A method and apparatus for seismic data acquisition

Abstract

This application provides a seismic data acquisition method and apparatus. The method includes: acquiring and storing raw seismic data of a selected area in the field using pre-deployed nodal seismometers; transmitting the raw seismic data to an indoor private cloud platform at preset sampling intervals using the nodal seismometers until sampling is complete; after the nodal seismometers are retrieved, retrieving the raw seismic data stored in the nodal seismometers via a 5G private network; sorting the raw seismic data in the nodal seismometers and the raw seismic data in the private cloud platform to obtain target seismic data, and removing all the raw seismic data; and saving the target seismic data in the private cloud platform. This enables remote operation and automation of the nodal seismometers, thereby improving the efficiency of parameter configuration and data copying and retrieval, reducing the degree of manual intervention, and enhancing the level of automation.

Description

Technical Field

[0001] This disclosure relates to the field of seismic data acquisition technology for oil and gas seismic exploration, and in particular to a seismic data acquisition method and apparatus. Background Technology

[0002] In the field of seismic exploration for oil and gas resources, the core equipment for field seismic data acquisition is undoubtedly the seismograph, especially the widely used nodal seismograph. With its advantages such as being cable-free, easy to operate, and highly efficient, it has become a core component of nodal seismic acquisition systems and is increasingly prevalent in practical applications. Specifically, during the preparation phase, working parameters still need to be set via a dedicated data transmission cabinet using a wired connection; similarly, during the data retrieval phase, data copying and downloading also rely on the data transmission cabinet. This process involves significant investment of manpower and resources, undoubtedly increasing the labor and equipment costs for the seismic team.

[0003] Currently, the number of nodal seismographs deployed in a single seismic acquisition area has surged to tens of thousands or even hundreds of thousands. Faced with such a large number of nodal seismographs, the configuration of their operating parameters and the downloading and copying of data still mainly rely on manual operation, requiring specialized data transmission cabinets. Each data transmission cabinet can only support a maximum of 50 nodal seismographs. Furthermore, during seismic acquisition operations, it is necessary to rationally plan and arrange the data transmission cabinet equipment and related operators based on factors such as the acquisition design and rolling construction schedule.

[0004] Given that improving the overall operational efficiency of the construction preparation and seismic data retrieval phases has become an urgent need for seismic teams, and the urgency of this need is becoming increasingly prominent, how to achieve rapid and efficient configuration of working parameters for a large number of nodal seismographs, how to achieve automated and rapid copying of data recorded by nodal seismographs, and how to reduce the degree of manual intervention to improve the level of automation during the seismic acquisition process have become key issues that urgently need to be addressed. Summary of the Invention

[0005] This disclosure provides a seismic data acquisition method and apparatus that enables remote operation and automation of nodal seismographs, thereby improving the efficiency of working parameter configuration and data copying and retrieval, reducing the degree of human intervention, and enhancing the level of automation.

[0006] In a first aspect, the present invention provides a seismic data acquisition method, comprising:

[0007] Use pre-deployed nodal seismometers to acquire and store raw seismic data for selected areas in the field;

[0008] Using the nodal seismograph, the raw seismic data is transmitted to an indoor private cloud platform at preset sampling intervals until sampling is complete;

[0009] After the node seismograph is recovered, the original seismic data stored in the node seismograph is recovered through a 5G private network;

[0010] The original seismic data from the node seismometer and the original seismic data from the private cloud platform are processed to obtain the target seismic data, and all the original seismic data are removed.

[0011] The target earthquake data is stored on the private cloud platform.

[0012] Optionally, using the nodal seismograph, the raw seismic data is transmitted to an indoor private cloud platform at preset sampling intervals until sampling is complete, including:

[0013] The node seismograph transmits the raw seismic data to a pre-deployed indoor 5G network system at preset sampling intervals; the indoor 5G network system is integrated into a trolley-style cabinet.

[0014] The trolley-style cabinet forwards the raw seismic data to the pre-configured private cloud platform.

