Seismic data compression methods, devices, equipment and storage media

Abstract

This application relates to the field of data compression technology, and in particular to a method, apparatus, device, and storage medium for seismic data compression. The method includes: acquiring co-offset seismic data; performing a two-dimensional DCT transform on the co-offset seismic data to obtain frequency-wavenumber domain data; processing the frequency-wavenumber domain data based on the SPECK compression algorithm to obtain primary coded data; and performing adaptive arithmetic coding on the primary coded data to obtain target compressed data. This application facilitates improved efficiency in real-time transmission and storage of seismic data.

Description

Technical Field

[0001] This application relates to the fields of oil and gas exploration and data compression technology, and in particular to a seismic data compression method, apparatus, equipment and storage medium. Background Technology

[0002] With the rapid development of petroleum geophysical exploration technology and the increasing demands for exploration accuracy, seismic exploration instruments are also moving towards multi-dimensional, multi-component, multi-parameter, and high-resolution capabilities. Consequently, the amount of seismic data generated by seismic exploration is growing exponentially. Faced with the current situation of real-time data retrieval from massive amounts of data and limitations in channel bandwidth transmission, improving the real-time transmission capability of massive data in seismic exploration systems is a significant bottleneck restricting production efficiency.

[0003] However, seismic data generated during seismic exploration needs to be transmitted and stored in real time. If the amount of seismic data is too large, the efficiency of real-time transmission and storage will be low. Since seismic exploration requires rapid real-time transmission and storage of seismic data, it is necessary to compress the seismic data immediately after it is acquired to reduce the amount of seismic data at the source, thereby improving the efficiency of real-time transmission and storage of seismic data. Summary of the Invention

[0004] To improve the efficiency of real-time transmission and storage of seismic data, this application provides a seismic data compression method, apparatus, device, and storage medium.

[0005] In a first aspect, this application provides a seismic data compression method, comprising:

[0006] Acquire co-offset seismic data;

[0007] Two-dimensional DCT transformation was performed on the co-offset seismic data to obtain frequency wavenumber domain data;

[0008] The frequency wavenumber domain data is processed using the SPECK compression algorithm to obtain primary encoded data.

[0009] The target compressed data is obtained by performing adaptive arithmetic encoding on the primary encoded data.

[0010] Secondly, this application provides a seismic data compression device, comprising:

[0011] The data acquisition module is used to acquire co-offset seismic data;

[0012] The data conversion module is used to perform a two-dimensional DCT transformation on the co-offset seismic data to obtain frequency wavenumber domain data;

[0013] The data encoding module is used to process the frequency wavenumber domain data based on the SPECK compression algorithm to obtain primary encoded data;

[0014] The data compression module is used to perform adaptive arithmetic encoding on the primary encoded data to obtain the target compressed data.

[0015] Thirdly, this application provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the method described above.

[0016] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method.

[0017] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0018] The aforementioned seismic data compression method, apparatus, equipment, and storage medium acquire co-offset seismic data; perform a two-dimensional DCT transform on the co-offset seismic data to obtain frequency-wavenumber domain data; process the frequency-wavenumber domain data based on the SPECK compression algorithm to obtain primary encoded data; and perform adaptive arithmetic encoding on the primary encoded data to obtain target compressed data. Through the above implementation, by converting the co-offset seismic data to the two-dimensional DCT domain, it is easier to subsequently encode the frequency-wavenumber domain data using the SPECK compression algorithm, thereby achieving primary compression of the co-offset seismic data. Then, adaptive arithmetic encoding is performed on the primary encoded data to achieve secondary compression of the co-offset seismic data. By performing primary and secondary compression on the co-offset seismic data, the data volume of the co-offset seismic data can be effectively reduced, thereby improving the efficiency of real-time transmission and storage of seismic data.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a seismic data compression method provided in the embodiments of this application;

[0022] Figure 2 This is a schematic diagram of a sub-band set at a first scale provided in an embodiment of this application;

[0023] Figure 3 This is a schematic diagram of a sub-band set at a second scale provided in an embodiment of this application;

[0024] Figure 4 This is a schematic diagram of a sub-band set at a third scale provided in an embodiment of this application;

[0025] Figure 5 This is a schematic diagram of the structure of a seismic data compression device provided in the embodiments of this application;

[0026] Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application;

[0027] Figure 7 This is an internal structural diagram of a computer-readable storage medium provided in an embodiment of this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this disclosure.

