A multi-thread-based OBN data fast segmentation method and device

Abstract

This application provides a method and apparatus for rapid OBN data segmentation based on multithreading. Its core lies in utilizing multithreaded processing technology to handle the massive data volumes in marine seismic exploration. Multithreaded processing significantly improves data processing speed, effectively solving the challenges of large data volumes and high processing difficulty in OBN technology, and significantly shortening the data processing cycle. Secondly, a refined data allocation strategy ensures balanced load across processing devices, avoiding resource idleness or overload, further improving processing efficiency. Thirdly, precise matching of shot point and receiver point information not only improves the positioning accuracy of seismic wave data but also enhances data reliability and application value. Finally, the highly automated and intelligent characteristics of this scheme reduce the cost of manual intervention, providing solid technical support for efficient and accurate marine seismic exploration operations.

Description

Technical Field

[0001] This application relates to the field of marine seismic exploration technology, and in particular to a method and apparatus for rapid OBN data segmentation based on multi-threading. Background Technology

[0002] In the field of marine seismic exploration, with continuous technological advancements, Ocean Bottom Node (OBN) technology is increasingly favored for its efficient and flexible data acquisition capabilities. OBN technology achieves flexible deployment without cable constraints by deploying multi-component seismometers on the seabed capable of autonomously acquiring and recording seismic signals, significantly improving the positioning accuracy and acquisition quality of seismic wave data. This technology utilizes a blind acquisition method, autonomously recording seismic wave signals without relying on pre-set cable connections, thereby greatly enriching the amount and coverage of seismic wave data acquired.

[0003] However, the blind acquisition nature of OBN technology also brings significant data processing challenges. Due to the rapid increase in seismic wave data volume under blind acquisition, traditional data segmentation and quality control methods are inadequate when dealing with such large and complex datasets. Data segmentation, as a crucial step in seismic wave data processing, directly impacts subsequent data analysis and interpretation. Traditional methods, when processing large-scale OBN data, often fail to meet the actual needs of scientific research and production due to slow processing speed and low efficiency, thus affecting the accuracy and overall efficiency of seismic exploration. Summary of the Invention

[0004] The purpose of this application is to provide a method and apparatus for fast OBN data splitting based on multi-threading, which can improve the above-mentioned problems.

[0005] The embodiments of this application are implemented as follows:

[0006] Firstly, this application provides a method for fast OBN data splitting based on multi-threading, which includes steps S1 to S4; wherein, S1, S2, etc. are only step identifiers, and the execution order of the method does not necessarily follow the order of numbers from smallest to largest. For example, step S2 can be executed first and then step S1 can be executed. This application does not impose any restrictions.

[0007] S1, Obtain the shot point information table and receiver point information table of the marine seismic exploration system;

[0008] S2, receiving seismic wave data collected by each OBN in the marine seismic exploration system;

[0009] S3, add the shot point information and / or receiver point information that match the seismic wave data to the shot point information table and / or the receiver point information table, and update the seismic wave data;

[0010] S4, all the updated seismic wave data are aggregated into a data set, and all data sets are distributed to at least two data processing devices for synchronous processing according to a preset strategy, and the common receiver point gather data corresponding to each OBN are output.

[0011] This application provides a multi-threaded method for rapid OBN data segmentation, the core of which lies in using multi-threaded processing technology to handle the massive data volume in marine seismic exploration. The method first integrates shot point and receiver point information, then receives and updates seismic wave data acquired by the OBN. Crucially, it utilizes multi-threaded parallel processing of this data, employing an intelligent allocation strategy to efficiently distribute data blocks to multiple processing devices, achieving synchronous and rapid processing, and ultimately generating common receiver point gather data for each OBN. Multi-threaded processing significantly improves data processing speed, effectively solving the challenges of large data volume and high processing difficulty in OBN technology, and significantly shortening the data processing cycle. Secondly, the refined data allocation strategy ensures balanced load across processing devices, avoiding resource idleness or overload, further improving processing efficiency. Thirdly, accurate matching of shot point and receiver point information not only improves the positioning accuracy of seismic wave data but also enhances data reliability and application value. Finally, the highly automated and intelligent characteristics of this solution reduce the cost of manual intervention, providing solid technical support for efficient and accurate marine seismic exploration operations.

