Processing method and device of seismic first arrival data, electronic equipment and storage medium

Abstract

This invention discloses a method, apparatus, electronic device, and storage medium for processing first-arrival data of earthquakes. The method includes: acquiring raw first-arrival data and processing the raw first-arrival data to obtain forward-modeled first-arrival data; performing signal processing on the forward-modeled first-arrival data to determine the first-arrival data to be processed corresponding to the forward-modeled first-arrival data; performing interpolation and noise reduction on the first-arrival data to be processed according to a preset interpolation algorithm, and determining the target first-arrival data based on the first-arrival data obtained after interpolation and noise reduction. Based on the above technical solution, by augmenting the acquired raw first-arrival data, the quality of the first-arrival data is improved, thereby improving the picking quality and picking rate of the first-arrival data, providing data support for subsequent near-surface velocity modeling, static correction, and other technical steps.

Description

Technical Field

[0001] This invention relates to the field of earthquake data enhancement technology, and in particular to a method, apparatus, electronic device, and storage medium for processing earthquake first arrival data. Background Technology

[0002] Near-surface velocity modeling in complex regions is a key challenge for imaging, with the accuracy of the near-surface velocity model having a significant impact on imaging. Near-surface velocity modeling relies on the quality of first-arrival acquisition. The geological features and acquisition methods in complex regions result in extremely low signal-to-noise ratios in seismic data. Therefore, improving the quality and acquisition rate of first-arrivals is crucial for near-surface velocity modeling and imaging.

[0003] However, the data processing methods and first-arrival picking tools used in the existing technology cannot achieve high-quality picking and processing of first-arrival data. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for processing earthquake first arrival data. By performing augmentation processing on the acquired raw first arrival data, the quality of the first arrival is improved, thereby enhancing the picking quality and picking rate of the first arrival, and providing data support for subsequent technical steps such as near-surface velocity modeling and static correction.

[0005] According to one aspect of the present invention, a method for processing earthquake first arrival data is provided, comprising:

[0006] The raw first-arrival data of earthquakes are acquired, and the raw first-arrival data of earthquakes are processed to obtain forward-modeled first-arrival data of earthquakes.

[0007] Signal processing is performed on the forward modeled first arrival data to determine the first arrival data of the earthquake to be processed corresponding to the forward modeled first arrival data;

[0008] The first arrival data of the earthquake to be processed is interpolated and denoised according to a preset interpolation algorithm, and the target first arrival data is determined based on the first arrival data of the earthquake obtained after interpolation and denoising.

[0009] According to another aspect of the present invention, an apparatus for processing first arrival data of earthquakes is provided, comprising:

[0010] The earthquake data forward modeling module is used to acquire raw earthquake first arrival data and process the raw earthquake first arrival data to obtain forward modeled earthquake first arrival data;

[0011] The first arrival data preprocessing module performs signal processing on the forward modeling first arrival data to determine the first arrival data to be processed corresponding to the forward modeling first arrival data.

[0012] The target earthquake first arrival data determination module is used to perform interpolation and noise reduction on the earthquake first arrival data to be processed according to a preset interpolation algorithm, and determine the target earthquake first arrival data based on the earthquake first arrival data obtained after interpolation and noise reduction.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the earthquake first arrival data processing method according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the earthquake first arrival data processing method according to any embodiment of the present invention.

[0018] The technical solution of this invention involves acquiring raw first-arrival data and processing it to obtain forward-modeled first-arrival data. Signal processing is then performed on the forward-modeled first-arrival data to determine the corresponding first-arrival data to be processed. Furthermore, a preset interpolation algorithm is used to interpolate and denoise the first-arrival data to be processed, and the target first-arrival data is determined based on the first-arrival data obtained after interpolation and denoising. Based on this technical solution, by augmenting the acquired raw first-arrival data, the quality of the first-arrivals is improved, thereby enhancing the picking quality and picking rate, and providing data support for subsequent near-surface velocity modeling, static correction, and other technical steps.