[0029] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings herein are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0030] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0031] Example 1

[0032] Figure 1 A flowchart of a seismic data compression method provided in Embodiment 1 of this application is shown below. Figure 1 The method can be executed by a device that performs the method, which can be implemented in software and / or hardware, and the method includes:

[0033] S110. Obtain common offset seismic data.

[0034] To obtain seismic data, shot points are typically set at predetermined locations within the exploration area, and seismic source equipment is installed at these shot points. This source equipment includes, but is not limited to, explosives. The source equipment actively generates seismic waves, which are reflected at the interfaces between different media. Geophones are also set at locations equidistant from the shot points but at different positions, and geophones are installed at these geophones to capture the reflected seismic waves, thus obtaining the seismic data corresponding to that geophone point. The distance between the geophone and the shot point is also known as the offset distance. The common offset seismic data is the collection of seismic data corresponding to each geophone point equidistant from the shot point but at different positions.

[0035] Specifically, after the shot point emits seismic waves, the corresponding seismic data are obtained from each geophone equidistant but at different locations from the shot point. The seismic data corresponding to each geophone point are then combined to obtain the common offset seismic data.

[0036] S120. Perform a two-dimensional DCT transformation on the co-offset seismic data to obtain frequency wavenumber domain data.

[0037] The co-offset seismic data is in the time-space domain, and the two-dimensional DCT transform is used to convert the time-space domain data to the two-dimensional DCT domain. The frequency-wavenumber domain data is the data obtained after transforming the co-offset seismic data using the two-dimensional DCT transform. In this embodiment, the two-dimensional DCT transform specifically adopts the Discrete Cosine Transform (DCT transform). The DCT transform is used to convert the time-space domain co-offset seismic data to the two-dimensional DCT domain, thereby obtaining the corresponding frequency-wavenumber domain data.

[0038] It should be noted that co-offset seismic data is band-limited data, while frequency wavenumber domain data is sparser than co-offset seismic data. That is, compared to co-offset seismic data, the energy of frequency wavenumber domain data is more concentrated, which makes it easier to improve the compression efficiency of frequency wavenumber domain data, thereby improving the compression efficiency of seismic data.

[0039] Specifically, a two-dimensional DCT transformation is performed on the co-offset seismic data to obtain frequency wavenumber domain data.

[0040] S130. The frequency wavenumber domain data is processed based on the SPECK compression algorithm to obtain primary encoded data.

[0041] The SPECK compression algorithm is used to compress and encode the frequency wavenumber domain data. The primary encoded data is the data obtained after compressing and encoding the frequency wavenumber domain data using the SPECK compression algorithm.

[0042] It should be noted that the SPECK compression algorithm is a lossy compression process used to compress and encode this frequency wavenumber domain data. It can achieve a high compression ratio while allowing for a small amount of information loss, thereby reducing the amount of data obtained after compressing and encoding the frequency wavenumber domain data. This makes it easier to reduce the amount of data obtained after compressing seismic data, so as to improve the efficiency of real-time transmission and storage of seismic data.

[0043] Specifically, the frequency wavenumber domain data is input into the SPECK compression algorithm for processing, and the primary encoded data is output.

[0044] S140. Adaptive arithmetic coding is performed on the primary encoded data to obtain the target compressed data.