[0015] Optionally, raw seismic data for a selected area in the field can be acquired and stored using pre-deployed nodal seismometers, including:

[0016] In the selected field area, seismic waves are generated using an artificial seismic source;

[0017] The seismic waves are collected using the pre-deployed nodal seismometers and converted into the raw seismic data.

[0018] Optionally, before the step of saving the target seismic data to the private cloud platform, the method further includes:

[0019] Data cleaning is performed on the target seismic data.

[0020] Optionally, the target seismic data is cleaned, including:

[0021] The target seismic data is denoised using filtering techniques.

[0022] Verify whether there are outliers in the target seismic data, and if there are outliers, delete, replace or smooth them.

[0023] Verify whether there are missing data points in the target seismic data, and if so, use interpolation methods to fill in the missing data points.

[0024] Optionally, storing the target seismic data on the private cloud platform includes:

[0025] Determine whether the target earthquake data exceeds a preset data volume threshold; if so, compress the target earthquake data and encrypt it before saving it to the private cloud platform; if not, encrypt and save the target earthquake data to the private cloud platform.

[0026] Secondly, the present invention provides a seismic data acquisition device, comprising:

[0027] The acquisition module is used to acquire raw seismic data of a selected area in the field using pre-deployed nodal seismometers;

[0028] The transmission module is used to transmit the raw seismic data to the indoor private cloud platform at preset sampling intervals using the nodal seismograph until sampling is completed.

[0029] The recovery module is used to recover the original seismic data stored in the node seismograph via a 5G private network after the node seismograph is recovered.

[0030] The data processing module is used to process the raw seismic data in the node seismometer and the raw seismic data in the private cloud platform to obtain the target seismic data and remove all the raw seismic data.

[0031] A storage module is used to store the target seismic data on the private cloud platform.

[0032] Optionally, the transmission module includes:

[0033] The transmission submodule is used to transmit the raw seismic data to a pre-deployed indoor 5G network system at preset sampling intervals using the node seismograph; the indoor 5G network system is integrated into a trolley cabinet.

[0034] The forwarding submodule is used to forward the raw seismic data to the pre-configured private cloud platform via the trolley cabinet.

[0035] Optionally, the acquisition module includes:

[0036] The excitation submodule is used to excite seismic waves using an artificial source in the selected area in the field.

[0037] The conversion submodule is used to collect the seismic waves using the pre-deployed nodal seismometers and convert them into the raw seismic data.

[0038] Optionally, it also includes:

[0039] The data cleaning module is used to clean the target seismic data.

[0040] Optionally, the data cleaning module includes:

[0041] The denoising processing submodule is used to denoise the target seismic data using filtering techniques.

[0042] The outlier verification submodule is used to verify whether there are outliers in the target seismic data, and if there are outliers, to delete, replace or smooth them.

[0043] The missing value verification submodule is used to verify whether there are missing data points in the target seismic data, and when missing data points are found, interpolation methods are used to fill in the corresponding data points.

[0044] Optionally, the storage module includes:

[0045] The judgment submodule is used to determine whether the target seismic data is greater than a preset data volume threshold; if so, the target seismic data is compressed and encrypted and saved to the private cloud platform; if not, the target seismic data is encrypted and saved to the private cloud platform.

[0046] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory storing computer-readable instructions that, when executed by the processor, perform the steps of the method provided in the first aspect above.

[0047] Fourthly, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the method provided in the first aspect above.

[0048] Fifthly, the present invention provides a computer program product comprising a computer program that, when executed by a processor, performs the steps of the method provided in the first aspect above.

[0049] As can be seen from the above technical solutions, the present invention has the following advantages:

[0050] This invention provides a method and apparatus for seismic data acquisition. The method includes: acquiring and storing raw seismic data of a selected area in the field using pre-deployed nodal seismometers; transmitting the raw seismic data to an indoor private cloud platform at preset sampling intervals using the nodal seismometers until sampling is complete; after the nodal seismometers are retrieved, retrieving the raw seismic data stored in the nodal seismometers via a 5G private network; sorting the raw seismic data in the nodal seismometers and the raw seismic data in the private cloud platform to obtain target seismic data, and removing all raw seismic data; and saving the target seismic data in the private cloud platform. This enables remote operation and automation of the nodal seismometers, thereby improving the efficiency of parameter configuration and data copying and retrieval, reducing the degree of manual intervention, and enhancing the level of automation. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart illustrating the steps of a first embodiment of the seismic data acquisition method of the present invention;

[0053] Figure 2 This is a flowchart illustrating the steps of a second embodiment of the seismic data acquisition method of the present invention.

