Earthquake crack prediction method, device and equipment
By combining a radial observation system with component geophones, the earthquake crack prediction process is simplified, resource consumption is reduced, prediction accuracy is improved, and the problems of complex operation and high cost in existing technologies are solved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-03
- Publication Date
- 2026-06-05
AI Technical Summary
Existing methods for predicting earthquake cracks require significant human and material resources and involve complex procedures, making it difficult to efficiently obtain information on underground cracks.
A radial observation system is used to generate seismic shear waves through a shear wave excitation source. Multiple component geophones are distributed around the radiation center to acquire component data along different directions. Combined with dynamic correction and in-phase superposition techniques, the direction of underground fractures is analyzed.
It simplifies the deployment and operation of the observation system, reduces the consumption of human and material resources, and improves the accuracy and efficiency of crack prediction.
Smart Images
Figure CN122151165A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of earthquake detection technology, and in particular to a method, apparatus, and device for predicting earthquake cracks. Background Technology
[0002] Seismic exploration is a method that uses seismic waves to detect underground structures and material distribution. It is widely used in the exploration and development of oil, natural gas, and mineral resources, as well as the prevention and control of geological disasters. Shear waves, a type of seismic wave, are characterized by their vibration direction being perpendicular to the propagation direction, and can provide more information about the underground environment.
[0003] In related technologies, the direction of underground fissures is typically obtained by using a method of horizontally orthogonally exciting shear waves twice, combined with multi-component horizontal component receiving technology. This method involves the following observation system: shear waves are excited in two vertical directions, and the horizontal component data is recorded using a detector array. By processing and analyzing this data, the direction of the underground fissures can be inferred.
[0004] However, while the aforementioned conventional observation systems can acquire more underground information, their deployment and operation are quite complex and require a large amount of human and material resources. Summary of the Invention
[0005] This application provides a method, apparatus, and device for predicting earthquake cracks. By adjusting the layout of the detectors and seismic source, the manpower required to acquire earthquake crack information can be reduced, thereby improving the accuracy of the prediction results. The technical solution is as follows:
[0006] On the one hand, a method for predicting earthquake cracks is provided, the method comprising:
[0007] Seismic shear waves are generated by a shear wave excitation source;
[0008] The shear wave data acquired by multiple component geophones based on the seismic shear wave are obtained. The multiple component geophones are distributed in a radial arrangement structure in the study area with the shear wave excitation source as the radiation center.
[0009] Acquire the first component data along the first direction and the second component data along the second direction from the shear wave data. The first direction includes the radiation direction of the detection position of the component detector relative to the shear wave excitation source, and the second direction includes the component direction perpendicular to the radiation direction.
[0010] Based on the waveform changes represented by the first component data and the second component data collected by the multiple component geophones, and the distribution location of the multiple component geophones, the seismic cracks in the study area and the crack directions of the seismic cracks are determined.
[0011] On the other hand, an earthquake crack prediction device is provided, the device comprising:
[0012] The excitation module is used to excite seismic shear waves through a shear wave excitation source;
[0013] The acquisition module is used to acquire shear wave data collected by multiple component geophones based on the seismic shear wave. The multiple component geophones are distributed in a radial arrangement structure in the study area with the shear wave excitation source as the radiation center.
[0014] The acquisition module is further configured to acquire the first component data along the first direction and the second component data along the second direction in the shear wave data, wherein the first direction includes the radiation direction of the detection position of the component detector relative to the shear wave excitation source, and the second direction includes the component direction perpendicular to the radiation direction.
[0015] The crack prediction module is used to determine the seismic cracks and their directions in the study area based on the waveform changes represented by the first component data and the second component data collected by the multiple component geophones, as well as the distribution of the multiple component geophones.
[0016] In an optional embodiment, the plurality of component detectors are distributed along multiple radiation lines centered on the transverse wave excitation source.
[0017] The excitation module is also used to excite the seismic shear wave along the i-th radiation line through the shear wave excitation source, where i is a positive integer;
[0018] The acquisition module is also used to acquire the shear wave data collected by at least two component detectors arranged on the i-th radiation line based on the seismic shear wave.
[0019] In an optional embodiment, the excitation module is further configured to excite the seismic shear wave along the (i+1)th radiation line by means of the shear wave excitation source after the component detector on the i-th radiation line has completed the acquisition of the shear wave data.
[0020] The acquisition module is further configured to acquire the shear wave data collected by at least two component geophones arranged on the (i+1)th radiation line based on the seismic shear wave, until the data acquisition by the component geophones on the multiple radiation lines is completed.
[0021] In an optional embodiment, the component detectors are distributed along 36 radiation lines centered on the transverse wave excitation source; the angle between any two adjacent radiation lines is 10°.
[0022] In an optional embodiment, the seismic shear wave includes a first seismic shear wave and a second seismic shear wave;
[0023] The excitation module is also used to excite the first seismic shear wave through the shear wave excitation source;
[0024] The acquisition module is also used to acquire first shear wave data collected by multiple component detectors based on the first seismic shear wave;
[0025] The excitation module is also used to excite the second seismic shear wave through the shear wave excitation source;
[0026] The acquisition module is also used to acquire second shear wave data collected by multiple component geophones based on the second seismic shear wave;
[0027] The acquisition module is further configured to integrate the first sub-component data along the first direction in the first shear wave data and the second sub-component data along the first direction in the second shear wave data to obtain the first component data; and to integrate the third sub-component data along the second direction in the first shear wave data and the fourth sub-component data along the second direction in the second shear wave data to obtain the second component data.
[0028] In an optional embodiment, the acquisition module is further configured to acquire first wave velocity data along the first direction in the shear wave data as the first component data; and acquire second wave velocity data along the second direction in the shear wave data as the second component data.
[0029] In an optional embodiment, the acquisition module is further configured to acquire the first component data along the first direction and the second component data along the second direction from the shear wave data collected by the multiple component detectors respectively; and to perform dynamic correction and co-directional superposition on the first component data and the second component data from the multiple shear wave data to obtain the corrected first component data and the corrected second component data.
