Design method, device, equipment, storage medium and product of observation system

Abstract

This disclosure relates to a design method, apparatus, equipment, storage medium, and product for an observation system, applied in the field of seismic data acquisition technology. In this disclosure, multiple sets of seismic data at multiple scales are acquired for a target fault region. Based on each set of seismic data, the corresponding migration imaging data is determined. A relational scale for the observation system is determined based on each set of migration imaging data and each set of seismic data. This relational scale characterizes the relationship between the shot density of the observation system and the migration imaging data for the multi-scale fault region. Through forward modeling of fault regions at different scales, the shot density of the observation system required for high-precision migration imaging of faults at different exploration areas and scales can be confirmed. This allows for more precise deployment of the observation system design parameters corresponding to any geological requirement during seismic data acquisition. Therefore, the accuracy of seismic data acquisition can be improved.

Description

Technical Field

[0001] This disclosure relates to the field of seismic data acquisition technology, and in particular to a design method, apparatus, equipment, storage medium, and product for an observation system. Background Technology

[0002] An observation system refers to the relative positional relationship between the excitation and reception points of seismic waves, or the relative spatial positional relationship between the excitation and reception points. The design of the observation system significantly impacts how seismic waves are excited and received, and how the received seismic wave data is used to construct images of subsurface geological structures. A well-designed observation system is crucial for improving the quality, efficiency, and accuracy of seismic data acquisition.

[0003] Generally, degradation analysis can be performed on the coverage number of relatively high-density seismic data in the target area to establish a relationship curve between the coverage number and the signal-to-noise ratio of the seismic data in the target section. The shot density of the observation system can then be designed based on the coverage number and pixel size to facilitate forward modeling and migration imaging. However, this method of observation system design is not well-suited for imaging complex fault zones and cannot obtain high-precision images of such zones. Therefore, it reduces the accuracy of seismic data acquisition. Summary of the Invention

[0004] This disclosure provides a design method, apparatus, equipment, storage medium, and product for an observation system, which can improve the design accuracy of the observation system.

[0005] In a first aspect, this disclosure provides a design method for an observation system, including:

[0006] Acquire multi-scale, multi-set seismic data of the target fault region;

[0007] Based on each set of seismic data, determine the migration imaging data corresponding to each set of seismic data;

[0008] Based on each set of migration imaging data and each set of seismic data, a relational scale for the observation system is determined. This relational scale is used to characterize the relationship curve between the shot density of the observation system and the migration imaging data in a multi-scale fault region.

[0009] Optionally, determining the relational scale of the observation system based on each set of the migration imaging data and each set of the seismic data includes:

[0010] Obtain the signal-to-noise ratio of each shot in the earthquake data set.

[0011] Based on each set of offset imaging data, determine the corresponding imaging signal-to-noise ratio;

[0012] Based on the single-shot signal-to-noise ratio, a quantization plate is constructed to show the relationship between the imaging signal-to-noise ratio and the shot density of the observation system.

[0013] Optionally, after determining the relational scale of the observation system based on each set of the migration imaging data and each set of the seismic data, the method further includes:

[0014] The task requires obtaining the geological conditions of the target fault area;

[0015] Based on the geological task requirements, determine the target fracture scale;

[0016] The trajectory density of the observation system is determined based on the relationship between the target fracture scale and the observation system's parameters.

[0017] Optionally, determining the migration imaging data corresponding to each set of seismic data based on each set of seismic data includes:

[0018] Based on each set of earthquake data, the shot density of the observation system is degraded to obtain a degraded observation system.

[0019] Based on the degraded observation system, migration imaging is performed to obtain the migration imaging data corresponding to each set of seismic data.

[0020] Optionally, acquiring multiple sets of seismic data for multi-scale fault regions includes:

[0021] Construct a geophysical model of a multi-scale fault region;

[0022] Numerical simulations were performed based on the geophysical model of the multi-scale fault region to obtain multiple sets of single-shot records.

[0023] Noise is added to multiple sets of the single-shot records to obtain multiple sets of the seismic data.

