Pre-stack seismic data frequency division compression method, device and equipment and storage medium

Abstract

The application provides a pre-stack seismic data frequency division compression method, device and equipment and a storage medium, and belongs to the field of oil and gas exploration. The method comprises the following steps: obtaining pre-stack seismic data; performing Hartley transformation on the 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 comprises at least one low-frequency transformation coefficient group, and the high-frequency data comprises at least one high-frequency transformation coefficient group; respectively performing compression coding of different orders on the low-frequency transformation coefficient group and the high-frequency transformation coefficient group to obtain compressed data, and the compression coding order of the low-frequency transformation coefficient group is greater than that of the high-frequency transformation coefficient group. According to the method, the high-frequency part and the low-frequency part in the pre-stack seismic data are distinguished by Hartley transformation, then the low-frequency part which concentrates the main energy of the seismic data is coded at a high order to ensure the signal-to-noise ratio of the compressed data, and the high-frequency part is coded at a low order to improve the compression ratio of the data.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of oil and gas exploration, and relates to seismic data acquisition and signal processing technology, 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

[0002] With the rapid development of oil geophysical exploration technology and the increasingly high requirement for exploration accuracy, seismic exploration instruments are moving towards multi-dimension, multi-component, multi-parameter and high resolution, and the amount of seismic exploration data is exponentially increasing. In the face of the current situation of massive data real-time recovery and channel bandwidth transmission constraints, how to improve the real-time transmission capability of massive data of the seismic exploration system is an important bottleneck problem restricting production efficiency.

[0003] Seismic data compression and reconstruction technology provides an effective way to solve this problem. Seismic data compression is a key technology for solving massive seismic data transmission and storage. Data compression can reduce data volume from the source of transmission, improve real-time processing speed of data and save storage space.

[0004] Seismic exploration data compression methods can be divided into lossless compression and lossy compression according to whether information is lost: 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, but its compression efficiency is low, and the compression multiple is generally less than 2; lossy compression can obtain high compression multiple under the condition of allowing a small amount of information loss, 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 to be solved. SUMMARY

[0006] The purpose of the embodiments of the present application is to provide a pre-stack seismic data frequency division compression method, device, equipment and storage medium. The method separates the high frequency part and the low frequency part in the pre-stack seismic data by Hartley transform, and then compresses and encodes the low frequency part and the high frequency part with different orders respectively. The low frequency part which concentrates the main energy of the seismic data is encoded with high order to ensure the signal-to-noise ratio of the compressed data, and the high frequency part is encoded with low order to improve the compression ratio of the data.

[0007] In order to achieve the above purpose, the first aspect of the present application provides a pre-stack seismic data frequency division compression method, which comprises:

[0008] acquiring pre-stack seismic data;

[0009] performing Hartley transform on the pre-stack seismic data to obtain transformed seismic data;

[0010] divide the transformed seismic data into low frequency data and high frequency data; 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;

[0011] respectively compress and encode the low frequency transform coefficient group and the high frequency transform coefficient group in different levels to obtain compressed data, the compression and encoding level of the low frequency transform coefficient group is greater than that of the high frequency transform coefficient group, and the compressed data comprises target encoding symbol groups of each level and auxiliary scanning data of each level;

[0012] the compression and encoding comprises:

[0013] in the main scanning stage, the transform coefficient group is scanned by level-by-level encoding to obtain initial encoding symbol groups of each level, each level of the level-by-level encoding corresponds to a threshold, and the initial encoding symbol groups comprise important encoding symbols and secondary encoding symbols; the secondary encoding symbols after the last important encoding symbol in the initial encoding symbol groups of each level are deleted to obtain target encoding symbol groups of each level;

[0014] determine important transform coefficients in the transform coefficient group according to the important encoding symbols in the primary encoding symbol group;

[0015] in the auxiliary scanning stage, each important transform coefficient in the transform coefficient group is quantized by level-by-level according to the threshold corresponding to each level of the encoding, and auxiliary scanning data of each level is output.

[0016] 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 in different levels. The low frequency part which concentrates the main energy of the seismic data is encoded in a high level to ensure the signal-to-noise ratio of the compressed data, and the high frequency part is encoded in a low level to improve the compression ratio of the data. At the same time, in the compression and encoding process, the secondary encoding symbols after the last important encoding symbol are deleted, which further reduces the amount of data after compression and encoding, and saves the data transmission resources while ensuring the integrity of the data.

[0017] In the embodiments of the present application, the transformed seismic data is divided into low frequency data and high frequency data, which comprises:

[0018] According to the acquisition parameters and data quality of the seismic data, the transformed seismic data is divided into low frequency data and high frequency data.

[0019] According to the above technical means, the transformed seismic data can be more accurately divided into low frequency data and high frequency data.

[0020] In the embodiment of the present application, the data quality comprises a Nyquist frequency, and the sampling parameter comprises a frequency sampling interval.