[0045] To improve the compression efficiency and level of seismic data, further compression of the primary encoded data is required. This embodiment employs adaptive arithmetic coding to further compress the primary encoded data. Arithmetic coding treats the entire primary encoded data as an interval on a real number axis, with different data points corresponding to different sub-intervals. As different data points in the primary encoded data are processed one by one, the encoding interval continuously shrinks, eventually resulting in a unique interval representing the entire primary encoded data. Any real number within this interval can be used as the encoded output. Adaptive arithmetic coding also dynamically updates the probability of each data point in the primary encoded data during the arithmetic coding process, thereby achieving a more efficient compression coding effect. The target compressed data is the result obtained after adaptive arithmetic coding of the primary encoded data.

[0046] It should be noted that adaptive arithmetic coding can automatically adapt to the statistical characteristics of the data during the encoding process of the primary coded data without knowing the probability of each data point in the primary coded data in advance. This facilitates the further compression and encoding of the primary coded data. In addition, by continuously and accurately updating the probability of each data point in the primary coded data, adaptive arithmetic coding can more finely divide the coding interval according to the actual situation of the data, thereby achieving a higher compression ratio, enabling more efficient compression of the primary coded data in advance, and thus achieving efficient compression of seismic data.

[0047] Specifically, adaptive arithmetic encoding is performed on the primary encoded data to obtain the target compressed data.

[0048] It should be noted that this embodiment acquires co-offset seismic data; performs a two-dimensional DCT transform on the co-offset seismic data to obtain frequency-wavenumber domain data; processes the frequency-wavenumber domain data based on the SPECK compression algorithm to obtain primary encoded data; and performs adaptive arithmetic encoding on the primary encoded data to obtain target compressed data. Through the above implementation, by converting the co-offset seismic data to the two-dimensional DCT domain, it is easier to subsequently encode the frequency-wavenumber domain data using the SPECK compression algorithm, thereby achieving primary compression of the co-offset seismic data. Then, adaptive arithmetic encoding is performed on the primary encoded data to achieve secondary compression of the co-offset seismic data. By performing primary and secondary compression on the co-offset seismic data, the data volume of the co-offset seismic data can be effectively reduced, thereby improving the efficiency of real-time transmission and storage of seismic data.

[0049] It should also be noted that this application fully utilizes the sparsity of DCT domain data and the correlation of unimportant coefficients within the same subband of the SPECK compression algorithm. Unimportant coefficients are more concentrated in the high-frequency band; therefore, the SPECK compression algorithm uses zero-tree and directional tree structures to represent these unimportant coefficients, which can fully utilize the correlation of unimportant coefficients within the same subband and eliminate inter-block redundancy. This greatly improves the compression effect of seismic data.

[0050] Furthermore, the aforementioned seismic data compression method can be applied not only to the compression of co-offset seismic data, but also to the compression of shot gather data and receiver gather data. Specifically, the compression method involves replacing the co-offset seismic data in the aforementioned seismic data compression method with shot gather data and receiver gather data, which will not be elaborated further. Relatively speaking, the aforementioned seismic data compression method has the best compression effect on co-offset seismic data.

[0051] Example 2

[0052] This application provides a seismic data compression method in Embodiment 2, which optimizes the "acquiring common offset seismic data" step in Embodiment 1. It should be noted that for parts not detailed in this embodiment, please refer to the descriptions in other embodiments. The method includes:

[0053] S211. Set up a shot point and multiple receiver points at different positions, with each receiver point having the same offset distance from the shot point.

[0054] The shot point is set in a preset exploration area, which can be an oil exploration area, and the specific location is not limited. A seismic source device is set at the shot point to emit seismic waves, which will be reflected at the interface between different media. Several geophones are set around the shot point, and each geophone is equipped with a geophone so that it can detect the reflected seismic waves. The distance between the geophone and the shot point is the offset distance. In this embodiment, the offset distance between each geophone and the shot point is set to be the same. It should be noted that by making the offset distance between each geophone and the shot point consistent, the adverse effects of different offset distances on subsequent seismic data compression encoding can be eliminated.

