Method, device, equipment and medium for establishing near-surface velocity model in loess area

Abstract

The application discloses a method, device and equipment for establishing a near-surface velocity model in a loess area and a medium. The method comprises the following steps: acquiring shot record data of the near-surface in the loess area, and obtaining first arrival time information by performing first arrival picking on the shot record data; establishing a first velocity model based on first target information in the first arrival time information; acquiring micro-logging information, and establishing a first constraint field based on the micro-logging information; the first constraint field is used for constraining the velocity of the first velocity model; determining a second velocity model based on the first velocity model and the first constraint field; wherein the second velocity model is used for describing the relationship between the velocity and the stratum thickness; acquiring second target information in the first arrival time information, and determining a target velocity model of the near-surface in the loess area based on the second target information and the second velocity model. The application solves the problem of low precision of the previously established near-surface velocity model in the thick loess area, and greatly improves the reliability and stability of the velocity model.

Description

Technical Field

[0001] This invention relates to the field of exploration geophysics, and in particular to a method, apparatus, equipment, and medium for establishing a near-surface velocity model in loess regions. Background Technology

[0002] The near-surface conditions in the Loess region of western my country are extremely complex. The thickness of the loess and the underlying gravel and sandstone strata vary greatly, resulting in significant variations in first-arrival waves within the same offset range. First-arrival waves, when analyzed according to time-offset, exhibit multiple distinct layers, making it difficult to obtain accurate near-surface velocity models. Currently, first-arrival travel-time tomography remains the primary method for near-surface velocity modeling in seismic data imaging processing.

[0003] Currently, near-surface models are generally established using unconstrained first-arrival tomographic inversion or constrained tomographic inversion with low-resolution information such as micro-logging. For example, all first-arrival information can be directly used for inversion or first-arrival information within a certain offset range can be selected for tomographic inversion to obtain velocity models. However, the accuracy of the velocity models established so far is relatively low.

[0004] Therefore, it is very important to establish a high-precision velocity model for the near-surface of complex loess regions. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, and medium for establishing near-surface velocity models in loess regions, which solves the problem of low accuracy in establishing near-surface velocity models in loess regions in the past, and greatly improves the reliability and stability of velocity models.

[0006] According to one aspect of the present invention, a method for establishing a near-surface velocity model in a loess region is provided, the method comprising:

[0007] The shot record data near the surface of the loess region is acquired, and the first arrival time information is obtained by picking the first arrival data; wherein, the near surface of the loess region includes at least the loess layer, and the first arrival time information includes the distribution relationship between the shot-receiver distance and the velocity, wherein the shot-receiver distance is the distance between the shot point and the receiver point;

[0008] Based on the first target information in the first arrival time information, a first velocity model is determined; wherein, the first target information is the data of the velocity of the first arrival wave passing through the loess layer from the ground surface within a preset velocity range, and the first velocity model is used to describe the relationship between velocity and stratum thickness.

[0009] Acquire micrologging information and establish a first constraint field based on the micrologging information; the first constraint field is used to constrain the velocity of the first velocity model.

[0010] Based on the first velocity model and the first constraint field, a second velocity model is determined; wherein, the second velocity model is used to describe the relationship between velocity and formation thickness;

[0011] The second target information is obtained from the arrival time information, and the target velocity model near the surface of the loess area is determined based on the second target information and the second velocity model; wherein, the second target information is the data of the shot-receiver distance within a preset distance range.

[0012] According to another aspect of the present invention, a velocity model establishment apparatus for near-surface loess regions is provided, the apparatus comprising:

[0013] The information acquisition module is used to acquire shot record data near the surface of the loess region and to pick up the first arrival time information from the shot record data; wherein, the loess region near the surface includes at least a loess layer, and the first arrival time information includes the distribution relationship between shot-receiver distance and velocity, wherein the shot-receiver distance is the distance between the shot point and the receiver point;

[0014] The first velocity model establishment module is used to determine the first velocity model based on the first target information in the first arrival time information; wherein, the first target information is the data of the velocity of the first arrival wave passing through the loess layer from the ground surface within a preset velocity range, and the first velocity model is used to describe the relationship between velocity and stratum thickness.