[0021] According to the acquisition parameter and the data quality of the seismic data, the transformed seismic data is divided into low-frequency data and high-frequency data, comprising:

[0022] According to the Nyquist frequency and the frequency sampling interval, the frequency range of the low-frequency data and the frequency range of the high-frequency data are determined;

[0023] According to the determined frequency range, the transformed seismic data is divided into low-frequency data and high-frequency data.

[0024] According to the above technical means, the high-frequency data and the low-frequency data are divided according to the data acquisition parameter, and the division mode is more consistent with the actual data, which is more conducive to ensuring the integrity of the data after subsequent compression.

[0025] In the embodiment of the present application, the frequency range of the low-frequency data satisfies the following relationship:

[0026]

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

[0028]

[0029] Wherein, f1 is a low-frequency frequency, f2 is a high-frequency frequency, f max is a Nyquist frequency, and df is a 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 stage, the transform coefficient array is scanned by stages to obtain a plurality of initial encoding symbol groups, comprising:

[0032] According to the iteration threshold function and the transform coefficient array, a first threshold corresponding to the current stage of encoding scanning is determined;

[0033] The absolute value of each transform coefficient in the transform coefficient array is compared with the size relationship of the first threshold;

[0034] 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 a positive important transform coefficient, the symbol N corresponds to a negative important transform coefficient, and the symbol P and the symbol N are important encoding symbols;

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

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

[0037] According to the above technical means, the transform coefficient group is converted into the initial encoding 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 step by step according to the threshold value corresponding to each level encoding, and the auxiliary scanning data of each level is output, including:

[0039] According to the iteration threshold function and the transform coefficient group, a threshold value corresponding to the current level encoding is determined;

[0040] According to the threshold value corresponding to the current level encoding, a quantization interval corresponding to the current level encoding is determined, and the quantization interval is divided into two subintervals.

[0041] According to the quantization interval corresponding to the current level encoding, a current level quantization result of each important transform coefficient is determined.

[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, according to the quantization interval corresponding to the current level encoding, the current level quantization result of each important transform coefficient is determined, including:

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

[0045] In the embodiment of the present application, after the low-frequency transform coefficient group and the high-frequency transform coefficient group are respectively compressed and encoded for different levels, the method further includes:

[0046] The compressed data is decoded for the corresponding levels to obtain decoded data.

[0047] The decoded data is merged and subjected to Hartley inverse 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] The second aspect of the present application provides a pre-stack seismic data frequency division compression device, the device comprising:

[0050] a data acquisition unit configured to acquire pre-stack seismic data;

[0051] a data transformation unit configured to perform Hartley transform on the 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 comprises at least one low-frequency transform coefficient group, and the high-frequency data comprises at least one high-frequency transform coefficient group;

[0053] a data compression unit configured to respectively perform compression encoding of different orders on the low-frequency transform coefficient group and the high-frequency transform coefficient group to obtain compressed data; the compression encoding order of the low-frequency transform coefficient group is greater than the compression encoding order of the high-frequency transform coefficient group; and the compressed data comprises target encoding symbol groups of each order and auxiliary scanning data of each order;

[0054] the data compression unit comprises:

[0055] a main scanning module configured to perform step-by-step encoding scanning on the transform coefficient group to obtain initial encoding symbol groups of each order; each step of the step-by-step encoding corresponds to a threshold value; and the initial encoding symbol groups comprise important encoding symbols and secondary encoding symbols; and the target encoding symbol groups of each order are obtained by deleting the secondary encoding symbols after the last important encoding symbol in the initial encoding symbol groups of each order;

[0056] a determination module configured to determine important transform coefficients in the transform coefficient group according to the important encoding symbols in the primary encoding symbol group;

[0057] an auxiliary scanning module configured to quantize each important transform coefficient in the transform coefficient group step by step according to the threshold value corresponding to each step of the step-by-step encoding, and output auxiliary scanning data of each order.

[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 respectively compressed and encoded with different orders. The low-frequency part, which concentrates the main energy of the seismic data, is encoded with a high order to ensure the signal-to-noise ratio of the compressed data, and the high-frequency part is encoded with a low order to improve the compression ratio of the data. At the same time, in the compression encoding process, the secondary encoding symbols after the last important encoding symbol are deleted, which further reduces the amount of data after compression encoding and saves data transmission resources while ensuring data integrity.

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

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

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

[0062] Through the above technical solution, the Hartley domain high frequency and low frequency data are encoded separately by using the EZW encoding method, since the energy of the seismic data is mainly concentrated in the low frequency part, the low frequency data has a high encoding level, which ensures the signal-to-noise ratio of the compressed data, and the high frequency data has a low encoding level, which improves the compression ratio of the data. The method can better ensure high signal-to-noise ratio and compression ratio at the same time, and is more suitable for high-precision compression of seismic data.

