Transient electromagnetic arbitrary waveform three-dimensional forward modeling method, device and equipment

Abstract

The invention relates to a transient electromagnetic arbitrary waveform three-dimensional forward modeling method and device and computer equipment. The method comprises the following steps: decomposing an emission source into a plurality of independent sources, adaptively constructing a local grid of each receiving point according to skin depth information of each time channel, and forming a minimum observation unit on a single time channel by a single independent source and a single local grid; determining a characteristic step length of a corresponding time channel according to the skin depth information, and calculating an electromagnetic field response result on a minimum observation unit; electromagnetic field response results of the multiple minimum observation units are subjected to parallel calculation, and a complete transient electromagnetic arbitrary waveform three-dimensional forward modeling result is obtained through synthesis. According to the method, a complete parallelization calculation framework is realized, the calculation load is greatly reduced while the numerical precision is maintained, the broadband transient electromagnetic efficient forward modeling simulation is possible in a large-scale parallel calculation environment, and a powerful technical support is provided for three-dimensional electromagnetic detection under a complex geological condition.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration technology, and in particular to a method, apparatus, and computer equipment for three-dimensional forward modeling of transient electromagnetic arbitrary waveforms. Background Technology

[0002] Transient electromagnetic methods, with their high efficiency, low cost, and high signal-to-noise ratio, have become an indispensable geophysical tool in fields such as mineral exploration, environmental research, and airborne geophysical exploration. Within the transient electromagnetic technology system, forward modeling, as a key component, provides core support for feasibility studies, data quality control, field data interpretation, and inversion imaging processing.

[0003] In 3D simulation, the time-stepping method is a widely used time discretization technique. This method divides the simulation time into discrete step sizes and calculates the electromagnetic field response step by step for each time step. Early time traces use smaller step sizes, while later time traces are extrapolated based on earlier calculations. The step size can be constant or variable, but balancing the time step size with computational accuracy is crucial. Model reduction methods can achieve concurrent computation across multiple time traces; however, when considering arbitrary transmitted waveforms, the governing equations become non-homogeneous differential equations after spatial discretization, making the simulation of arbitrary waveforms using model reduction methods complex.

[0004] The observation decomposition framework treats any electromagnetic observation data as a simple assembly or linear combination of solutions to the single-time-channel dipole source problem. While existing observation decomposition methods rigorously solve the complete Maxwell's equations for all subproblems at a relatively low computational cost, they require fine time discretization of the entire transmitted waveform to ensure response accuracy when applied to arbitrary waveforms. This global waveform refinement strategy leads to an order-of-magnitude increase in the number of time steps, significantly reducing the efficiency of 3D forward modeling. Consequently, the parallelization advantages of this framework are not fully realized in practical applications, highlighting the core contradiction between computational accuracy and practical efficiency that remains to be resolved.

[0005] Therefore, existing technologies suffer from poor adaptability and low efficiency, and there is an urgent need for an innovative technical framework to achieve rapid three-dimensional forward modeling of arbitrary transmitted waveforms. Summary of the Invention

[0006] Therefore, it is necessary to provide a method, apparatus, computer equipment, and storage medium for three-dimensional forward modeling of transient electromagnetic arbitrary waveforms that can significantly reduce computational load, in order to address the aforementioned technical problems.

[0007] A method for three-dimensional forward modeling of transient electromagnetic arbitrary waveforms, the method comprising:

[0008] A transient electromagnetic three-dimensional forward model is constructed, and the transmitted waveform information, the transmitter information, the receiver point information, the observation time channel information, and the global grid information are set; the global grid information includes global grid coordinate information and global grid electrical parameters;

[0009] Based on the observation decomposition method, the emission source is decomposed into multiple independent sources according to the emission source information. The skin depth information of each time channel is determined according to the observation time channel information. A local grid for each receiving point is constructed according to the receiving point information and the skin depth information. The smallest observation unit is formed by a single independent source and a single local grid on a single time channel. The center position of the local grid is determined by the receiving point position, and the discretization region range and grid size of the local grid are determined by the skin depth information.

[0010] Based on the local grid coordinate information and the global grid information, the local grid electrical parameters corresponding to each smallest observation unit are obtained through a model transformation algorithm;

[0011] The characteristic step size of the corresponding time channel is determined based on the skin depth information, and the electromagnetic field response result is calculated on the smallest observation unit based on the characteristic step size, the local grid electrical parameters, and the emission waveform information.