[0015] The first constraint field establishment module is used to acquire micrologging information and establish a first constraint field based on the micrologging information; the first constraint field is used to constrain the velocity of the first velocity model.

[0016] The second velocity model establishment module is used to determine a second velocity model based on the first velocity model and the first constraint field; wherein, the second velocity model is used to describe the relationship between velocity and formation thickness;

[0017] The target velocity model establishment module is used to acquire the second target information from the first arrival time information, and to determine the target velocity model near the surface of the loess area based on the second target information and the second velocity model; wherein, the second target information is data of the shot-receiver distance within a preset distance range.

[0018] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0019] At least one processor; and

[0020] A memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to execute the method for establishing a near-surface velocity model in the loess region according to any embodiment of the present invention.

[0022] 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 method for establishing a near-surface velocity model in the loess region as described in any embodiment of the present invention.

[0023] The technical solution of this invention includes acquiring shot record data near the surface of a loess region, and performing first-arrival picking on the shot record data to obtain first-arrival time information; wherein, the loess region near the surface includes at least a loess layer, and the first-arrival time information includes the distribution relationship between shot-receiver distance and velocity, where shot-receiver distance is the distance between the shot point and the receiver point; then, based on first target information in the first-arrival time information, determining a first velocity model; wherein, the first target information is the data of the velocity of the first-arrival wave passing through the loess layer from the surface within a preset velocity range, and the first velocity model is used to describe the relationship between velocity and formation thickness; further acquiring micrologging information, and establishing a first constraint field based on the micrologging information; the first constraint field is used to constrain the velocity of the first velocity model; then, based on the first velocity model and the first constraint field, determining a second velocity model; wherein, the second velocity model is used to describe the relationship between velocity and formation thickness; finally, acquiring second target information in the first-arrival time information, and based on the second target information and the second velocity model, determining a target velocity model near the surface of the loess region; wherein, the second target information is the data of the shot-receiver distance within a preset distance range. This application accurately determines the first velocity model based on the first target information, and then accurately determines the second velocity model by combining the first velocity model with the first constraint field, thus avoiding the model from deviating from the actual geological conditions. Finally, based on the second target information and the second velocity model, the target velocity model near the surface of the loess region is accurately determined, which solves the problem of low accuracy of the previous near-surface velocity model in the loess region and greatly improves the reliability and stability of the velocity model.

[0024] 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

[0025] 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.

[0026] Figure 1 This is a flowchart of a method for establishing a near-surface velocity model in a loess region according to Embodiment 1 of the present invention;

[0027] Figure 2 This is a schematic diagram of a loess region in western China to which this embodiment of the invention applies;

[0028] Figure 3 This is a comparison chart before and after optimizing the first arrival time information of the Loess Plateau according to the embodiments of the present invention;

[0029] Figure 4 This is a schematic diagram illustrating the distribution relationship between the gun-receiver distance and velocity according to an embodiment of the present invention.

[0030] Figure 5 This is a schematic diagram of the selected first target information applicable to embodiments of the present invention;

[0031] Figure 6 This is a schematic diagram of a first velocity model applicable to an embodiment of the present invention;

[0032] Figure 7 This is a schematic diagram of micro-logging information display applicable to embodiments of the present invention;

[0033] Figure 8 This is a schematic diagram comparing the output data of the second velocity model applicable to the embodiments of the present invention with actual survey information;

[0034] Figure 9 This is a schematic diagram of a target velocity model near the surface of the loess region applicable to an embodiment of the present invention.

[0035] Figure 10 This is a schematic diagram of static correction amount superposition imaging applicable to embodiments of the present invention;

[0036] Figure 11 This is a schematic diagram of a velocity model establishment device for near-surface loess areas provided in Embodiment 2 of the present invention;

[0037] Figure 12 This is a schematic diagram of the structure of an electronic device for implementing the method for establishing a near-surface velocity model in the loess region according to an embodiment of the present invention. Detailed Implementation

[0038] 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.

[0039] 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.