[0024] Optionally, the observation system includes a high-density observation system.

[0025] Secondly, this disclosure provides a design apparatus for an observation system, comprising:

[0026] The acquisition module is used to acquire multiple sets of seismic data at multiple scales for the target fault region.

[0027] The first determining module is used to determine the migration imaging data corresponding to each set of seismic data based on each set of seismic data.

[0028] The second determining module is used to determine the relational scale of the observation system based on each set of migration imaging data and each set of seismic data. The relational scale is used to characterize the relationship curve between the shot density of the observation system and the migration imaging data in the multi-scale fault region.

[0029] Thirdly, this disclosure provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the design method for the observation system described in the above aspects.

[0030] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the design method for the observation system described in the above aspects.

[0031] Fifthly, this disclosure provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the design method for the observation system described above.

[0032] This disclosure involves acquiring multiple sets of seismic data at multiple scales for a target fault region. Based on each set of seismic data, the corresponding migration imaging data is determined. A relational scale for the observation system is determined based on each set of migration imaging data and each set of seismic data. This relational scale characterizes the relationship between the shot density of the observation system and the migration imaging data for the multi-scale fault region. Through forward modeling of fault regions at different scales, the shot density of the observation system required for high-precision migration imaging of faults at different exploration areas and scales can be confirmed. This allows for more precise deployment of the observation system's design parameters to meet any geological requirements during seismic data acquisition. Therefore, the accuracy of seismic data acquisition can be improved. Attached Figure Description

[0033] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0034] Figure 1 A flowchart illustrating a design method for an observation system provided in this disclosure.

[0035] Figure 2 A flowchart of the relational plate method for determining the observation system provided in this disclosure.

[0036] Figure 3 A flowchart of the method for acquiring seismic data provided in this disclosure.

[0037] Figure 4 Another flowchart for the design method of an observation system provided in this disclosure.

[0038] Figure 5 This is a schematic diagram of seismic data under different signal-to-noise ratio conditions provided in this disclosure.

[0039] Figure 6 This is a schematic diagram of fracture zone imaging under different signal-to-noise ratio conditions provided in this disclosure.

[0040] Figure 7 This is a schematic diagram of the structure of a design device for an observation system provided in this disclosure. Detailed Implementation

[0041] To enable those skilled in the art to better understand the technical solution of this application, the application scenario of this application will be described first below.

[0042] Complex fault zones are important areas for the accumulation of oil, gas, and coalbed methane resources. Rock fracturing and magmatic activity within these fault zones may provide favorable conditions for the formation of these resources. Therefore, complex fault zones are an important research subject in oil, gas, and coalbed methane exploration. The seismic wavefields in complex fault zones are complex, with well-developed diffraction waves, making seismic data acquisition and imaging challenging. Seismic data acquisition plays a crucial role in oil and gas exploration, coalfield exploration, and engineering geological investigation. By understanding the propagation patterns of seismic waves, the properties and morphology of underground rock strata can be inferred, providing a scientific basis for resource exploration and engineering construction. Improving the accuracy of seismic data acquisition can enhance the precision of migration imaging in complex fault zones.

[0043] Current observation system design techniques mainly involve analyzing the degradation of coverage times in relatively high-density seismic data in the target area, establishing a relationship curve between coverage times and the signal-to-noise ratio of seismic data in the target layer, determining the coverage times that balance geological performance and acquisition costs based on the inflection point of the relationship curve, calculating the cell size that meets the requirements for lateral resolution, the highest non-aliasing frequency, and the migration aliasing-free frequency, and determining the shot density of the observation system in the target area based on the calculated coverage times and cell size.

[0044] However, this observation system design method has certain flaws. Determining the coverage number and element size separately fails to consider the combined effect of these two parameters, resulting in a lack of specificity for imaging complex fault zones and an inability to obtain high-precision images of such zones. Therefore, it reduces the accuracy of seismic data acquisition.

