Seismic data storage method, reading method, storage device, and reading device

Abstract

The application discloses a seismic data storage method, a reading method, a storage device and a reading device, wherein the storage method comprises the following steps: determining a precision mode used for storing seismic data according to user demand; determining metadata used for describing the seismic data according to the precision mode; wherein the metadata comprises a global scale factor, a precision level factor, a sampling point number factor and a data format factor; determining a storage format of the seismic data according to the precision mode; wherein the number of bits occupied by the mantissa of the storage format corresponding to each precision mode is different; writing the metadata into the header of a seismic data file; and writing the seismic data into a seismic trace set of the seismic data file according to the storage format. The storage method can not only reduce the consumption of storage space, but also ensure the integrity and accuracy of the seismic data within the precision requirement range.

Description

Technical Field

[0001] This invention relates to the field of seismic exploration, and more specifically to a seismic data storage method, storage device, seismic data reading method, reading device, and computing equipment. Background Technology

[0002] Seismic exploration data is typically massive, with a single work area potentially containing hundreds of terabytes of data. Traditional seismic data storage uses standardized data storage formats, such as SEGY (Standard for the Exchange of Geophysical Data), which includes information such as sample values, timestamps, and sampling rates. However, the SEGY format offers limited control over data precision, making it difficult to meet the flexible precision requirements of different application scenarios. With the development of seismic exploration technology, the demand for storing massive amounts of seismic data is gradually increasing, and the need for storage at varying precisions is becoming increasingly important. Therefore, how to effectively control the storage precision of seismic data while ensuring storage efficiency and data recovery accuracy has become an urgent problem to be solved.

[0003] While existing technologies offer methods to compress or optimize the accuracy of seismic data, they generally suffer from difficulties in balancing accuracy and storage efficiency, and limitations in data recovery accuracy. Therefore, there is an urgent need for a method that can optimize storage space and improve storage efficiency while meeting storage accuracy requirements. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed to provide an earthquake data storage method, storage device, earthquake data reading method, and reading device that overcome or at least partially solve the above problems.

[0005] According to one aspect of the present invention, an earthquake data storage method includes the following steps:

[0006] Determine the accuracy mode for storing seismic data based on user needs;

[0007] Based on the accuracy mode, determine the metadata used to describe the seismic data; the metadata includes: global scaling factor, accuracy level factor, number of sampling points factor, and data format factor;

[0008] The storage format of seismic data is determined based on the precision mode; the number of bits occupied by the mantissa is different for each precision mode.

[0009] Metadata is written to the header of the seismic data file, and seismic data is written to the seismic trace set of the seismic data file according to the storage format.

[0010] Optionally, the global scaling factor represents the scaling factor used to scale the maximum amplitude value of the seismic data to the mantissa of the corresponding accuracy level; the accuracy level factor is used to describe the data accuracy of the seismic data; the sampling point number factor is used to describe the number of sampling points for each seismic data trace; and the data format factor is used to describe the floating-point recording format of the seismic data.

[0011] Optionally, determining the storage format of seismic data according to the precision mode further includes: determining the number of bits occupied by the sign bit, exponent bit, and mantissa bit of the seismic data according to the precision mode.

[0012] Optionally, the sign bit occupies 1 bit, the exponent bit occupies 3 bits, and the number of bits occupied by the mantissa bit is determined based on the precision mode.

[0013] Optionally, the earthquake data file is a SEGY file, wherein preset bytes for recording metadata are added to the header of the SEGY file.

[0014] According to another aspect of the present invention, a seismic data reading method is provided, which is implemented by the above-described seismic data storage method; the seismic data reading method includes the following steps:

[0015] Read metadata from the header of the seismic data file, and read seismic data from the seismic trace set of the seismic data file;

[0016] Based on the metadata, the seismic data is processed to obtain the processed seismic data.

[0017] Optionally, data processing is performed according to the following formula:

[0018] sign*integers*10^exponent*scalar_global

[0019] Where sign is the data recorded in the sign bit, integers is the data recorded in the mantissa bit, exponent is the data recorded in the exponent bit, and scalar_global is the global scaling factor.