[0040] Example 1

[0041] Figure 1 This is a flowchart illustrating a method for establishing a near-surface velocity model in loess regions according to Embodiment 1 of the present invention. This embodiment is applicable to establishing near-surface velocity models in thick loess regions. The method can be executed by a device for establishing near-surface velocity models in loess regions. This device can be implemented in hardware and / or software and can be configured in an electronic device that incorporates the method for establishing near-surface velocity models in loess regions. Figure 1 As shown, the method includes:

[0042] S110. Obtain shot record data near the surface of the loess region, and perform first arrival picking on the shot record data to obtain first arrival time information; wherein, the near surface of the loess region includes at least a loess layer, and the first arrival time information includes the distribution relationship between shot-receiver distance and velocity, wherein the shot-receiver distance is the distance between the shot point and the receiver point.

[0043] Among them, the near-surface layer in loess areas includes at least a loess layer, for example... Figure 2 This is a schematic diagram of a loess region in western China to which this invention is applicable. The loess layer is located above the bottom loess layer in the diagram.

[0044] Specifically, in order to accurately obtain near-surface shot record data in loess areas, detectors are placed in the loess areas and cannons are ignited at different intervals. The detectors will receive various information, and the collection of this information is the shot record data. Then, by picking up the first arrival data, accurate first arrival time information can be obtained.

[0045] Optionally, first-arrival picking is performed on the shot record data to obtain first-arrival time information. Specifically, this can be done by: optimizing the shot record data to obtain optimized data; wherein, the optimization processing includes at least filtering, gain, and wavelet consistency processing; and then performing first-arrival picking on the optimized data to obtain first-arrival time information, thereby improving the accuracy of the first-arrival time information. For example... Figure 3 This is a comparison chart showing the first arrival time information of the Loess Plateau region before and after optimization, applicable to embodiments of the present invention. The chart clearly shows that after optimizing the shot record data, the first arrival acquisition is significantly better, resulting in clearer and more accurate acquisition. Furthermore, quality control of the first arrival time information, by filtering and deleting data that does not meet the criteria, further enhances the accuracy of the first arrival time information.

[0046] S120. Based on the first target information in the first arrival time information, determine the first velocity model; wherein, the first target information is the data of the velocity of the first arrival wave passing through the loess layer from the ground surface within a preset velocity range, and the first velocity model is used to describe the relationship between velocity and stratum thickness.

[0047] The preset speed range can be determined based on actual experience and the actual conditions in the Loess Plateau region; no specific limits are set here.

[0048] Specifically, analyzing and processing the first arrival time information can generate a distribution diagram of the relationship between shot-receiver distance and velocity, such as... Figure 4 As shown in the figure, the slope is the reciprocal of the velocity. Because the velocity of the first arrival wave in the loess layer is relatively slow, data from the range with a larger slope are selected as the primary target information. Figure 4 The data within the gray box is selected and extracted. Quality control is then applied to the primary target information to filter out unsuitable data, thereby obtaining more accurate primary target information. Figure 5 As shown; then, tomographic inversion is performed on the first target information (such as small-grid ray tracing tomographic inversion) to accurately determine the first velocity model, for example, as... Figure 6 The diagram shows the first velocity model.

[0049] S130. Obtain micrologging information and establish a first constraint field based on the micrologging information; the first constraint field is used to constrain the velocity of the first velocity model.

[0050] Specifically, micro-logging information is determined based on actual surveys, for example... Figure 7 The diagram shown illustrates the micrologging information. By analyzing and processing the micrologging information, the actual propagation speed of the first arrival wave in the loess layer is determined. This allows for the establishment of constraint coefficients for the velocity of the first arrival wave in the loess layer at different thicknesses from the surface to the bottom of the loess layer. This accurately establishes the first constraint field, facilitating the subsequent accurate acquisition of a second velocity model that better reflects reality.

[0051] S140. Based on the first velocity model and the first constraint field, determine the second velocity model; wherein the second velocity model is used to describe the relationship between velocity and formation thickness.

[0052] Specifically, a first velocity model and a first constraint field are obtained, and then the first constraint field is used to perform constraint tomography inversion on the first velocity model to determine the second velocity model, thus realizing the establishment of a highly accurate and reliable second velocity model.

[0053] In one feasible embodiment, optionally, after determining the second velocity model based on the first velocity model and the first constraint field, the method further includes steps A1-A3:

[0054] Step A1: Obtain actual survey information; the actual survey information includes at least actual drilling information, surface survey data, and outcrop information.