[0012] In optional embodiments of this application, the shot point information table includes at least one of the following: shot point identifier; shot point location; firing time; shot point type; the receiver point information table includes at least one of the following: OBN identifier; OBN location; OBN deployment time; OBN retrieval time; OBN working status.

[0013] In optional embodiments of this application, the method of obtaining the shot point information table includes at least one of the following: obtaining the shot point information table compiled during the design phase of the marine seismic exploration system; and creating and / or supplementing the shot point information table by means of detection information for each shot point.

[0014] In optional embodiments of this application, the method of obtaining the receiving point information table includes at least one of the following: obtaining the receiving point information table compiled during the design phase of the marine seismic exploration system; or creating and / or supplementing the receiving point information table based on feedback information from each OBN on-site.

[0015] In an optional embodiment of this application, step S3 includes:

[0016] S31, Extract shot point association information and receiver point association information from the seismic wave data;

[0017] S32, Traverse the shot point information table and search for shot point information that matches the shot point association information;

[0018] S33, Traverse the receiving point information table and search for receiving point information that matches the receiving point association information;

[0019] S34, the found shot point information and receiver point information are added to and the seismic wave data is updated.

[0020] In an optional embodiment of this application, the shot point association information includes timestamp information; the receiver point association information includes at least one of the following: OBN identifier; OBN location.

[0021] As can be understood, in step S3, this method meticulously extracts shot point association information and receiver point association information from the seismic wave data and matches them with the shot point information table and receiver point information table, respectively, ensuring that each piece of seismic wave data can be accurately associated with a specific shot point and receiver point. This precise matching not only provides accurate spatial and temporal location for subsequent analysis of the seismic wave data but also greatly improves the interpretability of the data. Because the information of the shot point and receiver point is accurately recorded and integrated into the seismic wave data, the reliability and application value of the data are significantly enhanced.

[0022] In optional embodiments of this application, the preset strategy includes at least one of the following.

[0023] Strategy 1: Calculate the parameter ratios of the computational parameters of each data processing device, divide the total data set into at least two data blocks according to the parameter ratios, and allocate each data block to the corresponding data processing device for synchronous processing. It can be understood that by accurately calculating the ratios of key parameters such as processor performance and memory performance of each data processing device, this strategy can intelligently divide the total data set into data blocks that match the processing capabilities of each device. This dynamic allocation method based on device performance ensures that each data processing device can operate in its optimal state, avoiding resource waste or overload, thereby significantly improving the overall efficiency and speed of data processing.

[0024] Strategy 2: The data in the aggregate dataset is divided into multiple data units, and each data unit is allocated to at least one data unit in multiple batches, ensuring that the time difference between the computations completed by each data processing device is less than a first threshold. It can be understood that by subdividing the aggregate dataset into multiple data units and dynamically allocating data units in multiple batches based on the real-time processing progress of each data processing device, this strategy ensures a balanced load on each device in terms of processing tasks. In particular, by monitoring the amount of unprocessed data in real time and accurately allocating subsequent data accordingly, the processing time difference between devices is kept within a small range, effectively avoiding processing delays or bottlenecks caused by uneven task allocation. This highly flexible and dynamic allocation mechanism not only improves the continuity and stability of data processing but also further enhances the robustness and reliability of the entire data processing flow.

[0025] In optional embodiments of this application, the calculation parameters include at least one of the following: processor performance parameters corresponding to the data processing device; memory performance parameters corresponding to the data processing device.

[0026] In an optional embodiment of this application, the step of dividing the data in the data set into multiple data units and allocating each data unit to at least one data unit in multiple batches, so that the difference in the time taken for each data processing device to complete the calculation is less than a first threshold, includes: dividing the data in the data set into multiple data units, initially allocating the data units to each data processing device, monitoring the amount of unprocessed data in each data processing device in real time, and allocating the data units to at least one data unit in multiple batches, so that the difference in the amount of unprocessed data in each data processing device is less than a second preset threshold.

