect of the present application provides a pre-stack seismic data frequency division and compression device, the device comprising:

[0050] A data acquisition unit, used for acquiring pre-stack seismic data;

[0051] A data transformation unit, used for performing Hartley transformation on pre-stack seismic data to obtain transformed seismic data;

[0052] A data division unit, configured to divide the transformed seismic data into low-frequency data and high-frequency data; the low-frequency data includes at least one low-frequency transformation coefficient group, and the high-frequency data includes at least one high-frequency transformation coefficient group;

[0053] a data compression unit, configured to perform compression coding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group, respectively, to obtain compressed data, wherein the compression coding level of the low-frequency transform coefficient group is greater than the compression coding level of the high-frequency transform coefficient group, and the compressed data includes target coding symbol groups at each level and auxiliary scanning data at each level;

[0054] The data compression unit comprises:

[0055] a main scanning module for performing a level-by-level coding scan on the transform coefficient group to obtain initial coding symbol groups at each level, wherein each level of coding in the level-by-level coding corresponds to a threshold value, and the initial coding symbol groups include important coding symbols and minor coding symbols; and deleting the minor coding symbols following the last important coding symbol in the initial coding symbol groups at each level to obtain target coding symbol groups at each level;

[0056] a determination module, configured to determine important transform coefficients in the transform coefficient group based on the important coding symbols in the primary coding symbol group;

[0057] The auxiliary scanning module is used to quantize each important transform coefficient in the transform coefficient group step by step according to the threshold value corresponding to each level of coding, and output auxiliary scanning data of each level.

[0058] According to the above technical means, the high-frequency part and the low-frequency part in the pre-stack seismic data are distinguished by Hartley transform, and then the low-frequency part and the high-frequency part are compressed and coded at different levels respectively. The low-frequency part that concentrates the main energy of the seismic data is encoded at a high level to ensure the signal-to-noise ratio of the compressed data, and the high-frequency part is encoded at a low level to improve the compression ratio of the data. At the same time, in the compression coding process, the secondary coding symbols after the last important coding symbol are deleted, while ensuring the integrity of the data, the amount of data after compression coding is further reduced, saving data transmission resources.

[0059] A third aspect of the present application provides a computer device, which includes a processor and a memory. The memory stores a computer program, and the computer program is loaded and executed by the processor to implement the pre-stack seismic data frequency division and compression method.

[0060] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is loaded and executed by a processor to implement the pre-stack seismic data frequency division and compression method.

[0061] The fifth aspect of the present application provides a computer program product, which includes a computer program stored in a computer-readable storage medium. A processor reads and executes the computer program from the computer-readable storage medium to implement the pre-stack seismic data frequency division and compression method.

[0062] The above technical solution uses EZW encoding for the Hartley domain high- and low-frequency data separately. Since the energy of seismic data is primarily concentrated in the low-frequency portion, the low-frequency data is encoded at a high level, ensuring the compressed data's signal-to-noise ratio, while the high-frequency data is encoded at a low level, improving the data compression ratio. This method effectively maintains both a high signal-to-noise ratio and a high compression ratio, better meeting the requirements for high-precision seismic data compression.

[0063] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0065] FIG1 is a schematic diagram of a main scan code provided by the EZW coding method;

[0066] FIG2 is a schematic diagram of an 8×8 wavelet coefficient group provided by the EZW encoding method;

[0067] FIG3 is a schematic diagram of the first level main scan code provided by the EZW encoding method;

[0068] FIG4 is a schematic diagram of the second level main scan code provided by the EZW encoding method;

[0069] FIG5 is a flow chart of a method for frequency division and compression of pre-stack seismic data provided by one embodiment of the present application;

[0070] FIG6 is a schematic diagram of pre-stack seismic data acquired by a single shot of a Sigsbee 2A model provided in one embodiment of the present application;

[0071] FIG7 is a schematic diagram of a Hartley transform result provided by one embodiment of the present application;

[0072] FIG8a is a partial schematic diagram of low-frequency data provided by one embodiment of the present application;

[0073] FIG8b is a partial schematic diagram of high-frequency data provided by one embodiment of the present application;

[0074] FIG9 is a schematic diagram showing a comparison of signal-to-noise ratios of decompressed data at different high-frequency coding levels when the number of low-frequency coding levels is 8, provided by one embodiment of the present application;

[0075] FIG10 is a schematic diagram showing a comparison of compression ratios of decompressed data at different high-frequency coding levels when the number of low-frequency coding levels is 8, provided in one embodiment of the present application;

[0076] FIG11 is a schematic diagram showing a comparison of signal-to-noise ratios of decompressed data at different high-frequency coding levels when the number of low-frequency coding levels is 10, provided in one embodiment of the present application;

[0077] FIG12 is a schematic diagram showing a comparison of compression ratios of decompressed data at different high-frequency coding levels when the number of low-frequency coding levels is 10, according to an embodiment of the present application;

[0078] FIG13 is a block diagram of a pre-stack seismic data frequency division and compression device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0079] The following describes the specific embodiments of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention and are not intended to limit the present invention.