[0012] The electromagnetic field response results of multiple smallest observation units are calculated in parallel and synthesized to obtain a complete three-dimensional forward modeling simulation result of transient electromagnetic arbitrary waveform.

[0013] In one embodiment, the method further includes: determining the skin depth information of each time channel based on the observed time channel information.

[0014]

[0015] in: Indicates skin depth. Indicates background resistivity. For the time of day.

[0016] In one embodiment, the method further includes: determining a transformation matrix between the local mesh and the global mesh based on the local mesh coordinate information and the global mesh coordinate information;

[0017] Multiple uniformly distributed random sampling points are generated in the local grid. The multiple random sampling points are transformed to the global grid according to the transformation matrix. A weighted average matrix is ​​constructed according to the cell position of the sampling points in the global grid.

[0018] Based on the weighted average matrix and the global grid electrical parameters, the local grid electrical parameters corresponding to the smallest observation unit are obtained.

[0019] In one embodiment, the method further includes: determining the feature step size of the corresponding time channel based on the skin depth information.

[0020]

[0021] in, Indicates the characteristic step size.

[0022] In one embodiment, the method further includes: performing a time-domain numerical integration with a constant step size based on the characteristic step size and the local grid electrical parameters to obtain the step-off electromagnetic field response;

[0023] The discrete impulse response of the smallest observation unit is obtained by differential operation based on the step-off electromagnetic field response.

[0024] Based on the transmitted waveform information, an optimized effective transmitted waveform segment is obtained. The discrete impulse response is then convolved with the effective transmitted waveform segment to obtain the electromagnetic field response result calculated on the smallest observation unit.

[0025] In one embodiment, the method further includes: selecting a waveform segment within the last 50% pulse width range based on the transmitted waveform information and convolving it with the discrete pulse response to obtain an initial electromagnetic response value;

[0026] Divide the remaining pulse width into equal parts, take the last 50% of the waveform segment and superimpose it onto the calculated waveform, perform a new round of convolution operation, and obtain the updated electromagnetic response;

[0027] The relative error of the electromagnetic response obtained from two adjacent convolutions is compared and judged against a preset accuracy threshold. If the error exceeds the allowable range, the remaining pulse width is further divided into equal parts, and new waveform segments are added one by one for convolution calculation.

[0028] The calculation is terminated once the relative error between two adjacent convolution results stabilizes within a preset threshold range and the required accuracy is achieved.

[0029] In one embodiment, the method further includes: convolving the waveform segment with the discrete impulse response to obtain an arbitrary waveform electromagnetic field response as follows:

[0030]

[0031] in, Indicates the number of segments into which the waveform is divided. It is the time interval of the step waveform offset. It is a waveform function. It corresponds The discrete impulse response.

[0032] A three-dimensional forward modeling simulation device for transient electromagnetic arbitrary waveforms, the device comprising:

[0033] The global model construction module is used to construct a transient electromagnetic three-dimensional forward model, setting the transmitted waveform information, the transmitter information, the receiver point information, the observation time channel information, and the global grid information; the global grid information includes global grid coordinate information and global grid electrical parameters;

[0034] The observation decomposition module is used to decompose the emission source into multiple independent sources based on the emission source information according to the observation decomposition method, determine the skin depth information of each time channel according to the observation time channel information, and construct a local grid for each receiving point according to the receiving point information and the skin depth information. The smallest observation unit is composed of a single independent source and a single local grid on a single time channel. The center position of the local grid is determined by the receiving point position, and the discretization region range and grid size of the local grid are determined by the skin depth information.

[0035] The local model conversion module is used to obtain the local grid electrical parameters corresponding to each of the smallest observation units through a model conversion algorithm based on the local grid coordinate information and the global grid information.

[0036] The minimum observation unit calculation module is used to determine the characteristic step size of the corresponding time channel based on the skin depth information, and to calculate the electromagnetic field response result on the minimum observation unit based on the characteristic step size, the local grid electrical parameters and the emission waveform information.

[0037] The synthesis module is used to calculate the electromagnetic field response results of multiple smallest observation units in parallel and synthesize them to obtain complete three-dimensional forward modeling results of transient electromagnetic arbitrary waveforms.