[0027] In optional embodiments of this application, the common detector point gather data includes at least one of the following:

[0028] The OBN identifier of the OBN;

[0029] The OBN location;

[0030] The seismic wave data collected by the OBN;

[0031] The shot point identifiers corresponding to the seismic wave data collected by the OBN;

[0032] The shot point location corresponding to the seismic wave data collected by the OBN;

[0033] The excitation time corresponding to the seismic wave data collected by the OBN.

[0034] Secondly, this application discloses a multi-threaded OBN data fast splitting device, including a processor and a memory, the processor and the memory being interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to call the program instructions to execute the method as described in any of the first aspects.

[0035] Beneficial effects:

[0036] This application provides a method and apparatus for rapid OBN data segmentation based on multithreading. Its core lies in utilizing multithreaded processing technology to handle the massive data volumes in marine seismic exploration. Multithreaded processing significantly improves data processing speed, effectively solving the challenges of large data volumes and high processing difficulty in OBN technology, and significantly shortening the data processing cycle. Secondly, a refined data allocation strategy ensures balanced load across processing devices, avoiding resource idleness or overload, further improving processing efficiency. Thirdly, precise matching of shot point and receiver point information not only improves the positioning accuracy of seismic wave data but also enhances data reliability and application value. Finally, the highly automated and intelligent characteristics of this scheme reduce the cost of manual intervention, providing solid technical support for efficient and accurate marine seismic exploration operations.

[0037] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, optional embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of this application, 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 this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of a fast OBN data splitting method based on multithreading provided in this application;

[0040] Figure 2 This is a schematic diagram illustrating an application scenario of a multi-threaded OBN data fast splitting device provided in this application. Detailed Implementation

[0041] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0042] Firstly, such as Figure 1 As shown, this application provides a method for fast OBN data splitting based on multi-threading, which includes steps S1 to S4; wherein, S1, S2, etc. are only step identifiers, and the execution order of the method does not necessarily follow the order of numbers from smallest to largest. For example, step S2 can be executed first and then step S1 can be executed. This application does not impose any restrictions.

[0043] S1, obtain the shot point information table and receiver point information table of the marine seismic exploration system.

[0044] like Figure 2 As shown, the aforementioned marine seismic exploration system includes multiple shot points located on the sea surface, multiple OBNs laid on the seabed, an OBN data rapid segmentation device, and multiple data processing devices. Figure 2 In this context, m, n, and q are all positive integers greater than 1. A shot point is a device, such as a source vessel, used to generate seismic waves. The source vessel is equipped with source equipment like air guns to generate seismic waves, which penetrate the seabed strata and reflect back at different geological interfaces. Furthermore, shot points can be configured with communication modules to transmit shot point information to the OBN data rapid segmentation device in real time. OBNs are deployed at predetermined locations on the seabed using underwater robots or specialized deployment systems to receive these reflected seismic wave signals. Because OBN nodes have multi-component acquisition capabilities, they can simultaneously record multiple components of seismic waves, such as P-waves and S-waves. OBNs are typically equipped with high-precision positioning systems to ensure accurate location. Additionally, OBNs can be configured with communication modules to transmit receiving point information to the OBN data rapid segmentation device in real time. This OBN data rapid segmentation device executes steps S1 to S4 to efficiently distribute the acquired data blocks to multiple processing devices, achieving synchronous and rapid processing, and outputting the final common-detector point gather data corresponding to each OBN.

[0045] In optional embodiments of this application, the Shot Information Table (SIT) includes at least one of the following: shot identifier; shot location; firing time; shot type.

[0046] In optional embodiments of this application, the method of obtaining the Receiver Information Table (RIT) includes at least one of the following: obtaining the Receiver Information Table compiled during the design phase of the marine seismic exploration system; or creating and / or supplementing the Receiver Information Table by means of detection information for each Receiver Information Table.

[0047] It is understandable that obtaining the shot point information table is a crucial step in marine seismic exploration, as its accuracy and completeness directly affect the efficiency and quality of subsequent data processing. Besides the fundamental method of compiling the shot point information table during the design phase, various other methods can be used to acquire and supplement shot point information during actual operations. For example, detailed firing parameters, including shot point location, firing time, and shot point type, can be recorded simultaneously during shot point firing. This information is transmitted in real-time to the OBN data rapid segmentation device and integrated into the shot point information table. Furthermore, advanced positioning technologies and monitoring equipment can be used to track and monitor shot points in real time, thereby obtaining more accurate shot point location information. During operations, if any missing or incorrect shot point information is found, it should be promptly supplemented or corrected, and the shot point information table updated to ensure data completeness and accuracy.