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

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

[0065] Figure 1 is a schematic diagram of the main scanning encoding provided by the EZW encoding method;

[0066] Figure 2 is a schematic diagram of the 8x8 wavelet coefficient array provided by the EZW encoding method;

[0067] Figure 3 is a schematic diagram of the first level main scanning encoding provided by the EZW encoding method;

[0068] Figure 4 is a schematic diagram of the second level main scanning encoding provided by the EZW encoding method;

[0069] Figure 5 is a flowchart of the pre-stack seismic data frequency division compression method provided by an embodiment of the present application;

[0070] Figure 6 is a schematic diagram of pre-stack seismic data of a Sigsbee 2A model single shot acquisition provided by an embodiment of the present application;

[0071] Figure 7 is a schematic diagram of a Hartley transform result provided by an embodiment of the present application;

[0072] Figure 8a is a schematic diagram of a low frequency data part provided by an embodiment of the present application;

[0073] Figure 8b is a schematic diagram of a high frequency data part provided by an embodiment of the present application;

[0074] Figure 9 is a schematic diagram of a comparison of signal-to-noise ratios of decompressed data of different high frequency encoding levels when the low frequency encoding level is 8 provided by an embodiment of the present application;

[0075] Figure 10 is a schematic diagram of a comparison of compression ratios of decompressed data of different high frequency encoding levels when the low frequency encoding level is 8 provided by an embodiment of the present application;

[0076] Figure 11 is a schematic diagram of a comparison of signal-to-noise ratios of decompressed data of different high frequency encoding levels when the low frequency encoding level is 10 provided by an embodiment of the present application;

[0077] Figure 12 is a schematic diagram of a comparison of compression ratios of decompressed data of different high frequency encoding levels when the low frequency encoding level is 10 provided by an embodiment of the present application;

[0078] Figure 13 is a block diagram of a pre-stack seismic data frequency division compression device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0079] The specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely intended to illustrate and explain the present application, and are not intended to limit the present application.

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

[0081] EZW algorithm: EZW is an image encoding algorithm. Its core is to perform progressive encoding and quantization in the wavelet domain. The main scan determines the sign and spatial position of important coefficients through progressive encoding; the auxiliary scan only finely quantizes the important coefficients in the main scan.

[0082] The steps of the EZW algorithm are as follows.

[0083] (1) Determining the iteration threshold formula. EZW adopts progressive quantization coding, and progressive quantization applies a series of thresholds T1, T2, …, T N to determine the importance of wavelet coefficients:

[0084]

[0085] wherein c is the wavelet coefficient, N is the maximum coding level, T i is the threshold corresponding to the i-th coding.

[0086] (2) Main scanning. Main scanning is used to determine the sign and spatial position of important coefficients, and is performed by progressive scanning for coarse quantization and by zero tree structure for improving coding efficiency. Please refer to Figure 1 , which shows a schematic diagram of main scanning coding provided by the EZW algorithm. First, the zero tree characteristic of the wavelet coefficient is utilized, and at the i-th scanning, the wavelet coefficient is marked, and when the absolute value of the wavelet coefficient is greater than T i , it is an important coefficient at the i-th scanning, and is coded as a sign P (positive important coefficient) or a sign N (negative important coefficient); otherwise, it is an unimportant coefficient. If the important coefficient is found at the i-th scanning, it will not continue to be scanned and coded at the next level. If the wavelet coefficient is an unimportant coefficient with respect to the threshold T i , and all its descendants are less than the threshold T i , then it is a 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 i in the descendants of the coefficient, it is an isolated zero value Z.

[0087] (3) Auxiliary scanning. The important coefficients (the wavelet coefficients corresponding to P and N) of the main scanning table are finely quantized. At the i-th scanning, the maximum value of the quantization interval is 2 times the initial threshold T1, and the minimum value is the current threshold T i , and the total quantization interval is [T i , 2T1), and the quantization interval is T i , so the number of quantizers at the i-th scanning is (please refer to formula 2):

[0088]

[0089] The quantizer interval is [dT i , dT i + T i ), wherein 1≤d≤Q, which is equally divided into two 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 sub-interval, the output quantization symbol is "0", otherwise the output quantization symbol is "1". The output symbols "0" and "1" are recorded by an auxiliary scan table. After determining the number of quantizers and the quantization intervals, the quantization values corresponding to "0" and "1" in each quantizer are determined. In the qthquantizer, the reconstructed value of the symbol "0" is Tq+0.25, please refer to formula 3:

[0090] T i (q+0.25) (formula 3)

[0091] The reconstructed value of the symbol "1" is Tq+0.75, please refer to formula 4:

[0092] T i (q+0.75) (formula 4)

[0093] The important coefficients coded in the previous stage are to be quantized in the next stage, and the important coefficients coded in the next stage are not to be quantized in the previous stage, so as to reduce the number of output symbols. Due to the sparsity of the wavelet coefficients, the large important coefficients are finely quantized (quantized many times), and the small important coefficients are quantized less times and occupy less bits.

[0094] Please refer to Figure 2 , which shows a schematic diagram of a 8x8 wavelet coefficient array 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 value corresponding to the first stage coding is 32, the threshold value corresponding to the second stage coding is 16, the threshold value corresponding to the third stage coding is 8, and the threshold value corresponding to the fourth stage coding is 4.