[0038] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing the following steps:

[0039] A transient electromagnetic three-dimensional forward model is constructed, and the transmitted waveform information, the transmitter information, the receiver point information, the observation time channel information, and the global grid information are set; the global grid information includes global grid coordinate information and global grid electrical parameters;

[0040] Based on the observation decomposition method, the emission source is decomposed into multiple independent sources according to the emission source information. The skin depth information of each time channel is determined according to the observation time channel information. A local grid for each receiving point is constructed according to the receiving point information and the skin depth information. The smallest observation unit is formed by a single independent source and a single local grid on a single time channel. The center position of the local grid is determined by the receiving point position, and the discretization region range and grid size of the local grid are determined by the skin depth information.

[0041] Based on the local grid coordinate information and the global grid information, the local grid electrical parameters corresponding to each smallest observation unit are obtained through a model transformation algorithm;

[0042] The characteristic step size of the corresponding time channel is determined based on the skin depth information, and the electromagnetic field response result is calculated on the smallest observation unit based on the characteristic step size, the local grid electrical parameters, and the emission waveform information.

[0043] The electromagnetic field response results of multiple smallest observation units are calculated in parallel and synthesized to obtain a complete three-dimensional forward modeling simulation result of transient electromagnetic arbitrary waveform.

[0044] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0045] A transient electromagnetic three-dimensional forward model is constructed, and the transmitted waveform information, the transmitter information, the receiver point information, the observation time channel information, and the global grid information are set; the global grid information includes global grid coordinate information and global grid electrical parameters;

[0046] Based on the observation decomposition method, the emission source is decomposed into multiple independent sources according to the emission source information. The skin depth information of each time channel is determined according to the observation time channel information. A local grid for each receiving point is constructed according to the receiving point information and the skin depth information. The smallest observation unit is formed by a single independent source and a single local grid on a single time channel. The center position of the local grid is determined by the receiving point position, and the discretization region range and grid size of the local grid are determined by the skin depth information.

[0047] Based on the local grid coordinate information and the global grid information, the local grid electrical parameters corresponding to each smallest observation unit are obtained through a model transformation algorithm;

[0048] The characteristic step size of the corresponding time channel is determined based on the skin depth information, and the electromagnetic field response result is calculated on the smallest observation unit based on the characteristic step size, the local grid electrical parameters, and the emission waveform information.

[0049] The electromagnetic field response results of multiple smallest observation units are calculated in parallel and synthesized to obtain a complete three-dimensional forward modeling simulation result of transient electromagnetic arbitrary waveform.

[0050] The aforementioned method, apparatus, computer equipment, and storage medium for three-dimensional forward modeling of transient electromagnetic arbitrary waveforms are based on the observation decomposition method. This method decomposes the transmitting source into multiple independent sources and adaptively constructs a local mesh for each receiving point based on the skin depth information of each time channel. A single independent source and a single local mesh constitute the smallest observation unit on a single time channel. This transforms the large-scale global computation task into a series of independently solvable sub-problems in the spatial dimension. In the temporal dimension, by implementing an independent discretization strategy for each time channel, it completely breaks through the sequential constraints of the traditional time-progression method. The electrical parameters of the local mesh corresponding to each smallest observation unit are obtained through model transformation from the global model to the local model. The characteristic step size of the corresponding time channel is determined based on the skin depth information, and the electromagnetic field response results are calculated on the smallest observation unit. The electromagnetic field response results of multiple smallest observation units are calculated in parallel and synthesized to obtain a complete three-dimensional forward modeling result for transient electromagnetic arbitrary waveforms. This invention addresses the problem of inefficient parallel computing in 3D forward modeling of arbitrary waveforms. Based on observation decomposition and scale matching, it realizes a fully parallel computing architecture similar to frequency domain methods. While maintaining numerical accuracy, it significantly reduces the computational load, making it possible to conduct efficient forward modeling of broadband transient electromagnetics in a large-scale parallel computing environment. This provides strong technical support for 3D electromagnetic exploration under complex geological conditions. Attached Figure Description

[0051] Figure 1 This is a flowchart illustrating a three-dimensional forward modeling simulation method for transient electromagnetic arbitrary waveforms in one embodiment.

[0052] Figure 2 This is a schematic diagram of a three-dimensional complex geological model in a specific embodiment;

[0053] Figure 3 This is a multi-track map along the X-direction survey line in a specific embodiment;

[0054] Figure 4 The figure below shows a comparison between the method of this application and the conventional method in a specific embodiment, where (a) is a graph of induced voltage attenuation; and (b) is a graph of relative error between the method of this application and the conventional method.