[0080] Before introducing and explaining the technical solution of this application, some concepts involved in this application are first defined and explained.

[0081] EZW algorithm: EZW is an image coding algorithm. Its core is progressive encoding and quantization in the wavelet domain. The main scan determines the signs and spatial positions of important coefficients through progressive encoding; the auxiliary scan only performs fine quantization on the important coefficients in the main scan.

[0082] The EZW algorithm has the following three steps.

[0083] (1) Determine the iterative threshold formula. EZW uses step-by-step quantization coding, which applies a series of thresholds T1, T2, ..., T in turn. N To determine the importance of wavelet coefficients:

[0084] Among them, c is the wavelet coefficient, N is the maximum coding level, T iis the threshold corresponding to the i-th encoding.

[0085] (2) Main scan. The main scan is used to determine the sign and spatial position of important coefficients, perform coarse quantization through level-by-level scanning, and improve coding efficiency through the zero tree structure. Please refer to Figure 1, which shows a schematic diagram of the main scan coding provided by the EZW algorithm. First, the zero tree characteristics of the wavelet coefficients are used to mark the wavelet coefficients at the i-th level scan. When the absolute value of the wavelet coefficient is greater than T i If the wavelet coefficient is about the threshold T, it is an important coefficient of the i-th level scan, and is encoded as the symbol P (positive important coefficient) or the symbol N (negative important coefficient); otherwise, it is an unimportant coefficient. If the important coefficient is scanned out at the i-th level, it will not be scanned and encoded at the next level. i The unimportant coefficient of , and its descendants are all less than the threshold T i , then it is the zero tree root T, and the descendants of the zero tree root do not need to be coded; but if there is a coefficient greater than the set threshold T in the descendants of the coefficient i The coefficient of , then it is an isolated zero value Z.

[0086] (3) Auxiliary scanning. Fine quantization is performed on the important coefficients of the main scanning table (wavelet coefficients corresponding to P and N). At the i-th level scanning, the maximum value of the quantization interval is twice the initial threshold T1, and the minimum value is the current threshold T i , the total quantization interval is [T i , 2T1), the quantization interval is T i , so the number of quantizers for the i-th level scan is (please refer to formula 2):

[0087] The quantizer interval is [dT i , dT i +T i ), where 1≤d≤Q, is divided into two equal quantization subintervals [dT i , dT i +0.5T i ) and [dT i +0.5T i , dT i +T i If the wavelet coefficient belongs to the previous subinterval, the quantization symbol "0" is output; otherwise, the quantization symbol "1" is output. The output symbols "0" and "1" are recorded by an auxiliary scanning table. After determining the number of quantizers and the quantization interval, the quantization values ​​corresponding to "0" and "1" in each quantizer must be determined. In the qth quantizer, the reconstructed value of the symbol "0" is, please refer to Formula 3:

[0088] T i (q+0.25)(Formula 3)

[0089] The reconstructed value of symbol "1" is, please refer to formula 4:

[0090] T i (q+0.75)(Formula 4)

[0091] The important coefficients of the previous level coding are quantized in the next level coding, and the important coefficients of the next level coding are not quantized in the previous level, thereby reducing the number of symbols of the quantization output. Due to the sparsity of wavelet coefficients, large important coefficients are quantized finely (quantized more times), while small important coefficients are quantized less times and occupy fewer bits.

[0092] Please refer to Figure 2, which shows a schematic diagram of an 8×8 wavelet coefficient group provided by an embodiment. As shown in Figure 2, the wavelet coefficient with the largest absolute value is 63, so according to Formula 1, we can get According to T i =T1 / 2 i-1 , we can get T1=32, T2=16, T3=8, T4=4, that is, the threshold corresponding to the first level coding is 32, the threshold corresponding to the second level coding is 16, the threshold corresponding to the third level coding is 8, and the threshold corresponding to the fourth level coding is 4.

[0093] Please refer to Table 1, which shows the symbols output by the main scan and auxiliary scan of the wavelet coefficients shown in Figure 2 using the EZW algorithm. In the first level main scan, the wavelet coefficients in Figure 2 are scanned with a threshold of 32. If the absolute value of the wavelet coefficient is greater than or equal to 32, the wavelet coefficient is encoded as a symbol P or a symbol N, indicating that it is an important wavelet coefficient. If the wavelet coefficient is a positive number, it is encoded as P, and if the wavelet coefficient is a negative number, it is encoded as N. If the absolute value of the wavelet coefficient is less than 32, it is determined whether it is a descendant coefficient of the zero tree, and is encoded or not encoded.