[0095] Please refer to Table 1, which shows the output symbols of the primary scan and the auxiliary scan of the wavelet coefficients shown in Figure 2 , using the EZW algorithm. In the first stage primary scan, the wavelet coefficients in Figure 2 are scanned with a threshold value of 32, and if the absolute value of the wavelet coefficient is greater than or equal to 32, the wavelet coefficient is coded as a symbol P or a symbol N, representing that it is an important wavelet coefficient, wherein if the wavelet coefficient is positive, it is coded as P, and if the wavelet coefficient is negative, it is coded as N, and if the absolute value of the wavelet coefficient is less than 32, it is coded by judging whether it is a zero-tree descendant coefficient or not.

[0096] For example, in the first level main scan, the wavelet coefficient -31 (at position 21) is not a descendant of the zero tree and there is a significant coefficient among its descendants, so it is coded as Z, which means it is an isolated zero value. For example, the wavelet coefficient 23 (at position 22) is not a descendant of the zero tree and there is no significant coefficient among its descendants, so it is coded as T, which means it is a zero tree root.

[0097] Because Figure 2 The absolute values of the wavelet coefficients 63 (at position 23), -34 (at position 24), 49 (at position 25) and 47 (at position 26) are greater than the threshold value 32 corresponding to the first level coding, so the corresponding coding in the first level main scan is P, N, P and P respectively. Please refer to Figure 3 which shows a schematic diagram of the first level main scan coding provided by an embodiment of the EZW algorithm. In the diagram, P in P1 represents the coding of the wavelet coefficient 63 in the first level main scan, and the subscript 1 means that the coding symbol corresponds to the first symbol in the first level main scan output sequence in Table 1. When the output symbol of a wavelet coefficient is T, all its descendants are no longer scanned, and are represented by "x". Figure 2 The coding symbol of 63 is coded as P, and the subscript 1 means that the coding symbol corresponds to the first symbol in the first level main scan output sequence in Table 1, and when the output symbol of a wavelet coefficient is T, all its descendants are no longer scanned, and are represented by "x".

[0098] 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 symbol of the auxiliary scan output is as follows:

[0099] (1) Determine the quantizer of 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 equally divided into two quantization subintervals [32, 48) and [48, 64).

[0100] (2) Determine the coding character of the wavelet coefficient. The wavelet coefficient 63 is in the latter subinterval [48, 64) of the interval [32, 64), so the quantization symbol of the auxiliary scan is 1 (corresponding to the first character "1" of the first level auxiliary scan output); for example, the absolute value of the wavelet coefficient -34 is in the former subinterval [32, 48) of the interval [32, 64), so the auxiliary scan coding character is 0 (corresponding to the second character "0" of the first level auxiliary scan output).

[0101] According to the above method, the coding characters of the second level main scan and auxiliary scan can be determined. In the second level main scan, with a threshold of 16, the wavelet coefficients in Figure 2 are scanned. Please refer toFigure 4 This illustrates a schematic diagram of the second-level main scan encoding provided in one embodiment of this application. Because... Figure 2 The wavelet coefficients 63, -34, 49, and 47 have already been encoded in the first-level main scan, and are used... The marker indicates that it will not be encoded in the second-level main scan.

[0102] In the second-level main scan, 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, important wavelet coefficients 63, -34, 49, and 47 from the first-level main scan and important wavelet coefficients -31 and 23 from the second-level main scan are quantized. For example, the process of determining the symbol of wavelet coefficient 63 in the auxiliary scan output is as follows:

[0103] (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, 2, or 3. The first quantizer interval is [16, 32), the second quantizer interval is [32, 48), and the third quantizer interval is [48, 64).

[0104] (2) Determine the wavelet coefficient encoding character. Wavelet coefficient 63 is located in the sub-interval [56, 64) after the third quantizer interval [48, 64), so the auxiliary scan encoding character is 1 (corresponding to the first character "1" in the output of the second-level auxiliary scan); for example, the absolute value of wavelet coefficient -34 is located in the sub-interval [32, 40) before the second quantizer interval [32, 48), so the auxiliary scan encoding character is 0 (corresponding to the second character "0" in the output of the first-level auxiliary scan).

[0105] Based on the method described above, the encoding symbols for each level of main scan and auxiliary scan can be determined. See Table 1 below.

[0106] Table 1

[0107]

[0108] By using the above method to encode wavelet coefficients step by step, the isolated zero values ​​(symbol Z) and zero roots (symbol T) of the secondary coded symbols generated at the previous level will also be re-scanned and encoded at the next level. Please refer to [reference needed]. Figure 3 31, 32 and Figure 4 At positions 41 and 42, the wavelet coefficients are encoded in both the first and second main scans. This results in an increase in the number of isolated zero values ​​and zero roots, reducing the data compression ratio and requiring more storage space.

