Seismic imaging method, device, electronic equipment, storage medium and product

Abstract

The application discloses a seismic imaging method, device, electronic equipment, storage medium and product. The method comprises the following steps: correcting a full-azimuth residual delay velocity model according to seismic data; performing full-azimuth multi-ray migration in a Fresnel zone according to the velocity model to obtain a multi-dimensional wave field gather; and reconstructing different types of wave fields according to the multi-dimensional wave field gather and a geological type to obtain seismic imaging. The technical solution has the advantages that the full-azimuth residual delay velocity model is used, full-azimuth multi-ray migration is performed, different azimuth angles are considered, different types of wave fields are reconstructed, and the accuracy of seismic imaging is improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a seismic imaging method, apparatus, electronic device, storage medium, and product. Background Technology

[0002] Current seismic data processing faces two major challenges. Firstly, changes in exploration and development patterns mean that processed seismic data often originates from old, deep, fragmented, thin, and steep areas. As exploration depth increases, finding favorable exploration targets becomes more difficult, leading to higher demands on data processing results and imaging of specific geological targets. Predictive and descriptive accuracy is often low for situations with low signal-to-noise ratios, unclear fault sections, and poor fracture-cavity imaging. Secondly, rapid advancements in acquisition technology, particularly the widespread application of "wide azimuth" and OBN acquisition techniques, theoretically reduce uncertainty in subsequent interpretation. Maximizing the utilization of acquired wide azimuth information presents a challenge for seismic data processors. Conventional methods such as Kirchhoff co-offset migration have achieved some success in seismic imaging, but suffer from limitations such as single-dimensionality and insufficient accuracy. In conclusion, the accuracy of seismic imaging needs improvement. Summary of the Invention

[0003] This application provides a seismic imaging method, apparatus, electronic device, storage medium, and product to improve the accuracy of geophysical interpretation work.

[0004] In a first aspect, embodiments of this application provide a seismic imaging method, including:

[0005] Based on the comprehensive residual delay correction velocity model of earthquake data;

[0006] Based on the velocity model, perform omnidirectional multi-ray migration within the Fresnel zone to obtain multi-dimensional wavefield gathers.

[0007] Based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic images.

[0008] Secondly, embodiments of this application also provide a seismic imaging device, comprising:

[0009] The correction module is used to correct the velocity model based on the residual delay of the seismic data in all aspects.

[0010] The offset module is used to perform omnidirectional multi-ray offset within the Fresnel zone according to the velocity model to obtain multi-dimensional wavefield gathers.

[0011] The imaging module is used to reconstruct different types of wavefields based on the multi-dimensional wavefield gathers and geological types to obtain seismic images.

[0012] Thirdly, embodiments of this application provide an electronic device, including:

[0013] One or more processors;

[0014] Storage device for storing one or more programs;

[0015] When the one or more programs are executed by the one or more processors, the one or more processors implement the seismic imaging method as described in the first aspect.

[0016] Fourthly, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the seismic imaging method as described in the first aspect.

[0017] Fifthly, embodiments of this application also provide a computer program product, including a computer program and / or instructions, which, when executed by a processor, implement the seismic imaging method as described in any of the above embodiments.

[0018] This application provides a seismic imaging method, apparatus, electronic device, storage medium, and product. The seismic imaging method includes: a holistic residual delay-corrected velocity model based on seismic data; holistic multi-ray migration within the Fresnel zone based on the velocity model to obtain a multi-dimensional wavefield gather; and reconstruction of different types of wavefields based on the multi-dimensional wavefield gather and geological type to obtain a seismic image. The above technical solution utilizes a holistic residual delay-corrected velocity model and performs holistic multi-ray migration, considering different azimuth angles to reconstruct different types of wavefields, thereby improving the accuracy of seismic imaging. Attached Figure Description

[0019] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0020] Figure 1 A flowchart of a seismic imaging method provided in an embodiment of this application;

[0021] Figure 2 A schematic diagram of Kirchhoff offset and omnidirectional multi-ray offset provided for one embodiment;

[0022] Figure 3 This is a schematic diagram illustrating the imaging optimization effect in a low signal-to-noise ratio region according to one embodiment.

[0023] Figure 4 This is a schematic diagram illustrating the optimized effect of crack imaging in one embodiment;

[0024] Figure 5 This is a schematic diagram illustrating the effect of well vibration error correction in one embodiment;

[0025] Figure 6 A schematic diagram of a seismic imaging process provided in one embodiment;

[0026] Figure 7 This is a schematic diagram of the structure of a seismic imaging device provided in an embodiment of this application;

[0027] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0028] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present application, not the entire structure.