[0045] To address the aforementioned technical problems, this disclosure provides a design method, apparatus, equipment, storage medium, and product for an observation system. This disclosure involves acquiring multiple sets of seismic data at multiple scales from a target fault region. Based on each set of seismic data, the corresponding migration imaging data is determined. A relational scale for the observation system is determined based on each set of migration imaging data and each set of seismic data. This relational scale characterizes the relationship between the shot density of the observation system and the migration imaging data in the multi-scale fault region. Through forward modeling of fault regions at different scales, the shot density of the observation system required for high-precision migration imaging of faults at different exploration areas and scales can be confirmed. This allows for more precise deployment of the observation system's design parameters to meet any geological requirements during seismic data acquisition. Therefore, the accuracy of seismic data acquisition can be improved.

[0046] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0047] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure 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 this disclosure 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 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.

[0048] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0049] Example 1

[0050] Figure 1 This is a flowchart illustrating a design method for an observation system provided in this disclosure. Figure 1 As shown, the method includes:

[0051] S101: Acquire multiple sets of seismic data at multiple scales for the target fault region.

[0052] Specifically, within a pre-defined seismic exploration and development area, target fault zones with existing fractures are identified. Seismic waves are generated by blasting into these target fault zones, acquiring seismic data at different scales. The fracture characteristics of the target fault zone can then be determined based on this data. Here, different scales represent faults of varying lengths.

[0053] S102: Based on each set of seismic data, determine the migration imaging data corresponding to each set of seismic data.

[0054] Specifically, after obtaining seismic data by generating seismic waves, the data needs to be migrated to reconstruct the original propagation path of the seismic waves through the geological structure, thus obtaining migration imaging data. Higher-precision migration imaging data can help explorers better understand the distribution of underground oil and gas reservoirs, improving exploration efficiency and success rate.

[0055] S103: Determine the relational scale of the observation system based on each set of migration imaging data and each set of seismic data.

[0056] Specifically, the signal-to-noise ratio (SNR) of a single shot can be determined based on seismic data, thus obtaining the SNR of fractures at different scales. Similarly, the corresponding imaging SNR can be determined based on migration imaging data. Different parameter settings in the observation system during seismic wave generation will also affect the seismic data results, thereby affecting the SNR of both single shots and imaging SNR. Among these, shot density, as a crucial parameter in the observation system, has a significant impact on the system's design.

[0057] Extensive forward modeling studies and practical seismic data applications have demonstrated that the signal-to-noise ratio (SNR) of seismic data is a key factor affecting fault identification. During seismic acquisition, the most effective means to improve the SNR of a single shot is combined reception and increasing the number of times the observation system covers the target area. In migration imaging, sufficient wavefield sampling effectively reduces noise introduced by migration, thereby improving the imaging SNR. The most important indicator for measuring the sufficiency of wavefield sampling is the shot density of the observation system. With advancements in seismic acquisition equipment and technology, and a shift in acquisition philosophy, combined reception has gradually evolved into single-point reception. Therefore, the most effective method to improve the imaging accuracy of complex faults is to increase the number of times the target area is covered and to increase the shot density of the observation system.

[0058] In this embodiment, a relationship gauge between shot density and imaging signal-to-noise ratio is constructed using the single-shot signal-to-noise ratio corresponding to seismic data of faults at different scales as constraints. This relationship gauge characterizes the relationship curve between shot density and migration imaging data of the observation system in multi-scale fault regions.

[0059] This disclosure involves acquiring multiple sets of seismic data at multiple scales for a target fault region. Based on each set of seismic data, the corresponding migration imaging data is determined. A relational scale for the observation system is determined based on each set of migration imaging data and each set of seismic data. This relational scale characterizes the relationship between the shot density of the observation system and the migration imaging data for the multi-scale fault region. Through forward modeling of fault regions at different scales, the shot density of the observation system required for high-precision migration imaging of faults at different exploration areas and scales can be confirmed. This allows for more precise deployment of the observation system's design parameters to meet any geological requirements during seismic data acquisition. Therefore, the accuracy of seismic data acquisition can be improved.

