Land geophysical prospecting method, electronic device and readable storage medium

Abstract

The application discloses a land geophysical exploration method, an electronic device and a readable storage medium, and belongs to the technical field of land geophysical exploration. The land geophysical exploration method comprises the following steps: detecting a first seismic wave generated by vibration at a preset position of the underground or the ground and transmitted to the ground; detecting a second seismic wave transmitted by the vibration to the air above the ground; calculating a ground parameter in a set range of the preset position according to the first seismic wave and the second seismic wave; and calculating an underground velocity model and a density model according to the ground parameter. The second seismic wave transmitted to the air from the ground is detected by utilizing the characteristics that the sound speed and the density of the air are consistent under the same meteorological condition, so that the subsequent inversion algorithm is more accurate, and the underground velocity model and the density model are more accurate.

Description

Technical Field

[0001] This invention belongs to the field of land geophysical exploration technology, and particularly relates to a land geophysical exploration method, electronic device and readable storage medium. Background Technology

[0002] In onshore seismic exploration for oil, current geophones used to receive seismic waves are in direct, close contact with the Earth's surface. This is achieved through methods such as inserting a pointed cone into the surface or shallow burial, allowing the geophone to couple directly with the earth. Artificial seismic waves are generated by explosives or controlled seismic sources and propagate underground. When these waves encounter underground structures, they are reflected back to the surface, where they are received and recorded by surface geophones, yielding seismic data. This data is then processed through a series of mathematical and physical algorithms to ultimately produce images of the underground structures, providing the basis for oil companies to locate oil.

[0003] Current land seismic data processing does not require accurate surface attributes. It only uses simple averaging effects to estimate a near-surface average velocity or inverts a simple near-surface velocity. This leads to a heavy reliance on the personal experience of data processors, resulting in subjective factors and uncertainties in the data processing results, making the imaging results unreliable. Consequently, the subsequent processing results deviate significantly from actual engineering and drilling practices, posing a huge risk to oil exploration and development. Summary of the Invention

[0004] (I) Purpose of the Invention

[0005] The purpose of this invention is to provide a land geological survey method and equipment to solve the problem that the existing technology can only use a simple average effect to estimate a near-surface average velocity, or invert a simple near-surface velocity, which leads to unreliable subsequent imaging results.

[0006] (II) Technical Solution

[0007] This invention provides a method for land geophysical exploration, comprising:

[0008] Detects the first seismic wave transmitted from a predetermined location underground or on the surface to the surface.

[0009] Detect the second seismic wave transmitted from the vibration to the air above the Earth's surface;

[0010] Calculate the surface parameters within a set range of the preset location based on the first seismic wave and the second seismic wave;

[0011] The underground velocity model and density model are calculated based on the surface parameters.

[0012] In an optional embodiment, calculating the surface parameters within a predetermined range of the preset location based on the first seismic wave and the second seismic wave includes:

[0013] Detecting the first seismic wave includes detecting the energy of the first seismic wave;

[0014] Detecting the second seismic wave includes detecting the energy of the second seismic wave;

[0015] The actual reflection coefficient within a set range at the preset location is calculated based on the energy of the first seismic wave and the energy of the second seismic wave.

[0016] In an optional embodiment, calculating the surface parameters within a predetermined range of the preset location based on the first seismic wave and the second seismic wave includes:

[0017] Based on the first seismic wave and the second seismic wave, obtain the direct wave or surface wave that reaches the detector point at the preset location;

[0018] The surface velocity within a set range at the preset location is calculated based on the direct wave or surface wave.

[0019] In an optional embodiment, calculating the surface parameters within a predetermined range of the preset location based on the first seismic wave and the second seismic wave includes:

[0020] The surface density within a predetermined range at the preset location is obtained using the formula for calculating surface density.

[0021] The formula for calculating the surface density is:

[0022] Where, ρ g Let υ be the surface density. g Let r be the surface velocity. g υ is the actual reflection coefficient. air The air velocity ρ is the air velocity within a set range of the preset position. air The air density within a set range at the preset location.

[0023] In an optional embodiment, calculating the subsurface velocity model and density model based on the surface parameters includes:

[0024] Multiple predetermined locations are set up on the ground surface, and the first seismic wave and the second seismic wave are detected at each of the predetermined locations;

[0025] Based on the first and second seismic waves at each of the set locations, the surface density and surface velocity at each of the set locations are obtained;

[0026] An initial near-surface model is constructed based on air density, air velocity, and surface density and velocity at each of the specified locations;

[0027] Based on the initial near-surface model, a subsurface velocity model and a density model are obtained using a full waveform inversion algorithm. The inverted subsurface velocity model matches the actual subsurface velocity, and the inverted subsurface density model matches the actual subsurface density model.

[0028] In an optional embodiment, the initial near-surface model is an initial near-surface model covered by an air layer, the air layer containing at least two parameters: air density and air velocity, and the upper boundary of the air layer is set as an absorbing boundary.