[0109] Therefore, the application provides a pre-stack seismic data frequency division compression method, which first performs Hartley domain transformation on seismic data, and then divides low frequency part and high frequency part according to seismic data acquisition parameters and data quality. The low frequency data has high coding level, which ensures the signal-to-noise ratio of compressed data, and the high frequency data has low coding level, which improves the compression ratio of data. On this basis, the improved EZW algorithm is used to delete the secondary coding symbols after the last important coding symbol in the initial coding symbol group obtained after each main scanning is completed, so as to obtain the target coding symbol group, further reduce the data amount, save the storage space and reduce the occupation of the data transmission channel.

[0110] Figure 5 is a flow chart of a pre-stack seismic data frequency division compression method provided by an embodiment of the application. The execution subject of each step of the method can be a computer device. As shown in Figure 5 , the method comprises the following steps S1-S4.

[0111] S1: Obtain pre-stack seismic data.

[0112] In the embodiment of the application, the pre-stack seismic data refers to seismic data that has been collected and processed, but has not been subjected to seismic migration correction and stacking. It contains all the information of the seismic wave signal recorded by the seismic instrument, including the reflection and refraction characteristics of the underground medium. The pre-stack seismic data can be used for seismic imaging and underground structure interpretation, but due to the absence of migration correction, the underground interfaces located at different positions may have the phenomenon of misalignment. As shown in Figure 6 , the figure shows the pre-stack seismic data of a single shot acquisition of a Sigsbee2A model.

[0113] S2: Perform Hartley transformation on the pre-stack seismic data to obtain transformed seismic data.

[0114] The seismic data is transformed according to the following formula:

[0115]

[0116] Wherein, x(t) is seismic data, cast=cost+sint, f is frequency, t is time, and dt is the differential of time. The Hartley transformation separates the high frequency part and the low frequency part in the pre-stack seismic data, and the transformed seismic data is as shown in Figure 7 .

[0117] S3: Divide the transformed seismic data into low frequency data and high frequency data; 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.

[0118] In the embodiments of the present application, the transformed seismic data is divided into low-frequency data and high-frequency data, including:

[0119] According to the acquisition parameters and data quality of the seismic data, the transformed seismic data is divided into low-frequency data and high-frequency data.

[0120] According to the above technical means, the transformed seismic data can be more accurately divided into low-frequency data and high-frequency data.

[0121] In the embodiments of the present application, the data quality includes Nyquist frequency, and the sampling parameters include frequency sampling interval.

[0122] First, according to the acquisition parameters and data quality of the seismic data, the transformed seismic data is divided into low-frequency data and high-frequency data, including:

[0123] According to the Nyquist frequency and the frequency sampling interval, the frequency range of the low-frequency data and the frequency range of the high-frequency data are calculated and determined, and the frequency range of the low-frequency data satisfies the following relationship:

[0124]

[0125] The frequency range of the high-frequency data satisfies the following relationship:

[0126]

[0127] Wherein, f1 is the low-frequency frequency, f2 is the high-frequency frequency, f max is the Nyquist frequency, and df is the frequency sampling interval.

[0128] According to the above technical means, the transformed data can be accurately divided into high-frequency part and low-frequency part.

[0129] Then, according to the determined frequency range, the transformed seismic data is divided into low-frequency data and high-frequency data, and the frequency division result is as shown in Figure 8a and Figure 8b Figure 8a is the low-frequency data part, Figure 8b is the high-frequency data part.

[0130] According to the above technical means, the high-frequency data and the low-frequency data are divided according to the data acquisition parameters, the division mode is more consistent with the actual data, and it is more conducive to ensuring the integrity of the data after subsequent compression.

[0131] ​S4: different levels of compression encoding are performed on the low-frequency transform coefficient set and the high-frequency transform coefficient set respectively, to obtain compressed data, the compression encoding level of the low-frequency transform coefficient set is greater than that of the high-frequency transform coefficient set, and the compressed data comprises target encoding symbol groups of different levels and auxiliary scanning data of different levels. The low-frequency part 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, and the high-frequency part is encoded at a low level to improve the compression ratio of the data.

[0132] In the embodiments of the present application, the compression encoding comprises:

[0133] In the main scanning stage, the transform coefficient set is scanned and encoded level by level to obtain initial encoding symbol groups of different levels, each level of encoding corresponds to a threshold value, and the initial encoding symbol groups comprise important encoding symbols and secondary encoding symbols; the secondary encoding symbols after the last important encoding symbol in the initial encoding symbol groups of different levels are deleted to obtain target encoding symbol groups of different levels.

[0134] The level-by-level encoding process in the main scanning stage is the same as the EZW encoding process described above, and the first threshold value corresponding to the current level of encoding scanning is determined according to the iterative threshold function and the transform coefficient set. It has been described above that the threshold value corresponding to each level of encoding can be obtained through the iterative threshold function. Specifically, the threshold value corresponding to the first level of encoding is 32, the threshold value corresponding to the second level of encoding is 16, the threshold value corresponding to the third level of encoding is 8, and the threshold value corresponding to the fourth level of encoding is 4.