[0094] For example, in the first level main scan, the wavelet coefficient -31 (21) is not a descendant coefficient of the zero tree and there are important coefficients among the descendant coefficients of this wavelet coefficient, so it is encoded as Z, indicating that it is an isolated zero value. For example, the wavelet coefficient 23 (22) is not a descendant coefficient of the zero tree and there are no important coefficients among the descendant coefficients of this wavelet coefficient, so it is encoded as T, indicating that it is a zero tree root.

[0095] Since the absolute values ​​of the wavelet coefficients 63 (23), -34 (24), 49 (25), and 47 (26) in FIG2 are greater than the threshold value 32 corresponding to the first-level encoding, the corresponding codes in the first-level main scan are P, N, P, and P, respectively. Please refer to FIG3, which shows a schematic diagram of the first-level main scan encoding provided by an embodiment of the EZW algorithm. The P in P1 in the figure represents that the encoding symbol 63 in FIG2 is encoded as P, and the subscript 1 represents that the encoding symbol corresponds to the first symbol of the first-level main scan output sequence in Table 1. When the output symbol of a wavelet coefficient is T, all its descendant coefficients are no longer scanned and are represented by "×".

[0096] In the first level auxiliary scan, the important wavelet coefficients 63, -34, 49 and 47 in the first level main scan are quantized. For example, for the wavelet coefficient 63, the process of determining the quantization sign of its auxiliary scan output is as follows:

[0097] (1) Determine the quantizer for the first level main scan, including determining the number of quantizers and the quantizer interval. According to formula 2, the number of quantizers is Therefore, the value of d is 1, and the quantizer interval is [dT i , dT i +T i ), i.e. [32, 64), which is divided equally into two quantization subintervals [32, 48) and [48, 64).

[0098] (2) Determine the wavelet coefficient encoding character. The wavelet coefficient 63 is in the next subinterval [48, 64) of the interval [32, 64), so the quantization symbol of the auxiliary scan is 1 (corresponding to the first character "1" output by the first level auxiliary scan); for example, the absolute value of the wavelet coefficient -34 is in the previous subinterval [32, 48) of the interval [32, 64), so the auxiliary scan encoding character is 0 (corresponding to the second character "0" output by the first level auxiliary scan).

[0099] According to the above method, the coded characters of the second level main scan and auxiliary scan can be determined. In the second level main scan, the wavelet coefficients in FIG2 are scanned with a threshold of 16. Please refer to FIG4, which shows a schematic diagram of the second level main scan coding provided by an embodiment of the present application. Since the wavelet coefficients 63, -34, 49 and 47 in FIG2 have been encoded in the first level main scan, Mark, indicating that it is not encoded in the second level main scan.

[0100] In the second-level main scan, the wavelet coefficients -31 (at position 21) and 23 (at position 22) are encoded as symbols N and P, respectively. In the second-level auxiliary scan, the important wavelet coefficients 63, -34, 49, and 47 in the first-level main scan and the important wavelet coefficients -31 and 23 in the second-level main scan are quantized. For example, for the wavelet coefficient 63, the process of determining the symbol of its auxiliary scan output is as follows:

[0101] (1) Determine the quantizer for the first level main scan, including determining the number of quantizers and the quantizer interval. According to formula 2, the number of quantizers is Therefore, the values ​​of d are 1, 2, and 3. The first quantizer interval is [16, 32), the second quantizer interval is [32, 48), and the third quantizer interval is [48, 64).

[0102] (2) Determine the wavelet coefficient coding character. The wavelet coefficient 63 is in the next subinterval [56, 64) of the third quantizer interval [48, 64), so the auxiliary scan coding character is 1 (corresponding to the first character "1" output by the second level auxiliary scan); for example, the absolute value of the wavelet coefficient -34 is in the previous subinterval [32, 40) of the second quantizer interval [32, 48), so the auxiliary scan coding character is 0 (corresponding to the second character "0" output by the first level auxiliary scan).

[0103] According to the above method, the coding symbols of each level of main scanning and auxiliary scanning can be determined, as shown in Table 1 below.

[0104] Table 1

[0105] The wavelet coefficients are encoded step by step using the above method. The secondary coding symbols isolated zero values ​​(symbol Z) and zero tree roots (symbol T) encoded in the previous level will also be rescanned and encoded in the next level. Please refer to 31 and 32 in Figure 3 and the corresponding 41 and 42 in Figure 4. The wavelet coefficients are encoded in the first level main scan and in the second level main scan at the same time. This will result in an increase in the number of encoded isolated zero values ​​and zero tree roots, reduce the data compression ratio, and require more storage space.