[0029] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processes, many of these steps can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the steps can be rearranged. The process can be terminated when its operation is complete, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0030] It should be noted that the concepts of "first" and "second" mentioned in the embodiments of this application are only used to distinguish different devices, modules, units or other objects, and are not used to limit the order of functions performed by these devices, modules, units or other objects or their interdependencies.

[0031] Furthermore, the embodiments and features described in this application may be combined with each other, unless otherwise specified.

[0032] The acquisition, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.

[0033] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the relevant content of the solution.

[0034] Figure 1 This is a flowchart illustrating a seismic imaging method provided in an embodiment of this application. This embodiment is applicable to situations where wavefields are reconstructed from seismic data for imaging. Specifically, this seismic imaging method can be executed by a seismic imaging device, which can be implemented through software and / or hardware and integrated into an electronic device. The electronic device includes, but is not limited to, devices with data processing capabilities such as computers, smartphones, or servers.

[0035] like Figure 1 As shown, the method specifically includes the following steps:

[0036] S110, a velocity model with comprehensive residual delay correction based on seismic data.

[0037] Specifically, seismic data includes data obtained from observations in all 360-degree azimuth. The main task of processing seismic data is to derive geological information from it, which can be presented through seismic profiles. Since seismic waves record reflection time, while geological strata are measured in depth, the time-depth conversion requires accurate velocity. Therefore, determining the velocity model parameters is crucial in the processing. In this embodiment, the residual delay is calculated based on the azimuth differences in the seismic data and applied to the correction of the velocity model. The azimuth differences in velocity are considered during the velocity update process, thereby improving the accuracy of the velocity model and providing a foundation for subsequent 360-degree migrations, ensuring imaging effects at different azimuth angles.

[0038] S120. Perform omnidirectional multi-ray migration within the Fresnel zone according to the velocity model to obtain a multi-dimensional wavefield gather.

[0039] Specifically, the Fresnel zone can refer to the superposition area of ​​diffracted waves formed during wave propagation. In this embodiment, a comprehensive multi-ray, multi-dimensional migration is performed within the Fresnel zone. Starting from the actual underground reflection point, the dip angle and ray pair information of the underground reflection point are constructed using ray scanning and tracing methods. Specifically, rays can be calculated towards the ground according to parameters such as dip angle, azimuth angle, ray pair angle, and azimuth angle, which can make seismic imaging more accurate and provide richer information.

[0040] It should be noted that conventional Kirchhoff migration is a single-ray imaging method, and the gathers obtained by integrating and differentiating within the aperture are equivalent to information aliasing within the aperture, which does not show any azimuth information. In contrast, omnidirectional multi-ray multi-dimensional migration can simultaneously obtain multi-dimensional information such as the dip angle and azimuth angle of the subsurface strata, as well as the opening angle and azimuth angle of the ray pairs, which can improve the omnidirectional imaging effect.

[0041] Figure 2 This is a schematic diagram of a Kirchhoff offset and an omnidirectional multi-ray offset, provided as an embodiment. Figure 2 As shown, the left side shows the result obtained by Kirchhoff migration, and the right side shows the result obtained by multi-ray migration in all directions. The comparison shows that the position signal indicated by the arrow is enhanced.

[0042] S130. Based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic imaging.

[0043] Specifically, by combining geological characteristics and target orientation, and considering the structural understanding of different types of geology, scanning parameters can be optimized, and seismic imaging of different types of geology can be achieved based on the reconstruction of multi-dimensional wavefields.

[0044] The seismic imaging method provided in this application utilizes a multi-dimensional wavefield reconstruction processing method to provide a higher accuracy velocity model. The omnidirectional multi-ray migration enables a comprehensive scan of stratigraphic and ray parameters from underground reflection points to the surface. The output result set includes multi-dimensional information such as azimuth, reflection angle, and dip angle. Thus, the migration imaging accuracy is improved by using multi-ray combination. Through wavefield reconstruction, different geological needs and target processing requirements can be met, providing a basis for subsequent geological research.

[0045] In one embodiment, the multidimensional wavefield gather (information on the dip angle and ray pair of the subsurface reflection point) includes: the dip angle of the subsurface strata, the dip azimuth angle, the opening angle of the ray pair, and the azimuth angle of the ray pair.

[0046] Specifically, a multidimensional wave field gather can be represented as: Where U refers to ground data, (S x S y R x R y ,t) represents the coordinates of the shot receiver, I represents the underground data, M represents the imaging point, v1 represents the dip angle, v2 represents the dip angle azimuth, γ1 represents the opening angle, and γ2 represents the opening angle azimuth.