[0054] Figure 3 This is one of the schematic diagrams of the hardware structure of an indoor 5G networking system according to a second embodiment of the earthquake data acquisition method of the present invention;

[0055] Figure 4 This is the second schematic diagram of the hardware structure of an indoor 5G networking system according to a second embodiment of the earthquake data acquisition method of the present invention;

[0056] Figure 5 This is the third schematic diagram of the hardware structure of an indoor 5G networking system according to Embodiment 2 of the earthquake data acquisition method of the present invention;

[0057] Figure 6 This is a flowchart illustrating the hardware deployment of an indoor 5G networking system according to a second embodiment of the earthquake data acquisition method of the present invention.

[0058] Figure 7 This is a structural block diagram of an embodiment of an earthquake data acquisition device according to the present invention. Detailed Implementation

[0059] This invention provides a seismic data acquisition method and apparatus that enables remote operation and automated processes for nodal seismographs, thereby improving the efficiency of working parameter configuration and data copying and retrieval, reducing the degree of manual intervention, and enhancing the level of automation.

[0060] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0061] Example 1, please refer to Figure 1 , Figure 1 This is a flowchart illustrating the steps of a seismic data acquisition method according to a first embodiment of the present invention. The method includes:

[0062] Step S101: Use pre-deployed nodal seismometers to acquire and store raw seismic data of a selected area in the field;

[0063] In this embodiment, a pre-calibrated and configured nodal seismograph is deployed in a selected area in the field, and then raw seismic data is acquired. The acquired raw seismic data is stored in the nodal seismograph's local storage device, typically a memory card or solid-state drive.

[0064] Step S102: Using the nodal seismograph, the raw seismic data is transmitted to the indoor private cloud platform at preset sampling intervals until sampling is completed;

[0065] In this embodiment of the application, the nodal seismograph transmits the raw seismic data it collects to a private cloud platform at a set sampling interval.

[0066] Step S103: After the node seismograph is recovered, the original seismic data stored in the node seismograph is recovered through the 5G private network.

[0067] In this embodiment of the application, the recovered node seismograph is connected to a 5G private network, and the raw seismic data stored in the node seismograph is transmitted to a private cloud platform through the 5G private network.

[0068] Step S104: Organize the original seismic data in the node seismometer and the original seismic data in the private cloud platform to obtain the target seismic data, and remove all the original seismic data.

[0069] In this embodiment of the application, the raw seismic data transmitted from the node seismometer to the private cloud platform is integrated with the raw seismic data already stored in step S102.

[0070] Step S105: Save the target earthquake data to the private cloud platform.

[0071] In this embodiment of the application, the generated target seismic data is archived and saved to ensure the integrity and traceability of the data.

[0072] This invention provides a seismic data acquisition method, comprising: acquiring and storing raw seismic data of a selected area in the field using pre-deployed nodal seismometers; transmitting the raw seismic data to an indoor private cloud platform at preset sampling intervals using the nodal seismometers until sampling is complete; retrieving the raw seismic data stored in the nodal seismometers via a 5G private network after the nodal seismometers are retrieved; sorting the raw seismic data in the nodal seismometers and the raw seismic data in the private cloud platform to obtain target seismic data, and removing all raw seismic data; and saving the target seismic data in the private cloud platform. This method enables remote operation and automation of the nodal seismometers, thereby improving the efficiency of parameter configuration and data copying and retrieval, reducing manual intervention, and enhancing automation.