[0029] In an optional embodiment, obtaining the subsurface velocity model and density model using a full waveform inversion algorithm based on the initial near-surface model includes:

[0030] The source wavelet function is obtained by inverting the wavelet morphology of each excitation source using the first arrival wave of a single shot. At the preset location where the vibration occurs, the subsurface velocity model and density model are obtained using the full waveform inversion algorithm based on the source wavelet function, so that the wavefield forward modeling results are consistent with the actual data.

[0031] In an optional embodiment, obtaining the subsurface velocity model and density model using a full waveform inversion algorithm based on the initial near-surface model includes:

[0032] The first seismic wavelet is shaped using the second seismic wave to obtain comprehensive observation data of the first and second seismic waves. The comprehensive observation data is used to ensure that the detector point terms of the forward modeling data in the full waveform inversion are consistent with the actual data.

[0033] In an optional embodiment, obtaining the subsurface velocity model and density model using a full waveform inversion algorithm based on the initial near-surface model includes:

[0034] The filtering operator for the receiver point at the set location on the ground surface is obtained by combining the second seismic wave and the first seismic wave. The filtering operator is then used to simulate the receiver point term in the forward modeling during full waveform inversion, so as to eliminate the inconsistency between the forward modeling data waveform and the actual data waveform caused by the inconsistency of the coupling of the ground receiver points.

[0035] In addition, the present invention also provides an electronic device, including: a processor, a memory, and a program or instructions stored in the memory and executable in the processor, wherein the program or instructions, when executed by the processor, implement the steps of the land geophysical exploration method as described above.

[0036] In an optional embodiment, the electronic device further includes:

[0037] A detector, used to be installed at the Earth's surface to detect the first seismic wave transmitted from underground vibrations to the surface; and

[0038] A microphone is used to position itself at a distance from the ground surface and to detect a second seismic wave transmitted into the air by the vibration.

[0039] In an optional embodiment, the electronic device further includes: a soundproof shell, which is a sleeve structure, the soundproof shell being used to be erected on the ground, and the microphone being disposed inside one end of the soundproof shell along its axial direction.

[0040] In an optional embodiment, the electronic device further includes a linear amplifier, an analog-to-digital converter module, and an acquisition control module. The linear amplifier is connected to the analog-to-digital converter module, the analog-to-digital converter module is connected to the acquisition control module, and the linear amplifier is connected to the microphone or the detector.

[0041] In addition, the present invention provides a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the land geophysical exploration method as described above.

[0042] (III) Beneficial Effects

[0043] The above-described technical solution of the present invention has the following beneficial technical effects:

[0044] This invention generates vibrations at predetermined locations underground or on the surface. Simultaneously, it detects the first seismic wave transmitted to the surface and, taking advantage of the consistent sound speed and density of air under the same meteorological conditions, detects the second seismic wave that penetrates the surface and reaches the air. This allows for the inference of surface parameters, such as surface density, surface velocity, and actual reflection coefficient, from the first and second seismic waves. This achieves consistency in surface data during land exploration, yields more accurate underground velocity and density models, and ultimately provides a non-ambiguous underground structure. It solves the problem of unreliable imaging results caused by subjective factors in data processing and the resulting uncertainties. Attached Figure Description

[0045] Figure 1 This is a general flowchart of the land geophysical exploration method according to a specific embodiment of the present invention;

[0046] Figure 2 This is a detailed flowchart of the land geophysical exploration method according to a specific embodiment of the present invention;

[0047] Figure 3 This is a flowchart of the land geophysical exploration method combined with the full waveform inversion algorithm according to a specific embodiment of the present invention;

[0048] Figure 4 This is a flowchart of the main preparation process of the land geophysical exploration method described in a specific embodiment of the present invention before performing the full waveform inversion algorithm;

[0049] Figure 5 This is a flowchart detailing the preparation process before performing the full waveform inversion algorithm in the land geophysical exploration method described in a specific embodiment of the present invention;

[0050] Figure 6 This is a schematic diagram showing the interconnection of the linear amplifier, analog-to-digital converter, acquisition control module, microphone, and detector in the electronic device according to a specific embodiment of the present invention.

[0051] Figure 7 This is a schematic structural diagram of the soundproof shell of the land geophysical exploration equipment according to a specific embodiment of the present invention;

[0052] Figure 8 yes Figure 7 A schematic diagram of direction E in the diagram. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and the accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0054] The accompanying drawings illustrate a layer structure according to an embodiment of the present invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0055] Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0056] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0057] The invention will now be described in more detail with reference to the accompanying drawings. In the various drawings, the same elements are indicated by similar reference numerals. For clarity, the various parts in the drawings are not drawn to scale.

[0058] For existing components that do not involve the improvements of this invention, they will be briefly described or not described at all, while the focus will be on describing the components that have been improved relative to the prior art.