[0030] In an optional embodiment, the crack prediction module is further configured to acquire P-wave data of the study area based on seismic P-wave acquisition; and determine the seismic cracks and crack directions of the seismic cracks in the study area by combining the waveform changes represented by the P-wave data, the first component data, and the second component data, as well as the distribution positions of the multiple component geophones.
[0031] On the other hand, a computer device is provided, the computer device including a processor and a memory, the memory storing at least one instruction, at least one program, code set or instruction set, the at least one instruction, the at least one program, the code set or instruction set being loaded and executed by the processor to implement the earthquake crack prediction method as described in any of the embodiments of this application above.
[0032] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction, at least one program, code set, or instruction set is stored therein, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the earthquake crack prediction method as described in any of the embodiments of this application above.
[0033] On the other hand, a computer program product or computer program is provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the earthquake crack prediction method described in any of the above embodiments.
[0034] The beneficial effects of the technical solutions provided in this application include at least the following:
[0035] By utilizing the characteristics of shear waves and setting up a radial observation system to acquire multi-directional component data from a three-component geophone, it is possible to analyze and process seismic signals in multiple directions based on the component data, thereby obtaining information on the direction of underground fractures. The deployment and operation of the radial observation system are relatively simple, requiring less manpower and material resources compared to other observation systems, thus reducing detection costs. By changing the angle of the radial observation system, the accuracy of fracture prediction direction can be improved, reducing errors caused by the difficulty in accurately predicting shear wave propagation paths and energy attenuation. Attached Figure Description
[0036] To more clearly illustrate the technical solutions in the embodiments of this application, 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0037] Figure 1 This is a schematic diagram of an earthquake crack prediction system provided in an exemplary embodiment of this application;
[0038] Figure 2 This is a flowchart of a method for predicting earthquake cracks provided in an exemplary embodiment of this application;
[0039] Figure 3 This is a schematic diagram of a radial observation system provided in an exemplary embodiment of this application;
[0040] Figure 4 This is a schematic diagram of the first component data and the second component data provided in an exemplary embodiment of this application;
[0041] Figure 5 This is a schematic diagram of the survey results data of an anisotropic wave field provided by a radial receiving array according to an exemplary embodiment of this application;
[0042] Figure 6 This is a structural block diagram of an earthquake crack prediction device provided in an exemplary embodiment of this application;
[0043] Figure 7 This is a structural block diagram of a computer device provided in an exemplary embodiment of this application. Detailed Implementation
[0044] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.
[0045] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0046] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.
[0047] It should be noted that all information and data involved in this application are authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions.
[0048] It should be understood that although the terms first, second, etc., may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, a first parameter may also be referred to as a second parameter, and similarly, a second parameter may also be referred to as a first parameter. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."
[0049] First, a brief introduction to the terms used in the embodiments of this application:
[0050] Seismic waves: Seismic waves are elastic waves generated when an earthquake occurs. When rocks inside the Earth are subjected to stress and fracture or shift, energy propagates from the epicenter in the form of waves. They are an important tool for studying the Earth's internal structure.
[0051] Seismic waves include body waves, which are waves that can propagate within the Earth. These are further divided into longitudinal waves (P-waves) and transverse waves (S-waves).
[0052] Longitudinal waves propagate in the same direction as the particle vibration, while transverse waves propagate perpendicular to the particle vibration. Transverse waves can be used to predict the distribution of underground fissures.
[0053] Component detectors: These are special detectors used in fields such as seismic exploration, and mainly include three-component detectors and four-component detectors.
[0054] The component detector used in this application is a three-component detector, with the following structural features: each three-component detector contains three mutually perpendicular sensors. These three sensors are used to record the three components of the particle vibration velocity vector, and can simultaneously receive and record different types of seismic wave signals such as P-waves, S-waves, and converted waves, and convert the seismic wave data into electrical signals.
[0055] In a three-component detector, the three directional components typically refer to the X-axis, Y-axis, and Z-axis. With the ground as a reference, the Z-axis is vertical, with upward as the positive direction, and primarily records longitudinal wave information. The X-axis and Y-axis are horizontal and perpendicular to each other, used to record transverse wave vibrations in two different horizontal directions.
[0056] In this application, the first component data along the first direction and the second component data along the second direction in the transverse wave data acquired by the component detector refer to the component data in the X-axis direction and the Y-axis direction.
[0057] Observation System: In the field of seismic exploration, the observation system refers to the relative positions of the excitation and receiving points and their spatial relationship with underground geological structures. Its design purpose is to effectively obtain information about underground geological structures. The components are as follows: (1) Excitation System: Used to generate seismic waves. Common excitation sources include explosive sources and non-explosive sources. Explosive sources generate powerful seismic waves by detonating explosives at a certain depth underground. Non-explosive sources include controlled sources, etc. Controlled sources use mechanical devices to generate vibrations with controllable frequencies. After continuous vibration for a period of time, relevant technologies are used to extract effective information from the received signals. (2) Receiving System: Mainly seismic detectors. A seismic detector is a device that can convert ground vibrations (caused by seismic waves) into electrical signals. It can convert mechanical motion into electrical signals, which are then amplified, filtered, and recorded. Multiple seismic detectors are arranged in a certain way to form a seismic array, such as a linear array or an area array, to receive seismic wave signals from different directions and depths.
[0058] The observation system in this application is radial, consisting of a shear wave excitation source and multiple component detectors. The multiple component detectors are arranged radially around the shear wave excitation source, with at least two component detectors in each radial direction.
[0059] Normal Moveout Correction (NMO): NMO is primarily used in seismic exploration data processing. Because the travel time of reflected waves varies at different source-receiver offsets (distances between the excitation and reception points) as they propagate from underground reflection points to the surface geophone, NMO aims to correct the travel time of reflected waves from non-zero source-receiver offsets to an equivalent travel time at zero source-receiver offsets. This ensures that the phase axis of the reflected waves on the same reflection interface becomes a horizontal straight line after correction.