[0055] Step A2: If the output data of the second velocity model meets the similarity threshold with the actual survey information, then continue to determine the near-surface velocity model in the loess area.

[0056] Step A3: If the output data of the second velocity model does not meet the similarity threshold with the actual survey information, then return the first target information based on the loess layer passed through in the initial arrival time information to determine the first velocity model.

[0057] The similarity threshold can be limited according to the actual situation.

[0058] Specifically, the actual survey information is acquired, analyzed, and processed to distinguish information on different soil types. This information is then compared with the output data of the second velocity model. For example... Figure 8 The diagram illustrates the comparison between the output data of the second velocity model and the actual survey information in this embodiment of the invention. If the output data of the second velocity model and the actual survey information meet the similarity threshold, the subsequent model building continues, i.e., the determination of the near-surface velocity model in the loess region. If the output data of the second velocity model and the actual survey information do not meet the similarity threshold, the process returns to S120 to determine the first velocity model based on the first target information in the arrival time information, and subsequent operations are performed. This ensures that the second velocity model is closer to reality, has higher accuracy, and is more reliable.

[0059] S150. Obtain the second target information from the initial arrival time information, and determine the target velocity model near the surface of the loess area based on the second target information and the second velocity model; wherein, the second target information is data of the shot-receiver distance within a preset distance range.

[0060] The preset distance range can be determined according to the actual situation. In order to ensure the accuracy of the subsequent model building, this application selects data with a distance range that is as large as possible compared to the actual situation, such as data of the close, medium (or even long) gun-detector distance range.

[0061] Specifically, the second target information is obtained from the initial arrival time information, and a second constraint field is established to constrain the velocity of the second velocity model. Then, tomographic inversion (constrained ray tracing tomographic inversion) is performed on the second target information, the second velocity model, and the second constraint field to accurately determine the near-surface target velocity model in the loess region. Figure 9 The diagram shows a target velocity model near the surface of the loess region.

[0062] Optionally, to determine the accuracy of the velocity model, static correction can be performed, specifically as follows:

[0063] Well logging information from the Loess Plateau is acquired, and a first static correction is calculated based on this information; the well logging is from a preset depth. A second static correction is calculated based on a velocity model. The first and second static corrections are then overlaid to create an image, and the overlay effect is determined, for example... Figure 10 The diagram shown is a schematic of static correction superposition imaging applicable to the embodiment of the present invention. Then, the superposition effect is compared with the preset superposition effect to accurately determine the accuracy of the velocity model, and further determine the rationality and accuracy of the velocity model.

[0064] The technical solution of this invention includes acquiring shot record data near the surface of a loess region, and performing first-arrival picking on the shot record data to obtain first-arrival time information; wherein, the loess region near the surface includes at least a loess layer, and the first-arrival time information includes the distribution relationship between shot-receiver distance and velocity, where shot-receiver distance is the distance between the shot point and the receiver point; then, based on first target information in the first-arrival time information, determining a first velocity model; wherein, the first target information is the data of the velocity of the first-arrival wave passing through the loess layer from the surface within a preset velocity range, and the first velocity model is used to describe the relationship between velocity and formation thickness; further acquiring micrologging information, and establishing a first constraint field based on the micrologging information; the first constraint field is used to constrain the velocity of the first velocity model; then, based on the first velocity model and the first constraint field, determining a second velocity model; wherein, the second velocity model is used to describe the relationship between velocity and formation thickness; finally, acquiring second target information in the first-arrival time information, and based on the second target information and the second velocity model, determining a target velocity model near the surface of the loess region; wherein, the second target information is the data of the shot-receiver distance within a preset distance range. This application accurately determines the first velocity model based on the first target information, and then accurately determines the second velocity model by combining the first velocity model with the first constraint field, avoiding the model from deviating from the actual geological conditions. Finally, based on the second target information and the second velocity model, the target velocity model near the surface of the loess region is determined, which solves the problem of low accuracy of the previous near-surface velocity model in the loess region and greatly improves the reliability and stability of the velocity model.