[0059] See Figure 1 and Figure 2 This embodiment provides a land geophysical exploration method, including:

[0060] This involves causing vibrations at a predetermined location underground or on the surface; this predetermined location is also known as the seismic source. Furthermore, the vibration at this predetermined location can be generated by an underground explosion of explosives, or by a controlled seismic source generating vibrations at the surface.

[0061] Detect the first seismic wave that travels to the Earth's surface;

[0062] Detecting the second seismic wave transmitted from the vibration to the air above the Earth's surface;

[0063] Calculate the surface parameters within a set range at the preset location based on the first seismic wave and the second seismic wave, such as the actual reflection coefficient, surface velocity, and surface density.

[0064] Calculate underground velocity and density models based on surface parameters.

[0065] It should be noted that the term "land surface" as used in this invention refers to the surface of land.

[0066] In addition, the first seismic wave here is the surface seismic wave component, and the second seismic wave is the seismic wave component that penetrates the air to the surface.

[0067] In addition, detecting the first seismic wave transmitted to the ground surface can be achieved by setting up multiple geophones at the ground surface, with each geophone equipped with a corresponding geophone. These geophones can then detect the first seismic wave transmitted to the ground surface. Similarly, detecting the second seismic wave transmitted to the air above the ground surface can be achieved by setting up multiple detection devices, such as microphones, at a preset height above the ground. These detection devices can then detect the second seismic wave.

[0068] Additionally, the preset location range here refers to the near-surface area traversed by the direct wave as it propagates from the seismic source to each detector. This range includes both the depth and distance of the journey. The grid selection for this range is related to the frequency of the subsurface velocity density model achieved through full-wave inversion, i.e., it is related to the inversion frequency. The minimum grid size for the preset range is one-quarter of a wavelength, meaning the grid size within the range is:

[0069] Where v min f is the wave propagation speed. max This is the inversion frequency.

[0070] The inventors of this invention have discovered that the main reason why accurate requirements for surface properties are not currently proposed, and only a simple averaging effect can be used to estimate a near-surface average velocity or to invert a simple near-surface velocity, is that the physical properties of different parts of the land surface vary significantly from both a temporal and spatial perspective. For example, at the same surface point, with temperature changes, surface moisture freezes in the morning and melts at noon; different locations may have grasslands or gravel, resulting in severe inconsistencies in surface conditions. Due to the lack of direct surface observation evidence, this inconsistency is difficult to quantitatively realize in wavefield simulations. In other words, existing observation records are insufficient to determine the reflection coefficient at the surface-air interface, making it difficult to establish the boundary conditions for solving the wave equation. On the other hand, conventional full-waveform inversion algorithms assume that the wavelet morphology at the shot point (source) is also uniform. However, in actual operation, the wavelets generated by explosive explosions or controlled seismic sources on land are inconsistent, changing with each shot point explosion or controlled seismic source excitation; at the same time, the coupling between each receiver point and the land is not completely consistent.

[0071] As mentioned above, for the full waveform inversion algorithm, due to the inconsistency between the source and receiver wavelets, and the inconsistency of the reflection coefficients at various points on the surface, the existing inversion algorithm cannot effectively solve the underground velocity model in the current land data processing process. It needs to rely on the experience of the processing personnel, resulting in extremely unstable processing results, which directly affects the application effect of the full waveform inversion algorithm in land oil exploration.

[0072] Therefore, this invention generates vibrations at predetermined locations underground or on the surface, and while detecting the first seismic wave transmitted to the surface, it also utilizes the characteristic that the speed of sound and density of air are consistent under the same meteorological conditions to detect the second seismic wave that penetrates the surface and reaches the air, thus achieving the goal of consistent surface detection in land exploration.

[0073] This allows for the accurate determination of physical properties such as the actual surface reflection coefficient, surface velocity, and surface density. By utilizing air coupling consistency, source wavelet and receiver wavelet are obtained, resulting in surface-consistent source wavelet and receiver wavelet operators. This leads to more accurate underground velocity and density models, and ultimately provides a non-multiple-solution underground structure. This addresses the problem of unreliable imaging results caused by subjective factors in data processing and the resulting uncertainties.

[0074] Additionally, it should be noted that the source wavelet mentioned in this embodiment refers to the source wavelet function.

[0075] Additionally, it should be noted that the detector wavelets include: the first seismic wave detected by the detector at the Earth's surface, and the second seismic wave detected by the detector in the air above the Earth's surface.

[0076] See Figure 1 and Figure 2 In an optional embodiment, the first seismic wave is a velocity component, denoted as z, and the second seismic wave is an air seismic wave component, which may include a pressure change component and a velocity component, denoted as p.

[0077] See Figure 1 and Figure 2 In an optional embodiment, calculating the surface parameters within a set range of the preset location based on the first seismic wave and the second seismic wave includes: obtaining the direct wave or surface wave at the receiver point of the preset location based on the first seismic wave and the second seismic wave, and calculating the surface velocity within a set range of the preset location based on the direct wave or surface wave.