[0020] According to another aspect of the present invention, an earthquake data storage device is provided, comprising:

[0021] The accuracy selection module is used to determine the accuracy mode for storing seismic data according to user needs;

[0022] The metadata acquisition module is used to determine the metadata used to describe the seismic data based on the accuracy mode; the metadata includes: global scaling factor, accuracy level factor, number of sampling points factor, and data format factor;

[0023] The storage format processing module is used to determine the storage format of seismic data according to the precision mode; wherein, the number of bits occupied by the mantissa of the storage format is different for each precision mode.

[0024] The data writing module is used to write metadata into the header of the seismic data file, and, according to the storage format, write the seismic data into the seismic trace set of the seismic data file.

[0025] According to yet another aspect of the present invention, a seismic data reading device is provided, which is implemented based on the above-described seismic data storage device; the seismic data reading device includes:

[0026] The data reading module is used to read metadata from the header of the seismic data file and to read seismic data from the seismic trace set of the seismic data file.

[0027] The data processing module is used to process earthquake data based on metadata to obtain processed earthquake data.

[0028] According to the earthquake data storage method, storage device, and earthquake data reading method and reading device of the present invention, the following steps are taken: First, a precision mode for storing earthquake data is determined based on user requirements. Second, metadata for describing the earthquake data is determined based on the precision mode. The metadata includes a global scaling factor, a precision level factor, a sampling point number factor, and a data format factor. Third, the storage format of the earthquake data is determined based on the precision mode. The number of bits occupied by the mantissa of the storage format varies for each precision mode. Fourth, the metadata is written to the header of the earthquake data file, and the earthquake data is written to the seismic trace set of the earthquake data file according to the storage format. Fifth, the metadata is read from the header of the earthquake data file, and the earthquake data is read from the seismic trace set of the earthquake data file. Sixth, the earthquake data is processed based on the metadata to obtain processed earthquake data. The earthquake data storage and reading methods of this application not only precisely control the precision of each stored earthquake data point to meet the needs of different application scenarios, but also allow for precision adjustment and reduce bit occupancy, significantly reducing data storage space consumption. Furthermore, they are compatible with existing earthquake data formats (such as SEGY) and support flexible conversion to existing earthquake data formats.

[0029] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0030] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0031] Figure 1 A schematic flowchart of an earthquake data storage method according to an embodiment of the present invention is shown;

[0032] Figure 2 A schematic diagram of a seismic data format according to an embodiment of the present invention is shown;

[0033] Figure 3 A schematic diagram of a seismic trace in a seismic data format according to an embodiment of the present invention is shown;

[0034] Figure 4 A schematic diagram illustrating different precision modes of existing seismic data storage formats and embodiments of the present invention is shown.

[0035] Figure 5 A flowchart illustrating a seismic data reading method according to an embodiment of the present invention is shown;

[0036] Figure 6 A schematic diagram of the structure of an earthquake data storage device according to an embodiment of the present invention is shown;

[0037] Figure 7 A schematic diagram of the structure of a seismic data reading device according to an embodiment of the present invention is shown; and

[0038] Figure 8 A schematic diagram of the structure of a computing device according to an embodiment of the invention is shown. Detailed Implementation

[0039] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0040] Figure 1 A flowchart illustrating an earthquake data storage method according to an embodiment of the present invention is shown, as follows: Figure 1 As shown, the earthquake data storage method of this invention includes the following steps:

[0041] Step S110: Determine the accuracy mode for storing seismic data based on user requirements.

[0042] Specifically, users can determine the precision mode for storing seismic data based on the required precision. Different precision modes can meet different precision requirements. For example, different precision modes are represented as P1-PN, where N is a positive integer, meaning there are N precision modes (precision requirements) available for the user to choose from. P1 indicates that the seismic data to be stored retains two significant digits, P2 indicates that the seismic data to be stored retains three significant digits, and so on. PN indicates that the seismic data to be stored retains N+1 significant digits. When selecting a precision mode, the larger N is, the higher the precision requirement of the seismic data to be stored, and the larger the storage space required. Conversely, the smaller N is, the lower the precision requirement of the seismic data to be stored, and the smaller the storage space required. Users can comprehensively consider the required precision mode based on the required precision requirements and storage space.

[0043] Table 1 illustrates the relationship between precision mode, precision requirements, and storage space through a specific example (taking N equals 5). As shown in Table 1, the lower the precision mode selected by the user, i.e., the lower the precision requirement, the greater the storage space saved; conversely, the higher the precision mode selected by the user, i.e., the higher the precision requirement, the smaller the storage space saved.