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

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1This is a flowchart of a method for processing earthquake first arrival data according to an embodiment of the present invention;

[0022] Figure 2 This is a comparison chart of the original first-arrival data and the forward-modeled first-arrival data of the earthquake provided in the embodiments of the present invention;

[0023] Figure 3 This is a waveform diagram of single-shot data without surface consistency correction provided according to an embodiment of the present invention;

[0024] Figure 4 This is a waveform diagram of single-shot data after surface consistency correction according to an embodiment of the present invention;

[0025] Figure 5 This is a comparison diagram of the original first arrival data and the target first arrival data after data augmentation, provided according to an embodiment of the present invention;

[0026] Figure 6 This is a schematic diagram of a device for processing earthquake first arrival data according to an embodiment of the present invention;

[0027] Figure 7 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

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

[0030] Example 1

[0031] Figure 1This is a flowchart illustrating a method for processing first-arrival data according to an embodiment of the present invention. This embodiment is applicable to situations where, after acquiring raw first-arrival data, data augmentation is performed on the raw data to obtain high-quality first-arrival data. This method can be executed by a first-arrival data processing device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0032] S110. Obtain the original earthquake first arrival data and process the original earthquake first arrival data to obtain forward model earthquake first arrival data.

[0033] The raw initial earthquake data can be unprocessed raw first-arrival data. Forward-modeled earthquake first-arrival data can be understood as the first-arrival data obtained after processing the raw data.

[0034] Specifically, raw first-arrival data can be acquired using seismic exploration instruments. These instruments record the moment a seismic wave signal is first detected by a seismic detector, known as the first-arrival time. The acquired signal is then used as raw first-arrival data and stored in a database. When processing is required, the raw first-arrival data can be retrieved from the database and processed to obtain forward-modeled first-arrival data. For example, filtering methods can be used to remove noise interference from the raw data, improving the signal-to-noise ratio. Positional and temporal corrections can be applied to the acquired data to ensure accuracy. Then, using automatic picking algorithms based on wavelet transform, signal processing filters, and machine learning, the first-arrival wave can be quickly and accurately identified. Finally, based on a pre-established mathematical model, forward-modeled first-arrival data is performed on the pre-processed data to obtain forward-modeled first-arrival data corresponding to the raw first-arrival data.

[0035] Based on the above technical solution, the step of processing the original first-arrival data to obtain forward-modeled first-arrival data includes: performing tomographic processing on the original first-arrival data to determine the near-surface velocity model corresponding to the original first-arrival data; and determining the forward-modeled first-arrival data based on the near-surface velocity model.

[0036] Tomography can be used to analyze the propagation path and travel time of seismic waves to invert the velocity distribution at different depths underground. Near-surface velocity models can be understood as mathematical models describing velocity variations at different depths underground.

[0037] Specifically, seismic waves are generated in the target area using seismic exploration equipment, and their propagation process, especially the arrival time of the first arrival wave, is recorded. The acquired raw first arrival data is then denoised, filtered, and corrected to improve the signal-to-noise ratio and accuracy. For example, instrument noise, surface reflections, and other interference signals can be removed from the raw data, and the location and response time of the geophones can be corrected. Based on the propagation principle of seismic waves and the location of the surface geophones, the propagation path of the seismic waves from the source to the geophones is calculated. Based on the approximate velocity model and ray tracing results, the travel time of each ray is calculated. By comparing the calculated travel time with the actual observed first arrival time, the parameters in the velocity model are adjusted to minimize the difference between the calculated travel time and the observed value. Furthermore, the underground velocity distribution information obtained from tomography, especially the velocity structure in the near-surface region, can be used to construct a near-surface velocity model. The near-surface velocity model is then used as input to run seismic wave forward modeling software. Forward modeling software calculates the propagation process of seismic waves in the subsurface medium based on the velocity model, source location, and detector layout. It extracts the arrival time of the first arrival wave from the results of the forward modeling simulation, which is the forward modeling earthquake first arrival data.