[0073] Example 2, please refer to Figure 2 , Figure 2 This is a flowchart illustrating a second embodiment of the seismic data acquisition method of the present invention, the steps of which include:

[0074] Step S201: In the selected area in the field, seismic waves are generated using an artificial seismic source;

[0075] In this embodiment of the application, seismic waves are generated in a selected area in the field using an artificial seismic source. These seismic waves will penetrate the earth's crust and be reflected back, carrying information about the underground structure.

[0076] Step S202: The seismic waves are collected using the pre-deployed nodal seismometers and converted into the raw seismic data;

[0077] In step S203, the nodal seismograph transmits the raw seismic data to a pre-deployed indoor 5G network system at preset sampling intervals; the indoor 5G network system is integrated into a trolley cabinet.

[0078] In this embodiment, the indoor 5G networking system for 5G smart node instruments is specifically a miniaturized indoor 5G networking system, consisting of indoor miniaturized 5G networking system carrier hardware, a customized dedicated core network management system, dedicated communication commands, and supporting software. The indoor miniaturized 5G networking system comprises a lightweight 5G core network, 5G base stations and expansion units, switches, and 5G antennas. To ensure system reliability, the lightweight 5G core network incorporates system backup, consisting of two identical core network servers. Furthermore, the system supports expansion; multiple 5G base stations can be connected to the core network server via switches to improve system performance. The customized dedicated core network management system is tailored to the needs of the seismic data acquisition industry, simplifying network management configuration, lowering the barrier to entry, and allowing users to locate and troubleshoot network problems themselves. The supporting data recovery software and private cloud storage can be deployed on a separate workstation or server, connected to the core network via a switch, thereby enabling hardware and network support for setting operating parameters, upgrading firmware, and copying data for the aforementioned smart node instruments.

[0079] The 5G indoor miniaturized 5G networking system's hardware equipment fully considers the demands of harsh transportation and indoor environments. The hardware design and maintenance prioritize ease of maintenance in the field, adaptability to outdoor environments, and long-distance transport requirements. It adopts a trolley-style integrated miniature cabinet design, integrating the lightweight 5G core network, 5G base stations and expansion units, switches, and other equipment into the cabinet, with external interfaces for power, fiber optics, and network cables. Furthermore, considering dustproofing, shock absorption, and cooling requirements during operation, the cabinet features shockproof internal design, a cooling fan, dust plugs at wiring connections, and a transparent panel to avoid the harsh environmental impact of the node camp. (See [link to relevant documentation]). Figures 3-5 ,in, Figure 3 This is one of the schematic diagrams of the hardware structure of an indoor 5G networking system according to a second embodiment of the earthquake data acquisition method of the present invention. Figure 4 This is the second schematic diagram of the hardware structure of an indoor 5G networking system according to a second embodiment of the earthquake data acquisition method of the present invention. Figure 5 This is the third schematic diagram of the hardware structure of an indoor 5G networking system, which is a second embodiment of the earthquake data acquisition method of the present invention.

[0080] This customized core network management system, designed for the seismic data acquisition industry, lowers the barrier to entry for 5G professional network management, making it easy for non-5G professionals to use. Based on the needs of the 5G intelligent node instrument system, the 5G network management system is customized and includes the following functions: displaying all connection session information; statistically analyzing all session online / offline information, terminal rate information, core network configuration, etc. The core network management system can be deployed co-located with the 5GC when necessary, facilitating deployment and saving power; it can provide an interface for SIM card information for all connections, allowing nodes to obtain the SIM card number (IMSI) via commands, enabling core network and base station health status queries, reporting core network and base station alarm information, and supporting static IP configuration and software power on / off functions for terminals.

[0081] In step S204, the trolley-type cabinet forwards the raw seismic data to the pre-configured private cloud platform until sampling is complete;

[0082] Step S205: After the node seismograph is recovered, the original seismic data stored in the node seismograph is recovered through the 5G private network.

[0083] In the indoor work of the node camp during seismic acquisition construction, before the node seismograph is deployed to the field, the indoor technicians usually use the dedicated data transmission cabinet that comes with the node seismograph to configure the working parameters of the node seismograph (including but not limited to sampling interval, working time, detector parameters, etc.). After the node seismograph is returned to the camp, the indoor technicians usually use the data transmission cabinet to copy and retrieve the data.