[0060] Example 2

[0061] Based on the above embodiments, Figure 2 The flowchart of the relational plate method for determining the observation system provided in this disclosure is as follows: Figure 2 As shown.

[0062] Exemplary methods for determining the relational scale of the observation system based on each set of migration imaging data and each set of seismic data include:

[0063] S201: Obtain the signal-to-noise ratio of a single shot for each set of seismic data.

[0064] Specifically, the signal-to-noise ratio (SNR) per shot refers to the ratio between the signal intensity and noise intensity recorded at a single shot point in seismic exploration. After generating seismic waves, the SNR of the seismic data is calculated based on the signal and noise intensities in the received seismic data.

[0065] S202: Determine the corresponding imaging signal-to-noise ratio based on each set of offset imaging data.

[0066] Specifically, after obtaining seismic data by generating seismic waves, the data needs to be migrated to restore the original propagation path of the seismic waves through the geological structure, thus obtaining migration imaging data. Higher-precision migration imaging data can help explorers better understand the distribution of underground oil and gas reservoirs, improving exploration efficiency and success rate. In the imaging field, signal usually refers to the desired image information, while noise is the random variation in image density. In this embodiment, image density is related to shot density.

[0067] S203: Based on the single-shot signal-to-noise ratio, a scale is constructed to measure the relationship between the imaging signal-to-noise ratio and the shot density of the observation system.

[0068] Specifically, as mentioned earlier, this embodiment acquired seismic data at different scales. Therefore, it can be seen that different scales correspond to different single-shot signal-to-noise ratios (SNRs), and under the same single-shot SNR, the relationship between the imaging SNR and different shot densities can be determined. This allows for the confirmation of the shot density of the observation system required for high-precision migration imaging of faults at different exploration areas and scales, improving the accuracy of seismic data acquisition.

[0069] Example 3

[0070] Based on the above embodiments, after determining the relational scale of the observation system according to each set of migration imaging data and each set of seismic data, the method further includes:

[0071] The task requires obtaining the geological information of the target fault area.

[0072] Specifically, based on the progress of seismic exploration and development, the current geological requirements for the target fault area are determined.

[0073] Determine the target fault scale based on the geological task requirements.

[0074] Specifically, in the target fault region, there may be faults of multiple scales. Determining the scale of the target fault can more quickly and accurately determine the number of blast channels used to generate seismic waves.

[0075] The density of the blast channel in the observation system is determined based on the relationship between the target fracture scale and the observation system.

[0076] Specifically, as mentioned above, a scale was pre-established to measure the relationship between the target's expected imaging signal-to-noise ratio and the ballistic density under different fracture scales.

[0077] Example 4

[0078] Based on the above embodiments, an exemplary method for determining the migration imaging data corresponding to each set of seismic data includes:

[0079] Based on each set of seismic data, the shot density of the observation system is degraded to obtain a degraded observation system.

[0080] Specifically, observation system degradation refers to thinning the seismic data acquired through forward modeling or actual acquisition. For example, extracting shots 1, 3, 5, 7, 9, 11, 13… from the original shot record doubles the shot spacing of the new observation system, while extracting shots 1, 5, 9, 13… quadruples the shot spacing. Similarly, seismic traces, shot lines, and receiver lines can be thinned, thereby increasing trace spacing, shot line spacing, and receiver line spacing, respectively. Because parameters such as shot spacing, trace spacing, shot line spacing, and receiver line spacing change after data thinning, the corresponding element size and coverage number in the observation system also change, resulting in a degraded new observation system. Based on this, seismic imaging from the actual acquisition system and the degraded observation system can be compared to analyze the influence of key acquisition parameters on seismic imaging.