[0038] For example, such as Figure 2 As shown, Figure 2 In the diagram, red represents the original first-arrival data, and blue represents the forward-modeled first-arrival data. The forward first-arrival refers to the first identifiable signal when a seismic wave reaches a ground receiver; this signal is generally considered to represent the time it takes for the seismic wave to travel directly from the source point to the receiver. Obtaining accurate forward first-arrivals is crucial for subsequent data processing, as it provides information about the velocity distribution in the subsurface medium, thus aiding in the construction of subsurface structure models. First, the original seismic data needs to be first-arrival picked. This is achieved through automated algorithms, which can identify the first obvious peak or trough in the seismic record. However, because seismic data typically has a low signal-to-noise ratio (SNR), automated picking may miss some important first-arrival information. Therefore, in addition to automated picking, manual correction is needed to ensure accuracy. To overcome the problem of missing first-arrivals due to low SNR, tomography is first performed using the existing picked information to obtain a near-surface velocity model. Then, forward simulation is performed based on this model, i.e., predicting the first arrival of seismic waves, resulting in simulated first arrivals that provide a complete and reliable forward first-arrival for subsequent processing.

[0039] Based on the above technical solution, the step of determining the forward modeling earthquake first arrival data based on the near-surface velocity model includes: performing forward modeling based on the near-surface velocity model, and using the simulated first arrival data obtained through the forward modeling simulation as the forward modeling earthquake first arrival data.

[0040] Forward modeling can be a numerical or physical process that calculates or observes the geophysical effects produced by a geological body by constructing a mathematical model or a physical model based on the body's shape, occurrence, and physical properties.

[0041] Specifically, based on the near-surface velocity model, source characteristics such as source location, source type, and source intensity, as well as the geophone layout, the parameters for forward modeling are set. These parameters determine the calculation of the propagation process and first arrival time of the simulated seismic waves. Appropriate forward modeling software, such as the finite difference method, finite element method, or ray tracing method, is used. The near-surface velocity model and simulation parameters are input, and the software is run to calculate the propagation process of seismic waves in the subsurface medium. During the forward modeling process, the simulated first arrival time of the seismic waves arriving at each geophone is recorded. The simulated first arrival time of each geophone is extracted from the results of the forward modeling to form a forward seismic first arrival dataset.

[0042] S120. Perform signal processing on the forward modeling first arrival data to determine the first arrival data of the earthquake to be processed corresponding to the forward modeling first arrival data.

[0043] Among them, the earthquake first arrival data to be processed can be the earthquake first arrival data obtained after signal processing of the forward modeling earthquake first arrival data.

[0044] Specifically, high-quality data segments with strong signal-to-noise ratios are selected from the forward modeling first-arrival data to ensure the accuracy and reliability of subsequent signal processing. The selected forward modeling first-arrival data can then be processed, for example, by using filtering techniques such as bandpass filtering and notch filtering to remove high-frequency noise and low-frequency interference from the seismic data and improve the signal-to-noise ratio. Then, signal processing is performed on the preprocessed forward modeling first-arrival data, for example, by using the sliding window method or correlation coupling method to extract the features of the seismic signal, thereby determining the first-arrival data to be processed.

[0045] Based on the above technical solution, the step of performing signal processing on the forward modeling first arrival data to determine the first arrival data to be processed corresponding to the forward modeling first arrival data includes: performing time alignment on the forward modeling first arrival data to obtain forward modeling first arrival data after data flattening; and performing non-surface consistency correction on the forward modeling first arrival data after data flattening to determine the first arrival data to be processed.

[0046] Time alignment is used to eliminate first-arrival time differences caused by factors such as differences in seismic wave propagation paths and instrument response. Non-surface consistency correction is a method used to eliminate differences in seismic wave propagation velocity and first-arrival time caused by differences in surface conditions.