[0044] In this embodiment, five precision modes are described based on the characteristics of seismic data and the needs of actual seismic data processing. In existing technologies, the ratio of the maximum to minimum recordable value in the standard SEGY float32 record reaches 10^83, which is significantly redundant for seismic data. Firstly, the dynamic range of existing seismic data acquisition instruments is generally 120 dB, corresponding to a difference of 10^6, or one million times, between the maximum and minimum recordable amplitude values. Precision mode P5 in this embodiment already fully meets the precision requirements of the original seismic data record, so there is no need to increase the number of bits for data characterization. Other precision modes can be selected according to user needs. Generally, simple quality control using precision mode P1 for data storage is sufficient. For routine data processing, selecting precision modes P2 and P3 for data storage generally meets user requirements. Specific limitations and selections of precision modes can be adjusted by the user according to specific circumstances and are not limited here. Determining the precision mode for storing seismic data according to user needs not only reduces storage space consumption but also ensures the integrity and accuracy of the seismic data within the required precision range.

[0045] Table 1

[0046]

[0047]

[0048] Step S120: Determine the metadata used to describe the seismic data according to the accuracy mode; wherein the metadata includes: global scaling factor, accuracy level factor, number of sampling points factor, and data format factor.

[0049] Figure 2 A schematic diagram of a seismic data format according to an embodiment of the present invention is shown. For example... Figure 2 As shown, in the seismic data format of this embodiment, based on the existing general seismic data storage format (SEGY), metadata, an EBCDIC header, and a binary header are added to the header of the seismic data, followed by the data information of each seismic trace. Specifically, the metadata is used to describe the seismic data; preferably, the metadata occupies 60 bytes; the EBCDIC header is used to describe the basic information of the seismic data, and it is located at the very beginning of the seismic data, used to describe the basic information and descriptions of the seismic data in a user-readable format, such as acquisition parameters, processing history, and file descriptions; and the binary header is used to describe some basic parameters and key information of the entire seismic data. Preferably, the EBCDIC header occupies 3200 bytes and the binary header occupies 400 bytes, and the number of bytes occupied by the EBCDIC header and the binary header is consistent with the number of bytes occupied by the EBCDIC header and the binary header of the existing data storage format SEGY, so as to facilitate reading the seismic data stored by the storage method of this embodiment and support flexible conversion with SEGY.

[0050] In an embodiment of the present invention, the global scaling factor represents the scaling factor used to scale the maximum amplitude value of the seismic data to the mantissa of the corresponding precision level; the precision level is used to describe the data precision of the seismic data; the sampling point number factor is used to describe the number of sampling points for each seismic data trace; and the data format factor is used to describe the floating-point recording format of the seismic data. Specifically, the global scaling factor (scalar_global) describes the amplitude magnitude of the global seismic data, scaling the maximum amplitude value to a certain number of positive integers corresponding to the precision level. For example, when the user selects precision mode P1, two significant digits (counting from left to right starting from non-zero values) will be retained when storing the corresponding seismic data. When storing seismic data in precision mode P1, the maximum data error is 0.5%. The precision level describes the precision of the seismic data in OCSEGY (the seismic data format used in this embodiment's storage method). When converting back to SEGY format, the corresponding data configuration information can be selected according to the precision level to correctly read the data, achieving flexible conversion between OCSEGY and SEGY. The number of sampling points (samples) describes the number of sampling points for each seismic trace to facilitate data reading of the seismic data stored according to the seismic data storage method of this embodiment. The data format factor (dataFormat) describes the floating-point recording format of the seismic data, where "1" represents IBM floating-point and "5" represents IEEE floating-point data.

[0051] Specifically, Figure 3 A schematic diagram of a seismic trace in a seismic data format according to an embodiment of the present invention is shown. Figure 3 As shown, each trace includes a trace header and float32 (SEGY) data of the corresponding sampling points. The trace header is used to describe the information of the seismic data in that trace. Preferably, the number of bytes occupied by the trace header in this embodiment is consistent with the number of bytes occupied by the trace header in SEGY format, which is 240 bytes.