[0060] NMO velocity (dynamic correction velocity) is a velocity parameter used in the dynamic correction (NMO) process of seismic data processing. It refers to the velocity used to flatten the phase axis of the reflected wave after dynamic correction, assuming a horizontal subsurface reflection interface. The dynamic correction amount is calculated based on the NMO velocity, serving as the amount to advance the reflected wave time, thus achieving dynamic correction.
[0061] In-phase superposition: In-phase superposition is an important method in seismic data processing. It refers to superimposing multiple seismic signals with the same phase. In seismic exploration, multiple firing (shotting) and receiving are usually performed at the same location to obtain multiple seismic records. The purpose of in-phase superposition is to enhance the effective signal and suppress random noise. When multiple seismic signals are in phase, their waveforms are aligned in time. According to the principle of signal superposition, effective signals will reinforce each other when superimposed in phase because the amplitudes of in-phase signals are added together. Random noise, because its phase is random, will have its energy dispersed and weakened after multiple superpositions.
[0062] Anisotropy refers to the physical properties (such as elasticity, electrical conductivity, and thermal conductivity) of a material or medium exhibiting different characteristics in different directions. In the fields of geology and geophysics, underground rocks and other media are often not isotropic (isotropy means that physical properties are the same in all directions), but rather anisotropic.
[0063] The anisotropy of subsurface rocks affects seismic wave propagation, making its development more complex than in isotropic media. Shear waves split in anisotropic media, producing fast and slow shear waves. The polarization direction of fast shear waves is typically parallel to the anisotropic symmetry axis of the subsurface medium (e.g., the direction of a fracture), while the polarization direction of slow shear waves is perpendicular to it. This splitting phenomenon provides important clues for detecting anisotropic features such as subsurface fractures.
[0064] Seismic detection is an extremely important detection method. It primarily utilizes the changes in the reflection and refraction properties of seismic waves as they propagate underground due to different structures and materials to detect underground structural conditions and material distribution. In the exploration and development of oil, natural gas, and mineral resources, seismic detection can accurately determine the location and reserve range of potential resources, providing a solid basis for effective resource extraction. Simultaneously, in the prevention and control of geological disasters, such as monitoring seismic activity zones and identifying potential landslide-prone areas, seismic detection can provide early warnings, significantly reducing the losses caused by disasters.
[0065] Seismic waves come in many types, including transverse waves. A notable characteristic of transverse waves is that their vibration direction is perpendicular to their propagation direction. This characteristic allows transverse waves to interact more complexly with different structures when penetrating the underground medium, thus carrying more information about the underground environment. This information is extremely important for a deeper understanding of underground geological structures, strata lithology, and the existence of special geological bodies.
[0066] The method of horizontal orthogonal double excitation of shear waves combined with multi-component horizontal component reception is a commonly used approach to obtain information about the direction of underground fissures. The operational process of its observation system is as follows: First, shear waves are excited in two mutually perpendicular directions. Then, a detector array is used to receive the generated seismic wave signals, focusing on recording the horizontal component data. Technicians perform data processing and analysis steps on the horizontal component data, such as filtering, signal enhancement, and analyzing phase and amplitude changes, to gradually infer the direction of the underground fissures.
[0067] However, conventional observation systems have many inconveniences in practical applications. Their deployment requires a high degree of precision and specialization, and the operation is complex and cumbersome. Furthermore, the entire system requires a significant human resource investment to operate.
[0068] Secondly, the earthquake crack prediction system involved in the embodiments of this application will be described illustratively. Please refer to the following examples. Figure 1 The system involves a radial observation system 100 and a terminal 110.
[0069] The radial observation system 100 includes a shear wave excitation source 101 and multiple component detectors 102. The component detectors 102 are arranged radially outward from the shear wave excitation source 101, and each row of component detectors 102 contains at least two component detectors 102. The radial observation system 100 covers the surface of the study area.
[0070] Seismic shear waves are excited by two types of shear wave sources using shear wave excitation source 101. Each time the seismic shear wave is excited, it is along the direction of one of the component geophones 102. The number of excitations is determined by the total number of geophones in the radial observation system 100.
[0071] After each seismic shear wave is generated, the component detector 102 of the generating column collects shear wave data based on the seismic shear wave of that column and sends it to the terminal 110 through a communication connection. The shear wave data contains the seismic waveform.
[0072] Terminal 110 preprocesses the acquired shear wave data to remove noise and interference in order to improve the quality of the shear wave data. The preprocessing methods include, but are not limited to, bandpass filtering and detrending analysis.
[0073] Terminal 110 performs waveform analysis on the preprocessed shear wave data, acquiring component data along the X and Y axes. Dynamic correction and in-phase superposition of the component data are then performed to preliminarily analyze the direction of the underground fractures. Based on the calculated fracture directions, a fast-slow wave comparison analysis is conducted on the X and Y axis components of the shear wave data to analyze and predict the distribution of underground fractures, yielding prediction results. These prediction results include the existence and direction of the underground fractures.
[0074] The principle of fast-slow wave comparison analysis is as follows: When a shear wave propagates in an anisotropic medium (such as rock containing fractures), it splits, producing fast and slow shear waves. The polarization direction of the fast shear wave is parallel to the direction of the underground fracture, while the polarization direction of the slow shear wave is perpendicular to the fracture direction. The presence of fractures alters the elastic properties of the medium, causing the shear wave to propagate at different speeds in different directions. By performing fast-slow wave comparison analysis on the components along the X and Y axes, the fast and slow shear waves are separated. Once the polarization direction of the fast shear wave is determined, the direction of the underground fracture can be inferred; the polarization direction of the fast shear wave is parallel to the fracture direction.
[0075] Based on the prediction results, the radial excitation observation of each column of component detectors 102 is repeated, and the excitation is carried out along the adjacent arrangement. Each excitation ensures that the two transverse wave sources are excited once to improve the accuracy of the prediction results.
[0076] Repeat the above steps until the accuracy of the prediction results meets the preset accuracy requirements.
[0077] This system and its predictive methods can effectively improve the accuracy of determining the direction of underground fissures, simplify the deployment and operation of the observation system, and reduce the consumption of human and material resources.