[0055] Figure 5 This is a structural block diagram of a three-dimensional forward modeling device for transient electromagnetic arbitrary waveforms in one embodiment;

[0056] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0058] In one embodiment, such as Figure 1 As shown, a three-dimensional forward modeling simulation method for transient electromagnetic arbitrary waveforms is provided, including the following steps:

[0059] Step 102: Construct a transient electromagnetic three-dimensional forward model and set the transmitted waveform information, transmitted source information, received point information, observation time channel information and global grid information.

[0060] Constructing a transient electromagnetic three-dimensional forward model involves establishing a three-dimensional digital model containing a three-dimensional target body, background, and air layer, based on geological and geophysical data or design assumptions, as a unified spatial framework for all subsequent simulation calculations.

[0061] Setting the transmitted waveform information involves determining the time-varying function form and related parameters of the excitation electromagnetic field. Transmitted waveforms include various typical types such as HELITEM, VTEM, and Skytem. Setting the transmitting source information involves determining the geometry, spatial location, and physical intensity of the transmitting device. Setting the receiving point information involves setting up the spatial network of virtual receiving points, the measurement components, and directions. Setting the observation time channel information involves planning the time series and sampling scheme for data acquisition. Setting the global grid information involves discretizing the global model into a grid suitable for numerical calculation and assigning physical property parameters. In this embodiment, the global grid information includes global grid coordinate information and global grid electrical parameters.

[0062] Step 104: Based on the observation decomposition method, the emission source is decomposed into multiple independent sources according to the emission source information. The skin depth information of each time channel is determined according to the observation time channel information. The local grid of each receiving point is constructed according to the receiving point information and the skin depth information. The smallest observation unit is formed by a single independent source and a single local grid on a single time channel.

[0063] The inventive concept of this invention is as follows: In the spatial dimension, this method deconstructs the complex transmitter and distributed receiver points into independent source-receiver pairs, and establishes an adapted local computational grid for each pair, thereby transforming the large-scale global computation task into a series of independently solvable sub-problems. In the temporal dimension, an independent discretization strategy is implemented for each time channel. After this double decoupling, each sub-problem strictly corresponds to the smallest observation unit of "single transmitter - single receiver - single time channel," thus refining the computational granularity and laying the foundation for large-scale parallel computing.

[0064] The local computational grid corresponding to each smallest observation unit is also called the local grid. The center position of the local grid is determined by the position of the receiving point, and the discretization region range and grid size of the local grid are determined by the skin depth information.

[0065] Based on the skin depth characteristics of the electromagnetic field corresponding to each time channel, a dedicated forward modeling grid for each smallest observation unit is adaptively constructed based on the scale matching principle. This can completely eliminate the data dependency between time channels, thereby reducing computational complexity.

[0066] In one specific embodiment, the vertical extent of the discretized region of the local mesh is typically set to at least three times the skin depth, and the horizontal extent is the same as the vertical extent. The mesh size is set to 1 / 5 to 1 / 4 of the skin depth.

[0067] Step 106: Based on the local grid coordinate information and the global grid information, obtain the local grid electrical parameters corresponding to each smallest observation unit through the model transformation algorithm.

[0068] Given the local and global mesh coordinates, the goal is to convert the global mesh model to a local mesh model. This conversion transfers the known electrical parameters from the global mesh model to the local mesh model, thereby determining the local mesh's electrical parameters.

[0069] Step 108: Determine the characteristic step size of the corresponding time channel based on the skin depth information, and calculate the electromagnetic field response result on the smallest observation unit based on the characteristic step size, local grid electrical parameters and emission waveform information.

[0070] This invention determines the feature step size of the corresponding time channel based on skin depth information. In this embodiment, the feature step size is:

[0071]

[0072] in, Indicates the characteristic step size.

[0073] The feature step size of the corresponding time trace is determined based on the skin depth information. The same feature step size is used to solve the response at each time step, requiring only one matrix decomposition, which greatly improves the computational efficiency of 3D forward modeling.

[0074] Specifically, the electromagnetic field response results are calculated as follows:

[0075] The step-turn-off electromagnetic field response is obtained by performing time-domain numerical integration with a constant step size based on the characteristic step size and local grid electrical parameters. When calculating the step-turn-off response, the staggered-grid finite volume method is used for spatial discretization, and the first-order backward Euler method is used for time discretization. The turn-off response can be solved using the double curl equation.

[0076]

[0077] in, Here, B is the curl operator, σ is the magnetic flux density, μ is the conductivity, δt is the time step size, and J is the permeability. s The source current density.