[0052] Step S130: Determine the storage format of the seismic data according to the precision mode; wherein, the number of bits occupied by the mantissa of the storage format is different for each precision mode.

[0053] Specifically, determining the storage format of seismic data according to the precision mode further includes: determining the number of bits occupied by the sign bit, exponent bit, and mantissa bit of the seismic data, based on the precision mode. Further, based on each seismic data (such as...) Figure 3The Trace Data in the data is redesigned and encoded at the bit level. Different mantissa bits are set for different accuracy levels to represent the data, so as to save storage space while meeting the accuracy requirements and realize controllable accuracy seismic data storage.

[0054] Table 2 shows the bit occupancy table for the five precision levels of seismic data when storing seismic data using the data storage method of this embodiment. As shown in Table 2, it illustrates the correspondence between precision level, precision, number of significant bits to retain, positive integer range, number of bits occupied by positive integers, total number of bits, and storage space saved in this embodiment. In this embodiment, 32-bit floating-point data is normalized to pure integers. For any precision level selected, the sign bit occupies 1 bit, the exponent bit occupies 3 bits, and the number of bits occupied by the mantissa is determined based on the precision mode. A sign bit of 1 indicates that the stored seismic data is negative, and a sign bit of 0 indicates that the stored seismic data is zero or positive, denoted as sign.

[0055] Table 2

[0056]

[0057]

[0058] Since the dynamic range of the aforementioned seismic data acquisition instruments is generally 120 dB, the difference between the maximum and minimum recordable amplitude values ​​is 10^6. The calculated maximum exponent is 6. Since 3 bits can represent numbers from 0 to 7, 3 exponent bits are sufficient to accurately represent the magnitude of all seismic data. Therefore, in the seismic data format of this embodiment, the exponent occupies 3 bits, representing the magnitude of the energy difference between the absolute value of the current seismic data and the global maximum amplitude value in the current seismic trace set. The specific calculation method is as follows:

[0059] exponent=log(|sample| / max_amplitude)

[0060] Where |sample| represents the absolute value of the current seismic data, and max_amplitude represents the global maximum amplitude value in the previous seismic trace set.

[0061] Figure 4 This diagram illustrates different precision modes of the seismic data storage format according to an embodiment of the present invention. The mantissa, also known as the integer bits, such as... Figure 4As shown, depending on the precision mode selected by the user, the integer bits M of the five precision modes P1 to P5 occupy 7, 10, 14, 17, and 20 bits respectively, representing the 2, 3, 4, 5, and 6 significant digits of each sampling point, denoted as integers. This achieves seismic data format and storage under controllable precision. Based on storing seismic data using the five precision modes P1, P2, P3, P4, and P5, the corresponding percentage savings in storage space compared to existing technologies are 65.6%, 56.3%, 43.8%, 34.4%, and 25.0%, respectively.

[0062] In this embodiment, the seismic data file is a SEGY file. Preset bytes for recording metadata are added to the header of the SEGY file. The metadata includes information such as global scaling factor, accuracy level factor, number of sampling points factor, and data format factor. Preferably, the metadata occupies 60 bytes.

[0063] Step S140: Write metadata to the header of the seismic data file, and write seismic data to the seismic trace set of the seismic data file according to the storage format.

[0064] Specifically, the global scaling factor, accuracy level factor, number of sampling points factor, and data format factor of the metadata are written into the header of the seismic data file, and the seismic data is written into the seismic trace set of the seismic data file according to the storage format, thus completing the storage of the seismic data.

[0065] Figure 5 A schematic flowchart of a seismic data reading method according to an embodiment of the present invention is shown. The seismic data reading method is implemented based on the above-described seismic data storage method. The seismic data reading method includes the following steps S210-S220.

[0066] S210 reads metadata from the header of the seismic data file and reads seismic data from the seismic trace set of the seismic data file.

[0067] Specifically, the metadata includes information such as the global scaling factor, accuracy level factor, number of sampling points factor, and data format factor.

[0068] S220: Based on the metadata, the seismic data is processed to obtain the processed seismic data.

[0069] Specifically, the seismic data stored using the seismic data storage method of this application will be read based on the global scaling factor, accuracy level factor, number of sampling points factor, and data format factor; data processing of the seismic data based on metadata can be seen in the specific examples below.