[0048] In optional embodiments of this application, the receiving point information table includes at least one of the following: OBN identifier; OBN location; OBN deployment time; OBN retrieval time; OBN working status.

[0049] In optional embodiments of this application, the method of obtaining the receiver point information table includes at least one of the following: obtaining the receiver point information table compiled during the design phase of the marine seismic exploration system; or creating and / or supplementing the receiver point information table based on feedback information from each OBN on-site.

[0050] It is understandable that obtaining the receiver point information table plays a crucial role in marine seismic exploration, directly impacting the accurate positioning of seismic wave data and the effectiveness of subsequent processing. Besides compiling the receiver point information table based on the pre-set locations of the OBN during the design phase, receiver point information can be acquired and updated through various means during actual operations. For example, after the OBN is deployed, its built-in high-precision positioning system can acquire its current location information in real time and transmit this information to the OBN data rapid segmentation device via a communication module, thereby dynamically updating the receiver point information table. Furthermore, during operations, if the OBN moves or its status changes—such as minor displacement due to water currents or seabed topography, or changes in its working state due to battery power or storage space limitations—the OBN can upload this information in real time for timely adjustment and updating of the receiver point information table. These methods ensure the accuracy and real-time nature of the receiver point information table, providing a reliable foundation for subsequent data processing.

[0051] S2 receives seismic wave data collected by each OBN in the marine seismic exploration system.

[0052] The "seismic wave data" in step S2 refers to the seismic wave signal data received by the OBN (Onshore Surface No. 3) on the seabed and reflected back from the strata. This data contains various information about the seismic waves during their underground propagation, such as propagation time, amplitude, frequency, and phase, and is crucial for subsequent geological interpretation and oil and gas exploration. For example, when seismic waves encounter different geological interfaces, reflection and refraction occur, and the OBN records these reflected and refracted wave signals, forming seismic wave data. This data not only reflects the structure and properties of the underground strata but also contains information about geological targets such as oil and gas reservoirs.

[0053] In step S2, the OBN data rapid segmentation device receives seismic wave data from each OBN in real time. This data is typically transmitted in digital signal form and includes OBN identification information to accurately distinguish data acquired from different OBNs during subsequent processing. During reception, the device ensures data integrity and accuracy, preventing data loss or errors. By receiving seismic wave data in real time, a timely and reliable information foundation can be provided for subsequent data processing and analysis, thereby effectively improving the efficiency and accuracy of marine seismic exploration.

[0054] S3, add the shot point information and / or receiver point information that match the seismic wave data to the shot point information table and / or receiver point information table, and update the seismic wave data.

[0055] S4: All updated seismic wave data are aggregated into a data set. According to the preset strategy, all data sets are distributed to at least two data processing devices for synchronous processing, and the common receiver point gather data corresponding to each OBN is output.

[0056] This application provides a multi-threaded method for rapid OBN data segmentation, the core of which lies in using multi-threaded processing technology to handle the massive data volume in marine seismic exploration. The method first integrates shot point and receiver point information, then receives and updates seismic wave data acquired by the OBN. Crucially, it utilizes multi-threaded parallel processing of this data, employing an intelligent allocation strategy to efficiently distribute data blocks to multiple processing devices, achieving synchronous and rapid processing, and ultimately generating common receiver point gather data for each OBN. Multi-threaded processing significantly improves data processing speed, effectively solving the challenges of large data volume and high processing difficulty in OBN technology, and significantly shortening the data processing cycle. Secondly, the refined data allocation strategy ensures balanced load across processing devices, avoiding resource idleness or overload, further improving processing efficiency. Thirdly, accurate matching of shot point and receiver point information not only improves the positioning accuracy of seismic wave data but also enhances data reliability and application value. Finally, the highly automated and intelligent characteristics of this solution reduce the cost of manual intervention, providing solid technical support for efficient and accurate marine seismic exploration operations.