[0065] Example 2

[0066] Figure 11 This is a schematic diagram of a velocity model establishment device for near-surface loess areas provided in Embodiment 2 of the present invention. Figure 11 As shown, the device includes:

[0067] The information acquisition module 210 is used to acquire shot record data near the surface of the loess region and to pick up the first arrival time information from the shot record data; wherein, the loess region near the surface includes at least a loess layer, and the first arrival time information includes the distribution relationship between shot-receiver distance and velocity, wherein the shot-receiver distance is the distance between the shot point and the receiver point;

[0068] The first velocity model establishment module 220 is used to determine the first velocity model based on the first target information in the first arrival time information; wherein, the first target information is the data of the velocity of the first arrival wave passing through the loess layer from the ground surface within a preset velocity range, and the first velocity model is used to describe the relationship between velocity and stratum thickness.

[0069] The first constraint field establishment module 230 is used to acquire micro-logging information and establish a first constraint field based on the micro-logging information; the first constraint field is used to constrain the velocity of the first velocity model.

[0070] The second velocity model establishment module 240 is used to determine a second velocity model based on the first velocity model and the first constraint field; wherein, the second velocity model is used to describe the relationship between velocity and formation thickness;

[0071] The target velocity model establishment module 250 is used to acquire the second target information in the first arrival time information, and determine the target velocity model near the surface of the loess area based on the second target information and the second velocity model; wherein, the second target information is data of the shot-receiver distance within a preset distance range.

[0072] Optionally, the information acquisition module includes an initial arrival time information acquisition unit, used for:

[0073] The shot recording data is optimized to obtain optimized data; wherein the optimization process includes at least filtering, gain and wavelet consistency processing.

[0074] The optimized data is subjected to initial arrival picking to obtain initial arrival time information.

[0075] Optional, the first velocity model building module is specifically used for:

[0076] Perform tomographic inversion on the first target information to determine the first velocity model.

[0077] Optional, a second velocity model building module, specifically used for:

[0078] The first velocity model is subjected to constraint tomography inversion using the first constraint field to determine the second velocity model.

[0079] Optionally, the second velocity model building module also includes a judgment unit, specifically used for:

[0080] Obtain actual survey information; the actual survey information includes at least actual drilling information, surface survey data, and outcrop information;

[0081] If the output data of the second velocity model meets the similarity threshold with the actual survey information, then the determination of the near-surface velocity model in the loess area will continue.

[0082] If the output data of the second velocity model does not meet the similarity threshold with the actual survey information, the first target information based on the arrival time information is returned to determine the first velocity model.

[0083] Optional, target velocity model building module, specifically used for:

[0084] Establish a second constraint field to constrain the velocity of the second velocity model;

[0085] The second target information, the second velocity model, and the second constraint field are subjected to tomographic inversion to determine the target velocity model near the surface of the loess region.

[0086] The near-surface velocity model establishment device for loess regions provided in this embodiment of the invention can execute the near-surface velocity model establishment method for loess regions provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0087] The acquisition, storage, use, and processing of data in this application comply with relevant national laws and regulations and do not violate public order and good morals.

[0088] Example 3

[0089] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0090] Figure 12 A schematic diagram of a near-surface velocity model building device for loess regions, as provided in Embodiment 2 of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, 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.

[0091] like Figure 12 As 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.

[0092] 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.

[0093] 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 the method for establishing near-surface velocity models in loess regions.

[0094] In some embodiments, the method for establishing a near-surface velocity model in loess regions can 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 can 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 establishing a near-surface velocity model in loess regions described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the method for establishing a near-surface velocity model in loess regions by any other suitable means (e.g., by means of firmware).

[0095] 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), complex 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.

[0096] 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.

[0097] 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.

[0098] 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).