[0084] Step S206: Organize the original seismic data in the node seismometer and the original seismic data in the private cloud platform to obtain the target seismic data, and remove all the original seismic data;

[0085] Step S207: Perform data cleaning on the target seismic data;

[0086] In this embodiment, the data cleaning step includes: using filtering technology to denoise the target seismic data; verifying whether there are outliers in the target seismic data, and deleting, replacing or smoothing the outliers if they exist; verifying whether there are missing data points in the target seismic data, and filling the missing data points using interpolation methods if they exist.

[0087] In practice, firstly, filtering techniques (such as median filtering and bandpass filtering) are used to remove noise interference from the original seismic data and improve the signal-to-noise ratio of the data.

[0088] Then, outliers are handled by methods such as deletion, replacement, or smoothing. These outliers may be caused by instrument malfunctions or data transmission errors.

[0089] Subsequently, the seismic data is checked for missing data points. If missing data points are found, interpolation methods are used to fill in the missing data points to ensure the continuity and integrity of the data.

[0090] Step S208: Save the target earthquake data to the private cloud platform.

[0091] In this embodiment of the application, it is determined whether the target seismic data is greater than a preset data volume threshold; if so, the target seismic data is compressed and encrypted and saved to the private cloud platform; if not, the target seismic data is encrypted and saved to the private cloud platform.

[0092] Additionally, please see Figure 6 , Figure 6 This is a flowchart illustrating the hardware deployment of an indoor 5G networking system according to a second embodiment of the earthquake data acquisition method of the present invention. In actual indoor work at the node camp, through dedicated commands, supporting control software, and data retrieval software, indoor staff can configure node working parameters, remotely upgrade firmware, and perform supplementary data transmission via the indoor 5G private network. Specific usage steps include:

[0093] (1) Connect the 5G antenna to the trolley cabinet via an optical-electric composite cable;

[0094] (2) Connect the private cloud platform to the trolley cabinet via a network cable;

[0095] (3) Connect the power supply to the trolley cabinet and turn it on;

[0096] (3) After powering on and waiting for 20 minutes, verify the connectivity of the 5G network itself and the connectivity between the 5G network and the private cloud platform. If there are any problems, check and troubleshoot them.

[0097] (4) After the system network is connected, before the 5G node seismograph is deployed in the field, the node network access status can be checked through the industry-customized core network management system, and the node working parameters can be configured and the firmware can be upgraded remotely using the supporting software.

[0098] (5) After the 5G node seismograph is retrieved from the field, the node’s network access status can be checked through the industry-customized core network management system, and the data stored in the node can be recovered using the supporting software.

[0099] This invention discloses a seismic data acquisition method, comprising: acquiring and storing raw seismic data of a selected area in the field using pre-deployed nodal seismographs; transmitting the raw seismic data to an indoor private cloud platform at preset sampling intervals using the nodal seismographs until sampling is complete; after the nodal seismographs are retrieved, retrieving the raw seismic data stored in the nodal seismographs via a 5G private network; sorting the raw seismic data in the nodal seismographs and the raw seismic data in the private cloud platform to obtain target seismic data, and removing all the raw seismic data; and saving the target seismic data in the private cloud platform. By using an indoor miniaturized 5G networking system to carry hardware equipment, a customized dedicated core network management system, dedicated communication commands, and supporting software, an indoor private 5G network can be provided for indoor work during field seismic acquisition operations. This can assist indoor technicians in remotely configuring nodal work parameters, upgrading firmware, and retrieving data, thereby improving the automation level of indoor work at nodal camps, improving the efficiency of work parameter configuration and data copying and retrieval, reducing the degree of manual intervention, and enhancing the level of automation.

[0100] Example 3, please refer to Figure 7 , Figure 7 This is a structural block diagram of an embodiment of a seismic data acquisition device according to the present invention. The device includes:

[0101] The acquisition module 301 is used to acquire raw seismic data of a selected area in the field using pre-deployed nodal seismometers;

[0102] The transmission module 302 is used to transmit the raw seismic data to the indoor private cloud platform at preset sampling intervals using the nodal seismograph until sampling is completed.