[0057] In an optional embodiment of this application, step S3 includes steps S31 to S34.

[0058] S31, extract shot point association information and receiver point association information from seismic wave data.

[0059] In optional embodiments of this application, the shot point association information includes timestamp information; the receiver point association information includes at least one of the following: OBN identifier; OBN location.

[0060] S32, traverse the shot point information table and search for shot point information that matches the shot point association information.

[0061] In step S32, the system parses the shot point association information in the seismic wave data, mainly extracting the timestamp information, which records the precise time of seismic wave excitation. Subsequently, the system iterates through the pre-acquired shot point information table, which records detailed shot point information for each excitation, including shot point identifier, shot point location, excitation time, and shot point type.

[0062] The matching process is primarily based on timestamp information. The system compares the timestamps in the seismic wave data with the excitation times in the shot point information table to find the correspondence between the two. For example, if a timestamp in the seismic wave data is exactly the same as or very close to the excitation time of a shot point in the shot point information table (considering possible transmission delays or time synchronization errors), then the system considers this seismic wave data to be associated with this shot point, thereby extracting the corresponding shot point information, such as shot point location and shot point type, for subsequent processing.

[0063] Through this matching method, the system can accurately correspond each seismic wave data point to the shot point that generated it, providing accurate shot point location information for subsequent data analysis, imaging, and interpretation, thereby improving the accuracy and reliability of seismic exploration.

[0064] S33, Traverse the receiver point information table and search for receiver point information that matches the receiver point association information.

[0065] In step S33, the system parses the receiver point association information in the seismic wave data, mainly extracting information such as OBN identifiers and / or OBN locations. This information records the identity and location of the OBN node receiving the seismic wave signal.

[0066] Subsequently, the system will traverse the pre-acquired receiving point information table, which records detailed information about each OBN node, including OBN identifier, OBN location, deployment time, recycling time, and OBN working status.

[0067] The matching process is primarily based on OBN identifiers and / or OBN location information. The system compares the OBN identifiers or location information in the seismic wave data with records in the receiver point information table to find the correspondence between them. For example, if the OBN identifier in the seismic wave data is exactly the same as a certain OBN identifier in the receiver point information table, or if the OBN location in the seismic wave data is very close to a certain OBN location in the receiver point information table (considering possible positioning errors), then the system will assume that this seismic wave data was received by this OBN, and thus extract the corresponding receiver point information, such as the OBN's deployment time and working status.

[0068] This matching method allows the system to accurately associate each seismic wave data point with its corresponding OBN (On-Board Number), providing precise receiver location and operational status information for subsequent data processing, imaging, and interpretation, thereby further improving the accuracy and reliability of seismic exploration. It also facilitates subsequent OBN data management and maintenance.

[0069] S34: Add the found shot point information and receiver point information to the seismic wave data and update it.

[0070] As can be understood, in step S3, this method meticulously extracts shot point association information and receiver point association information from the seismic wave data and matches them with the shot point information table and receiver point information table, respectively, ensuring that each piece of seismic wave data can be accurately associated with a specific shot point and receiver point. This precise matching not only provides accurate spatial and temporal location for subsequent analysis of the seismic wave data but also greatly improves the interpretability of the data. Because the information of the shot point and receiver point is accurately recorded and integrated into the seismic wave data, the reliability and application value of the data are significantly enhanced.

[0071] In optional embodiments of this application, the preset strategy includes the following strategy 1 and / or strategy 2.

[0072] Strategy 1: Calculate the parameter ratio of the computational parameters of each data processing device, divide the data set into at least two data blocks according to the parameter ratio, and assign each data block to the corresponding data processing device for synchronous processing.

[0073] In optional embodiments of this application, the calculation parameters include at least one of the following: processor performance parameters corresponding to the data processing device; and memory performance parameters corresponding to the data processing device. The processor performance parameters include processor clock speed, number of processor cores, and processor cache size, etc.; the memory performance parameters include memory capacity and memory frequency, etc.

[0074] It is understandable that by accurately calculating the ratios of key parameters such as processor performance and memory performance of each data processing device, this strategy can intelligently divide the total data set into data blocks that match the processing capabilities of each device. This dynamic allocation method based on device performance ensures that each data processing device can operate in its optimal state, avoiding resource waste or overload, thereby significantly improving the overall efficiency and speed of data processing.