[0078] The discrete impulse response of the smallest observation unit is obtained by differentiation based on the step-off electromagnetic field response; the discrete impulse response is specifically as follows:

[0079]

[0080] in: Indicates from +Δt time to + The step waveform turn-off response at time t. Then corresponding to to + The step waveform shutdown response within the time interval -Δt.

[0081] Based on the transmitted waveform information, an optimized effective transmitted waveform segment is obtained. The discrete impulse response is then convolved with the effective transmitted waveform segment to obtain the calculated electromagnetic field response on the smallest observation unit.

[0082]

[0083] in, Indicates the number of segments into which the waveform is divided. It is the time interval of the step waveform offset. It is a waveform function. It corresponds The discrete impulse response.

[0084] Step 110: Calculate the electromagnetic field response results of multiple smallest observation units in parallel, and synthesize them to obtain the complete three-dimensional forward modeling simulation results of transient electromagnetic arbitrary waveforms.

[0085] In the aforementioned three-dimensional forward modeling simulation method for transient electromagnetic arbitrary waveforms, the transmitting source is decomposed into multiple independent sources based on the observation decomposition method. A local mesh for each receiving point is adaptively constructed based on the skin depth information of each time channel. A single independent source and a single local mesh constitute the smallest observation unit on a single time channel. This transforms the large-scale global computation task into a series of independently solvable sub-problems in the spatial dimension. In the temporal dimension, by implementing an independent discretization strategy for each time channel, the sequential constraints of the traditional time-progression method are completely overcome. The electrical parameters of the local mesh corresponding to each smallest observation unit are obtained through model transformation from the global model to the local model. The characteristic step size of the corresponding time channel is determined based on the skin depth information, and the electromagnetic field response results are calculated on the smallest observation unit. The electromagnetic field response results of multiple smallest observation units are calculated in parallel and synthesized to obtain the complete three-dimensional forward modeling simulation result for transient electromagnetic arbitrary waveforms. This invention addresses the problem of inefficient parallel computing in 3D forward modeling of arbitrary waveforms. Based on observation decomposition and scale matching, it realizes a fully parallel computing architecture similar to frequency domain methods. While maintaining numerical accuracy, it significantly reduces the computational load, making it possible to conduct efficient forward modeling of broadband transient electromagnetics in a large-scale parallel computing environment. This provides strong technical support for 3D electromagnetic exploration under complex geological conditions.

[0086] In one embodiment, the method further includes: determining a transformation matrix between the local grid and the global grid based on the local grid coordinate information and the global grid coordinate information; generating multiple uniformly distributed random sampling points in the local grid; transforming the multiple random sampling points to the global grid based on the transformation matrix; constructing a weighted average matrix based on the cell positions of the sampling points in the global grid; and obtaining the local grid electrical parameters corresponding to the smallest observation cell based on the weighted average matrix and the global grid electrical parameters.

[0087] This method constructs a weighted average matrix. Derive the target mesh model.

[0088] Specifically, in the conversion generation stage, firstly in Np uniformly distributed random sampling points are generated within each cell, and then these points are transformed to coordinate system 1. The location of these points is determined by querying the cell index. The host cells in the grid are used to construct the weight matrix. When it originates from The sampling point of unit i falls into When element j is selected, the matrix elements are... Add 1. In the matrix elements Represents the global grid Medium element j relative to the target mesh The relative contribution weight of unit i in the matrix. To ensure strict adherence to the law of conservation of mass, the matrix... The sum of the elements in each row must satisfy:

[0089]

[0090] Therefore, the matrix rows are normalized before the model transformation is performed.

[0091] according to The matrix derivation of the target mesh model is as follows:

[0092]

[0093] in: This represents the conductivity of the global grid. This represents the electrical conductivity of the local mesh.

[0094] In practical applications, since the target mesh cell usually only has spatial intersection with a few global mesh cells, the matrix It exhibits high sparsity. If non-activated units exist, the matrix needs to be removed. The corresponding rows and columns.

[0095] In model conversion, the volume-weighted average method is commonly used in this field, offering high modeling accuracy. While the weighted average matrix method described in this invention is faster and more efficient, its modeling accuracy is lower than that of the volume-weighted average method. Since this invention implements parallel computation based on the smallest observation unit, the computational granularity of the smallest observation unit is smaller, resulting in lower local model complexity. This allows for a moderate trade-off between model accuracy and higher computational efficiency; therefore, this invention employs the weighted average matrix method. Theoretical verification shows that when Np approaches infinity, the intersection volume estimated by this method is equivalent to the analytical geometric solution. Engineering practice confirms that approximately 80 sampling points are sufficient to quickly generate a conversion model that meets general modeling accuracy requirements. This method has significant advantages when dealing with complex mesh scenes, effectively avoiding the high computational cost problem of analytical methods.