[0103] The recovery module 303 is used to recover the original seismic data stored in the node seismograph via a 5G private network after the node seismograph is recovered.

[0104] The data processing module 304 is used to process the original seismic data in the node seismometer and the original seismic data in the private cloud platform to obtain the target seismic data and remove all the original seismic data.

[0105] The storage module 305 is used to store the target seismic data on the private cloud platform.

[0106] In an optional embodiment, the transmission module 302 includes:

[0107] The transmission submodule is used to transmit the raw seismic data to a pre-deployed indoor 5G network system at preset sampling intervals using the node seismograph; the indoor 5G network system is integrated into a trolley cabinet.

[0108] The forwarding submodule is used to forward the raw seismic data to the pre-configured private cloud platform via the trolley cabinet.

[0109] In an optional embodiment, the acquisition module 301 includes:

[0110] The excitation submodule is used to excite seismic waves using an artificial source in the selected area in the field.

[0111] The conversion submodule is used to collect the seismic waves using the pre-deployed nodal seismometers and convert them into the raw seismic data.

[0112] In an optional embodiment, it further includes:

[0113] The data cleaning module is used to clean the target seismic data.

[0114] In an optional embodiment, the data cleaning module includes:

[0115] The denoising processing submodule is used to denoise the target seismic data using filtering techniques.

[0116] The outlier verification submodule is used to verify whether there are outliers in the target seismic data, and if there are outliers, to delete, replace or smooth them.

[0117] The missing value verification submodule is used to verify whether there are missing data points in the target seismic data, and when missing data points are found, interpolation methods are used to fill in the corresponding data points.

[0118] In an optional embodiment, the storage module 305 includes:

[0119] The judgment submodule is used to determine whether the target seismic data is greater than a preset data volume threshold; if so, the target seismic data is compressed and encrypted and saved to the private cloud platform; if not, the target seismic data is encrypted and saved to the private cloud platform.

[0120] Example 4: This embodiment of the invention also provides an electronic device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it causes the processor to perform a seismic data acquisition method according to any embodiment, including:

[0121] Use pre-deployed nodal seismometers to acquire and store raw seismic data for selected areas in the field;

[0122] Using the nodal seismograph, the raw seismic data is transmitted to an indoor private cloud platform at preset sampling intervals until sampling is complete;

[0123] After the node seismograph is recovered, the original seismic data stored in the node seismograph is recovered through a 5G private network;

[0124] The original seismic data from the node seismometer and the original seismic data from the private cloud platform are processed to obtain the target seismic data, and all the original seismic data are removed.

[0125] The target earthquake data is stored on the private cloud platform.

[0126] In an optional embodiment, the nodal seismograph is used to transmit the raw seismic data to an indoor private cloud platform at preset sampling intervals until sampling is complete, including:

[0127] The node seismograph transmits the raw seismic data to a pre-deployed indoor 5G network system at preset sampling intervals; the indoor 5G network system is integrated into a trolley-style cabinet.

[0128] The trolley-style cabinet forwards the raw seismic data to the pre-configured private cloud platform.

[0129] In one optional embodiment, raw seismic data of a selected area in the field is acquired using pre-deployed nodal seismometers, including:

[0130] In the selected field area, seismic waves are generated using an artificial seismic source;

[0131] The seismic waves are collected using the pre-deployed nodal seismometers and converted into the raw seismic data.

[0132] In an optional embodiment, prior to the step of saving the target seismic data to the private cloud platform, the method further includes:

[0133] Data cleaning is performed on the target seismic data.

[0134] In one optional embodiment, data cleaning of the target seismic data includes:

[0135] The target seismic data is denoised using filtering techniques.

[0136] Verify whether there are outliers in the target seismic data, and if there are outliers, delete, replace or smooth them.

[0137] Verify whether there are missing data points in the target seismic data, and if so, use interpolation methods to fill in the missing data points.