[0106] Therefore, this application proposes a frequency division compression method for prestack seismic data. This method first performs a Hartley domain transform on the seismic data. Then, based on the seismic data acquisition parameters and data quality, the data is divided into low-frequency and high-frequency components. The low-frequency data is encoded at a high level to ensure the signal-to-noise ratio of the compressed data, while the high-frequency data is encoded at a low level to improve the data compression ratio. Based on this, an improved EZW algorithm is used. After each level of main scanning is completed, the secondary encoding symbols following the last significant encoding symbol in the initial encoding symbol group are deleted to obtain the target encoding symbol group. This further reduces the data volume, saves storage space, and reduces the occupancy of the data transmission channel.

[0107] FIG5 is a flow chart of a method for frequency division and compression of prestack seismic data provided by one embodiment of the present invention. Each step of the method may be performed by a computer device. As shown in FIG5 , the method includes the following steps S1-S4.

[0108] S1: Acquire pre-stack seismic data.

[0109] In the present embodiment, pre-stack seismic data refers to seismic data that has been collected and processed but not subjected to seismic offset correction and stacking. It contains all the information about the seismic wave signals recorded by the seismic instrument, including the reflection and refraction characteristics of the underground medium. Pre-stack seismic data can be used for seismic imaging and underground structural interpretation, but because it has not been offset corrected, underground interfaces at different locations may be misaligned. As shown in Figure 6, this figure shows pre-stack seismic data collected by a single shot of the Sigsbee 2A model.

[0110] S2: Perform Hartley transform on pre-stack seismic data to obtain transformed seismic data. Transform seismic data according to the following formula:

[0111] Where x(t) is the seismic data, cast = cost + sint, f is the frequency, t is the time, and dt is the time differential. The Hartley transform separates the high-frequency and low-frequency components of prestack seismic data. The transformed seismic data is shown in Figure 7.

[0112] S3: Divide the transformed seismic data into low-frequency data and high-frequency data; the low-frequency data includes at least one low-frequency transformation coefficient group, and the high-frequency data includes at least one high-frequency transformation coefficient group.

[0113] In the embodiment of the present application, the transformed seismic data is divided into low-frequency data and high-frequency data, including:

[0114] The transformed seismic data are divided into low-frequency data and high-frequency data according to the acquisition parameters and data quality of the seismic data.

[0115] According to the above technical means, the transformed seismic data can be more accurately divided into low-frequency data and high-frequency data.

[0116] In an embodiment of the present application, the data quality includes the Nyquist frequency, and the sampling parameters include: a frequency sampling interval;

[0117] First, the transformed seismic data is divided into low-frequency data and high-frequency data according to the acquisition parameters and data quality of the seismic data, including:

[0118] The frequency range of the low-frequency data and the frequency range of the high-frequency data are calculated and determined according to the Nyquist frequency and the frequency sampling interval. The frequency range of the low-frequency data satisfies the following relationship:

[0119] The frequency range of the high-frequency data satisfies the following relationship:

[0120] or

[0121] Among them, f1 is the low frequency, f2 is the high frequency, f max is the Nyquist frequency, and df is the frequency sampling interval.

[0122] According to the above technical means, the transformed data can be accurately divided into a high-frequency part and a low-frequency part.

[0123] Then, the transformed seismic data is divided into low-frequency data and high-frequency data according to the determined frequency range. The results after frequency division are shown in Figures 8a and 8b. Figure 8a is the low-frequency data part, and Figure 8b is the high-frequency data part.

[0124] According to the above technical means, high-frequency data and low-frequency data are divided according to data acquisition parameters. The division method is more consistent with the actual data and is more conducive to ensuring the integrity of the data after subsequent compression.

[0125] S4: Compression encoding of different levels is performed on the low-frequency transform coefficient group and the high-frequency transform coefficient group, respectively, to obtain compressed data. The compression encoding level of the low-frequency transform coefficient group is greater than that of the high-frequency transform coefficient group. The compressed data includes target coding symbol groups at each level and auxiliary scanning data at each level. The low-frequency portion, which concentrates the main energy of the seismic data, is encoded at a high level to ensure the signal-to-noise ratio of the compressed data, while the high-frequency portion is encoded at a low level to improve the data compression ratio.

[0126] In the embodiment of the present application, the compression coding includes:

[0127] In the main scanning stage, the transformation coefficient group is subjected to step-by-step coding scanning to obtain initial coding symbol groups at each level. Each level of coding in the step-by-step coding corresponds to a threshold value, and the initial coding symbol group includes important coding symbols and secondary coding symbols. The secondary coding symbols following the last important coding symbol in the initial coding symbol group at each level are deleted to obtain target coding symbol groups at each level.

[0128] The level-by-level encoding process during the main scan phase is identical to the EZW encoding process described above. The first threshold for the current level of encoding is determined based on the iterative threshold function and the transform coefficient group. As described above, the threshold for each level of encoding can be obtained by iterating the threshold function. The threshold for level 1 is 32, for level 2 is 16, for level 3 is 8, and for level 4 is 4.