[0047] Specifically, dynamic time warping (DTW) is used to achieve time alignment. By comparing the waveform characteristics of different seismic traces, the optimal matching path between waveforms is found, thereby determining the time offset and making corresponding adjustments. A reference trace can be selected, which can be a trace with good quality and high signal-to-noise ratio, as the benchmark. Other traces are aligned with the reference trace. After alignment, the first arrival data on all seismic traces will have the same starting time point. Then, non-surface consistency correction is performed on the flattened first arrival data of the seismic data to be processed. This can be done by establishing surface and near-surface velocity models and predicting and correcting the first arrival time difference through forward modeling, or by using the statistical characteristics of seismic data for non-surface consistency correction.

[0048] For example, after obtaining high-quality forward-modeled first-arrival data, the seismic data needs to be flattened. Flattening refers to the process of adjusting signals received at different depths to the same horizontal plane. The purpose of this is to ensure that all first arrivals are located at the same time position, thus forming an approximate straight line. Although flattening can significantly reduce nonlinear components in the data, such as... Figure 3 As shown, due to calculation errors, some high-frequency jitter may still occur. Therefore, to eliminate these unnecessary jitters, first arrival correction is necessary. Specifically, non-surface consistency correction can be performed by analyzing the in-phase axis characteristics within a short time window near the first arrival. After considering factors such as terrain changes, the first arrival time of each receiving point is fine-tuned to eliminate the influence of high-frequency fluctuations. The correction results are shown below. Figure 4 As shown, it should be noted that the corrected values ​​will be recorded in the header information of the data file for use in subsequent processing steps.

[0049] S130. The earthquake first arrival data to be processed is interpolated and denoised according to a preset interpolation algorithm, and the target earthquake first arrival data is determined based on the earthquake first arrival data obtained after interpolation and denoising.

[0050] The preset interpolation algorithm can be understood as a pre-set algorithm used to interpolate the first-arrival data of earthquakes. The target first-arrival data can be the final first-arrival data of earthquakes after data augmentation.

[0051] Specifically, based on a preset interpolation algorithm, the first arrival data of the earthquake to be processed is interpolated to increase the sampling rate. The interpolated data is then used for noise reduction to eliminate or reduce noise components in the earthquake data. Noise reduction methods may include filtering, wavelet transform, singular value decomposition (SVD), etc., and then error elimination is performed on the processed first arrival data to obtain the target first arrival data of the earthquake.

[0052] Based on the above technical solution, the step of interpolating and denoising the earthquake first arrival data to be processed according to a preset interpolation algorithm includes: performing interpolation and denoising processing on the earthquake first arrival data to be processed using a five-dimensional interpolation method based on a preset interpolation dimension.

[0053] The preset interpolation dimension can be understood as the data dimension that is set in advance for interpolation processing. The dimension can include space (XYZ), time (T), and frequency (F).

[0054] Specifically, even after the aforementioned leveling and correction steps, some areas of the seismic data may still have missing data or low signal-to-noise ratios. Five-dimensional interpolation can be used to supplement and denoise the data. Five-dimensional interpolation refers to estimating data within a space containing multiple dimensions of the data. This method effectively fills gaps and enhances the signal-to-noise ratio while preserving the original data characteristics, thereby improving the data quality within the first-arrival window. After completing the interpolation and denoising process, a second first-arrival picking can be performed. Because the data has been fully optimized, the signal-to-noise ratio is greatly improved, and simulated first arrivals can be used as guidance, resulting in more accurate and reliable picking results.

[0055] Based on the above technical solution, the step of determining the target earthquake first arrival data based on the earthquake first arrival data obtained after interpolation and denoising processing includes: processing the earthquake first arrival data obtained after interpolation and denoising processing based on an error compensation algorithm to determine the target earthquake first arrival data.