[0081] In existing technologies, degradation processing experiments were conducted using 3D seismic data from the Beihai Sea to investigate the impact of parameters such as coverage number, maximum shot-receiver distance, and lateral receiver spacing on the signal-to-noise ratio (SNR), wavelet consistency, seismic properties, and deep reflection imaging. Degradation processing experiments were also conducted using high-resolution 3D seismic data from the Junggar Basin to investigate the effects of changes in parameters such as array size, shot count, and array length on the SNR, resolution, and reflection energy. Degradation processing of high-density 3D seismic data was performed to explore the relationship between shot density and imaging, SNR, and cost. Degradation processing of a finely detailed array observation system was conducted using high-precision 3D seismic data from the Yongxin area, and the impact of different array sizes and coverage numbers on the SNR was analyzed. Degradation processing of high-precision 3D seismic data from the Tarim Oilfield was also performed to investigate the impact of different array sizes, coverage numbers, and shot-receiver distances on imaging fractured-vuggy reservoirs, and optimization schemes for acquisition parameters for fractured-vuggy reservoirs were proposed. Degradation processing of shot density in high-density 3D seismic data identified a balance between geological tasks and economic costs. The observation system degradation of the wide-azimuth 3D seismic data of Shanian was investigated, and the effects of different acquisition azimuths and coverage times on the imaging of the igneous strata were analyzed.

[0082] Migration imaging was performed based on the degraded observation system to obtain migration imaging data corresponding to each set of seismic data.

[0083] Specifically, degradation processing of observation systems can remove unnecessary redundant information, reducing the workload of data acquisition and processing. This helps to lower exploration or monitoring costs and improve overall efficiency. Through degradation processing, the resources of the observation system, such as the number and location of sensors, can be allocated more rationally, maximizing resource utilization and improving the overall performance of the observation system. Therefore, migration imaging based on seismic data from a degradation observation system yields more accurate imaging results.

[0084] Example 5

[0085] Based on the above embodiments, Figure 3 A flowchart of the method for acquiring seismic data provided in this disclosure, such as Figure 3 As shown.

[0086] Exemplary methods for acquiring multiple sets of seismic data for multi-scale fault regions include:

[0087] S301: Construct a geophysical model of a multi-scale fault region.

[0088] Specifically, based on actual geological data, reservoir models incorporating fractures of different scales are designed. Seismic physics simulation technology is used to simulate seismic wave propagation in these models, thereby constructing geophysical models of multi-scale fault regions. These geophysical models of faults at different scales have wide-ranging applications in oil and gas exploration, geological research, and earthquake prediction.

[0089] S302: Numerical simulation based on a geophysical model of a multi-scale fault region yielded multiple sets of single-shot records.

[0090] Specifically, numerical simulations were performed on multiple constructed geophysical models, namely, simulating single-shot records of seismic waves generated by blasting, expanding the data volume, and forming a more complete single-shot record.

[0091] S303: Noise is added to multiple sets of single-shot records to obtain multiple sets of seismic data.

[0092] Specifically, as mentioned earlier, single-shot records are obtained through numerical simulation and therefore do not contain noise data, while seismic data obtained from normal blasting of actual strata is affected by noise. Adding noise to each set of single-shot records can generate seismic data with different signal-to-noise ratio levels.

[0093] Example 6

[0094] Based on the above embodiments, the observation system includes a high-density observation system.

[0095] Specifically, high-density observation systems utilize a large number of sensors to collect real-time data on the environment or objects. The system processes and analyzes this sensor data to obtain more accurate and comprehensive observation results. By increasing the number and density of sensors, high-density observation systems can significantly improve observation accuracy, making the results more accurate and reliable. The high sensitivity of high-density observation systems allows them to keenly perceive subtle changes in the environment, providing comprehensive observation data. High-density observation systems typically employ redundant designs; when one sensor fails, others can continue to operate, ensuring the normal operation of the system. Through parallel processing and other technologies, high-density observation systems can rapidly acquire and process observation data, improving observation efficiency.

[0096] Example 7

[0097] Based on the above embodiments, this embodiment provides an application example. Figure 4 Another flowchart illustrating the design method of an observation system provided in this disclosure. Figure 4 As shown, the method includes:

[0098] S401: Constructing geophysical models of fractures at different scales.

[0099] Specifically, based on actual geological data, reservoir models incorporating fractures at different scales are designed. Seismic physics simulation techniques are used to simulate seismic wave propagation in the models, thereby constructing geophysical models of multi-scale fault zones.