[0096] In one embodiment, the method further includes: selecting a waveform segment within the last 50% of the pulse width based on the transmitted waveform information and convolving it with the discrete pulse response to obtain an initial electromagnetic response value; dividing the remaining pulse width equally, taking the last 50% of the waveform segment and superimposing it onto the calculated waveform to perform a new round of convolution operation to obtain an updated electromagnetic response; comparing the relative error of the electromagnetic responses obtained from two adjacent convolutions and judging it against a preset accuracy threshold; if the error exceeds the allowable range, continuing to divide the remaining pulse width equally and successively accumulating new waveform segments for convolution calculation; iterating until the relative error of two adjacent convolution results stabilizes within the preset threshold range, and the calculation is terminated after the accuracy requirement is met.

[0097] It should be understood that, although Figure 1The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order in which these steps are executed, and they can be performed in other orders. Furthermore, Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0098] In one specific embodiment, to test the method proposed in the invention, the following was designed: Figure 2 The three-dimensional geological model shown is described in detail below:

[0099] This invention constructs a three-dimensional low-resistivity anomaly model with a highly complex geometric morphology, such as... Figure 2 As shown, the electrical conductivity of air and surrounding rock was set to 10⁻¹⁰ S / m and 0.001 S / m, respectively. The transmitting source used a 200m × 200m rectangular loop, with 21 receiving stations spaced 20m apart along the x-direction. Recording 1× s to 1× Electromagnetic responses over 15 time channels within a time range of s were calculated. The HELITEM emission waveform was used, with a global mesh containing 252,300 elements, a minimum core element size of 20m, and a total of 781,219 degrees of freedom.

[0100] The simulation results clearly demonstrate the transient electromagnetic response characteristics of the three-dimensional anomaly model, such as... Figure 3 As shown, each curve represents the transient electromagnetic response characteristics at different receiving points within a given time channel. Compared to traditional time-stepping algorithms, the difference in calculation results across the entire region is generally controlled within 4%, such as... Figure 4 As shown, (a) is the induced voltage decay curve; (b) is the relative error diagram between the method of this application and the conventional method. This error range is within the generally accepted data uncertainty threshold range in 3D modeling. The conventional time-stepping method requires 651 seconds to calculate this 3D transient electromagnetic response, mainly due to the computational load of 690 time steps (including five different time-length schemes). The algorithm of this invention has a computation time of 54 seconds for the early time traces, while the computation time for the later time traces is significantly reduced to 25 seconds. While ensuring computational accuracy, this method achieves a 12-fold improvement in computational efficiency compared to the conventional time-stepping method.

[0101] In one embodiment, such as Figure 5As shown, a three-dimensional forward modeling simulation device for transient electromagnetic arbitrary waveforms is provided, comprising: a global model construction module 502, an observation decomposition module 504, a local model conversion module 506, a minimum observation unit calculation module 508, and a synthesis module 510, wherein:

[0102] The global model construction module 502 is used to construct a transient electromagnetic three-dimensional forward model, and to set the transmitted waveform information, the transmitted source information, the receiver point information, the observation time channel information, and the global grid information; the global grid information includes global grid coordinate information and global grid electrical parameters;

[0103] The observation decomposition module 504 is used to decompose the emission source into multiple independent sources based on the emission source information according to the observation decomposition method, determine the skin depth information of each time channel according to the observation time channel information, and construct the local grid of each receiving point according to the receiving point information and the skin depth information. The smallest observation unit is composed of a single independent source and a single local grid on a single time channel. The center position of the local grid is determined by the receiving point position, and the discretization region range and grid size of the local grid are determined by the skin depth information.

[0104] The local model conversion module 506 is used to obtain the local grid electrical parameters corresponding to each smallest observation unit based on the local grid coordinate information and the global grid information through a model conversion algorithm.

[0105] The minimum observation unit calculation module 508 is used to determine the characteristic step size of the corresponding time channel based on the skin depth information, and to calculate the electromagnetic field response results on the minimum observation unit based on the characteristic step size, local grid electrical parameters and emission waveform information.

[0106] The synthesis module 510 is used to calculate the electromagnetic field response results of multiple minimum observation units in parallel and synthesize them to obtain complete three-dimensional forward modeling results of transient electromagnetic arbitrary waveforms.