[0078] It should be noted that the direct wave here refers to the wave that arrives at the receiver earliest after the seismic wave passes through the Earth's surface and generates vibrations at the hypocenter at a predetermined location. This signal contains near-surface P-wave velocity information. A near-surface velocity model can be constructed by matching the travel time information of the direct wave using full waveform inversion or gyro-rotation tomography.

[0079] Furthermore, the surface waves here refer to shear waves propagating along the ground. These waves are characterized by low velocity, high energy, and frequency variation, making them clearly distinguishable in seismic records. They contain near-surface shear wave velocity information. The near-surface shear wave velocity model can be inverted using elastic wave full-waveform inversion techniques or surface wave dispersion analysis by matching the surface wave waveform or dispersion relationship. Then, the P-wave velocity model is derived from the obtained shear wave velocity model according to a certain scale.

[0080] See Figure 1 and Figure 2 In an optional embodiment, detecting the first seismic wave that the vibration is transmitted to the ground surface includes detecting the energy of the first seismic wave;

[0081] Detecting the second seismic wave transmitted from the ground to the air above the Earth's surface includes detecting the energy of the second seismic wave.

[0082] See Figure 1 and Figure 2 In an optional embodiment, calculating the surface parameters within a predetermined range of the preset location based on the first seismic wave and the second seismic wave includes:

[0083] Detecting the first seismic wave includes detecting the energy of the first seismic wave;

[0084] Detecting the second seismic wave includes detecting the energy of the second seismic wave;

[0085] The actual reflection coefficient within a set range at the preset location is calculated based on the energy of the first seismic wave and the energy of the second seismic wave.

[0086] In an optional embodiment, calculating the surface parameters within a predetermined range of the preset location based on the first seismic wave and the second seismic wave includes:

[0087] Based on the first seismic wave and the second seismic wave, obtain the direct wave or surface wave that reaches the detector point at the preset location;

[0088] The surface velocity within a set range at the preset location is calculated based on the direct wave or surface wave.

[0089] As a preferred method, the circuit correction coefficient can also be obtained based on the energy of the first and second seismic waves and the theoretical reflection coefficient;

[0090] The actual reflection coefficient is obtained based on the energy of the first and second seismic waves and the circuit correction coefficient.

[0091] See Figure 1 and Figure 2 In an optional embodiment, calculating the surface parameters within a predetermined range of the preset location based on the first seismic wave and the second seismic wave includes:

[0092] The surface density within a predetermined range at the preset location is obtained using the formula for calculating surface density.

[0093] According to the formula (1) for calculating surface density: Calculate the surface density;

[0094] Where, ρ g υ is the surface density. g Let r be the surface velocity. g υ is the actual reflection coefficient. air The air velocity ρ is the air velocity within a set range of the preset position. air The air density within a set range at the preset location.

[0095] Specifically, the obtained circuit correction coefficient is used to calibrate the linear amplification module coefficient of the detection instrument. The speed of sound in air under standard conditions is marked as υ1, and the density of air under standard conditions is marked as ρ1. A medium with known density and velocity is selected, such as steel plate or granite, whose sound wave velocity is marked as υ2 and whose density is marked as ρ2.

[0096] According to the theoretical reflection coefficient calculation formula (2):

[0097]

[0098] The theoretical reflection coefficient r was obtained. model According to the calculation formula (3) for the observation coefficient:

[0099]

[0100] Calculate the observation coefficient r obs , where p power The energy of the second seismic wave, z power This represents the energy of the first seismic wave.

[0101] Then, based on the climate conditions detected within a set range of the preset location, the air velocity υ within the set range of the preset location is calculated using an air velocity density meter. air and air density ρ air ;

[0102] Additionally, the air speed υ within the preset range of the aforementioned preset position. air and air density ρ air Alternatively, it can be a set of corresponding values ​​selected using empirical parameters.

[0103] According to the formula (4) for calculating the true reflectance coefficient:

[0104] r g =βr obs

[0105] Calculate the true reflection coefficient r g , where β is the circuit correction coefficient, which can be obtained by measuring the equipment at the factory, or β can be measured and corrected based on the known theoretical reflection coefficient and the known real reflection coefficient.

[0106] See Figures 1 to 5 In an optional embodiment, calculating the subsurface velocity model and density model based on the surface parameters includes:

[0107] Multiple predetermined locations are set up on the ground surface, and the first seismic wave and the second seismic wave are detected at each of the predetermined locations;

[0108] Based on the first and second seismic waves at each of the set locations, the surface density and surface velocity at each of the set locations are obtained;

[0109] An initial near-surface model is constructed based on air density, air velocity, and surface density and velocity at each of the specified locations;

[0110] Based on the initial near-surface model, a subsurface velocity model and a density model are obtained using a full waveform inversion algorithm. The inverted subsurface velocity model matches the actual subsurface velocity, and the inverted density model matches the actual subsurface density.