[0055] Specifically, a shot point is set in a pre-defined exploration area, along with several geophones that are offset from the shot point but located at different positions.

[0056] S212. Obtain the seismic data detected by each of the aforementioned detector points to obtain the common offset seismic data.

[0057] Among them, the common offset seismic data is the collection of seismic data detected by each receiver point.

[0058] Specifically, the seismic data detected by each receiver point are combined to obtain common offset seismic data.

[0059] S220. Perform a two-dimensional DCT transformation on the co-offset seismic data to obtain frequency wavenumber domain data.

[0060] S230. The frequency wavenumber domain data is processed based on the SPECK compression algorithm to obtain primary encoded data.

[0061] S240. Adaptive arithmetic encoding is performed on the primary encoded data to obtain the target compressed data.

[0062] Implementation Three

[0063] This application provides a seismic data compression method in Embodiment 3, which optimizes the "processing of frequency wavenumber domain data based on the SPECK compression algorithm to obtain primary coded data" in Embodiment 1. It should be noted that for parts not detailed in this embodiment, please refer to the descriptions in other embodiments. The method includes:

[0064] S310. Obtain common offset seismic data.

[0065] S320. Perform a two-dimensional DCT transformation on the co-offset seismic data to obtain frequency wavenumber domain data.

[0066] S331. Perform wavelet transform on the frequency wavenumber domain data to obtain a multi-scale sub-band set.

[0067] Among them, wavelet transform is used to transform the frequency wavenumber domain data to obtain different frequency sub-bands, and the set of different frequency sub-bands is also called the sub-band set. In this embodiment, multi-level wavelet transform is used to transform the frequency wavenumber domain data. The sub-band set generated after each level of wavelet transform is a sub-band set at one scale. The multi-scale sub-band set is the sub-band set obtained after performing multi-level wavelet transform on the frequency wavenumber domain data.

[0068] Specifically, multi-level wavelet transforms are performed on the frequency wavenumber domain data to obtain a multi-scale sub-band set.

[0069] S332. Encode the multi-scale subband set to obtain primary encoded data.

[0070] The primary encoded data is obtained by encoding a multi-scale subband set using the SPECK compression algorithm.

[0071] S340. Adaptive arithmetic encoding is performed on the primary encoded data to obtain the target compressed data.

[0072] Example 4

[0073] This application provides a seismic data compression method in Embodiment 4, which optimizes the "encoding of the multi-scale sub-band set to obtain primary encoded data" step in Embodiment 3. It should be noted that for parts not detailed in this embodiment, please refer to the descriptions in other embodiments. The method includes:

[0074] S410, Obtain common offset seismic data.

[0075] S420. Perform a two-dimensional DCT transformation on the co-offset seismic data to obtain frequency wavenumber domain data.

[0076] S431. Perform wavelet transform on the frequency wavenumber domain data to obtain a multi-scale sub-band set.

[0077] In this embodiment, a three-level wavelet transform is specifically used. The frequency wavenumber domain data is processed using the three-level wavelet transform as follows:

[0078] Perform a first-order wavelet transform on the frequency-wavenumber domain data, such as Figure 2 As shown, the subband set at the first scale is obtained, which includes a low-frequency subband LL1 and three high-frequency subbands LH1, HL1 and HH1.

[0079] Perform a second-level wavelet transform on the low-frequency subband LL1, such as... Figure 3As shown, the subband set at the second scale is obtained. The subband set at the second scale includes three high-frequency subbands LH1, HL1 and HH1, as well as a low-frequency subband LL2 obtained by wavelet transform of the low-frequency subband LL1 and three high-frequency subbands LH2, HL2 and HH2.

[0080] Perform a third-level wavelet transform on the low-frequency subband LL2, such as... Figure 4 As shown, the subband set at the third scale is obtained. The subband set at the third scale includes six high-frequency subbands LH1, HL1, HH1, LH2, HL2 and HH2, as well as a low-frequency subband LL3 obtained by wavelet transform of the low-frequency subband LL2 and three high-frequency subbands LH3, HL3 and HH3.