[0075] Strategy 2: Divide the data in the dataset into multiple data units and distribute them to each data unit in multiple batches, so that the time difference between the calculations completed by each data processing device is less than the first threshold.

[0076] In an optional embodiment of this application, the data in the total data set is divided into multiple data units, and each data unit is allocated to at least one data unit in multiple batches, so that the difference in the time taken for each data processing device to complete the calculation is less than a first threshold. This includes: dividing the data in the total data set into multiple data units, initially allocating data units to each data processing device, monitoring the amount of unprocessed data in each data processing device in real time, and allocating data units to each data unit in multiple batches to at least one data unit, so that the difference in the amount of unprocessed data in each data processing device is less than a second preset threshold.

[0077] It is understandable that by subdividing the total data set into multiple data units and dynamically allocating these units in batches based on the real-time processing progress of each data processing device, this strategy ensures a balanced workload across all devices. In particular, by monitoring the amount of unprocessed data in real time and accurately allocating subsequent data accordingly, the processing time differences between devices are kept within a small range, effectively avoiding processing delays or bottlenecks caused by uneven task allocation. This highly flexible and dynamic allocation mechanism not only improves the continuity and stability of data processing but also further enhances the robustness and reliability of the entire data processing workflow.

[0078] In optional embodiments of this application, the common detector point gather data includes at least one of the following:

[0079] The OBN identifier;

[0080] The OBN position;

[0081] Seismic wave data acquired by OBN;

[0082] The shot point identifiers corresponding to the seismic wave data acquired by OBN;

[0083] The shot point locations corresponding to the seismic wave data acquired by OBN;

[0084] The excitation time corresponding to the seismic wave data collected by OBN.

[0085] Secondly, this application provides a multi-threaded OBN data fast partitioning device. The multi-threaded OBN data fast partitioning device includes one or more processors and a memory. The processors and memory are connected via a bus. The memory stores a computer program, which includes program instructions, and the processor executes the program instructions stored in the memory. The processor is configured to invoke the program instructions to perform the operation of any of the methods in the first aspect:

[0086] It should be understood that, in the embodiments of the present invention, the processor may be a Central Processing Unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0087] The memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store information about the device type.

[0088] In specific implementations, the processor, input device, and output device described in the embodiments of the present invention can execute the implementation method described in any of the methods in the first aspect, or can execute the implementation method of the terminal device described in the embodiments of the present invention, which will not be repeated here.

[0089] Thirdly, the present invention provides a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, implement the steps of any of the methods of the first aspect.

[0090] The aforementioned computer-readable storage medium can be an internal storage unit of the terminal device in any of the foregoing embodiments, such as a hard disk or memory of the terminal device. The aforementioned computer-readable storage medium can also be an external storage device of the terminal device, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the terminal device. Furthermore, the aforementioned computer-readable storage medium may include both internal storage units and external storage devices of the terminal device. The aforementioned computer-readable storage medium is used to store the aforementioned computer program and other programs and data required by the terminal device. The aforementioned computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0091] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed terminal devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, or it may be an electrical, mechanical or other form of connection.

[0093] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0094] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0095] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0096] The terms "first," "second," "first," or "second" as used in the various embodiments of this disclosure may modify various components regardless of their order and / or importance, but these terms do not limit the corresponding components. The above terms are configured only for the purpose of distinguishing an element from other elements. For example, "first user equipment" and "second user equipment" refer to different user equipments, although both are user equipment. For example, without departing from the scope of this disclosure, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.

[0097] When a component (e.g., a first component) is referred to as being "(operably or communicatively) coupled" or "(operably or communicatively) coupled to" or "connected to" another component (e.g., a second component), it should be understood that the first component is directly connected to the second component or that the first component is indirectly connected to the second component via yet another component (e.g., a third component). Conversely, it can be understood that when a component (e.g., a first component) is referred to as being "directly connected" or "directly coupled" to another component (the second component), no component (e.g., a third component) is inserted between the two.