[0078] The aforementioned terminal 110 can be a variety of terminal devices such as mobile phones, tablets, desktop computers, portable laptops, smart TVs, vehicle terminals, and smart home devices. This application embodiment does not limit this type of terminal device.
[0079] In some embodiments, the operations performed by terminal 110 may also be performed by the server; or, they may be performed jointly by terminal 110 and the server.
[0080] It is worth noting that the aforementioned servers can be independent physical servers, server clusters or distributed systems composed of multiple physical servers, or cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.
[0081] Cloud technology refers to a hosting technology that unifies hardware, software, and network resources within a wide area network (WAN) or local area network (LAN) to achieve data computation, storage, processing, and sharing. Based on the cloud computing business model, cloud technology encompasses network technology, information technology, integration technology, management platform technology, and application technology. It can form resource pools, providing flexible and convenient on-demand access. Cloud computing technology will become a crucial support. Backend services of technical network systems require substantial computing and storage resources, such as video websites, image websites, and many portal websites. With the rapid development and application of the internet industry, every item may have its own identification mark in the future, requiring transmission to backend systems for logical processing. Data at different levels will be processed separately, and various industry data will require robust system support, which can only be achieved through cloud computing.
[0082] In some embodiments, the server described above can also be implemented as a node in a blockchain system.
[0083] Based on the above-described terminology and application scenarios, the earthquake crack prediction method provided in this application will be explained. This method can be executed by a server or a terminal, or by both a server and a terminal. In this embodiment, the method is illustrated by being executed by a terminal. Figure 2 As shown, Figure 2 This is a flowchart of a method for predicting earthquake cracks provided in an exemplary embodiment of this application. The method includes the following steps.
[0084] Step 210: Excite seismic shear waves using a shear wave excitation source.
[0085] Among them, multiple component detectors are distributed on multiple radiation lines with the transverse wave excitation source as the radiation center.
[0086] Indicative, such as Figure 3 As shown, Figure 3 This is a schematic diagram of a radial observation system, in which multiple component detectors 301 and shear wave excitation sources 302 together form a radial observation system 300.
[0087] Among them, multiple component detectors 301 are distributed in a radial arrangement structure in the study area with the transverse wave excitation source 302 as the radiation center.
[0088] For example, the component detectors 301 are distributed on 36 radiation lines centered on the transverse wave excitation source 302. The angle between any two adjacent radiation lines is 10°.
[0089] That is, each column of component detectors 301 is regarded as a radiation line, and the radiation line extends outward from the transverse wave excitation source 302 as the center.
[0090] Optionally, the number of component detectors 301 in each column is the same, and the spacing between the component detectors 301 is the same. Each column contains a component detectors 301, and the distance between adjacent component detectors 301 is b meters, where a and b are positive integers.
[0091] Optionally, the types of transverse wave excitation sources include, but are not limited to, the following.
[0092] (1) Controlled seismic source: This is a device that generates seismic waves through mechanical vibration. It typically consists of a weight, a hydraulic system, and a control system. Driven by the hydraulic system, the weight vibrates at a preset frequency and amplitude, transferring energy to the ground and thus generating seismic waves. By controlling parameters such as the frequency, amplitude, and duration of the vibration, seismic waves with different characteristics can be generated. Controlled seismic sources can precisely control the parameters of the generated seismic waves, facilitating signal processing and data analysis; they can be repeatedly excited, which helps improve the quality and reliability of data acquisition; they have a relatively small impact on the environment and are highly safe, making them suitable for seismic exploration in urban areas and surrounding regions.
[0093] (2) Mechanical impact source: This type of source uses a mechanical device to impact the ground or an object, generating vibrational energy and thus exciting transverse waves. For example, a mechanical component such as a hammer or drop hammer is used to drop the object from a certain height to impact the ground, or a mechanical device is used to push an object to impact the ground. Mechanical impact sources have a relatively simple structure, are easy to operate, and have a low cost. The force and frequency of the impact can be adjusted as needed, providing a certain degree of controllability.
[0094] Optionally, a seismic shear wave is excited along the i-th radiation line by a shear wave excitation source, where i is a positive integer.
[0095] Each time a shear wave excitation source excites a seismic shear wave, it excites the seismic shear wave along one of the radiation lines. The propagation direction of the seismic shear wave is along the radiation line, passing through all the component detectors on that radiation line in sequence.
[0096] Optionally, if the radial observation system contains k radiation lines, then the shear wave excitation source needs to excite seismic shear waves along k radiation lines respectively. That is, the shear wave excitation source needs to excite k seismic shear waves, where k is a positive integer.
[0097] Step 220: Acquire shear wave data from multiple component geophones based on seismic shear wave acquisition.
[0098] After the shear wave excitation source excites the seismic shear wave along the i-th radiation line, the component detector on the i-th radiation line will collect the seismic shear wave.
[0099] Acquire shear wave data based on seismic shear waves from at least two component geophones arranged along the i-th radiation line.
[0100] For example, the component detector is a three-component detector. The shear wave component data acquired by the three-component detector includes component data in three mutually perpendicular directions, which are used to indicate the waveform of the seismic shear wave.
[0101] This includes component data in the X, Y, and Z axes. The Z-axis is perpendicular to the ground, while the X and Y axes are perpendicular to each other on the horizontal plane.
[0102] Data acquired along the X and Y axes can capture the horizontal vibration of seismic shear waves. Because the vibration direction of shear waves is perpendicular to the propagation direction, when shear waves propagate in the underground medium, they will have vibration components in different directions on the horizontal plane.
[0103] The shear wave component data also includes time information; each shear wave component data sample has a corresponding time stamp to record the time it takes for the seismic shear wave to travel from the shear wave excitation source to the component geophone. Travel time data is crucial for determining the propagation velocity of the shear wave, as well as information such as the depth and distance of subsurface structures. Based on the distance between the seismic excitation source and the component geophone, and the travel time of the seismic shear wave, the average propagation velocity of the seismic shear wave can be calculated.