[0070] In one alternative implementation, data processing is performed according to the following formula:

[0071] sign*integers*10^exponent*scalar_global

[0072] Where sign is the data recorded in the sign bit, integers is the data recorded in the mantissa bit, exponent is the data recorded in the exponent bit, and scalar_global is the global scaling factor.

[0073] The earthquake data storage and retrieval methods of this application embodiment are described below using earthquake data 0.00052376 as an example.

[0074] Assume the user chooses to store the above seismic data using accuracy level P1, and assume the global maximum value in this seismic trace set is 0.897654;

[0075] Integer digits: The integer digits are the two significant digits to be retained, which should be 52.3 rounded to the nearest integer, resulting in 52.

[0076] Global scaling factor: This is the scaling factor that scales the global maximum value to two integers. It's essentially a global scaling factor, reducing 0.897654 to 89.7654. Here it's 10^-2, meaning all data is scaled down by 10^-2, and when restoring the data, it's scaled up by 10^-2.

[0077] Sign bit: Since 0.00052376 is greater than zero, the sign bit is represented by 0;

[0078] Exponent: Assuming the global maximum value in this seismic trace set is 0.897654, based on the formula exponent = log(|sample| / max_amplitude), which represents the order of magnitude difference between the current data and the assumed global maximum value, we know that the exponent is -3. Based on the formula sign*integers*10^exponent*scalar global, we can derive 1*52*10^(-3)*10^(-2)=0.00052.

[0079] Assume the user chooses to store the above seismic data using accuracy level P2, and assume the global maximum value in this seismic trace set is 0.897654;

[0080] Integer digits: The integer digits are the three significant digits to be retained. For example, 523.7 rounded to the nearest integer is 524.

[0081] Global scaling factor: This is a scaling factor that scales the global maximum value to two integers. It's essentially a global scaling factor, reducing 0.897654 to 897.654. ​​Here it's 10^-3, meaning all data is scaled down by 10^-3, and when restoring the data, it's scaled up by 10^-3.

[0082] Sign bit: Since 0.00052376 is greater than zero, the sign bit is represented by 0;

[0083] Exponent: Assuming the global maximum value in this seismic trace set is 0.897654, based on exponent = log(|sample| / max_amplitude), which represents the order of magnitude difference between the current data and the assumed global maximum value, we know that the exponent is -3. Based on the formula sign*integers*10^exponent*scalar global, we can derive 1*524*10^(-3)*10^-3=0.000524.

[0084] The earthquake data storage and retrieval methods of this application embodiment are described below using earthquake data -0.84654321 as an example.

[0085] Assume the user chooses to store the above seismic data using accuracy level P1, and assume the global maximum value in this seismic trace set is 12345.6;

[0086] Integer digits: The integer digits are the two significant digits to be retained, which should be 84.6 rounded to the nearest integer, resulting in 85.

[0087] Global scaling factor: This is the scaling factor that scales the global maximum value to two integers. It's essentially a global scaling factor that reduces 12345.6 to 12.3456. Here it's 10^3, meaning all data is scaled down by 10^3, and when restoring the data, it's scaled up by 10^3.

[0088] Sign bit: Since -0.84654321 is less than zero, the sign bit is represented by 1;

[0089] Exponent: Assuming the global maximum value in this seismic trace set is 12345.6, based on exponent = log(|sample| / max_amplitude), which represents the order of magnitude difference between the current data and the assumed global maximum value, we know that the exponent is -5. Based on the formula sign*integers*10^exponent*scalar global, we can derive -85*10^(-5)*10^3=-0.85.

[0090] Assume the user chooses to store the above seismic data using accuracy level P2, and assume the global maximum value in this seismic trace set is 12345.6;

[0091] Integer digits: The integer digits are the three significant digits to be retained. For example, 846.5 rounded to the nearest integer is 847.

[0092] Global scaling factor: This is a scaling factor that scales the global maximum value to two integers. In other words, it's a global scaling factor that reduces 12345.6 to 123.456. Here it's 10^2, meaning all data is scaled down by 10^2, and when restoring the data, it's scaled up by 10^2.