[0111] It should be noted that the phrase "the inverted subsurface velocity model matches the actual subsurface velocity, and the inverted density model matches the actual subsurface density" here can mean that the highest frequency reached is the nyquist frequency of the data sampling, which is related to the target volume velocity, and, depending on computing power and needs, can be calculated up to: v min / (4*f max The grid of ) where v min f is the target position velocity. max It refers to the data frequency. The standard can be determined based on the computing power and production needs of the oil extraction institution. If the oil extraction institution has high computing power, it will prefer smaller grids and higher precision calculations; conversely, if the oil extraction institution has insufficient computing power, it will prefer larger grids for corresponding processing according to its own needs.

[0112] The full waveform in the full waveform inversion algorithm (FWI) fully utilizes various wavefield information in seismic waves, such as amplitude, spectrum, phase, reflection, refraction, scattering, etc., to quantitatively invert the structure and properties of the subsurface medium.

[0113] The full waveform inversion algorithm has been put into production in the seismic data processing industry, and has achieved great success, especially in offshore exploration. However, its application in land exploration has not been ideal.

[0114] The inventors of this invention have discovered that the application of full-waveform inversion algorithms in land exploration has been unsatisfactory. Current full-waveform inversion algorithms cannot adequately address the inconsistency problem of the coupling between the detector and the surface. In other words, the physical properties of the contact layer between the land surface and the air vary greatly, with reflection coefficients ranging from 0 to -1. Even seismic signals from the same location can change significantly depending on climate and environmental variations at different acquisition times. Furthermore, whether using explosives or controlled-source equipment, the seismic source in land exploration changes with the surface properties and environmental factors at the epicenter location, making source consistency difficult to achieve. These problems prevent current wave equation forward modeling algorithms from accurately simulating actual wavefield conditions, severely impacting the effectiveness of full-waveform inversion algorithms in land oil exploration.

[0115] To address this, this invention utilizes the second seismic wave, detected and collected, that penetrates the Earth's surface and reaches the air. Combined with the first seismic wave received at the surface, it accurately determines the actual surface reflection coefficient, surface velocity, and surface density. These properties serve as the initial surface model, upon which an air layer model with velocity and density is overlaid. Leveraging the consistency of air coupling, source wavelets and receiver wavelets can be obtained. These wavelets are used to correct observational data or full-wave inversion and forward modeling data, maximizing the consistency between observational and forward modeling data. In full-wave inversion, the upper boundary condition of the air layer surface is set as an absorbing boundary, better fitting the real-world surface boundary conditions. This enables accurate full-waveform inversion. Starting from surface air, it accurately inverts underground velocity and density models, ultimately providing a non-ambiguous underground structure. This solves the problem of subjective factors in data processing and the resulting uncertainties, which lead to unreliable imaging results and significant errors between the processed results and actual engineering or drilling practices.

[0116] It should be noted that, by utilizing the consistency of air coupling, the source wavelet and detector wavelet can be obtained, for example, by obtaining the source wavelet:

[0117] First, an initial source wavelet function is assumed. Then, based on the constructed initial velocity and density model, a simulated direct wave record is generated through forward modeling (which can be based on the wave equation; if the medium or surface structure is simple, a ray-mapping algorithm can also be used). The actual direct wave records collected were Design another objective function When the similarity between the simulated direct wave record and the real direct wave record is the highest, the assumed source function f0(t) is consistent with the real source function. At this point, the iteration stops, and the real source function is obtained. Otherwise, a gradient function g is constructed using the lack of correlation between the two direct wave records. The input wavelet is corrected using the gradient function g to obtain the initial wavelet for the next round of forward modeling. The iteration continues until the direct wave generated by the forward modeling has the highest similarity with the real direct wave, and the objective function is less than a certain threshold. The iteration converges, and a reliable source wavelet function is finally obtained.

[0118] This solves the problem of quantitatively describing surface inconsistencies, enabling the full-waveform inversion algorithm to be used in onshore exploration. This significantly improves the accuracy and effectiveness of onshore oil exploration results, reduces the risks of onshore oil exploration and development, shortens the onshore oil exploration cycle, and brings new opportunities for increased production and efficiency in the energy industry.

[0119] In an optional embodiment, the initial near-surface model is an initial near-surface model covered by an air layer, the air layer containing at least two parameters: air density and air velocity, and the upper boundary of the air layer is set as an absorbing boundary.

[0120] The upper boundary of the air layer in the full waveform inversion algorithm is set as an absorbing boundary, which solves the problem of complex surface boundaries in land full waveform inversion. The surface model covered by the air layer adopts absorbing boundary conditions, ensuring the consistency and simplicity of the surface model realized by full waveform inversion. Furthermore, it makes subsequent inversion algorithms more accurate, resulting in more accurate subsurface velocity and density models.