[0104] Shear wave component data also includes amplitude information, which reflects the energy level of the seismic shear wave. In homogeneous subsurface media, the amplitude of seismic shear waves generally decreases gradually with increasing propagation distance due to factors such as geometric diffusion and medium absorption. However, when shear waves encounter subsurface fissures or other geological anomalies, the amplitude may change abruptly. For example, when the propagation direction of the seismic shear wave is perpendicular to the fissure, the amplitude may decrease significantly due to the scattering and reflection of the shear wave energy by the fissure; while when the seismic shear wave propagates parallel to the fissure, the decrease in amplitude may be relatively smaller. Analyzing the variations in seismic shear wave amplitude at different locations and directions can provide important clues for the detection and density estimation of subsurface fissures.
[0105] Optionally, after the component detector on the i-th radiation line completes the acquisition of shear wave data, a seismic shear wave is excited along the (i+1)-th radiation line by a shear wave excitation source.
[0106] Acquire shear wave data based on seismic shear waves from at least two component geophones arranged on the (i+1)th radiation line until the data acquisition of component geophones on multiple radiation lines is completed.
[0107] The component detectors on each radiation line collect transverse wave data in the same way.
[0108] In some embodiments, after acquiring the shear wave data, the data can be preprocessed to improve data quality. For example, bandpass filtering and detrending analysis can be used to remove noise and interference from the shear wave data, resulting in preprocessed shear wave data. Subsequent steps are then performed based on the preprocessed shear wave data.
[0109] Step 230: Obtain the first component data along the first direction and the second component data along the second direction from the shear wave data.
[0110] The first direction includes the radiation direction of the component detector relative to the transverse wave excitation source, and the second direction includes the component direction perpendicular to the radiation direction.
[0111] For example, the first direction refers to the X-axis direction in the shear wave data, and the second direction refers to the Y-axis direction in the shear wave data. The first component data and the second component data can capture the vibration of the shear wave in the horizontal direction. The vibration direction of the seismic shear wave is perpendicular to the propagation direction. When the seismic shear wave propagates in the underground medium, it will have vibration components in different directions on the horizontal plane.
[0112] Indicative, such as Figure 4 As shown, Figure 4 This is a schematic diagram of the first component data and the second component data. The first component data 410 is the seismic wave data generated by the shear wave excitation source SH received in the first direction (X), and the second component data 420 is the seismic wave data generated by the shear wave excitation source SH received in the second direction (Y).
[0113] In the first component data 410 and the second component data 420, the seismic shear wave propagates from the seismic excitation source (bottom center) and gradually spreads during propagation. The waveform lines show obvious curvature and fluctuations, which reflect the reflection, refraction, and scattering phenomena that occur when the seismic wave encounters different media or geological structures during propagation.
[0114] By comparing the first and second component data, the anisotropic characteristics of underground geological structures can be analyzed. If there are significant differences in the waveforms in the first and second directions, it indicates that the underground geological structure has different physical properties (such as elastic modulus, density, etc.) in these two directions, and there may be underground cracks or faults on the surface.
[0115] In some embodiments, in order to improve the accuracy of shear wave data, multiple shear wave sources can be used to excite seismic shear waves at the same location of the shear wave excitation source, so that each component detector can collect shear wave data generated by two sources, and the combined data can be analyzed to eliminate errors caused by randomness.
[0116] Optionally, the seismic shear wave includes a first seismic shear wave and a second seismic shear wave.
[0117] A first seismic shear wave is generated by a shear wave excitation source, which can be a controlled seismic source, a mechanical impact source, or the like. First shear wave data acquired by multiple component geophones based on the first seismic shear wave is then obtained.
[0118] A second seismic shear wave is generated using a shear wave excitation source. The excitation source can be a controlled seismic source, a mechanical impact source, or similar. Second shear wave data is acquired using multiple component geophones based on the second seismic shear wave.
[0119] The excitation sources used to generate the first and second seismic shear waves are different.
[0120] The first component data is obtained by integrating the first sub-component data along the first direction from the first shear wave data and the second sub-component data along the first direction from the second shear wave data.
[0121] The second component data is obtained by integrating the third sub-component data along the second direction from the first shear wave data and the fourth sub-component data along the second direction from the second shear wave data.
[0122] For example, the method of integrating two shear wave data to obtain the first component data and the second component data is the same. The following is an example of integrating the first sub-component data and the second sub-component data to obtain the first component data.
[0123] Identify the first arrival times in the first and second sub-component data. The first arrival wave refers to the waveform of the seismic shear wave that first arrives at the component detector. Calculate the time difference between the two and adjust them to align the time axes.
[0124] For example, if the first arrival time in the first sub-component data is TA1 and the first arrival time in the second sub-component data is TB1, calculate the time difference t0 = TA1 - TB1. Then, add t0 to all time series in the second sub-component data to align the two sub-component data on the time axis, ensuring that the time corresponding to the shear wave is consistent in subsequent analysis.
[0125] The transverse wave amplitudes in the first and second sub-component data are normalized. The average amplitude A0 in the first sub-component data and the average amplitude B0 in the second sub-component data are calculated. Each amplitude value Ai in the first sub-component data is multiplied by (B0 / A0), and each amplitude value Bi in the second sub-component data is multiplied by (A0 / B0).
[0126] Based on the characteristics and data quality of the two seismic sources, a weight is assigned to each sub-component data. For example, the weight WA is assigned to the first sub-component data and the weight WB is assigned to the second sub-component data, WA+WB=1. For each time point t and the location of each component detector, the integrated first component data S(t) is calculated by the following formula: S(t)=SA(t)*WA+SB(t)*WB.
[0127] Here, SA(t) is the shear wave data of the first sub-component at time t, and SB(t) is the shear wave data of the second sub-component at time t. By weighted superposition, the advantages of the two sub-components can be combined to improve the accuracy of the data. WA and WB can be any preset values.
[0128] It is worth noting that the above-described method of integrating sub-component data is only for illustrative purposes. In some embodiments, the transverse wave data generated by the two excitation sources can be compared or analyzed, and one of the sub-component data can be selected as the component data in that direction. Alternatively, the sub-component data can be integrated in other ways to obtain the component data in that direction. This embodiment does not limit this.