[0138] In an optional embodiment, storing the target seismic data on the private cloud platform includes:

[0139] Determine whether the target earthquake data exceeds a preset data volume threshold; if so, compress the target earthquake data and encrypt it before saving it to the private cloud platform; if not, encrypt and save the target earthquake data to the private cloud platform.

[0140] Example 5: This embodiment of the invention also provides a computer storage medium storing a computer program thereon. When the computer program is executed by the processor, it implements a seismic data acquisition method according to any embodiment, including:

[0141] Use pre-deployed nodal seismometers to acquire and store raw seismic data for selected areas in the field;

[0142] Using the nodal seismograph, the raw seismic data is transmitted to an indoor private cloud platform at preset sampling intervals until sampling is complete;

[0143] After the node seismograph is recovered, the original seismic data stored in the node seismograph is recovered through a 5G private network;

[0144] The original seismic data from the node seismometer and the original seismic data from the private cloud platform are processed to obtain the target seismic data, and all the original seismic data are removed.

[0145] The target earthquake data is stored on the private cloud platform.

[0146] In an optional embodiment, the nodal seismograph is used to transmit the raw seismic data to an indoor private cloud platform at preset sampling intervals until sampling is complete, including:

[0147] The node seismograph transmits the raw seismic data to a pre-deployed indoor 5G network system at preset sampling intervals; the indoor 5G network system is integrated into a trolley-style cabinet.

[0148] The trolley-style cabinet forwards the raw seismic data to the pre-configured private cloud platform.

[0149] In one optional embodiment, raw seismic data of a selected area in the field is acquired using pre-deployed nodal seismometers, including:

[0150] In the selected field area, seismic waves are generated using an artificial seismic source;

[0151] The seismic waves are collected using the pre-deployed nodal seismometers and converted into the raw seismic data.

[0152] In an optional embodiment, prior to the step of saving the target seismic data to the private cloud platform, the method further includes:

[0153] Data cleaning is performed on the target seismic data.

[0154] In one optional embodiment, data cleaning of the target seismic data includes:

[0155] The target seismic data is denoised using filtering techniques.

[0156] Verify whether there are outliers in the target seismic data, and if there are outliers, delete, replace or smooth them.

[0157] Verify whether there are missing data points in the target seismic data, and if so, use interpolation methods to fill in the missing data points.

[0158] In an optional embodiment, storing the target seismic data on the private cloud platform includes:

[0159] Determine whether the target earthquake data exceeds a preset data volume threshold; if so, compress the target earthquake data and encrypt it before saving it to the private cloud platform; if not, encrypt and save the target earthquake data to the private cloud platform.

[0160] Example 6: This embodiment of the invention also provides a computer program product, on which a computer program is stored. When the computer program is executed by the processor, it implements a seismic data acquisition method of any embodiment, including:

[0161] Use pre-deployed nodal seismometers to acquire and store raw seismic data for selected areas in the field;

[0162] Using the nodal seismograph, the raw seismic data is transmitted to an indoor private cloud platform at preset sampling intervals until sampling is complete;

[0163] After the node seismograph is recovered, the original seismic data stored in the node seismograph is recovered through a 5G private network;

[0164] The original seismic data from the node seismometer and the original seismic data from the private cloud platform are processed to obtain the target seismic data, and all the original seismic data are removed.

[0165] The target earthquake data is stored on the private cloud platform.

[0166] In an optional embodiment, the nodal seismograph is used to transmit the raw seismic data to an indoor private cloud platform at preset sampling intervals until sampling is complete, including:

[0167] The node seismograph transmits the raw seismic data to a pre-deployed indoor 5G network system at preset sampling intervals; the indoor 5G network system is integrated into a trolley-style cabinet.

[0168] The trolley-style cabinet forwards the raw seismic data to the pre-configured private cloud platform.

[0169] In one optional embodiment, raw seismic data of a selected area in the field is acquired using pre-deployed nodal seismometers, including:

[0170] In the selected field area, seismic waves are generated using an artificial seismic source;

[0171] The seismic waves are collected using the pre-deployed nodal seismometers and converted into the raw seismic data.