[0107] The observation decomposition module 504 is also used to determine the skin depth information of each time channel based on the observation time channel information:

[0108]

[0109] in: Indicates skin depth. Indicates background resistivity. For the time of day.

[0110] The local model conversion module 506 is also used to determine the conversion matrix between the local grid and the global grid based on the local grid coordinate information and the global grid coordinate information; generate multiple uniformly distributed random sampling points in the local grid; convert the multiple random sampling points to the global grid according to the conversion matrix; construct a weighted average matrix according to the cell position of the sampling points in the global grid; and obtain the local grid electrical parameters corresponding to the smallest observation cell based on the weighted average matrix and the global grid electrical parameters.

[0111] The minimum observation unit calculation module 508 is also used to determine the feature step size of the corresponding time trace based on the skin depth information:

[0112]

[0113] in, Indicates the characteristic step size.

[0114] The minimum observation unit calculation module 508 is also used to perform time-domain numerical integration with a constant step size based on the characteristic step size and local grid electrical parameters to obtain the step-off electromagnetic field response; to obtain the discrete impulse response of the minimum observation unit through differentiation operation based on the step-off electromagnetic field response; to obtain the optimized effective transmission waveform segment based on the transmission waveform information; and to perform convolution operation between the discrete impulse response and the effective transmission waveform segment to obtain the electromagnetic field response result calculated on the minimum observation unit.

[0115] The minimum observation unit calculation module 508 is also used to select waveform segments within the last 50% of the pulse width based on the transmitted waveform information and convolve them with the discrete pulse response to obtain the initial electromagnetic response value; divide the remaining pulse width equally, take the last 50% of the waveform segments and superimpose them onto the already calculated waveform to perform a new round of convolution operation to obtain the updated electromagnetic response; compare the relative error of the electromagnetic response obtained from two adjacent convolutions and judge it with the preset accuracy threshold: if the error exceeds the allowable range, continue to divide the remaining pulse width equally and accumulate new waveform segments for convolution calculation; iterate until the relative error of two adjacent convolution results stabilizes within the preset threshold range, and the calculation terminates after the accuracy requirement is met.

[0116] The minimum observation unit calculation module 508 is also used to convolve the waveform segment with the discrete impulse response to obtain the electromagnetic field response of any waveform:

[0117]

[0118] in, Indicates the number of segments into which the waveform is divided. It is the time interval of the step waveform offset. It is a waveform function. It corresponds The discrete impulse response.

[0119] Specific limitations regarding the transient electromagnetic arbitrary waveform three-dimensional forward modeling simulation device can be found in the limitations of the transient electromagnetic arbitrary waveform three-dimensional forward modeling simulation method above, and will not be repeated here. Each module in the aforementioned transient electromagnetic arbitrary waveform three-dimensional forward modeling simulation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in a computer device, or stored in software in the memory of a computer device, so that the processor can call and execute the corresponding operations of each module.

[0120] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When executed by the processor, the computer program implements a three-dimensional forward modeling simulation method for transient electromagnetic arbitrary waveforms. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0121] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0122] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps in the above method embodiment.

[0123] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0124] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0125] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0126] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A three-dimensional forward modeling simulation method for transient electromagnetic arbitrary waveforms, characterized in that, The method includes: A transient electromagnetic three-dimensional forward model is constructed, and the transmitted waveform information, the transmitter information, the receiver point information, the observation time channel information, and the global grid information are set; the global grid information includes global grid coordinate information and global grid electrical parameters; Based on the observation decomposition method, the emission source is decomposed into multiple independent sources according to the emission source information. The skin depth information of each time channel is determined according to the observation time channel information. A local grid for each receiving point is constructed according to the receiving point information and the skin depth information. The smallest observation unit is formed by a single independent source and a single local grid on a single time channel. The center position of the local grid is determined by the receiving point position, and the discretization region range and grid size of the local grid are determined by the skin depth information. Based on the local grid coordinate information and the global grid information, the local grid electrical parameters corresponding to each smallest observation unit are obtained through a model transformation algorithm; The characteristic step size of the corresponding time channel is determined based on the skin depth information, and the electromagnetic field response result is calculated on the smallest observation unit based on the characteristic step size, the local grid electrical parameters, and the emission waveform information. The electromagnetic field response results of multiple smallest observation units are calculated in parallel and synthesized to obtain a complete three-dimensional forward modeling simulation result of transient electromagnetic arbitrary waveform.