[0047] In one embodiment, based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic imaging, including:

[0048] S1310. For geological types with low signal-to-noise ratio, the reflected wave field is identified based on the multi-dimensional wave field gather.

[0049] S1320. Construct an energy weighting function based on the energy difference between the reflected wave and the diffracted wave;

[0050] S1330. Based on the energy weighting function, different types of wavefields are reconstructed to obtain seismic imaging.

[0051] In this embodiment, for geological types with low signal-to-noise ratios (e.g., signal-to-noise ratio below a set threshold), corresponding weights can be assigned to the energy of different waves based on the energy differences (amplitude energy differences) of the wavefield. This allows for the identification and enhancement of reflected wavefields on dip gathers generated by multi-ray, multi-dimensional depth migration. Specifically, an energy weighting function can be used to assign a larger weight to reflected wave energy, highlighting its reconstruction and superposition for imaging. This achieves the goals of improving the internal structure of fracture zones and enhancing the imaging quality of target areas.

[0052] Figure 3 This is a schematic diagram illustrating the imaging optimization effect in a low signal-to-noise ratio region, as described in Embodiment 1. Figure 3 As shown, the left side is the image before optimization, and the right side is the image after optimization using an energy weighting function. The comparison reveals that the signal at the location indicated by the arrow is enhanced. Based on this, the imaging problem of complex low signal-to-noise ratio data can be solved, specifically enhancing the continuity of seismic data and the reliability of seismic interpretation, laying the foundation for subsequent interpretation, geological research, reservoir prediction, and other research work.

[0053] In one embodiment, based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic imaging, including:

[0054] S1340. For small geological bodies, wavefield separation is performed based on the multidimensional wavefield gather and the kinematic difference between reflected and diffracted waves to obtain different types of wavefields.

[0055] S1350: Reconstruct different types of wavefields to obtain seismic images.

[0056] In this embodiment, for small geological bodies (such as geological bodies with an area smaller than a set area, or geological bodies with a Fresnel zone radius of reflected waves smaller than a set length), the kinematic differences between reflected waves and diffracted waves can be used to separate the wave fields, thereby achieving imaging of different types of wave fields based on kinematic characteristics. The purpose is to highlight the imaging feature details of small geological bodies.

[0057] In one embodiment, based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic imaging, including:

[0058] S1360. For fault zones and buried hill fractures, reconstruct the geological-guided wavefield based on the multi-dimensional wavefield gathers and the spatial distribution law of the wavefield.

[0059] S1370. Based on the azimuth differences between the geological-guided wavefield and the reflection angle gather, different types of wavefields are reconstructed to obtain seismic imaging.

[0060] In this embodiment, geological patterns can be analyzed using multi-dimensional wavefield gathers, and geological-guided wavefield reconstruction can be performed using the spatial distribution patterns of wavefields. Furthermore, different types of wavefields can be reconstructed by combining the azimuth differences of reflection angle gathers, which can make the seismic data processing results more reliable and more stable.

[0061] Figure 4 A schematic diagram illustrating the optimized effect of crack imaging in one embodiment is shown below. Figure 4 As shown, the left side is the image before optimization, and the right side is the image after optimization using multi-dimensional wavefield gathers and wavefield spatial distribution patterns. The comparison reveals that, as indicated by the arrows, more fracture details are visible in the coherence slice. Based on this, the weakness of high ambiguity in traditional fracture prediction techniques is effectively reduced, demonstrating significant advantages in the fine-grained exploration and development of fractured oil and gas.

[0062] In one embodiment, the method further includes:

[0063] S100. Correct the well-seismic error of the velocity model according to geostatistical constraints.

[0064] In this embodiment, geostatistical constraints can be used to update the velocity model.

[0065] It should be noted that traditional well-seismic error calculations use a Kriging-like circular approximation method to interpolate the single-well value across the entire work area, without considering the spatial geological structure. In this embodiment, however, during the well-seismic error correction stage, geostatistical constraints are used, incorporating stratigraphic distribution as a constraint term. The planar map shows structural morphology, avoiding the irrationality of traditional single-point well-seismic error calculations applied to the entire area. This eliminates Delta interpolation anomalies caused by uneven well location distribution, resulting in well-seismic errors that better conform to stratigraphic patterns.