[0098] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, components, features, and elements with the same names in different embodiments of this application may have the same meaning or different meanings, the specific meaning of which must be determined by its interpretation in that specific embodiment or further in conjunction with the context of that specific embodiment.

[0099] The above description is merely an optional embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in this application.

[0100] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0101] The above description is merely an optional embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in this application.

[0102] The above description is merely an optional embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A fast OBN data splitting method based on multi-threading, characterized in that, Includes the following steps: S1, Obtain the shot point information table and receiver point information table of the marine seismic exploration system; S2, receiving seismic wave data collected by each OBN in the marine seismic exploration system; S3, add the shot point information and / or receiver point information that match the seismic wave data to the shot point information table and / or the receiver point information table, and update the seismic wave data; S4, all the updated seismic wave data are aggregated into a data set, and all data sets are distributed to at least two data processing devices for synchronous processing according to a preset strategy, and the common receiver point gather data corresponding to each OBN are output.

2. The method for fast OBN data splitting based on multi-threading according to claim 1, characterized in that, The shot point information table includes at least one of the following: shot point identifier; shot point location; firing time; shot point type; The receiving point information table includes at least one of the following: OBN identifier; OBN location; OBN deployment time; OBN retrieval time; OBN working status.

3. The method for fast OBN data splitting based on multi-threading according to claim 2, characterized in that, The method of obtaining the shot point information table includes at least one of the following: obtaining the shot point information table compiled during the design phase of the marine seismic exploration system; or creating and / or supplementing the shot point information table based on the detection information of each shot point. The method of obtaining the receiving point information table includes at least one of the following: obtaining the receiving point information table compiled during the design phase of the marine seismic exploration system; or creating and / or supplementing the receiving point information table based on feedback information from each OBN on-site.

4. The method for fast OBN data splitting based on multi-threading according to claim 2, characterized in that, Step S3 includes: S31, Extract shot point association information and receiver point association information from the seismic wave data; S32, Traverse the shot point information table and search for shot point information that matches the shot point association information; S33, Traverse the receiving point information table and search for receiving point information that matches the receiving point association information; S34, the found shot point information and receiver point information are added to and the seismic wave data is updated.

5. The method for fast OBN data splitting based on multi-threading according to claim 4, characterized in that, The artillery point association information includes timestamp information; The receiving point association information includes at least one of the following: OBN identifier; OBN location.

6. The method for fast OBN data partitioning based on multi-threading according to any one of claims 1 to 5, characterized in that, The preset strategy includes at least one of the following: Calculate the parameter ratio of the calculation parameters of each data processing device, divide the data set into at least two data blocks according to the parameter ratio, and assign each data block to the corresponding data processing device for synchronous processing; The data in the data set is divided into multiple data units, and each data unit is allocated to at least one data unit in multiple batches, so that the time difference between the calculations completed by each data processing device is less than a first threshold.

7. The method for fast OBN data splitting based on multi-threading according to claim 6, characterized in that, The calculation parameters include at least one of the following: The processor performance parameters corresponding to the data processing device; Memory performance parameters corresponding to the data processing device.

8. The method for fast OBN data splitting based on multi-threading according to claim 6, characterized in that, The step of dividing the data in the aggregate into multiple data units and allocating them in multiple batches to at least one data unit, such that the time difference between the computations completed by the various data processing devices is less than a first threshold, includes: The data in the data set is divided into multiple data units. After the data units are initially allocated to each of the data processing devices, the amount of unprocessed data in each of the data processing devices is monitored in real time. The data units are allocated to at least one data unit in multiple batches, so that the difference in the amount of unprocessed data in each of the data processing devices is less than a second preset threshold.

9. The method for fast OBN data splitting based on multi-threading according to claim 1, characterized in that, The common detection point gather data includes at least one of the following: The OBN identifier of the OBN; The OBN location; The seismic wave data collected by the OBN; The shot point identifiers corresponding to the seismic wave data collected by the OBN; The shot point location corresponding to the seismic wave data collected by the OBN; The excitation time corresponding to the seismic wave data collected by the OBN.

10. A fast OBN data splitting device based on multi-threading, characterized in that, The device includes a processor and a memory interconnected thereto, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to invoke the program instructions to perform the method as described in any one of claims 1 to 9.

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