[0100] S402: Numerical simulation based on geophysical models.

[0101] Specifically, numerical simulations were performed on multiple constructed geophysical models to simulate single-shot records at different locations, thereby expanding the data volume and forming a more complete single-shot record.

[0102] S403: Add noise to single-shot records to generate seismic data with different signal-to-noise ratio levels.

[0103] Specifically, single-shot records are obtained through numerical simulation and therefore do not contain noise data, while seismic data obtained from normal blasting of actual strata are affected by noise. Adding noise to each set of single-shot records can generate seismic data with different signal-to-noise ratio levels. Figure 5 A schematic diagram of seismic data under different signal-to-noise ratio conditions, such as... Figure 5 As shown, the signal-to-noise ratio increases sequentially from left to right, and the resulting seismic data gradually becomes blurry and the clarity decreases.

[0104] S404: Based on seismic data at different signal-to-noise ratio levels, the shot density of the observation system is degraded, and migration imaging is performed separately to obtain migration imaging data.

[0105] Specifically, degradation processing of observation systems can remove unnecessary redundant information, reducing the workload of data acquisition and processing. This helps to lower exploration or monitoring costs and improve overall efficiency. Through degradation processing, the resources of the observation system, such as the number and location of sensors, can be allocated more rationally, maximizing resource utilization and improving the overall performance of the observation system. Therefore, migration imaging based on seismic data from a degradation observation system yields more accurate imaging results.

[0106] S405: Determine the signal-to-noise ratio of fracture imaging at different scales based on offset imaging data.

[0107] Specifically, higher-precision offset imaging data can help prospectors better understand the distribution of underground oil and gas reservoirs, improving exploration efficiency and success rate. In the field of imaging, signal usually refers to the desired image information, while noise is the random variation of image density. In this embodiment, image density is related to shot density. Figure 6 Schematic diagrams of fracture zone imaging under different signal-to-noise ratio conditions, such as... Figure 6 As shown, the signal-to-noise ratio increases sequentially from left to right, and the resulting seismic data gradually becomes blurry and the clarity decreases.

[0108] S406: Establish a quantitative model for the relationship between the imaging signal-to-noise ratio and the shot density of the observation system, with the single-shot signal-to-noise ratio of fractures at different scales as a constraint.

[0109] Specifically, different scales correspond to different single-shot signal-to-noise ratios (SNRs), and under the same single-shot SNR, a quantification of the relationship between the imaging SNR and different shot densities can be determined. This allows for the confirmation of the shot density of the observation system required for high-precision migration imaging of faults at different scales and in different exploration areas, thereby improving the accuracy of seismic data acquisition.

[0110] Example 8

[0111] Figure 7 This is a schematic diagram of the structural design of an observation system provided in this disclosure. Figure 7 As shown, the device 700 includes: an acquisition module 710, a first determination module 720, and a second determination module 730.

[0112] The acquisition module 710 is used to acquire multiple sets of seismic data at multiple scales for the target fault region.

[0113] The first determining module 720 is used to determine the migration imaging data corresponding to each set of seismic data based on each set of seismic data.

[0114] The second determining module 730 is used to determine the relationship plate of the observation system based on each set of migration imaging data and each set of seismic data. The relationship plate is used to characterize the relationship curve between the shot density of the observation system and the migration imaging data in the multi-scale fault region.

[0115] Optionally, determining the relational scale of the observation system based on each set of the migration imaging data and each set of the seismic data includes:

[0116] Obtain the signal-to-noise ratio of each shot in the earthquake data set.

[0117] Based on each set of offset imaging data, determine the corresponding imaging signal-to-noise ratio;

[0118] Based on the single-shot signal-to-noise ratio, a quantization plate is constructed to show the relationship between the imaging signal-to-noise ratio and the shot density of the observation system.