[0172] In an optional embodiment, prior to the step of saving the target seismic data to the private cloud platform, the method further includes:

[0173] Data cleaning is performed on the target seismic data.

[0174] In one optional embodiment, data cleaning of the target seismic data includes:

[0175] The target seismic data is denoised using filtering techniques.

[0176] Verify whether there are outliers in the target seismic data, and if there are outliers, delete, replace or smooth them.

[0177] Verify whether there are missing data points in the target seismic data, and if so, use interpolation methods to fill in the missing data points.

[0178] In an optional embodiment, storing the target seismic data on the private cloud platform includes:

[0179] Determine whether the target earthquake data exceeds a preset data volume threshold; if so, compress the target earthquake data and encrypt it before saving it to the private cloud platform; if not, encrypt and save the target earthquake data to the private cloud platform.

[0180] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0181] In the several embodiments provided in this application, it should be understood that the methods, apparatuses, electronic devices, and storage media disclosed in this invention can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units 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. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0182] The units described 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 this embodiment according to actual needs.

[0183] 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.

[0184] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present 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 readable 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 described in the various embodiments of the present invention. The aforementioned readable 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.

[0185] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A seismic data acquisition method, characterized in that, include: Use pre-deployed nodal seismometers to acquire and store raw seismic data for selected areas in the field; Using the nodal seismograph, the raw seismic data is transmitted to an indoor private cloud platform at preset sampling intervals until sampling is complete; After the node seismograph is recovered, the original seismic data stored in the node seismograph is recovered through a 5G private network; The original seismic data from the node seismometer and the original seismic data from the private cloud platform are processed to obtain the target seismic data, and all the original seismic data are removed. The target earthquake data is stored on the private cloud platform.

2. The seismic data acquisition method according to claim 1, characterized in that, Using the aforementioned nodal seismograph, the raw seismic data is transmitted to an indoor private cloud platform at preset sampling intervals until sampling is complete, including: The node seismograph transmits the raw seismic data to a pre-deployed indoor 5G network system at preset sampling intervals; the indoor 5G network system is integrated into a trolley-style cabinet. The trolley-style cabinet forwards the raw seismic data to the pre-configured private cloud platform.

3. The seismic data acquisition method according to claim 1, characterized in that, Raw seismic data for a selected field area is acquired and stored using pre-deployed nodal seismometers, including: In the selected field area, seismic waves are generated using an artificial seismic source; The seismic waves are collected using the pre-deployed nodal seismometers and converted into the raw seismic data.

4. The seismic data acquisition method according to claim 1, characterized in that, Before the step of saving the target seismic data to the private cloud platform, the method further includes: Data cleaning is performed on the target seismic data.

5. The seismic data acquisition method according to claim 1, characterized in that, Data cleaning of the target seismic data includes: The target seismic data is denoised using filtering techniques. Verify whether there are outliers in the target seismic data, and if there are outliers, delete, replace or smooth them. Verify whether there are missing data points in the target seismic data, and if so, use interpolation methods to fill in the missing data points.

6. The seismic data acquisition method according to claim 1, characterized in that, Storing the target seismic data on the private cloud platform includes: Determine whether the target earthquake data exceeds a preset data volume threshold; if so, compress the target earthquake data and encrypt it before saving it to the private cloud platform; if not, encrypt and save the target earthquake data to the private cloud platform.

7. A seismic data acquisition device, characterized in that, include: The acquisition module is used to acquire raw seismic data of a selected area in the field using pre-deployed nodal seismometers; The transmission module is used to transmit the raw seismic data to the indoor private cloud platform at preset sampling intervals using the nodal seismograph until sampling is completed. The recovery module is used to recover the original seismic data stored in the node seismograph via a 5G private network after the node seismograph is recovered. The data processing module is used to process the raw seismic data in the node seismometer and the raw seismic data in the private cloud platform to obtain the target seismic data and remove all the raw seismic data. A storage module is used to store the target seismic data on the private cloud platform.

8. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer-readable instructions that, when executed by the processor, perform the method as described in any one of claims 1-6.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it performs the method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-6.

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