[0129] comparing an absolute value of each transform coefficient in the transform coefficient group with the first threshold;

[0130] If the absolute value of the transform coefficient is greater than or equal to the first threshold, encoding the transform coefficient as a symbol P or a symbol N; wherein the symbol P corresponds to a significant transform coefficient with a positive value, and the symbol N corresponds to a significant transform coefficient with a negative value, and the symbol P and the symbol N are significant coding symbols;

[0131] If the absolute value of the transform coefficient is less than the first threshold, encoding the transform coefficient as symbol T or symbol Z or not encoding; wherein the transform coefficient corresponding to symbol T is a zero tree root, the transform coefficient corresponding to symbol Z is an isolated zero value, and the symbol T and the symbol Z are secondary coding symbols;

[0132] Based on the symbol P, the symbol N, the symbol T, and the symbol Z, an initial coding symbol group for the current level is obtained. Using the aforementioned technical means, the transform coefficient group is converted into an initial coding symbol group. Then, the secondary coding symbols following the last significant coding symbol in each level of the initial coding symbol group are deleted to obtain target coding symbol groups for each level. Table 2 shows the target coding symbol groups ultimately obtained by performing a primary scan on the wavelet coefficients in FIG. 2 .

[0133] Table 2

[0134] After the main scan is completed, the important transform coefficients in the transform coefficient group are determined based on the important coding symbols in the primary coding symbol group. That is, the transform coefficients corresponding to the coding symbols P and N in the main scan stage. Taking the wavelet coefficients in Figure 2 as an example, if it is the first level scan, then the first threshold is 32. The first symbol P of the first level main scan in Table 2 corresponds to 63 in Figure 2. We can determine the important transform coefficients based on P and N output from the main scan, and then quantize them step by step in the auxiliary scan stage.

[0135] In the auxiliary scanning stage, each important transform coefficient in the transform coefficient group is quantized level by level according to the threshold value corresponding to each level of coding, and auxiliary scanning data of each level is output, including:

[0136] The threshold corresponding to the current level encoding is determined according to the iterative threshold function and the transform coefficient group. As mentioned above, in the above text, we obtain that the thresholds for each level encoding corresponding to the wavelet coefficient group in Figure 2 are: T1=32, T2=16, T3=8, T4=4.

[0137] According to the threshold value corresponding to the current level code, the quantization interval corresponding to the current level code is determined, and the quantization interval is divided into two sub-intervals. According to the total quantization interval [T i , 2T1), and the number of quantizers and quantizer intervals corresponding to each level of coding. It can be obtained that, for example, the number of quantizers for level 1 coding is 1, and the quantizer quantization interval is [32, 64), which is equally divided into two subintervals: [32, 48) and [48, 64).

[0138] Exemplarily, the number of quantizers for the second-level encoding is 3, the first quantizer interval is [16, 32), which is divided equally into two sub-intervals: [16, 24) and [24, 32); the second quantizer interval is [32, 48), which is divided equally into two sub-intervals: [32, 40) and [40, 48); the third quantizer interval is [48, 64), which is divided equally into two sub-intervals: [48, 56) and [56, 64).

[0139] The current-level quantization result for each significant transform coefficient is determined based on the quantization interval corresponding to the current-level code: if the significant transform coefficient belongs to the previous subinterval of the quantization interval corresponding to the code, the quantization result is 0; if the significant transform coefficient belongs to the next subinterval of the quantization interval corresponding to the code, the quantization result is 1. During the first-level auxiliary scan, wavelet coefficient 63 is in the next subinterval [48, 64) of the interval [32, 64), so the quantization sign for the first-level auxiliary scan is 1. During the second-level auxiliary scan, it is in the next subinterval [56, 64) of the third quantizer interval [48, 64), so the second-level auxiliary scan code is 1.

[0140] According to the current-level quantization result of each important transform coefficient, the current-level auxiliary scanning data is output.

[0141] According to the above technical means, the high-frequency part and the low-frequency part in the pre-stack seismic data are distinguished by Hartley transform, and then the low-frequency part and the high-frequency part are compressed and encoded at different levels respectively. At the same time, in the compression encoding process, the secondary coding symbols after the last important coding symbol are deleted. While ensuring the integrity of the data, the amount of data after compression encoding is further reduced, saving data transmission resources.