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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 for establishing a near-surface velocity model in loess regions, characterized in that, include: The shot record data near the surface of the loess region is acquired, and the first arrival time information is obtained by picking the first arrival data; wherein, the near surface of the loess region includes at least the loess layer, and the first arrival time information includes the distribution relationship between the shot-receiver distance and the velocity, wherein the shot-receiver distance is the distance between the shot point and the receiver point; A first velocity model is established based on the first target information in the first arrival time information; wherein, the first target information is the data of the velocity of the first arrival wave passing through the loess layer from the surface within a preset velocity range, and the first velocity model is used to describe the relationship between velocity and stratum thickness. Acquire micrologging information and establish a first constraint field based on the micrologging information; the first constraint field is used to constrain the velocity of the first velocity model. Based on the first velocity model and the first constraint field, a second velocity model is determined; wherein, the second velocity model is used to describe the relationship between velocity and formation thickness; The second target information is obtained from the first arrival time information, and based on the second target information and the second velocity model, the target velocity model near the surface of the loess area is determined; wherein, the second target information is data of the shot-receiver distance within a preset distance range; Among them, based on the first target information in the initial arrival time information, a first velocity model is established, including: Perform tomographic inversion on the first target information to determine the first velocity model; Specifically, based on the second target information and the second velocity model, the target velocity model near the surface of the loess region is determined, including: Establish a second constraint field to constrain the velocity of the second velocity model; The second target information, the second velocity model, and the second constraint field are subjected to tomographic inversion to determine the target velocity model near the surface of the loess region.

2. The method according to claim 1, characterized in that, First arrival time information is obtained by picking up the first arrival data from the gun recording data, including: The shot recording data is optimized to obtain optimized data; wherein the optimization process includes at least filtering, gain and wavelet consistency processing. The optimized data is subjected to initial arrival picking to obtain initial arrival time information.

3. The method according to claim 1, characterized in that, Based on the first velocity model and the first constraint field, the second velocity model is determined, including: The first velocity model is subjected to constraint tomography inversion using the first constraint field to determine the second velocity model.

4. The method according to claim 1, characterized in that, After determining the second velocity model based on the first velocity model and the first constraint field, the method further includes: Obtain actual survey information; the actual survey information includes at least actual drilling information, surface survey data, and outcrop information; If the output data of the second velocity model meets the similarity threshold with the actual survey information, then the determination of the target velocity model near the surface of the loess area will continue. If the output data of the second velocity model does not meet the similarity threshold with the actual survey information, the first target information based on the arrival time information is returned to determine the first velocity model.

5. A device for establishing a near-surface velocity model in a loess region, characterized in that, include: The information acquisition module is used to acquire shot record data near the surface of the loess region and to pick up the first arrival time information from the shot record data; wherein, the loess region near the surface includes at least a loess layer, and the first arrival time information includes the distribution relationship between shot-receiver distance and velocity, wherein the shot-receiver distance is the distance between the shot point and the receiver point; The first velocity model establishment module is used to determine the first velocity model based on the first target information in the first arrival time information; wherein, the first target information is the data of the velocity of the first arrival wave passing through the loess layer from the ground surface within a preset velocity range, and the first velocity model is used to describe the relationship between velocity and stratum thickness. The first constraint field establishment module is used to acquire micrologging information and establish a first constraint field based on the micrologging information; the first constraint field is used to constrain the velocity of the first velocity model. The second velocity model establishment module is used to determine a second velocity model based on the first velocity model and the first constraint field; wherein, the second velocity model is used to describe the relationship between velocity and formation thickness; The target velocity model building module is used to acquire the second target information from the first arrival time information, and to determine the target velocity model near the surface of the loess area based on the second target information and the second velocity model; wherein, the second target information is data of the shot-receiver distance within a preset distance range; The first velocity model establishment module is used to: perform tomographic inversion on the first target information to determine the first velocity model; The target velocity model establishment module is specifically used to: establish a second constraint field to constrain the velocity of the second velocity model; and perform tomographic inversion on the second target information, the second velocity model, and the second constraint field to determine the target velocity model near the surface of the loess region.

6. The apparatus according to claim 5, characterized in that, The information acquisition module includes an arrival time information acquisition unit, used for: The shot recording data is optimized to obtain optimized data; wherein the optimization process includes at least filtering, gain and wavelet consistency processing. The optimized data is subjected to initial arrival picking to obtain initial arrival time information.

7. An electronic device, characterized in that, 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 establishing a near-surface velocity model in the loess region as described in any one of claims 1-4.

8. 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 establishing a near-surface velocity model in the loess region as described in any one of claims 1-4.

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