[0081] The multi-scale subband set includes a target low-frequency subband and a target high-frequency subband. In this embodiment, the low-frequency subband LL3 is denoted as the target low-frequency subband S, and the set of high-frequency subbands LH1, HL1, HH1, LH2, HL2, HH2, LH3, HL3 and HH3 is taken as the target low-frequency subband I.

[0082] S432A: Encode the target low-frequency sub-band based on the initial low-frequency threshold to obtain the low-frequency coding result.

[0083] The initial low-frequency threshold is a preset value used to determine whether the target low-frequency subband contains important coefficients. It should be noted that the target low-frequency subband generally contains multiple coefficients. If the target low-frequency subband contains coefficients not less than the initial low-frequency threshold, it indicates that the target low-frequency subband contains important coefficients. If the target low-frequency subband does not contain important coefficients, it can be encoded as 0. If the target low-frequency subband contains important coefficients, it can be encoded as 1. Then, it is determined whether the target low-frequency subband contains only one coefficient. If not, the target low-frequency subband can be divided into four sub-target low-frequency subbands with the same number of coefficients. Each sub-target low-frequency subband is then used as a new target low-frequency subband, and the above encoding process is repeated until it is determined that the target low-frequency subband contains only one coefficient. The low-frequency encoding result is the encoding result obtained by encoding the target low-frequency subband.

[0084] Specifically, based on the initial low-frequency threshold, it is determined whether the target low-frequency subband contains important coefficients. If not, the target low-frequency subband is encoded as 0; if yes, it is encoded as 1. Then, it is determined whether the target low-frequency subband contains only one coefficient. If yes, the encoding of the target low-frequency subband ends; if not, the target low-frequency subband is split into four sub-target low-frequency subbands with the same number of coefficients. Each sub-target low-frequency subband is then used as a new target low-frequency subband, and the above encoding process is repeated until it is determined that the target low-frequency subband contains only one coefficient. By executing the above encoding process for the target low-frequency subband, the encoding result is obtained.

[0085] S432B: Encode the target high-frequency subband based on the initial high-frequency threshold to obtain the high-frequency coding result.

[0086] The initial high-frequency threshold is a preset value used to compare with the coefficients in the target high-frequency subband I. The target high-frequency subband I contains multiple coefficients. If there is a coefficient that is not less than the initial high-frequency threshold, it indicates that the target high-frequency subband I contains important coefficients. Therefore, the initial high-frequency threshold can be used to determine whether the target high-frequency subband I contains important coefficients. If it is determined that the target high-frequency subband I does not contain important coefficients, the target high-frequency subband I can be encoded as 0. Otherwise, the target high-frequency subband I is encoded as 1, and the target high-frequency subband I is split into 1 sub-target high-frequency subband and 3 sub-target low-frequency subbands. Then, the 3 sub-target low-frequency subbands are used as new target low-frequency subbands S, and the encoding continues according to the process shown in S632A. The aforementioned 1 sub-target high-frequency subband is used as a new target high-frequency subband I, and the new target high-frequency subband I is encoded according to the above encoding process for the target high-frequency subband I until the new target high-frequency subband I is empty. The high-frequency encoding result is the encoding result obtained by performing the above encoding process for the target high-frequency subband I.

[0087] Specifically, based on the initial high-frequency threshold, it is determined whether the target high-frequency subband I contains an important coefficient; if not, the target high-frequency subband I is encoded as 0; if so, the target high-frequency subband I is encoded as 1, and the target high-frequency subband I is split into 1 sub-target high-frequency subband and 3 sub-target low-frequency subbands; then, the 3 sub-target low-frequency subbands are respectively used as new target low-frequency subbands S, and the encoding continues according to the process shown in S632A; the aforementioned 1 sub-target high-frequency subband is used as a new target high-frequency subband I, and the new target high-frequency subband I is encoded according to the above encoding process for target high-frequency subband I, until the new target high-frequency subband I is empty; by executing the above encoding process for target high-frequency subband I, the high-frequency encoding result is obtained.