[0093] Sign bit: Since -0.84654321 is less than zero, the sign bit is represented by 1;

[0094] Exponent: Assuming the global maximum value in this seismic trace set is 12345.6, based on exponent = log(|sample| / max_amplitude), which represents the order of magnitude difference between the current data and the assumed global maximum value, we know that the exponent is -5. Based on the formula sign*integers*10^exponent*scalar global, we can derive -847*10^(-5)*10^2=-0.847.

[0095] The above examples are merely illustrative of the earthquake data storage and retrieval methods of this embodiment and do not limit the earthquake data storage and retrieval methods of this embodiment. Based on the above examples, it can be seen that controlling the accuracy of earthquake data according to user needs significantly saves storage space while meeting user requirements, and different accuracy modes can meet the needs of different application scenarios.

[0096] The earthquake data storage and retrieval method according to this embodiment can not only precisely control the accuracy of each stored sampling point to meet the needs of different application scenarios, but also significantly reduce the space consumption of data storage by adjusting the accuracy and reducing the bit occupancy. It is also compatible with existing earthquake data formats (such as SEGY) and supports flexible conversion with existing earthquake data formats.

[0097] Figure 6 A schematic diagram of the structure of an earthquake data storage device according to an embodiment of the present invention is shown. Figure 6 As shown, the earthquake data storage device 300 includes:

[0098] Precision selection modulus 310 is used to determine the precision mode for storing seismic data based on user needs.

[0099] The metadata acquisition module 320 is used to determine the metadata used to describe the seismic data according to the accuracy mode; wherein the metadata includes: global scaling factor, accuracy level factor, sampling point number factor and data format factor.

[0100] The storage format processing module 330 is used to determine the storage format of the seismic data according to the precision mode; wherein the number of bits occupied by the mantissa of the storage format corresponding to each precision mode is different.

[0101] The data writing module 340 is used to write metadata to the header of the seismic data file, and to write seismic data to the seismic trace set of the seismic data file according to the storage format.

[0102] In one alternative implementation, the global scaling factor represents a scaling factor used to scale the maximum amplitude value of the seismic data to the mantissa of the corresponding precision level; the precision level describes the data precision of the seismic data; the sampling point factor describes the number of sampling points for each seismic data trace; and the data format factor describes the floating-point recording format of the seismic data.

[0103] In an alternative implementation, the storage format processing module 330 is further adapted to: determine the number of bits occupied by the sign bit, exponent bit, and mantissa bit of the seismic data according to the precision mode.

[0104] In one alternative implementation, the sign bit occupies 1 bit, the exponent bit occupies 3 bits, and the number of bits occupied by the mantissa bit is determined based on the precision mode.

[0105] In one alternative implementation, the seismic data file is a SEGY file, wherein preset bytes for recording metadata are added to the header of the SEGY file.

[0106] Figure 7 A schematic diagram of a seismic data reading device according to an embodiment of the present invention is shown. Figure 7 The seismic data reading device 400 shown is implemented based on the aforementioned seismic data storage device 300; the seismic data reading device 400 includes:

[0107] The data reading module 410 is used to read metadata from the header of the seismic data file, and to read seismic data from the seismic trace set of the seismic data file.

[0108] The data processing module 420 is used to process the seismic data based on the metadata to obtain the processed seismic data.

[0109] In one alternative implementation, data processing is performed according to the following formula:

[0110] sign*integers*10^exponent*scalar_global

[0111] Where sign is the data recorded in the sign bit, integers is the data recorded in the mantissa bit, exponent is the data recorded in the exponent bit, and scalar_global is the global scaling factor.

[0112] The seismic data storage device and reading device according to this embodiment can not only accurately control the accuracy of each stored sampling point to meet the needs of different application scenarios, but also significantly reduce the space consumption of data storage by adjusting the accuracy and reducing the bit occupancy. It is also compatible with existing seismic data formats (such as SEGY) and supports flexible conversion with existing seismic data formats.

[0113] Figure 8 The diagram illustrates a structural schematic of a computing device according to an embodiment of the present invention. The specific embodiments of the present invention do not limit the specific implementation of the computing device.

[0114] like Figure 8 As shown, the computing device may include: a processor 802, a communications interface 804, a memory 806, and a communications bus 808.

[0115] The processor 802, communication interface 804, and memory 806 communicate with each other via communication bus 808. Communication interface 804 is used to communicate with other network elements such as clients or other servers. The processor 802 executes program 810, specifically performing the relevant steps in the embodiments of the above-described earthquake data storage method or earthquake data reading method.