[0066] Figure 5 This is a schematic diagram illustrating the effect of well vibration error correction in one embodiment. Figure 5 As shown, the left side represents the wellbore seismic error obtained through traditional calculations, the middle side represents the wellbore seismic error obtained through geostatistical algorithms, and the right side represents the wellbore seismic error corrected based on geostatistical constraints. The comparison reveals that correcting the wellbore seismic error based on geostatistical constraints better reflects geological characteristics, which is beneficial for obtaining accurate and reasonable velocity models. The integrated application of seismic and geological methods further improves the accuracy of velocity models.

[0067] Figure 6 This is a schematic diagram of a seismic imaging process provided as an embodiment. (As shown...) Figure 6 As shown, the seismic imaging process includes:

[0068] Integrated seismic-geological constraint modeling utilizes the comprehensive residual delay of seismic data and geostatistical constraints to update the velocity model, thereby improving the accuracy of the migration velocity field.

[0069] All-round multi-ray multi-dimensional migration, that is, obtaining multi-dimensional information such as azimuth, reflection angle, and tilt angle through all-round multi-ray multi-dimensional migration for wavefield reconstruction;

[0070] When reconstructing different types of wavefields, different geological needs and target processing requirements are considered. Wavefield reconstruction and imaging can be achieved based on energy differences, kinematic feature differences, and wavefield spatial distribution patterns for different geological types, thereby improving the imaging accuracy of different geological regions. Specifically, for imaging of low signal-to-noise ratio areas, energy weighting is used to highlight reflected wavefields and optimize imaging quality; for imaging of small geological bodies, kinematic feature differences are used to highlight imaging details of small geological bodies; for imaging of complex fault zones and prediction of buried hill fractures, wavefield spatial patterns and azimuth differences of reflection angle gathers are used to optimize imaging quality and improve fracture prediction accuracy.

[0071] The seismic imaging method of this application fully utilizes the azimuth differences of the omnidirectional residual delay information and takes into account geological information to improve velocity accuracy through velocity model iteration. Then, it uses an omnidirectional multi-ray multi-dimensional migration method to perform ray beam migration within the Fresnel zone, and simultaneously obtains multi-dimensional information such as the dip angle, azimuth angle of the subsurface strata, and the opening angle and azimuth angle of the ray pairs. Based on different geological needs and target processing requirements, wavefield reconstruction can be performed on this gather to achieve wavefield imaging of different geological targets.

[0072] Furthermore, information analysis and extraction of geological guidance are conducted by utilizing amplitude energy differences, kinematic feature distinctions, and wavefield reconstruction methods based on geological understanding within the wavefield. Specifically, energy weighting functions are constructed using the energy differences between reflected and diffracted waves to achieve energy-weighted imaging, thereby enhancing the signal-to-noise ratio and improving the imaging of continuously reflecting strata and transects. Kinematic differences between reflected and diffracted waves are used for wavefield separation to achieve kinematic feature-based imaging, highlighting imaging details such as small geological bodies. Comprehensive utilization of well data and geological understanding enables imaging based on spatial distribution patterns. The azimuth differences in omnidirectional reflection angle concentration can be used to improve the imaging quality of fracture zones and the prediction accuracy of fractures. Based on this, the identification and imaging of different types of wavefields are achieved, improving seismic imaging quality. A set of wavefield reconstruction processing schemes with high applicability to production projects, targeting low signal-to-noise ratio areas, fracture-developed areas, and fracture-vuggy areas, is developed. This allows for wavefield reconstruction imaging based on different geological needs and target processing requirements, comprehensively improving the quality of seismic data. Simultaneously, it provides more reliable data for exploration and subsequent oil and gas field development, and can be extended to other complex oil and gas reservoir exploration areas. This method has important theoretical and practical guiding significance for relevant exploration areas.

[0073] Figure 7 This is a schematic diagram of a seismic imaging device provided in an embodiment of this application. The seismic imaging device provided in this embodiment includes:

[0074] Correction module 210 is used to correct the velocity model based on the residual delay in all aspects of the seismic data;

[0075] The offset module 220 is used to perform omnidirectional multi-ray offset within the Fresnel zone according to the velocity model to obtain a multi-dimensional wavefield gather.

[0076] The imaging module 230 is used to reconstruct different types of wavefields based on the multi-dimensional wavefield gathers and geological types to obtain seismic images.

[0077] This device utilizes an all-around residual delay correction velocity model and performs all-around multi-ray migration, considering different azimuth angles to reconstruct different types of wavefields, thereby improving the accuracy of seismic imaging.

[0078] Optionally, the imaging module 230 is specifically used for:

[0079] For geological types with low signal-to-noise ratio, the reflected wave field is identified based on the multi-dimensional wave field gather.