[0088] S432C: Primary encoded data is obtained based on the low-frequency encoding result and the high-frequency encoding result.

[0089] The primary coding data includes low-frequency coding results and high-frequency coding results.

[0090] S440. Adaptive arithmetic encoding is performed on the primary encoded data to obtain the target compressed data.

[0091] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0092] Example 5

[0093] Based on the same inventive concept, this embodiment also provides a seismic data compression apparatus for implementing the seismic data compression method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more seismic data compression apparatus embodiments provided below can be found in the limitations of the seismic data compression method described above, and will not be repeated here.

[0094] In this embodiment, as Figure 5 As shown, a seismic data compression device is provided, comprising:

[0095] The data acquisition module is used to acquire co-offset seismic data;

[0096] The data conversion module is used to perform a two-dimensional DCT transformation on the co-offset seismic data to obtain frequency wavenumber domain data;

[0097] The data encoding module is used to process the frequency wavenumber domain data based on the SPECK compression algorithm to obtain primary encoded data;

[0098] The data compression module is used to perform adaptive arithmetic encoding on the primary encoded data to obtain the target compressed data.

[0099] Each module in the aforementioned seismic data compression device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0100] It should be noted that this embodiment acquires co-offset seismic data; performs a two-dimensional DCT transform on the co-offset seismic data to obtain frequency-wavenumber domain data; processes the frequency-wavenumber domain data based on the SPECK compression algorithm to obtain primary encoded data; and performs adaptive arithmetic encoding on the primary encoded data to obtain target compressed data. Through the above implementation, by converting the co-offset seismic data to the two-dimensional DCT domain, it is easier to subsequently encode the frequency-wavenumber domain data using the SPECK compression algorithm, thereby achieving primary compression of the co-offset seismic data. Then, adaptive arithmetic encoding is performed on the primary encoded data to achieve secondary compression of the co-offset seismic data. By performing primary and secondary compression on the co-offset seismic data, the data volume of the co-offset seismic data can be effectively reduced, thereby improving the efficiency of real-time transmission and storage of seismic data.

[0101] In one embodiment, in acquiring co-offset seismic data, the data acquisition module is specifically configured to: set a shot point and multiple receiver points at different locations, wherein the offset distance between each receiver point and the shot point is consistent; and acquire the seismic data detected by each receiver point to obtain the co-offset seismic data.

[0102] In one embodiment, in obtaining the co-offset seismic data by acquiring the seismic data detected by each of the geophones, the data acquisition module is specifically configured to: acquire the seismic wavelet emitted by the shot point detected by the geophone, and the reflection coefficient corresponding to the seismic wavelet; calculate the convolution of the seismic wavelet and the reflection coefficient to obtain the seismic data corresponding to the geophone; and aggregate the seismic data corresponding to each of the geophones to obtain the co-offset seismic data.

[0103] In one embodiment, in obtaining frequency wavenumber domain data by performing a two-dimensional DCT transformation on the co-offset seismic data, the data conversion module is specifically used to: perform a DCT transformation on the co-offset seismic data to obtain frequency wavenumber domain data.

[0104] In one embodiment, in processing the frequency wavenumber domain data based on the SPECK compression algorithm to obtain primary encoded data, the data encoding module is specifically used for: performing wavelet transform on the frequency wavenumber domain data to obtain a multi-scale sub-band set; and encoding the multi-scale sub-band set to obtain primary encoded data.

[0105] In one embodiment, the multi-scale subband set includes a target low-frequency subband and a target high-frequency subband; the data encoding module for encoding the multi-scale subband set to obtain primary encoded data is specifically used for: encoding the low-frequency subband based on an initial low-frequency threshold to obtain a low-frequency encoding result; encoding the target high-frequency subband based on an initial high-frequency threshold to obtain a high-frequency encoding result; and obtaining primary encoded data based on the low-frequency encoding result and the high-frequency encoding result.