[0135] The absolute value of each transform coefficient in the transform coefficient set is compared with the size of the first threshold value;

[0136] If the absolute value of the transform coefficient is greater than or equal to the first threshold value, 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, the symbol N corresponds to an important transform coefficient with a negative value, and the symbol P and the symbol N are important encoding symbols;

[0137] If the absolute value of the transform coefficient is less than the first threshold value, the transform coefficient is encoded as a symbol T or a symbol Z or not encoded; wherein the transform coefficient corresponding to the symbol T is a zero tree root, the transform coefficient corresponding to the symbol Z is an isolated zero value, and the symbol T and the symbol Z are secondary encoding symbols;

[0138] According to the symbol P, the symbol N, the symbol T and the symbol Z, the initial encoding symbol groups of the current level are obtained. According to the above technical means, the transform coefficient set is converted into the initial encoding symbol groups. Then, the secondary encoding symbols after the last important encoding symbol in the initial encoding symbol groups of different levels are deleted to obtain the target encoding symbol groups of different levels. Please refer to Table 2, which shows the encoding of the transform coefficient set of the first level. Figure 2The target coded symbol group obtained by performing the main scan on the wavelet coefficients is shown in Table 2.

[0139] Table 2

[0140]

[0141] After the main scan is completed, the important transform coefficients in the transform coefficient group are determined based on the important coded symbols in the primary coded symbol group, that is, the transform coefficients corresponding to coded symbols P and N in the main scan stage. Figure 2 Taking wavelet coefficients 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... Figure 2 In section 63, we can determine the important transformation coefficients based on the P and N outputs of the main scan, and then quantize them step by step during the auxiliary scan stage.

[0142] In the auxiliary scanning phase, each important transform coefficient in the transform coefficient group is quantized step by step according to the threshold corresponding to each level of encoding, and the auxiliary scanning data at each level is output, specifically including:

[0143] The threshold corresponding to the current level encoding is determined based on the iterative threshold function and the transform coefficient set. As mentioned above, in the preceding text, we obtained... Figure 2 The threshold values ​​for each level of coding corresponding to the wavelet coefficient group are: T1 = 32, T2 = 16, T3 = 8, T4 = 4.

[0144] Based on the threshold corresponding to the current level of encoding, the quantization interval corresponding to the current level of encoding is determined, and the quantization interval is divided into two sub-intervals. The total quantization interval is [T]. i , 2T1), and the number of quantizers and the quantizer range corresponding to each level of encoding. It can be obtained that, for example, the number of quantizers for the first level of encoding is 1, and the quantizer quantization range is [32, 64), which is divided into two sub-ranges: [32, 48) and [48, 64).

[0145] For example, the second-level encoding has 3 quantizers. The first quantizer interval is [16, 32), which is divided into two sub-intervals: [16, 24) and [24, 32). The second quantizer interval is [32, 48), which is divided into two sub-intervals: [32, 40) and [40, 48). The third quantizer interval is [48, 64), which is divided into two sub-intervals: [48, 56) and [56, 64).

[0146] Based on the quantization interval corresponding to the current level of encoding, the current level quantization result of each important transform coefficient is determined: 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. Wavelet coefficient 63 is located in the next sub-interval [48, 64) of the interval [32, 64) during the first-level auxiliary scan, therefore the quantization symbol for the first-level auxiliary scan is 1. During the second-level auxiliary scan, it is located in the next sub-interval [56, 64) of the third quantizer interval [48, 64), therefore the encoded character for the second-level auxiliary scan is 1.

[0147] Based on the current level quantization result of each important transform coefficient, output the current level auxiliary scan data.

[0148] Based on the above technical means, the high-frequency and low-frequency components in the pre-stack seismic data are separated by Hartley transform. Then, the low-frequency and high-frequency components are compressed and encoded at different levels. At the same time, during the compression and encoding process, the minor encoding symbols after the last important encoding symbol are deleted. While ensuring data integrity, the amount of data after compression and encoding is further reduced, saving data transmission resources.

[0149] In this embodiment, the number of compression coding levels for the low-frequency transform coefficient group is greater than the number of compression coding levels for the high-frequency transform coefficient group. Figure 9 This paper presents a comparison of the signal-to-noise ratio (SNR) of decompressed data with different high-frequency transform coefficient group coding levels when the low-frequency transform coefficient group coding level is 8. Figure 11 This shows a comparison of the signal-to-noise ratio (SNR) of decompressed data with different high-frequency transform coefficient group coding levels when the low-frequency transform coefficient group coding level is 10. Figure 9 and Figure 11 As can be seen, the higher the coding level of the high-frequency transform coefficient group, the greater the signal-to-noise ratio of the decompressed data. Moreover, as the coding level of the high-frequency transform coefficient group increases, the impact of each additional coding level on the signal-to-noise ratio becomes smaller and smaller. Figure 10 This paper presents a comparison of the decompression ratios of data with different high-frequency transform coefficient group coding levels when the low-frequency transform coefficient group coding level is 8. Figure 12 This shows a comparison of the decompression ratio of decompressed data with different high-frequency transform coefficient group coding levels when the low-frequency transform coefficient group coding level is 10. Figure 10 and Figure 12 As can be seen, the higher the coding level of the high-frequency transform coefficient group, the lower the compression ratio of the decompressed data.