[0142] In an embodiment of the present application, the compression coding level of the low-frequency transform coefficient group is greater than the compression coding level of the high-frequency transform coefficient group. FIG9 shows a comparison of the signal-to-noise ratio of the decompressed data at different coding levels of the high-frequency transform coefficient group when the coding level of the low-frequency transform coefficient group is 8, and FIG11 shows a comparison of the signal-to-noise ratio of the decompressed data at different coding levels of the high-frequency transform coefficient group when the coding level of the low-frequency transform coefficient group is 10. As can be seen from FIG9 and FIG11, the higher the coding level of the high-frequency transform coefficient group, the greater the signal-to-noise ratio of the decompressed data, and as the coding level of the high-frequency transform coefficient group increases, the impact of each additional level of coding on the signal-to-noise ratio becomes smaller and smaller. FIG10 shows a comparison of the compression ratio of the decompressed data at different coding levels of the high-frequency transform coefficient group when the coding level of the low-frequency transform coefficient group is 8, and FIG12 shows a comparison of the compression ratio of the decompressed data at different coding levels of the high-frequency transform coefficient group when the coding level of the low-frequency transform coefficient group is 10. As can be seen from FIG10 and FIG12, the higher the coding level of the high-frequency transform coefficient group, the lower the compression ratio of the decompressed data.

[0143] In order to obtain the best compression effect, it is necessary to conduct experiments with different compression levels. The coding levels of the low-frequency transform coefficient group are fixed at 8 and 10, and experiments with different coding levels of the high-frequency transform coefficient group are conducted respectively. When the coding level of the low-frequency transform coefficient group is 8, the test results are shown in Table 3. When the coding level of the low-frequency transform coefficient group is 10, the test results are shown in Table 4.

[0144] Table 3

[0145] Table 4

[0146] Based on the above experiments, the following experimental knowledge was obtained:

[0147] (1) In frequency division compression, as the number of high-frequency coding levels increases, the signal-to-noise ratio increases and the compression ratio decreases.

[0148] (2) Since high-frequency information has weaker energy than low-frequency information, when the number of high-frequency coding levels increases to a certain extent, the signal-to-noise ratio does not increase significantly and the compression ratio decreases. The conventional 8-level EZW coding compressed data has a signal-to-noise ratio of 30.82 and a compression ratio of 5.71. When the number of low-frequency coding levels of Hartley domain frequency division EZW compression is 8 and the number of high-frequency coding levels is 4, the compressed data has a signal-to-noise ratio of 30.94 and a compression ratio of 9.44. The conventional 10-level EZW coding compressed data has a signal-to-noise ratio of 44.67 and a compression ratio of 4.41. When the number of low-frequency coding levels of Hartley domain frequency division EZW compression is 10 and the number of high-frequency coding levels is 8, the compressed data has a signal-to-noise ratio of 45.45 and a compression ratio of 5.29. Both the signal-to-noise ratio and compression ratio of Hartley domain frequency division EZW compression are improved compared to conventional EZW compression.

[0149] In the embodiment of the present application, after respectively performing compression encoding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group, the method further includes:

[0150] The compressed data is decoded at the corresponding level to obtain the decoded data. Specifically, the quantizer corresponding to each level of coding is determined based on the iterative threshold function. The quantizer is used to indicate the number and range of quantization intervals corresponding to each level of coding. The reconstruction function is determined based on the quantizer and the threshold corresponding to each level of coding. The reconstructed value of each important transform coefficient is determined based on the reconstruction function, the coding symbol group, the auxiliary scan data, and the transform coefficient group.

[0151] Based on the number of quantization intervals and the range of the quantization intervals corresponding to each level of encoding described above, the wavelet coefficients in FIG2 are reconstructed.

[0152] For transform coefficient 63, the encoding symbol output by the first-level main scan is P, and the encoding symbol output by the first-level auxiliary scan is 1. This indicates that the coefficient is greater than the first-level encoding threshold of 32 and belongs to the last subinterval in the first-level encoding. This means that the transform coefficient has a value range of [48, 64), and the reconstruction value is T1(q+0.75)=56. In the second-level scan, the number of quantizers in the second-level auxiliary scan is 3, and T2=T1 / 2=16. The total quantization interval is [16, 64), and 63 is located in the last subinterval [56, 64) of the q=3rd quantization interval [48, 64). The reconstruction value is T2(q+0.75)=60. In the third-level scan, the number of quantizers in the third-level auxiliary scan is 7, and T3=T2 / 2=8. The total quantization interval is [8, 64), 63 is located in the next subinterval [60, 64) of the q=7th quantization interval [56, 64), and the reconstruction value is T3(q+0.75)=62; and so on, the decoded reconstruction value 63 can be finally obtained.

[0153] The decoded data are merged and then subjected to inverse Hartley transform to obtain reconstructed seismic data.

[0154] The combined data are subjected to the inverse Hartley transform as follows:

[0155] According to the above technical means, the compressed and encoded data is restored to obtain reconstructed seismic data.