[0129] Optionally, the first component data along the first direction and the second component data along the second direction are acquired from the shear wave data collected by multiple component detectors respectively.
[0130] Dynamic correction and co-directional superposition of the first and second component data from multiple shear wave data are performed to obtain the corrected first component data and the corrected second component data.
[0131] The purpose of dynamic correction is to adjust the travel time of seismic waves recorded at non-zero shot-receiver offsets to the time at zero shot-receiver offsets. For shear wave data, dynamic correction is necessary because shear wave velocities are relatively slower than p-waves, and their propagation time is significantly affected by shot-receiver offsets at different depths and locations. The dynamic correction amount is calculated for each sampling point using a pre-defined formula, and then the original time is subtracted from the dynamic correction amount to obtain the dynamically corrected time series.
[0132] After dynamic correction, in-phase superposition is performed. In-phase superposition is based on the concept of the seismic wave phase axis, which is a curve connecting points with the same phase in the seismic record, representing reflected waves from the same reflecting interface. Since geological structures such as underground fissures can cause changes in the in-phase axis of shear wave reflections, in-phase superposition of dynamically corrected shear wave data across different channels (different detector locations) can enhance the effective signal and suppress random noise. For example, summing or averaging shear wave data from the same time location (in-phase) after dynamic correction can be performed. Through the in-phase superimposed shear wave data, the approximate location and morphology of the underground reflecting interface can be initially observed, allowing for a preliminary inference of the direction of underground fissures. Because the direction of fissures affects the orientation of the in-phase axis of shear wave reflections, a significant tilt or distortion of the in-phase axis may indicate the presence and approximate direction of fissures.
[0133] In most regions, the subsurface medium exhibits azimuthal anisotropy. Although azimuthal anisotropy is not necessarily caused by fractures, this application still uses the fracture direction to represent the direction of azimuthal anisotropy, i.e., the direction of fast shear wave polarization. More accurate NMO velocities can be obtained from radial alignment test data through superposition and velocity analysis. To objectively reflect the shear wave splitting characteristics in anisotropic media, the same NMO velocities, the same static correction, and the same offset range are applied to all excitation directions and corresponding receiving alignments in the radial alignment. Under the same process and parameter conditions, the different characteristics of the receiving records in each direction are preserved.
[0134] Step 240: Based on the waveform changes characterized by the first and second component data collected by multiple component geophones, and the distribution of the multiple component geophones, determine the seismic cracks and crack directions in the study area.
[0135] In some embodiments, component data can also be acquired and analyzed in the following ways.
[0136] Optionally, a fast-slow wave comparison analysis is performed on the component data in the first and second directions of the shear wave data to obtain the first wave velocity data along the first direction as the first component data. And, the second wave velocity data along the second direction of the shear wave data is obtained as the second component data.
[0137] For example, the first wave velocity data refers to fast shear wave data and the second wave velocity data refers to slow shear wave component data. By constructing a covariance matrix, the fast and slow shear waves in the shear wave component data are separated to obtain the first wave velocity data and the second wave velocity data.
[0138] The polarization direction of fast shear waves is usually parallel to the anisotropic symmetry axis of the subsurface medium. When studying subsurface fractures, this direction is often closely related to the fracture orientation. For example, in a region with obvious fractures trending northeast-southwest, the polarization direction of fast shear waves will also roughly follow a northeast-southwest direction. Statistical analysis of a large amount of fast shear wave polarization direction data can depict the distribution of subsurface fracture orientations.
[0139] The polarization direction of slow shear waves is perpendicular to that of fast shear waves. This is because the anisotropy of the subsurface medium causes shear wave splitting, resulting in mutually perpendicular polarization directions for fast and slow shear waves. In actual data, the polarization direction of slow shear waves can be determined by analyzing the direction perpendicular to the polarization direction of fast shear waves, which can reflect the anisotropic characteristics of the subsurface medium from another perspective.
[0140] Indicative, such as Figure 5 As shown, Figure 5 This is a schematic diagram of the survey results of anisotropic wavefields with radially arranged receivers. The diagram includes the results of fast and slow wave comparison analysis of seismic waves generated by shear wave excitation sources: SVX510 refers to the shear wave component of the shear wave source SV in the first direction; SVY520 refers to the shear wave component of the shear wave source SV in the second direction; SHX530 refers to the shear wave component of the shear wave source SH in the first direction; and SHY540 refers to the shear wave component of the shear wave source SH in the second direction.
[0141] Figure 5 The "fast" and "slow" markings are used to indicate the positions of fast and slow shear waves.
[0142] For example, by combining fast shear wave polarization direction data from multiple component geophone locations, a subsurface fracture orientation map is plotted. If the fast shear wave polarization direction is approximately the same at multiple adjacent component geophone locations, then it can be determined that the subsurface fracture orientation in that area is approximately in that direction.
[0143] In some embodiments, the condition of underground seismic fissures can also be determined by combining P-wave data within the study area.
[0144] Acquire P-wave data for the study area based on seismic P-wave acquisition. For example, P-waves are generated within the study area using a P-wave excitation source, and P-wave data is acquired using a geophone. Both P-wave and S-wave data cover the study area. Types of P-wave excitation sources include, but are not limited to, controlled sources and hammer sources.
[0145] By combining the waveform changes represented by the P-wave data, the first component data, and the second component data, as well as the distribution of multiple component geophones, the seismic cracks and their directions in the study area are determined.
[0146] The acquired longitudinal wave data is bandpass filtered to remove interference frequencies, and detrending analysis is performed to remove linear or nonlinear trends in the data, thereby improving data quality.
[0147] The arrival times of the P-wave's first arrival at each detector are accurately recorded. Using the known positions of multiple detectors and the time difference of the first arrival, the propagation velocity of the P-wave along different paths is calculated using velocity formulas. Anomalies in velocity variation may indicate cracks. Amplitude characteristics of the P-wave data are extracted: a detailed analysis of the variation in P-wave amplitude at different detector positions is performed. When encountering a crack, the P-wave energy is reflected and scattered, causing amplitude attenuation, thus initially delineating potential crack regions.