[0056] Specifically, once all preprocessing is complete, the final first arrival can be calculated. Theoretically, if no new errors were introduced in the preceding steps, the resulting first arrival should be very close to a constant value; that is, the first arrival times recorded by receivers at different locations should be almost identical. Then, the manually acquired first arrival times and the adjustments made due to non-surface consistency correction are subtracted from the calculated first arrival to obtain the final target earthquake first arrival data, such as... Figure 5 As shown, the red signal represents the original earthquake first arrival data, and the blue signal represents the target earthquake first arrival data.

[0057] The technical solution of this invention involves acquiring raw first-arrival data and processing it to obtain forward-modeled first-arrival data. Signal processing is then performed on the forward-modeled first-arrival data to determine the corresponding first-arrival data to be processed. Furthermore, a preset interpolation algorithm is used to interpolate and denoise the first-arrival data to be processed, and the target first-arrival data is determined based on the first-arrival data obtained after interpolation and denoising. Based on this technical solution, by augmenting the acquired raw first-arrival data, the quality of the first-arrivals is improved, thereby enhancing the picking quality and picking rate, and providing data support for subsequent near-surface velocity modeling, static correction, and other technical steps.

[0058] Example 2

[0059] Figure 6 This is a schematic diagram of a device for processing first-arrival earthquake data according to an embodiment of the present invention. Figure 6 As shown, the device includes: a seismic data forward modeling module 610, a first-arrival data preprocessing module 620, and a target seismic first-arrival data determination module 630, wherein,

[0060] The earthquake data forward modeling module 610 is used to acquire raw earthquake first arrival data and process the raw earthquake first arrival data to obtain forward modeled earthquake first arrival data.

[0061] The first arrival data preprocessing module 620 performs signal processing on the forward modeling first arrival data to determine the first arrival data to be processed corresponding to the forward modeling first arrival data.

[0062] The target earthquake first arrival data determination module 630 is used to perform interpolation and noise reduction on the earthquake first arrival data to be processed according to a preset interpolation algorithm, and determine the target earthquake first arrival data based on the earthquake first arrival data obtained after interpolation and noise reduction.

[0063] Based on the above technical solution, the seismic data forward modeling module includes: a simulation model determination unit, used to perform tomographic processing on the original first-arrival data to determine the near-surface velocity model corresponding to the original first-arrival data; and a forward modeling data determination unit, used to determine the forward modeled first-arrival data based on the near-surface velocity model.

[0064] Based on the above technical solution, the forward modeling data determination unit is used to perform forward modeling simulation based on the near-surface velocity model, and uses the simulated first arrival data obtained through the forward modeling simulation as the forward modeling earthquake first arrival data.

[0065] Based on the above technical solution, the first arrival data preprocessing module is used to perform time alignment on the forward modeling first arrival data to obtain forward modeling first arrival data after data flattening; and to perform non-surface consistency correction on the forward modeling first arrival data after data flattening to determine the first arrival data of the earthquake to be processed.

[0066] Based on the above technical solution, the target earthquake first arrival data determination module is used to perform interpolation and noise reduction processing on the earthquake first arrival data to be processed using a five-dimensional interpolation method based on a preset interpolation dimension.

[0067] Based on the above technical solution, the target earthquake first arrival data determination module is used to process the earthquake first arrival data obtained after interpolation and noise reduction based on the error compensation algorithm to determine the target earthquake first arrival data.

[0068] The technical solution of this invention involves acquiring raw first-arrival data and processing it to obtain forward-modeled first-arrival data. Signal processing is then performed on the forward-modeled first-arrival data to determine the corresponding first-arrival data to be processed. Furthermore, a preset interpolation algorithm is used to interpolate and denoise the first-arrival data to be processed, and the target first-arrival data is determined based on the first-arrival data obtained after interpolation and denoising. Based on this technical solution, by augmenting the acquired raw first-arrival data, the quality of the first-arrivals is improved, thereby enhancing the picking quality and picking rate, and providing data support for subsequent near-surface velocity modeling, static correction, and other technical steps.