[0150] To achieve the best compression results, experiments with different compression levels are required. With the low-frequency transform coefficient group coding levels fixed at 8 and 10, experiments were conducted with different high-frequency transform coefficient group coding levels. The experimental results are shown in Table 3 when the low-frequency transform coefficient group coding level is 8, and in Table 4 when the low-frequency transform coefficient group coding level is 10.

[0151] Table 3

[0152] High frequency transform coefficient set number Signal to noise ratio Compression ratio 1 22.50 11.00 2 25.40 10.68 3 28.42 10.14 4 30.94 9.44 5 32.52 8.70 6 33.16 7.95 7 33.39 7.18 8 33.47 6.44

[0153] Table 4

[0154]

[0155]

[0156] Based on the above experiments, the following findings were obtained:

[0157] (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.

[0158] (2) Because high-frequency information has relatively weaker energy than low-frequency information, the signal-to-noise ratio (SNR) does not increase significantly when the number of high-frequency coding levels increases to a certain extent, resulting in a decrease in compression ratio. The conventional 8-level EZW coding compression data has an SNR of 30.82 and a compression ratio of 5.71. Hartley domain frequency-division EZW compression, with 8 low-frequency coding levels and 4 high-frequency coding levels, achieves an SNR of 30.94 and a compression ratio of 9.44. The conventional 10-level EZW coding compression data has an SNR of 44.67 and a compression ratio of 4.41. Hartley domain frequency-division EZW compression, with 10 low-frequency coding levels and 8 high-frequency coding levels, achieves an SNR of 45.45 and a compression ratio of 5.29. Both the SNR and compression ratio of Hartley domain frequency-division EZW compression are improved compared to conventional EZW compression.

[0159] In this embodiment of the application, after performing compression encoding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group respectively, the method further includes:

[0160] The compressed data is decoded at the corresponding number of levels to obtain the decoded data. Specifically, the quantizer corresponding to each level of encoding is determined according to the iterative threshold function. The quantizer is used to indicate the number and range of quantization intervals corresponding to each level of encoding. The reconstruction function is determined according to the quantizer and the threshold corresponding to each level of encoding. The reconstruction value of each important transform coefficient is determined according to the reconstruction function, the encoded symbol group, the auxiliary scan data, and the transform coefficient group.

[0161] Based on the number of quantization intervals and the range of quantization intervals corresponding to each level of encoding described above, for Figure 2The wavelet coefficients in the data are reconstructed.

[0162] For transform coefficient 63, its first-level main scan output encoding symbol is P, and its first-level auxiliary scan encoding is 1. Therefore, it is determined that it is greater than the first-level encoding threshold 32 and belongs to the latter sub-interval in the first-level encoding, meaning the transform coefficient's value range is [48, 64). The reconstructed 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). 63 is located in the latter sub-interval [56, 64) of the q = 3rd quantization interval [48, 64), and the reconstructed 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 sub-interval [60, 64) after the q=7th quantization interval [56, 64). The reconstructed value is T3(q+0.75)=62. Similarly, the final decoded reconstructed value 63 can be obtained.

[0163] The decoded data are merged and then subjected to an inverse Hartley transform to obtain the reconstructed seismic data.

[0164] Perform the Hartley inverse transform on the merged data using the following formula:

[0165]

[0166] Using the aforementioned technical methods, the compressed and encoded data is restored to obtain reconstructed seismic data.

[0167] A second aspect of this application provides a pre-stack seismic data frequency division compression device, such as... Figure 13 As shown, the device includes:

[0168] The data acquisition unit is used to acquire pre-stack seismic data.

[0169] The data transformation unit is used to perform Hartley transformation on pre-stack seismic data to obtain transformed seismic data.

[0170] A data partitioning unit is 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.

[0171] The data compression unit is used to perform compression coding of low-frequency transform coefficient groups and high-frequency transform coefficient groups at different levels to obtain compressed data. The compression coding 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.

[0172] The data compression unit includes:

[0173] The main scanning module is used to perform step-by-step encoding scanning on the transform coefficient group to obtain the initial encoding symbol group at each level. Each level of encoding in the step-by-step encoding corresponds to a threshold. The initial encoding symbol group includes important encoding symbols and secondary encoding symbols. The secondary encoding symbols after the last important encoding symbol in each level of the initial encoding symbol group are deleted to obtain the target encoding symbol group at each level.

[0174] The determination module is used to determine the important transform coefficients in the transform coefficient group based on the important coded symbols in the primary coded symbol group;

[0175] The auxiliary scanning module is used to quantize each important transform coefficient in the transform coefficient group step by step according to the threshold 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, and the quantization level refers to the number of times the important transform coefficient is quantized.

[0176] Based on the aforementioned technical methods, the high-frequency and low-frequency components of pre-stack seismic data are separated using Hartley transform. Then, different levels of compression coding are applied to the low-frequency and high-frequency components respectively. The low-frequency component, which concentrates the main energy of the seismic data, is encoded using high-level coding to ensure the signal-to-noise ratio of the compressed data, while the high-frequency component is encoded using low-level coding to improve the data compression ratio. At the same time, during the compression coding process, secondary coding symbols following the last important coding symbol are deleted, which further reduces the amount of data after compression coding while ensuring data integrity and saving data transmission resources.