[0156] In a second aspect of the present application, a pre-stack seismic data frequency division and compression device is provided, as shown in FIG13 , wherein the device comprises:

[0157] Data acquisition unit, used to acquire pre-stack seismic data,

[0158] A data transformation unit, used for performing Hartley transformation on pre-stack seismic data to obtain transformed seismic data;

[0159] A data division unit, configured to divide the transformed seismic data into low-frequency data and high-frequency data; the low-frequency data includes at least one low-frequency transformation coefficient group, and the high-frequency data includes at least one high-frequency transformation coefficient group;

[0160] a data compression unit, configured to perform compression coding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group, respectively, to obtain compressed data, wherein the compression coding level of the low-frequency transform coefficient group is greater than the compression coding level of the high-frequency transform coefficient group, and the compressed data includes target coding symbol groups at each level and auxiliary scanning data at each level;

[0161] The data compression unit comprises:

[0162] a main scanning module for performing a level-by-level coding scan on the transform coefficient group to obtain initial coding symbol groups at each level, wherein each level of coding in the level-by-level coding corresponds to a threshold value, and the initial coding symbol groups include important coding symbols and minor coding symbols; and deleting the minor coding symbols following the last important coding symbol in the initial coding symbol groups at each level to obtain target coding symbol groups at each level;

[0163] a determination module, configured to determine important transform coefficients in the transform coefficient group based on the important coding symbols in the primary coding symbol group;

[0164] The auxiliary scanning module is used to quantize each important transform coefficient in the transform coefficient group step by step according to the threshold value corresponding to each level of encoding, and output auxiliary scanning data at each level. The auxiliary scanning data includes the quantization level and quantization result of each important transform coefficient. The quantization level refers to the number of times the important transform coefficient is quantized.

[0165] According to the above technical means, the high-frequency part and the low-frequency part in the pre-stack seismic data are distinguished by Hartley transform, and then the low-frequency part and the high-frequency part are compressed and coded at different levels respectively. The low-frequency part that concentrates the main energy of the seismic data is coded at a high level to ensure the signal-to-noise ratio of the compressed data, and the high-frequency part is coded at a low level to improve the compression ratio of the data. At the same time, in the compression coding process, the secondary coding symbols after the last important coding symbol are deleted. While ensuring the integrity of the data, the amount of data after compression coding is further reduced, saving data transmission resources.

[0166] A third aspect of the present application provides a computer device, which includes a processor and a memory. The memory stores a computer program, and the computer program is loaded and executed by the processor to implement the pre-stack seismic data frequency division and compression method.

[0167] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is loaded and executed by a processor to implement the pre-stack seismic data frequency division and compression method.

[0168] The fifth aspect of the present application provides a computer program product, which includes a computer program stored in a computer-readable storage medium. A processor reads and executes the computer program from the computer-readable storage medium to implement the pre-stack seismic data frequency division and compression method.

[0169] Those skilled in the art will appreciate that all or part of the steps in the methods of the aforementioned embodiments can be accomplished by instructing the relevant hardware through a program, which is stored in a storage medium and includes a number of instructions for causing a single-chip microcomputer, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0170] The above describes in detail the optional embodiments of the present invention in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the technical concept of the embodiments of the present invention, a variety of simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the scope of protection of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner unless there is any contradiction. In order to avoid unnecessary repetition, the embodiments of the present invention will no longer describe the various possible combinations separately.

[0171] In addition, the various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed in the embodiments of the present invention.

Claims

1. A method for frequency division and compression of pre-stack seismic data, characterized in that: The method comprises: Acquire pre-stack seismic data; Perform Hartley transformation on pre-stack seismic data to obtain transformed seismic data; Dividing the transformed seismic data into low-frequency data and high-frequency data; the low-frequency data includes at least one low-frequency transformation coefficient group, and the high-frequency data includes at least one high-frequency transformation coefficient group; Performing compression coding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group respectively to obtain compressed data, wherein the compression coding level of the low-frequency transform coefficient group is greater than the compression coding level of the high-frequency transform coefficient group, and the compressed data includes target coding symbol groups at each level and auxiliary scanning data at each level; The compression coding includes: In the main scanning stage, the transformation coefficient group is scanned step by step to obtain initial coding symbol groups of each level, each level of coding in the step-by-step coding corresponds to a threshold value, and the initial coding symbol group includes important coding symbols and secondary coding symbols; the secondary coding symbols after the last important coding symbol in the initial coding symbol groups of each level are deleted to obtain target coding symbol groups of each level; Determining significant transform coefficients in the transform coefficient group based on significant coding symbols in the primary coding symbol group; In the auxiliary scanning stage, each important transform coefficient in the transform coefficient group is quantized level by level according to the threshold value corresponding to each level of coding, and auxiliary scanning data of each level is output.

2. The method for frequency division and compression of pre-stack seismic data according to claim 1, characterized in that: The transformed seismic data is divided into low-frequency data and high-frequency data, including: The transformed seismic data are divided into low-frequency data and high-frequency data according to the acquisition parameters and data quality of the seismic data.