[0069] The earthquake first arrival data processing apparatus provided in the embodiments of the present invention can execute the earthquake first arrival data processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0070] Example 3

[0071] Figure 7 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0072] like Figure 7As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0073] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0074] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as methods for processing first-arrival earthquake data.

[0075] In some embodiments, the method for processing first-arrival data may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for processing first-arrival data described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the method for processing first-arrival data by any other suitable means (e.g., by means of firmware).

[0076] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0077] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0078] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0079] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0080] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0081] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0082] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0083] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method of processing seismic first break data, characterized by, include: The raw first-arrival data of earthquakes are acquired, and the raw first-arrival data of earthquakes are processed to obtain forward-modeled first-arrival data of earthquakes. Signal processing is performed on the forward modeled first arrival data to determine the first arrival data of the earthquake to be processed corresponding to the forward modeled first arrival data; The first arrival data of the earthquake to be processed is interpolated and denoised according to a preset interpolation algorithm, and the target first arrival data is determined based on the first arrival data of the earthquake obtained after interpolation and denoising.

2. The method of claim 1, wherein, The process of processing the original first-arrival data to obtain forward-modeled first-arrival data includes: The original first-arrival data of the earthquake were subjected to tomography to determine the near-surface velocity model corresponding to the original first-arrival data of the earthquake. The forward-modeled earthquake first arrival data are determined based on the near-surface velocity model.

3. The method of claim 2, wherein, The determination of the forward-modeled first arrival data based on the near-surface velocity model includes: Forward modeling is performed based on the near-surface velocity model, and the simulated first arrival data obtained through the forward modeling is used as the forward modeling earthquake first arrival data.

4. The method of claim 1, wherein, The step of performing signal processing on the forward modeled first-arrival data to determine the corresponding first-arrival data to be processed includes: The forward model first arrival data is time-aligned to obtain forward model first arrival data after data flattening. Non-surface consistency correction is performed on the forward modeled first-arrival data after the data flattening process to determine the first-arrival data to be processed.

5. The method according to claim 1, characterized in that, The step of interpolating and denoising the first arrival data of the earthquake to be processed according to a preset interpolation algorithm includes: The five-dimensional interpolation method is used to perform interpolation and noise reduction on the earthquake first arrival data to be processed based on the preset interpolation dimension.

6. The method of claim 1, wherein, The determination of the target earthquake first arrival data based on the first arrival data obtained after interpolation and noise reduction processing includes: The first arrival data of the earthquake obtained after interpolation and denoising is processed based on the error compensation algorithm to determine the target first arrival data of the earthquake.

7. A processing device of seismic first arrival data, characterized by, include: The earthquake data forward modeling module is used to acquire raw earthquake first arrival data and process the raw earthquake first arrival data to obtain forward modeled earthquake first arrival data; The first arrival data preprocessing module performs signal processing on the forward modeling first arrival data to determine the first arrival data to be processed corresponding to the forward modeling first arrival data. The target earthquake first arrival data determination module is used to perform interpolation and noise reduction on the earthquake first arrival data to be processed according to a preset interpolation algorithm, and determine the target earthquake first arrival data based on the earthquake first arrival data obtained after interpolation and noise reduction.

8. The apparatus of claim 7, wherein, The seismic data forward modeling module includes: The simulation model determination unit is used to perform tomographic processing on the original first-arrival data of the earthquake and determine the near-surface velocity model corresponding to the original first-arrival data of the earthquake. The forward modeling data determination unit is used to determine the forward modeling earthquake first arrival data based on the near-surface velocity model.

9. An electronic device, comprising: The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for processing earthquake first arrival data according to any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method for processing earthquake first arrival data as described in any one of claims 1-6.

Images