[0177] A third aspect of this application provides a computer device, the computer device including a processor and a memory, the memory storing a computer program, the computer program being loaded and executed by the processor to implement the pre-stack seismic data frequency division compression method described above.

[0178] A fourth aspect of this application provides a computer-readable storage medium storing a computer program, which is loaded and executed by a processor to implement the pre-stack seismic data frequency division compression method.

[0179] The fifth aspect of this application provides a computer program product comprising a computer program stored in a computer-readable storage medium, wherein a processor reads from and executes the computer program to implement the pre-stack seismic data frequency division compression method.

[0180] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, 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 portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0181] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope 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 without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0182] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for frequency division compression of pre-stack seismic data, characterized in that, The method includes: Acquire pre-stack seismic data; The pre-stack seismic data were subjected to a Hartley transform to obtain the transformed seismic data. The transformed seismic data is divided 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. The low-frequency transform coefficient group and the high-frequency transform coefficient group are compressed and encoded at different levels to obtain compressed data. The compression coding 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 compression encoding includes: In the main scanning phase, the transform coefficient group is encoded and scanned step by step to obtain the initial encoded symbol group at each level. Each level of encoding in the step-by-step encoding corresponds to a threshold. The initial encoded symbol group includes important encoded symbols and secondary encoded symbols. The secondary encoded symbols following the last important encoded symbol in each level of the initial encoded symbol group are deleted to obtain the target encoded symbol group at each level. The important transform coefficients in the transform coefficient group are determined based on the important coded symbols in the primary coded symbol group; During the auxiliary scanning phase, each important transform coefficient in the transform coefficient group is quantized step by step according to the threshold corresponding to each level of encoding, and the auxiliary scanning data of each level is output.

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

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

4. The pre-stack seismic data frequency division compression method 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: Where f1 is the low-frequency frequency, f2 is the high-frequency frequency, and f max df is the Nyquist frequency and df is the frequency sampling interval.

5. The pre-stack seismic data frequency division compression method according to claim 1, characterized in that, During the main scan phase, the transform coefficient group is scanned step by step to obtain the initial coded symbol groups at each level, including: The first threshold corresponding to the current level of coding scan is determined based on the iterative threshold function and the transformation coefficient set. Compare the absolute value of each transformation coefficient in the transformation 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, the symbol N corresponds to an important transform coefficient with a negative value, and the symbol P and the symbol N are important encoded 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, symbol T and symbol Z are secondary encoded symbols; Based on the symbol P, the symbol N, the symbol T, and the symbol Z, the initial coding symbol group for the current level is obtained.

6. The pre-stack seismic data frequency division compression method according to claim 1, characterized in that, During the auxiliary scanning phase, each important transform coefficient in the transform coefficient group is quantized step by step according to the threshold corresponding to each level of encoding, and the auxiliary scanning data at each level is output, including: The threshold corresponding to the current level encoding is determined based on the iterative threshold function and the transformation coefficient set; Based on the threshold corresponding to the current level encoding, the quantization interval corresponding to the current level encoding is determined, and the quantization interval is divided into 2 sub-intervals; Based on the quantization range corresponding to the current level encoding, determine the current level quantization result for each important transform coefficient; Based on the current level quantization result of each important transform coefficient, output the current level auxiliary scan data.

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

8. The pre-stack seismic data frequency division compression method according to claim 1, characterized in that, After performing compression encoding of different levels on the low-frequency transform coefficient group and the high-frequency transform coefficient group respectively, the method further includes: The compressed data is decoded at the appropriate number of levels to obtain the decoded data; The decoded data are merged and then subjected to an inverse Hartley transform to obtain the reconstructed seismic data.

9. A pre-stack seismic data frequency division and compression device, characterized in that, The device includes: The data acquisition unit is used to acquire pre-stack seismic data. The data transformation unit is used to perform Hartley transformation on pre-stack seismic data to obtain transformed seismic data. A data partitioning unit is 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. The data compression unit is used to perform compression coding of low-frequency transform coefficient groups and high-frequency transform coefficient groups at different levels to obtain compressed data. The compression coding 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 data compression unit includes: The main scanning module is used to perform step-by-step encoding scanning on the transform coefficient group to obtain the initial encoding symbol group at each level. Each level of encoding in the step-by-step encoding corresponds to a threshold. The initial encoding symbol group includes important encoding symbols and secondary encoding symbols. The secondary encoding symbols after the last important encoding symbol in each level of the initial encoding symbol group are deleted to obtain the target encoding symbol group at each level. The determination module is used to determine the important transform coefficients in the transform coefficient group based on the important coded symbols in the primary coded 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 corresponding to each level of encoding, and output the auxiliary scanning data at each level.

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

11. 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 as described in any one of claims 1 to 8.

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