[0080] An energy weighting function is constructed based on the energy difference between the reflected wave and the diffracted wave;

[0081] Based on the energy weighting function, different types of wavefields are reconstructed to obtain seismic images.

[0082] Optionally, the imaging module 230 is specifically used for:

[0083] For small geological bodies, wavefield separation is performed based on the multidimensional wavefield gathers and the kinematic differences between reflected and diffracted waves to obtain different types of wavefields.

[0084] By reconstructing different types of wavefields, seismic imaging can be obtained.

[0085] Optionally, the imaging module 230 is specifically used for:

[0086] For fault zones and buried hill fractures, geologically guided wavefields are reconstructed based on the multi-dimensional wavefield gathers and wavefield spatial distribution patterns.

[0087] Based on the azimuth differences between the geological-guided wavefield and the reflection angle gather, different types of wavefields are reconstructed to obtain seismic imaging.

[0088] Optionally, the device may also include:

[0089] The correction module is used to correct well-seismic errors in the velocity model based on geostatistical constraints.

[0090] Optionally, the multidimensional wave field gather includes: the dip angle of the subsurface strata, the dip azimuth angle, the opening angle of the ray pair, and the azimuth angle of the ray pair.

[0091] The seismic imaging device provided in this application embodiment can be used to execute the seismic imaging method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0092] Figure 8 A schematic diagram of an electronic device 10, which can be used to implement embodiments of this application, is shown. The electronic device 10 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 10 may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, user equipment, 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 application described and / or claimed herein.

[0093] like Figure 8As 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.

[0094] 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 and wireless networks.

[0095] 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.

[0096] In some embodiments, the methods described above 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 methods described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the methods of any of the embodiments described above by any other suitable means (e.g., by means of firmware).

[0097] 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.

[0098] Computer programs used to implement the methods of this application 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.

[0099] In the context of this application, 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 can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can 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 fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0100] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device 10, which includes: 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 10. 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).

[0101] 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.

[0102] 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.

[0103] This application also provides a computer program product, including a computer program and / or instructions, which, when executed by a processor, implement the seismic imaging method as described in any of the above embodiments.

[0104] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0105] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. 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 application should be included within the scope of protection of this application.

Claims

1. A seismic imaging method, characterized in that, include: Based on the comprehensive residual delay correction velocity model of earthquake data; Based on the velocity model, perform omnidirectional multi-ray migration within the Fresnel zone to obtain multi-dimensional wavefield gathers. Based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic images.

2. The method according to claim 1, characterized in that, Based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic images, including: For geological types with low signal-to-noise ratio, the reflected wave field is identified based on the multi-dimensional wave field gather. An energy weighting function is constructed based on the energy difference between the reflected wave and the diffracted wave; Based on the energy weighting function, different types of wavefields are reconstructed to obtain seismic images.

3. The method according to claim 1, characterized in that, Based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic images, including: For small geological bodies, wavefield separation is performed based on the multidimensional wavefield gathers and the kinematic differences between reflected and diffracted waves to obtain different types of wavefields. By reconstructing different types of wavefields, seismic imaging can be obtained.

4. The method according to claim 1, characterized in that, Based on the multi-dimensional wavefield gathers and geological types, different types of wavefields are reconstructed to obtain seismic images, including: For fault zones and buried hill fractures, geologically guided wavefields are reconstructed based on the multi-dimensional wavefield gathers and wavefield spatial distribution patterns. Based on the azimuth differences between the geological-guided wavefield and the reflection angle gather, different types of wavefields are reconstructed to obtain seismic imaging.

5. The method according to claim 1, characterized in that, Also includes: The velocity model was corrected for well-seismic errors based on geostatistical constraints.

6. The method according to any one of claims 1-5, characterized in that, The multidimensional wave field gather includes: the dip angle of the subsurface strata, the dip azimuth angle, the opening angle of the ray pair, and the azimuth angle of the ray pair.

7. A seismic imaging device, characterized in that, include: The correction module is used to correct the velocity model based on the residual delay of the seismic data in all aspects. The offset module is used to perform omnidirectional multi-ray offset within the Fresnel zone according to the velocity model to obtain multi-dimensional wavefield gathers. The imaging module is used to reconstruct different types of wavefields based on the multi-dimensional wavefield gathers and geological types to obtain seismic images.

8. An electronic device, characterized in that, include: At least one processor; 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 seismic imaging method as described in any one of claims 1-6.

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

10. A computer program product comprising a computer program and / or instructions, characterized in that, When the computer program and / or instructions are executed by the processor, they implement the seismic imaging method as described in any one of claims 1-6.

Images