2. The method according to claim 1, characterized in that, Based on the observed time-channel information, the skin depth information for each time channel is determined, including: Based on the observed time-channel information, the skin depth information for each time channel is determined as follows: in: Indicates skin depth. Indicates background resistivity. For the time of day.

3. The method according to claim 2, characterized in that, Based on the local grid coordinate information and the global grid information, the local grid electrical parameters corresponding to each smallest observation unit are obtained through a model transformation algorithm, including: Based on the local grid coordinate information and the global grid coordinate information, determine the transformation matrix between the local grid and the global grid; Multiple uniformly distributed random sampling points are generated in the local grid. The multiple random sampling points are transformed to the global grid according to the transformation matrix. A weighted average matrix is ​​constructed according to the cell position of the sampling points in the global grid. Based on the weighted average matrix and the global grid electrical parameters, the local grid electrical parameters corresponding to the smallest observation unit are obtained.

4. The method according to claim 3, characterized in that, Determining the feature step size of the corresponding time channel based on the skin depth information includes: Based on the skin depth information, the feature step size for the corresponding time channel is determined as follows: in, Indicates the characteristic step size.

5. The method according to claim 4, characterized in that, The electromagnetic field response is calculated on the smallest observation unit based on the characteristic step size, the local grid electrical parameters, and the emitted waveform information, including: The step-off electromagnetic field response is obtained by performing time-domain numerical integration with a constant step size based on the characteristic step size and the local grid electrical parameters. The discrete impulse response of the smallest observation unit is obtained by differential operation based on the step-off electromagnetic field response. Based on the transmitted waveform information, an optimized effective transmitted waveform segment is obtained. The discrete impulse response is then convolved with the effective transmitted waveform segment to obtain the electromagnetic field response result calculated on the smallest observation unit.

6. The method according to claim 5, characterized in that, Based on the transmitted waveform information, an optimized effective transmitted waveform segment is obtained. The discrete impulse response is then convolved with the effective transmitted waveform segment to obtain the calculated electromagnetic field response on the smallest observation unit, including: Based on the transmitted waveform information, a waveform segment within 50% of the pulse width is selected and convolved with the discrete pulse response to obtain the initial electromagnetic response value; Divide the remaining pulse width into equal parts, take the last 50% of the waveform segment and superimpose it onto the calculated waveform, perform a new round of convolution operation, and obtain the updated electromagnetic response; The relative error of the electromagnetic response obtained from two adjacent convolutions is compared and judged against a preset accuracy threshold. If the error exceeds the allowable range, the remaining pulse width is further divided into equal parts, and new waveform segments are added one by one for convolution calculation. The calculation is terminated once the relative error between two adjacent convolution results stabilizes within a preset threshold range and the required accuracy is achieved.

7. The method according to claim 6, characterized in that, The waveform segment is convolved with the discrete impulse response, including: Convolving the waveform segment with the discrete impulse response yields the electromagnetic field response of any waveform: in, Indicates the number of segments into which the waveform is divided. It is the time interval of the step waveform offset. It is a waveform function. It corresponds The discrete impulse response.

8. A three-dimensional forward modeling simulation device for transient electromagnetic arbitrary waveforms, characterized in that, The device includes: The global model construction module is used to construct a transient electromagnetic three-dimensional forward model, setting the transmitted waveform information, the transmitter information, the receiver point information, the observation time channel information, and the global grid information; the global grid information includes global grid coordinate information and global grid electrical parameters; The observation decomposition module is used to decompose the emission source into multiple independent sources based on the emission source information according to the observation decomposition method, determine the skin depth information of each time channel according to the observation time channel information, and construct a local grid for each receiving point according to the receiving point information and the skin depth information. The smallest observation unit is composed of a single independent source and a single local grid on a single time channel. The center position of the local grid is determined by the receiving point position, and the discretization region range and grid size of the local grid are determined by the skin depth information. The local model conversion module is used to obtain the local grid electrical parameters corresponding to each of the smallest observation units through a model conversion algorithm based on the local grid coordinate information and the global grid information. The minimum observation unit calculation module is used to determine the characteristic step size of the corresponding time channel based on the skin depth information, and to calculate the electromagnetic field response result on the minimum observation unit based on the characteristic step size, the local grid electrical parameters and the emission waveform information. The synthesis module is used to calculate the electromagnetic field response results of multiple smallest observation units in parallel and synthesize them to obtain complete three-dimensional forward modeling results of transient electromagnetic arbitrary waveforms.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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