[0148] Based on the distribution of multiple component geophones, the P-wave data, first component data, and second component data are spatially compared and integrated. Areas where both show anomalies are highly likely to contain seismic cracks.
[0149] The direction of seismic cracks is primarily determined by the polarization direction of the fast shear waves within the seismic shear waves. The polarization directions of the fast shear waves at different detector locations are statistically analyzed, and combined with the spatial layout of the detectors, a crack direction map is plotted. For example, if the fast shear wave polarization direction at multiple adjacent detectors is northwest-southeast, then the crack direction in that area is approximately in this direction. Simultaneously, the velocity and amplitude variation characteristics of the P-wave in this direction are referenced for verification to ensure the accuracy of the crack direction determination.
[0150] In summary, the seismic fracture prediction method provided in this application can utilize the characteristics of shear waves and set up a radial observation system to obtain multi-directional component data from a three-component geophone. Based on this component data, it can analyze and process seismic signals in multiple directions to obtain underground fracture direction information. The radial observation system is relatively simple to deploy and operate, requiring less manpower and material resources compared to other observation systems, thus reducing detection costs. By changing the angle of the radial observation system, the accuracy of fracture prediction direction is improved, reducing errors caused by the difficulty in accurately predicting shear wave propagation paths and energy attenuation.
[0151] Figure 6 This is a structural block diagram of an earthquake crack prediction device provided in an exemplary embodiment of this application, as shown below. Figure 6 As shown, the device includes the following parts.
[0152] Excitation module 610 is used to excite seismic shear waves through a shear wave excitation source;
[0153] The acquisition module 620 is used to acquire shear wave data collected by multiple component geophones based on the seismic shear wave. The multiple component geophones are distributed in a radial arrangement structure in the study area with the shear wave excitation source as the radiation center.
[0154] The acquisition module 620 is further configured to acquire a first component data along a first direction and a second component data along a second direction in the shear wave data, wherein the first direction includes the radiation direction of the detection position of the component detector relative to the shear wave excitation source, and the second direction includes a component direction perpendicular to the radiation direction.
[0155] The crack prediction module 630 is used to determine the seismic cracks and their directions in the study area based on the waveform changes represented by the first component data and the second component data collected by the multiple component geophones, and the distribution of the multiple component geophones.
[0156] In an optional embodiment, the plurality of component detectors are distributed along multiple radiation lines centered on the transverse wave excitation source.
[0157] The excitation module 610 is also used to excite the seismic shear wave along the i-th radiation line through the shear wave excitation source, where i is a positive integer;
[0158] The acquisition module 620 is also used to acquire the shear wave data collected by at least two component detectors arranged on the i-th radiation line based on the seismic shear wave.
[0159] In an optional embodiment, the excitation module 610 is further configured to excite the seismic shear wave along the (i+1)th radiation line by means of the shear wave excitation source after the component detector on the i-th radiation line has completed the acquisition of the shear wave data.
[0160] The acquisition module 620 is further configured to acquire the shear wave data collected by at least two component geophones arranged on the (i+1)th radiation line based on the seismic shear wave, until the data acquisition by the component geophones on the multiple radiation lines is completed.
[0161] In an optional embodiment, the component detectors are distributed along 36 radiation lines centered on the transverse wave excitation source; the angle between any two adjacent radiation lines is 10°.
[0162] In an optional embodiment, the seismic shear wave includes a first seismic shear wave and a second seismic shear wave;
[0163] The excitation module 610 is also used to excite the first seismic shear wave through the shear wave excitation source;
[0164] The acquisition module 620 is also used to acquire first shear wave data collected by multiple component detectors based on the first seismic shear wave;
[0165] The excitation module 610 is also used to excite the second seismic shear wave through the shear wave excitation source;
[0166] The acquisition module 620 is also used to acquire second shear wave data collected by multiple component detectors based on the second seismic shear wave;
[0167] The acquisition module 620 is further configured to integrate the first sub-component data along the first direction in the first shear wave data and the second sub-component data along the first direction in the second shear wave data to obtain the first component data; and to integrate the third sub-component data along the second direction in the first shear wave data and the fourth sub-component data along the second direction in the second shear wave data to obtain the second component data.
[0168] In an optional embodiment, the acquisition module 620 is further configured to acquire first wave velocity data along the first direction in the shear wave data as the first component data; and acquire second wave velocity data along the second direction in the shear wave data as the second component data.
[0169] In an optional embodiment, the acquisition module 620 is further configured to acquire the first component data along the first direction and the second component data along the second direction from the shear wave data collected by the multiple component detectors respectively; and to perform dynamic correction and co-directional superposition on the first component data and the second component data from the multiple shear wave data to obtain the corrected first component data and the corrected second component data.
[0170] In an optional embodiment, the crack prediction module 630 is further configured to acquire P-wave data of the study area based on seismic P-wave acquisition; and determine the seismic cracks in the study area and the crack direction of the seismic cracks by combining the waveform changes represented by the P-wave data, the first component data and the second component data, and the distribution positions of the multiple component geophones.
[0171] In summary, the seismic fracture prediction device provided in this application utilizes the characteristics of shear waves and sets up a radial observation system to acquire multi-directional component data from a three-component geophone. Based on this component data, it can analyze and process seismic signals in multiple directions to obtain underground fracture direction information. The radial observation system is relatively simple to deploy and operate, requiring less manpower and material resources compared to other observation systems, thus reducing detection costs. By changing the angle of the radial observation system, the accuracy of fracture prediction direction is improved, reducing errors caused by the difficulty in accurately predicting shear wave propagation paths and energy attenuation.
[0172] It should be noted that the earthquake crack prediction device provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the earthquake crack prediction device and the earthquake crack prediction method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.
[0173] Figure 7 This illustration shows a structural block diagram of a computer device 700 provided in an exemplary embodiment of this application. The computer device 700 may be a smartphone, tablet computer, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, or desktop computer. The computer device 700 may also be referred to as a user device, portable terminal, laptop terminal, desktop terminal, or other names.