[0121] See Figures 1 to 5 In an optional embodiment, obtaining the subsurface velocity model and density model using the full waveform inversion algorithm based on the initial near-surface model includes: obtaining the source wavelet function by inverting the wavelet morphology of each excitation source using the first arrival wave of a single shot; and obtaining the subsurface velocity model and density model using the full waveform inversion algorithm based on the source wavelet function, so that the wavefield forward modeling results are consistent with the actual data.

[0122] Considering that seismic waves spread spherically after excitation, the waves reflected after spreading underground undergo significant changes in wavelet shape due to filtering effects caused by factors such as changes in medium impedance and absorption attenuation. Therefore, reflected waves are difficult to use to invert the source wavelet function.

[0123] Surface direct waves, especially those in the air component, have no influence on waveform except for energy attenuation caused by simple spherical diffusion. Therefore, accurate and reliable source wavelet functions can be obtained using wave equation inversion or ray casting methods. Thus, the source wavelet function can be obtained by inverting the wavelet morphology of each excitation source using the first arrival wave of a single shot from the surface direct waves. This provides an optimal solution for obtaining accurate source wavelet functions on land. Furthermore, the source wavelet function here is actually the waveform of the seismic wave generated from the start of the detonation to the end of the explosion. It can be considered a time-amplitude correlation function starting at time 0 from the start of the source excitation. This function, in effect, serves as the source function, generating a wave field through wave equation simulation, and then recording the wave field at the corresponding location. It can also be considered an input function of FWI.

[0124] For example:

[0125]

[0126] in, It is the source function, carrying information such as the Earth's location and time.

[0127] Based on the source wavelet function, the underground velocity model and density model are obtained using the full waveform inversion algorithm;

[0128] The wavelet of the excitation source here refers to the initial waveform of the seismic wave generated by explosives or a controlled source.

[0129] See Figures 1 to 5In an optional embodiment, obtaining the subsurface velocity model and density model using a full-waveform inversion algorithm based on the initial near-surface model includes: shaping the wavelet of the first seismic wave using the second seismic wave (the aforementioned detector wavelet) to obtain comprehensive observation data of the first and second seismic waves. This comprehensive observation data ensures that the detector term in the forward modeling data during full-waveform inversion is consistent with the actual data. This comprehensive observation data is essentially the composite data of the first and second seismic waves. If the signal-to-noise ratio of the second seismic wave data is sufficiently high and the data quality is stable, inversion can be performed directly without the first seismic wave data. However, if the signal-to-noise ratio is too low, the filtering operator information of the second seismic wave data is used to correct the first seismic wave data to obtain the composite data, i.e., the comprehensive observation data, thereby ensuring that the detector term in the forward modeling data during full-waveform inversion is consistent with the actual data.

[0130] See Figures 1 to 5 In an optional embodiment, obtaining the subsurface velocity model and density model using the full waveform inversion algorithm based on the initial near-surface model includes: finding the filter operator for the receiver at the set location on the surface, and using the filter operator to simulate the receiver term in the forward modeling in the full waveform inversion, so as to eliminate the inconsistency between the forward modeling data waveform and the actual observation data waveform caused by the inconsistency of the coupling of the surface receivers.

[0131] By detecting the second seismic wave transmitted to the air above the Earth's surface and ensuring consistent filtering effects, combined observation data of the first and second seismic waves are obtained. This combined observation data is denoted as D. pz With the consistency between the seismic source and the receiver point guaranteed, the underground velocity model and density model are obtained using the full waveform inversion algorithm based on the comprehensive observation data.

[0132] The full waveform inversion algorithm is as follows: The obtained source wavelet is obtained through inversion. The initial near-surface model is labeled M. vρn (Velocity and density models) are used as input for forward modeling (wavefield simulation program), and the simulation generates data D. m D m With integrated observation data D pz The residual, R, is calculated. If the L2 norm of the residual R is less than a specific threshold ∈ , it indicates that the iterative process has converged, the velocity and density models match the actual underground structural velocity and density, and the entire process is complete, resulting in an underground velocity model that matches the actual underground velocity model, and an underground density model that matches the actual underground density model. Conversely, if the L2 norm of the residual R is greater than or equal to the specific threshold ∈ , the residual is converted into a gradient function G using the migration operator M, and M is updated using G. vρnA new velocity model M is obtained. vρ(n+1) Continue using M vρ(n+1) Forward simulation generates new data D m The process continues in the next iteration, repeating until the L2 norm of the residual is less than a specific threshold ∈ . In the full waveform inversion, the surface boundary condition adopts an absorbing boundary above the air layer, which better reflects the actual situation in the physical world, thus making it more realistic and accurate.

[0133] In addition, the present invention also provides an electronic device, including: a processor, a memory, and a program or instructions stored in the memory and executable in the processor, wherein the program or instructions, when executed by the processor, implement the steps of the land geophysical exploration method.