3. The method for frequency division and compression of pre-stack seismic data according to claim 2, characterized in that: The data quality includes the Nyquist frequency, and the sampling parameters include the frequency sampling interval; According to the acquisition parameters and data quality of seismic data, the transformed seismic data is divided into low-frequency data and high-frequency data, including: The frequency range of low-frequency data and the frequency range of high-frequency data are determined by calculation according to the Nyquist frequency and the frequency sampling interval; The transformed seismic data are divided into low-frequency data and high-frequency data according to the determined frequency range.

4. The method for frequency division compression of pre-stack seismic data according to claim 3, characterized in that: The frequency range of the low-frequency data satisfies the following relationship: The frequency range of the high-frequency data satisfies the following relationship: or Among them, f1 is the low frequency, f2 is the high frequency, and f max is the Nyquist frequency, and df is the frequency sampling interval.

5. The method for frequency division and compression of pre-stack seismic data according to claim 1, characterized in that: In the main scanning stage, the transform coefficient groups are coded and scanned step by step to obtain initial coded symbol groups at each level, including: Determine a first threshold corresponding to the current level coding scan according to the iterative threshold function and the transform coefficient group; comparing the absolute value of each transform coefficient in the transform coefficient group with the first threshold; If the absolute value of the transform coefficient is greater than or equal to the first threshold, the transform coefficient is encoded as a symbol P or a symbol N; wherein the symbol P corresponds to an important transform coefficient with a positive value, and the symbol N corresponds to an important transform coefficient with a negative value, and the symbol P and the symbol N are important coding symbols; If the absolute value of the transform coefficient is less than the first threshold, the transform coefficient is encoded as symbol T or symbol Z or not encoded; wherein the symbol T and the symbol Z are secondary encoding symbols; According to the symbol P, the symbol N, the symbol T and the symbol Z, a current stage initial coding symbol group is obtained.

6. The method for frequency division and compression of pre-stack seismic data according to claim 1, characterized in that: In the auxiliary scanning stage, each important transform coefficient in the transform coefficient group is quantized level by level according to the threshold value corresponding to each level of coding, and auxiliary scanning data of each level is output, including: Determine a threshold corresponding to the current level of coding according to the iterative threshold function and the transform coefficient group; Determine a quantization interval corresponding to the current level code according to a threshold value corresponding to the current level code, wherein the quantization interval is divided into two sub-intervals; Determine the current level quantization result of each important transform coefficient according to the quantization interval corresponding to the current level coding; According to the current level quantization result of each important transform coefficient, the current level auxiliary scanning data is output.

7. The method for frequency division and compression of pre-stack seismic data according to claim 6, characterized in that: According to the quantization interval corresponding to the current level coding, the current level quantization result of each important transform coefficient is determined, including: If the important transform coefficient belongs to the previous sub-interval of the quantization interval corresponding to the encoding, the quantization result is 0; if the important transform coefficient belongs to the next sub-interval of the quantization interval corresponding to the encoding, the quantization result is 1.

8. The method for frequency division and compression of pre-stack seismic data according to claim 1, characterized in that: After respectively performing compression coding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group, the method further comprises: Decoding the compressed data in a corresponding level to obtain decoded data; The decoded data are combined and then subjected to inverse Hartley transform to obtain reconstructed seismic data.

9. A pre-stack seismic data frequency division and compression device, characterized in that: The device comprises: A data acquisition unit, used for acquiring pre-stack seismic data; A data transformation unit, used for performing Hartley transformation on pre-stack seismic data to obtain transformed seismic data; A data division unit, used to divide the transformed seismic data into low-frequency data and high-frequency data; the low-frequency data includes at least one low-frequency transformation coefficient group, and the high-frequency data includes at least one high-frequency transformation coefficient group; A data compression unit, used for performing compression coding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group respectively to obtain compressed data, wherein the compression coding level of the low-frequency transform coefficient group is greater than the compression coding level of the high-frequency transform coefficient group, and the compressed data includes target coding symbol groups of each level and auxiliary scanning data of each level; The data compression unit comprises: A main scanning module is used to perform a level-by-level coding scan on the transformation coefficient group to obtain initial coding symbol groups at each level, wherein each level of coding in the level-by-level coding corresponds to a threshold value, and the initial coding symbol group includes important coding symbols and secondary coding symbols; and to delete the secondary coding symbols after the last important coding symbol in the initial coding symbol groups at each level to obtain target coding symbol groups at each level; A determination module, configured to determine important transform coefficients in the transform coefficient group according to important coding symbols in the primary coding symbol group; The auxiliary scanning module is used to quantize each important transform coefficient in the transform coefficient group step by step according to the threshold value corresponding to each level of coding, and output auxiliary scanning data of each level.

10. A computer device, characterized in that: The computer device includes a processor and a memory, wherein a computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the pre-stack seismic data frequency division compression method according to any one of claims 1 to 8.

11. [Corrected 10.01.2025 in accordance with Rule 26] A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which is loaded and executed by a processor to implement the pre-stack seismic data frequency division compression method according to any one of claims 1 to 8.

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