[0174] Typically, computer device 700 includes a processor 701 and a memory 702.
[0175] Processor 701 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 701 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 701 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 701 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 701 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.
[0176] The memory 702 may include one or more computer-readable storage media, which may be non-transitory. The memory 702 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 702 are used to store at least one instruction, which is executed by the processor 701 to implement the seismic crack prediction method provided in the method embodiments of this application.
[0177] In some embodiments, the computer device 700 also includes other components 703, the type and number of which can be selected based on the functional needs of the computer device 700. Those skilled in the art will understand that... Figure 7 The structure shown does not constitute a limitation on the computer device 700, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.
[0178] Optionally, the computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), solid-state drives (SSDs), or optical discs, etc. The random access memory may include resistive random access memory (ReRAM) and dynamic random access memory (DRAM). The sequence numbers of the embodiments in this application are merely descriptive and do not represent the superiority or inferiority of the embodiments.
[0179] This application also provides a computer device, which includes a processor and a memory. The memory stores at least one instruction, at least one program, a code set, or an instruction set. The at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the earthquake crack prediction method as described in any of the above embodiments of this application.
[0180] This application also provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the earthquake crack prediction method as described in any of the above embodiments of this application.
[0181] This application also provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform any of the earthquake crack prediction methods described in the above embodiments.
[0182] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.
[0183] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A method of predicting seismic fractures, characterized in that, The method includes: Seismic shear waves are generated by a shear wave excitation source; The shear wave data acquired by multiple component geophones based on the seismic shear wave are obtained. The multiple component geophones are distributed in a radial arrangement structure in the study area with the shear wave excitation source as the radiation center. Acquire the first component data along the first direction and the second component data along the second direction from the shear wave data. The first direction includes the radiation direction of the detection position of the component detector relative to the shear wave excitation source, and the second direction includes the component direction perpendicular to the radiation direction. Based on the waveform changes represented by the first component data and the second component data collected by the multiple component geophones, and the distribution location of the multiple component geophones, the seismic cracks in the study area and the crack directions of the seismic cracks are determined.
2. The method of claim 1, wherein, The multiple component detectors are distributed on multiple radiation lines with the transverse wave excitation source as the radiation center; The method of exciting seismic shear waves through a shear wave excitation source includes: The seismic shear wave is excited along the i-th radiation line by the shear wave excitation source, where i is a positive integer; The acquisition of shear wave data from multiple component geophones based on the seismic shear wave includes: Acquire the shear wave data based on the seismic shear wave from at least two component geophones arranged along the i-th radiation line.
3. The method of claim 2, wherein, The method further includes: After the component detector on the i-th radiation line completes the acquisition of the shear wave data, the seismic shear wave is excited along the (i+1)-th radiation line by the shear wave excitation source. Acquire the shear wave data based on the seismic shear wave from at least two component geophones arranged on the (i+1)th radiation line until the data acquisition of the component geophones on the multiple radiation lines is completed.
4. The method of claim 2, wherein, The component detectors are distributed along 36 radiation lines centered on the transverse wave excitation source. The included angle between any two adjacent radiation lines in the 36 radiation lines is 10°.
5. The method according to any one of claims 1 to 4, characterized in that, The seismic shear wave includes a first seismic shear wave and a second seismic shear wave; The method further includes: The first seismic shear wave is excited by the shear wave excitation source; Acquire first shear wave data based on the first seismic shear wave by multiple component geophones; The second seismic shear wave is excited by the shear wave excitation source; Acquire second shear wave data based on the second seismic shear wave obtained by multiple component geophones; The step of acquiring the first component data along the first direction and the second component data along the second direction in the shear wave data includes: The first component data is obtained by integrating the first sub-component data along the first direction in the first shear wave data and the second sub-component data along the first direction in the second shear wave data. The second component data is obtained by integrating the third sub-component data along the second direction in the first shear wave data and the fourth sub-component data along the second direction in the second shear wave data.
6. The method according to any one of claims 1 to 4, characterized in that, The step of acquiring the first component data along the first direction and the second component data along the second direction in the shear wave data includes: The first wave velocity data along the first direction in the shear wave data is obtained as the first component data; and, The second wave velocity data along the second direction in the shear wave data is obtained as the second component data.
7. The method according to any one of claims 1 to 4, characterized in that, The step of acquiring the first component data along the first direction and the second component data along the second direction in the shear wave data includes: Acquire the first component data along the first direction and the second component data along the second direction from the shear wave data collected by multiple component detectors respectively; Dynamic correction and co-directional superposition of the first and second component data from multiple shear wave data are performed to obtain the corrected first component data and the corrected second component data.
8. The method according to any one of claims 1 to 4, characterized in that, The determination of seismic cracks and their directions in the study area based on the waveform changes represented by the first and second component data acquired by the multiple component detectors, and the distribution of the multiple component detectors, includes: Acquire P-wave data of the study area based on seismic P-wave acquisition; By combining the waveform changes represented by the P-wave data, the first component data, and the second component data, as well as the distribution locations of the multiple component geophones, the seismic cracks in the study area and the crack directions of the seismic cracks are determined.
9. A device for predicting earthquake cracks, characterized in that, The device includes: The excitation module is used to excite seismic shear waves through a shear wave excitation source; The acquisition module is used to acquire shear wave data collected by multiple component geophones based on the seismic shear wave. The multiple component geophones are distributed in a radial arrangement structure in the study area with the shear wave excitation source as the radiation center. The acquisition module is further configured to acquire the first component data along the first direction and the second component data along the second direction in the shear wave data, wherein the first direction includes the radiation direction of the detection position of the component detector relative to the shear wave excitation source, and the second direction includes the component direction perpendicular to the radiation direction. The crack prediction module is used to determine the seismic cracks and their directions in the study area based on the waveform changes represented by the first component data and the second component data collected by the multiple component geophones, as well as the distribution of the multiple component geophones.
10. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one program, which is loaded and executed by the processor to implement the earthquake crack prediction method as described in any one of claims 1 to 8.