[0119] Optionally, after determining the relational scale of the observation system based on each set of the migration imaging data and each set of the seismic data, the method further includes:

[0120] The task requires obtaining the geological conditions of the target fault area;

[0121] Based on the geological task requirements, determine the target fracture scale;

[0122] The trajectory density of the observation system is determined based on the relationship between the target fracture scale and the observation system's parameters.

[0123] Optionally, determining the migration imaging data corresponding to each set of seismic data based on each set of seismic data includes:

[0124] Based on each set of earthquake data, the shot density of the observation system is degraded to obtain a degraded observation system.

[0125] Based on the degraded observation system, migration imaging is performed to obtain the migration imaging data corresponding to each set of seismic data.

[0126] Optionally, acquiring multiple sets of seismic data for multi-scale fault regions includes:

[0127] Construct a geophysical model of a multi-scale fault region;

[0128] Numerical simulations were performed based on the geophysical model of the multi-scale fault region to obtain multiple sets of single-shot records.

[0129] Noise is added to multiple sets of the single-shot records to obtain multiple sets of the seismic data.

[0130] Optionally, the observation system includes a high-density observation system.

[0131] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the design method of the observation system described in the above embodiments.

[0132] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the design method for the observation system described in the above embodiments.

[0133] In some embodiments of this example, a computer program product is provided, including a computer program / instructions, which, when executed by a processor, implements the steps of the design method for the observation system described in the above embodiments.

[0134] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component for performing the methods in the above embodiments. The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof. The computer-readable storage medium may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0135] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0136] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0137] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0138] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0139] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0140] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0141] While the embodiments disclosed herein are as described above, the foregoing content is merely for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Any person skilled in the art to which this disclosure pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope of this disclosure; however, the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.

Claims

1. A design method for an observation system, characterized in that, include: Acquire multi-scale, multi-set seismic data of the target fault region; Based on each set of seismic data, determine the migration imaging data corresponding to each set of seismic data; Based on each set of migration imaging data and each set of seismic data, a relational scale for the observation system is determined. This relational scale is used to characterize the relationship curve between the shot density of the observation system and the migration imaging data in a multi-scale fault region.

2. The method according to claim 1, characterized in that, The step of determining the relational scale of the observation system based on each set of migration imaging data and each set of seismic data includes: Obtain the signal-to-noise ratio of each shot in the earthquake data set. Based on each set of offset imaging data, determine the corresponding imaging signal-to-noise ratio; Based on the single-shot signal-to-noise ratio, a quantization plate is constructed to show the relationship between the imaging signal-to-noise ratio and the shot density of the observation system.

3. The method according to claim 1, characterized in that, After determining the relational scale of the observation system based on each set of the migration imaging data and each set of the seismic data, the method further includes: The task requires obtaining the geological conditions of the target fault area; Based on the geological task requirements, determine the target fracture scale; The trajectory density of the observation system is determined based on the relationship between the target fracture scale and the observation system's parameters.

4. The method according to claim 1, characterized in that, The step of determining the migration imaging data corresponding to each set of seismic data based on each set of seismic data includes: Based on each set of earthquake data, the shot density of the observation system is degraded to obtain a degraded observation system. Based on the degraded observation system, migration imaging is performed to obtain the migration imaging data corresponding to each set of seismic data.

5. The method according to claim 1, characterized in that, The acquisition of multiple sets of seismic data for multi-scale fault regions includes: Construct a geophysical model of a multi-scale fault region; Numerical simulations were performed based on the geophysical model of the multi-scale fault region to obtain multiple sets of single-shot records. Noise is added to multiple sets of the single-shot records to obtain multiple sets of the seismic data.

6. The method according to claim 1, characterized in that, The observation system includes a high-density observation system.

7. A design device for an observation system, characterized in that, include: The acquisition module is used to acquire multiple sets of seismic data at multiple scales for the target fault region. The first determining module is used to determine the migration imaging data corresponding to each set of seismic data based on each set of seismic data. The second determining module is used to determine the relational scale of the observation system based on each set of migration imaging data and each set of seismic data. The relational scale is used to characterize the relationship curve between the shot density of the observation system and the migration imaging data in the multi-scale fault region.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.

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