[0134] See Figures 4 to 6 In an optional embodiment, the electronic device further includes:

[0135] Detector 110 is used to be installed at the ground surface to detect the first seismic wave transmitted from underground vibrations to the ground surface.

[0136] Microphone 120 is used to position itself at a distance from the ground surface to detect the second seismic wave transmitted from underground vibrations into the air; and

[0137] The soundproof enclosure 410 is a sleeve structure. The soundproof enclosure 410 can be erected vertically on the ground along its axial direction, and the microphone 120 is disposed inside one end of the soundproof enclosure 410 along its axial direction. The soundproof enclosure 410 is used to block other noise between the ground and the microphone 120.

[0138] This land geophysical exploration equipment utilizes a geophone 110 to detect the first seismic wave transmitted to the surface, while simultaneously using a microphone 120 to detect the second seismic wave that has penetrated the surface and reached the air, taking advantage of the consistent sound speed and density of air under the same meteorological conditions. This allows the processing device to infer various surface-related parameters such as surface density, surface velocity, and actual reflection coefficient based on the first and second seismic waves, thereby achieving the goal of ensuring surface consistency in land exploration. This allows for the accurate determination of actual surface reflection coefficients, surface velocity, surface density, and other physical properties. These properties are used as the initial surface model, upon which an air velocity-density model is overlaid. By leveraging the consistency of air coupling, wavelets of the seismic source and receiver points can be obtained. These wavelets are then used to correct observational data or forward modeling data, maximizing the consistency between the observed and forward modeling data. In the full-wave inversion, the upper boundary condition of the air layer surface is set as an absorbing boundary, better fitting the surface boundary conditions of the real world. This makes subsequent inversion algorithms more accurate and ultimately provides subsurface structures without multiple solutions. This addresses the problem of unreliable imaging results and significant errors between the processed results and actual engineering or drilling data due to subjective factors and the resulting uncertainties in data processing.

[0139] See Figures 4 to 6 In an optional embodiment, the electronic device further includes a base 420 disposed on top of the soundproof housing 410, and multiple microphones 120 disposed on the bottom surface of the base 420 and inside the soundproof housing 410.

[0140] In an optional embodiment, the base 420 is a disc structure and is fixed to the top of the soundproof shell 410, and the multiple microphones 120 are arranged in multiple rings and set around the center of the base 420.

[0141] See Figures 3 to 5 In an optional embodiment, the detector 110 is connected to the bottom of the soundproof enclosure 410. This achieves an integrated setup, combining the microphone 120 and the detector 110 together, facilitating the arrangement of the detector 110 and the microphone 120.

[0142] See Figures 4 to 6 In an optional embodiment, the pickup 120 is a vector pickup used to detect at least one of the energy components of the second seismic wave, namely the velocity and pressure components. The pickup 120 may be a vector laser-air-coupled pickup or a MEMS vector pickup, capable of picking up vibration signals that travel from underground through the surface to the air.

[0143] See Figures 4 to 6In an optional embodiment, the detector 110 is a moving-coil detector, which is used to detect the pressure change component and / or the energy of the first seismic wave.

[0144] Of course, the detector 110 can also be a MEMS, or even a seismic detector in the form of an electrolyte or a pendulum.

[0145] See Figures 4 to 6 In an optional embodiment, the electronic device further includes a linear amplifier 210, an analog-to-digital converter module 220, and an acquisition control module 300. The linear amplifier 210 is connected to the analog-to-digital converter module 220, the analog-to-digital converter module 220 is connected to the acquisition control module 300, and the linear amplifier 210 is connected to a microphone 120 or a detector 110.

[0146] See Figures 4 to 6 In one optional embodiment, there are two linear amplifiers 210 and two analog-to-digital converter modules.

[0147] A microphone 120, a linear amplifier 210, and an analog-to-digital converter 220 are connected in sequence, and the analog-to-digital converter 220 is connected to the acquisition control module 300.

[0148] Detector 110, another linear amplifier 210, and another analog-to-digital converter 220 are connected in sequence, and the other analog-to-digital converter 220 is connected to the acquisition control module 300.

[0149] The signal acquired by the pickup 120 or the detector 110 is amplified by the linear amplifier 210 and then transmitted to the analog-to-digital conversion module to digitize the seismic signal. After digitization, the signal is sent to the acquisition control module 300 to record the corresponding first or second seismic wave.

[0150] The analog-to-digital converter module 220 here can be a high-precision analog-to-digital converter.

[0151] In addition, the present invention also provides a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the land geophysical exploration method.

[0152] It should be understood that the specific embodiments described above are merely illustrative or explanatory of the principles of the invention and do not constitute a limitation thereof. Therefore, any modifications, equivalent substitutions, improvements, etc., made without departing from the spirit and scope of the invention should be included within the protection scope of the invention. Furthermore, the appended claims are intended to cover all variations and modifications falling within the scope and boundaries of the appended claims, or equivalent forms of such scope and boundaries.