[0106] In one embodiment, the data acquisition module includes:

[0107] A shot detector setting unit is used to set the shot point and multiple detectors at different positions, with each detector having the same offset distance from the shot point.

[0108] The data acquisition unit is used to acquire the seismic data detected by each of the receiver points to obtain the common offset seismic data.

[0109] In one embodiment, the data encoding module includes:

[0110] The data transformation unit is used to perform wavelet transform on the frequency wavenumber domain data to obtain a multi-scale sub-band set.

[0111] The set coding unit is used to encode the multi-scale sub-band set to obtain primary coded data.

[0112] Example 6

[0113] In this embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows. Figure 6 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a seismic data compression method.

[0114] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the computer device to which the present disclosure is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0115] Example 7

[0116] In this embodiment, a computer-readable storage medium is provided, such as... Figure 7 As shown, a computer program is stored thereon, and when the computer program is executed by the processor, it implements the steps in the above-described method embodiments.

[0117] Example 8

[0118] In this embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0119] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0120] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this disclosure can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this disclosure may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this disclosure may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0121] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0122] The embodiments described above are merely illustrative of several implementations of this disclosure, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent disclosure. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this disclosure, and these all fall within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the appended claims.

Claims

1. A seismic data compression method, characterized in that, include: Acquire co-offset seismic data; Two-dimensional DCT transformation was performed on the co-offset seismic data to obtain frequency wavenumber domain data; The frequency wavenumber domain data is processed using the SPECK compression algorithm to obtain primary encoded data. The target compressed data is obtained by performing adaptive arithmetic encoding on the primary encoded data.

2. The method according to claim 1, characterized in that, The acquisition of common offset seismic data includes: A shot point and multiple receiver points at different locations are set up, with each receiver point having the same offset distance from the shot point. The common offset seismic data are obtained by acquiring the seismic data detected by each of the aforementioned receiver points.

3. The method according to claim 1, characterized in that, The process of processing the frequency wavenumber domain data using the SPECK compression algorithm to obtain primary encoded data includes: Wavelet transform is performed on the frequency wavenumber domain data to obtain a multi-scale subband set; The multi-scale subband set is encoded to obtain primary encoded data.

4. The method according to claim 3, characterized in that, The multi-scale subband set includes a target low-frequency subband and a target high-frequency subband; encoding the multi-scale subband set to obtain primary encoded data includes: The low-frequency sub-band is encoded based on the initial low-frequency threshold to obtain the low-frequency encoding result. The target high-frequency sub-band is encoded based on an initial high-frequency threshold to obtain a high-frequency coding result; Primary encoded data is obtained based on the low-frequency encoding results and the high-frequency encoding results.

5. A seismic data compression device, characterized in that, The device includes: The data acquisition module is used to acquire co-offset seismic data; The data conversion module is used to perform a two-dimensional DCT transformation on the co-offset seismic data to obtain frequency wavenumber domain data; The data encoding module is used to process the frequency wavenumber domain data based on the SPECK compression algorithm to obtain primary encoded data; The data compression module is used to perform adaptive arithmetic encoding on the primary encoded data to obtain the target compressed data.

6. The apparatus according to claim 5, characterized in that, The data acquisition module includes: A shot detector setting unit is used to set the shot point and multiple detectors at different positions, with each detector having the same offset distance from the shot point. The data acquisition unit is used to acquire the seismic data detected by each of the receiver points to obtain the common offset seismic data.

7. The apparatus according to claim 5, characterized in that, The data encoding module includes: The data transformation unit is used to perform wavelet transform on the frequency wavenumber domain data to obtain a multi-scale sub-band set. The set coding unit is used to encode the multi-scale sub-band set to obtain primary coded data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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