[0116] Specifically, program 810 may include program code that includes computer operation instructions.

[0117] Processor 802 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The computing device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0118] Memory 806 is used to store program 810. Memory 806 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0119] Specifically, program 810 can be used to cause processor 802 to execute the relevant steps in the embodiments of the above-described earthquake data storage method or earthquake data reading method.

[0120] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0121] Similarly, it should be understood that, in order to simplify the invention and aid in understanding one or more of the various inventive aspects, features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the above description of exemplary embodiments of the invention. However, this disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, wherein each claim itself is a separate embodiment of the invention.

[0122] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0123] Furthermore, those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0124] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A method for storing seismic data, characterized in that, Includes the following steps: Determine the accuracy mode for storing seismic data based on user needs; Based on the accuracy mode, metadata for describing the seismic data is determined; wherein, the metadata includes: a global scaling factor, an accuracy level factor, a sampling point number factor, and a data format factor; the global scaling factor represents a scaling factor used to scale the maximum amplitude value of the seismic data to the mantissa of the corresponding accuracy level; the accuracy level factor is used to describe the data accuracy of the seismic data; the sampling point number factor is used to describe the number of sampling points for each seismic trace; and the data format factor is used to describe the floating-point recording format of the seismic data. The storage format of the seismic data is determined according to the precision mode; wherein the number of bits occupied by the mantissa is different for each precision mode. The metadata is written to the header of the seismic data file, and the seismic data is written to the seismic trace set of the seismic data file according to the storage format.

2. The method according to claim 1, characterized in that, Determining the storage format of the seismic data based on the accuracy mode further includes: Based on the precision mode, determine the number of bits occupied by the sign bit, exponent bit, and mantissa bit of the seismic data.

3. The method according to claim 2, characterized in that, The sign bit occupies 1 bit, the exponent bit occupies 3 bits, and the number of bits occupied by the mantissa bit is determined based on the precision mode.

4. The method according to claim 1, characterized in that, The earthquake data file is a SEGY file, wherein preset bytes for recording the metadata are added to the header of the SEGY file.

5. A method for reading seismic data, characterized in that, The earthquake data reading method is implemented based on the earthquake data storage method according to any one of claims 1-4; the earthquake data reading method includes the following steps: The metadata is read from the header of the earthquake data file, and earthquake data is read from the seismic trace set of the earthquake data file; Based on the metadata, the seismic data is processed to obtain processed seismic data.

6. The method according to claim 5, wherein the data processing is performed according to the following formula: sign integers 10^exponent scalar_global in, `sign` is the data recorded in the sign bit, `integers` is the data recorded in the mantissa bit, `exponent` is the data recorded in the exponent bit, and `scalar_global` is the global scaling factor.

7. A seismic data storage device, characterized in that, include: The accuracy selection module is used to determine the accuracy mode for storing seismic data according to user needs; The metadata acquisition module is used to determine metadata describing the seismic data based on the accuracy mode; wherein the metadata includes: a global scaling factor, an accuracy level factor, a sampling point number factor, and a data format factor; the global scaling factor represents a scaling factor used to scale the maximum amplitude value of the seismic data to the mantissa of the corresponding accuracy level; the accuracy level factor is used to describe the data accuracy of the seismic data; the sampling point number factor is used to describe the number of sampling points for each seismic trace; and the data format factor is used to describe the floating-point recording format of the seismic data. The storage format processing module is used to determine the storage format of the seismic data according to the precision mode; wherein, the number of bits occupied by the mantissa of the storage format is different for each precision mode. The data writing module is used to write the metadata into the header of the seismic data file, and to write the seismic data into the seismic trace set of the seismic data file according to the storage format.

8. A seismic data reading device, characterized in that, The earthquake data reading device is implemented based on the earthquake data storage device of claim 7; The seismic data reading device includes: The data reading module is used to read the metadata from the header of the seismic data file and to read seismic data from the seismic trace set of the seismic data file. The data processing module is used to process the seismic data according to the metadata to obtain processed seismic data.

9. A computing device, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform an operation corresponding to the seismic data storage method as described in any one of claims 1-4, or to perform an operation corresponding to the seismic data reading method as described in claim 5.

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