Claims

1. A method of land geophysical prospecting, characterised in that, include: Detects the first seismic wave transmitted from a predetermined location underground or on the surface to the surface. Detect the second seismic wave transmitted from the vibration to the air above the Earth's surface; Calculate the surface parameters within a set range of the preset location based on the first seismic wave and the second seismic wave; Calculate the underground velocity model and density model based on the surface parameters; The calculation of surface parameters within a predetermined range at the preset location based on the first seismic wave and the second seismic wave includes: Detecting the first seismic wave includes detecting the energy of the first seismic wave; Detecting the second seismic wave includes detecting the energy of the second seismic wave; The actual reflection coefficient within a set range at the preset location is calculated based on the energy of the first seismic wave and the energy of the second seismic wave. The calculation of surface parameters within a predetermined range at the preset location based on the first seismic wave and the second seismic wave includes: Based on the first seismic wave and the second seismic wave, obtain the direct wave or surface wave that reaches the detector point at the preset location; Calculate the surface velocity within a set range at the preset location based on the direct wave or surface wave; The calculation of surface parameters within a predetermined range at the preset location based on the first seismic wave and the second seismic wave includes: The surface density within a predetermined range at the preset location is obtained using the formula for calculating surface density. The formula for calculating the surface density is: ​ in, The surface density is [the density of the land]. The surface velocity is... The actual reflection coefficient is... The air velocity within a set range at the preset position. The air density within a set range at the preset location.

2. The land geophysical exploration method according to claim 1, characterized in that, The calculation of underground velocity and density models based on the surface parameters includes: Multiple predetermined locations are set up on the ground surface, and the first seismic wave and the second seismic wave are detected at each of the predetermined locations; Based on the first and second seismic waves at each of the set locations, the surface density and surface velocity at each of the set locations are obtained; An initial near-surface model is constructed based on air density, air velocity, and surface density and velocity at each of the specified locations; Based on the initial near-surface model, a subsurface velocity model and a density model are obtained using a full waveform inversion algorithm. The inverted subsurface velocity model matches the actual subsurface velocity, and the inverted subsurface density model matches the actual subsurface density model.

3. The land geophysical exploration method according to claim 2, characterized in that, The initial near-surface model is an initial near-surface model covered by an air layer. The air layer contains at least two parameters: air density and air velocity. The upper boundary of the air layer is set as an absorbing boundary.

4. The land geophysical exploration method according to claim 3, characterized in that, Based on the initial near-surface model, the subsurface velocity and density models are obtained using a full waveform inversion algorithm, including: The source wavelet function is obtained by inverting the wavelet morphology of each excitation source using the first arrival wave of a single shot. At the preset location where the vibration occurs, the subsurface velocity model and density model are obtained using the full waveform inversion algorithm based on the source wavelet function, so that the wavefield forward modeling results are consistent with the actual data.

5. The land geophysical exploration method according to claim 4, characterized in that, Based on the initial near-surface model, the subsurface velocity and density models are obtained using a full waveform inversion algorithm, including: The first seismic wavelet is shaped using the second seismic wave to obtain comprehensive observation data of the first and second seismic waves. The comprehensive observation data is used to ensure that the detector point terms of the forward modeling data in the full waveform inversion are consistent with the actual data.

6. The land geophysical exploration method according to claim 5, characterized in that, Based on the initial near-surface model, the subsurface velocity and density models are obtained using a full waveform inversion algorithm, including: The filtering operator for the receiver point at the set location on the ground surface is obtained by combining the second seismic wave and the first seismic wave. The filtering operator is then used to simulate the receiver point term in the forward modeling during full waveform inversion, so as to eliminate the inconsistency between the forward modeling data waveform and the actual data waveform caused by the inconsistency of the coupling of the ground receiver points.

7. An electronic device, characterized in that, include: A processor, a memory, and a program or instructions stored in the memory and executable within the processor, wherein the program or instructions, when executed by the processor, implement the steps of the land geophysical exploration method as described in any one of claims 1-6.

8. The electronic device according to claim 7, characterized in that, The electronic device also includes: A detector for being positioned at the ground surface to detect a first seismic wave transmitted from underground vibrations to the ground surface; and a microphone for being positioned at a distance from the ground surface to detect a second seismic wave transmitted from the vibrations to the air.

9. The electronic device according to claim 8, characterized in that, The electronic device also includes: The soundproof shell is a sleeve structure, which is used to be erected on the ground surface, and the microphone is located inside one end of the soundproof shell along its axial direction.

10. The electronic device according to any one of claims 8 to 9, characterized in that, The electronic device further includes a linear amplifier, an analog-to-digital converter module, and an acquisition and control module. The linear amplifier is connected to the analog-to-digital converter module, the analog-to-digital converter module is connected to the acquisition and control module, and the linear amplifier is connected to the microphone or the detector.

11. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the land geophysical exploration method as described in any one of claims 1-6.

Images