A method for estimating acoustic velocity and stratigraphic dip of non-constant layer-thickness deposition layers

Abstract

The application provides a sound velocity and stratigraphic dip estimation method for non-equal layer thickness deposition layers, and belongs to the technical fields of seafloor shallow stratigraphic profile detection and digital signal processing. The method solves the problems of easy divergence and falling into trivial solution in parameter inversion under complex seafloor conditions. The method comprises the following steps: obtaining shallow stratigraphic echo data of multi-direction detection; establishing a multi-direction sound propagation geometric model, and constructing a nonlinear objective function with a physical time residual as a core to form a physical residual barrier against degradation; substituting actual observation echo time differences of each wave beam into the nonlinear objective function to jointly construct an over-determined nonlinear equation set; using a finite difference method to approximately solve a Jacobian matrix of the over-determined nonlinear equation set; performing constraint truncation on the trial updated geosound parameters; adaptively adjusting an algorithm damping factor, and performing cyclic iteration until a convergence condition is met, and finally outputting an estimated value. The method is mainly used for sound velocity and stratigraphic dip estimation of non-equal layer thickness deposition layers.

Description

Technical Field

[0001] This invention belongs to the field of seafloor shallow strata profiling and digital signal processing technology, and in particular relates to a method for estimating the sound velocity and dip angle of sedimentary layers with non-uniform thickness. Background Technology

[0002] Seafloor shallow seismic profiling is a key technology for marine geological surveys, underwater pipeline route inspections, and geological hazard assessments. Traditional techniques for interpreting exploration data often rely on simplified physical models, such as assuming horizontally equal-thickness seafloor sedimentary layers and using constant empirical values ​​for sound velocity.

[0003] In real marine environments, seabed topography often presents complex features such as inclination and uneven thickness. Using simplified models can lead to incorrect judgments of sound wave propagation paths and incorrect substitution of sound velocities, resulting in severe geometric distortion in the acquired profile images and consequently poor performance in geosonic parameter inversion and application. Existing methods are prone to falling into trivial solutions (sound velocity approaching zero) when dealing with multi-parameter coupled equations due to low signal-to-noise ratios or model mismatches, leading to inversion failure. Therefore, researching an adaptive, high-resolution, and robust method for extracting geosonic parameters under complex terrain is of great significance. Summary of the Invention

[0004] In view of this, the present invention aims to propose a method for estimating the sound velocity and dip angle of sedimentary layers with non-uniform thickness, so as to solve the problem that parameter inversion is prone to divergence and getting trapped in trivial solutions under complex seafloor conditions.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: According to a first aspect of the present invention, a method for estimating the sound velocity and dip angle of sedimentary layers with non-uniform thickness is provided, comprising the following steps: Acquire shallow subsurface echo data from multiple directions and extract the echo time difference between the seabed and sedimentary layer corresponding to each beam direction; A multi-directional sound propagation geometric model is established based on ray acoustics theory, and a nonlinear objective function is constructed with physical time residual as the core, forming a physical residual barrier against degradation in the solution space. Substitute the actual observed echo time difference of each beam into the nonlinear objective function to construct an overdetermined nonlinear equation set concerning the sound velocity of the sedimentary layer and the dip angle of the strata. The Jacobian matrix of the overdetermined nonlinear equation system is approximated by the finite difference method, and the damping LM iterative algorithm is initialized. Solve the LM incremental equation to obtain the parameter update step size, and combine the physical boundary conditions to constrain and truncate the experimentally updated ground acoustic parameters; Based on the trend of the overall residual change of the system before and after the trial update, the damping factor of the algorithm is adaptively adjusted, and the iteration is repeated until the convergence condition is met, and finally the estimated value is output.

[0006] Furthermore, the acquisition of shallow subsurface echo data from multi-directional detection, and the extraction of the echo time difference between the seabed and sedimentary layer corresponding to each beam direction, specifically includes: Multibeam shallow-profile sonar emits and collects a set of signals consisting of a normal beam and a sonar beam within a single detection cycle. A multidirectional echo signal composed of conventional scanning beams, where N is an integer greater than or equal to 2; Envelope detection and time delay estimation were performed on the acquired echo signals of each beam, and the observation echo time difference corresponding to the normal beam was extracted respectively. and the observation echo time difference corresponding to each scanning beam ,in, The travel time of the first echo from the seabed interface corresponding to each detection beam. This is the second echo travel time at the bottom interface of the sedimentary layer.

[0007] Furthermore, the specific expression of the multidirectional sound propagation geometric model is as follows: in, The one-way slant distance of the acoustic beam propagating within the sediment layer. ， The vertical thickness of the local deposition layer corresponding to the incident point of the acoustic beam; The angle of refraction of the sound wave within the sediment layer; This indicates the dip angle of the sedimentary strata.

[0008] Furthermore, the specific expression of the nonlinear objective function is as follows: in, The theoretical physical echo time difference of a sound wave traveling back and forth within the sediment layer is expressed as follows: , This represents the one-way slant distance of the acoustic beam propagating within the sediment layer. To determine the true sound velocity of the sedimentary layer to be inverted, Indicates the dip angle of the sedimentary strata. This indicates the actual observed echo time difference.

[0009] Furthermore, substituting the actual observed echo time difference of each beam into the nonlinear objective function to simultaneously construct an overdetermined set of nonlinear equations concerning the sound velocity of the sedimentary layer and the dip angle of the strata specifically includes: N probe beams, which are more than the number of parameters to be estimated, and an independent normal beam are selected to obtain the actual observed echo time difference of each beam, where N is an integer greater than or equal to 2. For the One beam, By utilizing geometric constraints to calculate the local sedimentary layer thickness variation caused by the stratum dip angle, and combining this with Snell's law to determine the acoustic wave refraction angle, the physical time residual function corresponding to the beam is then calculated. ; The residual functions of N beams are stacked and combined into a column vector, and an overdetermined nonlinear equation system is constructed for the sound velocity of the sedimentary layer and the dip angle of the strata.

[0010] Furthermore, the method of approximating the Jacobian matrix of the overdetermined nonlinear equation system using the finite difference method specifically includes: Preset small perturbations are applied to the sound velocity of the sedimentary layer and the dip angle of the strata, respectively. By calculating the rate of change of the system residuals before and after the perturbation, the partial derivative of the Jacobian matrix is ​​approximately approximated.

[0011] Furthermore, the step size for obtaining the parameter update by solving the LM incremental equation, and the constraint truncation of the experimentally updated ground acoustic parameters in combination with physical boundary conditions, specifically includes: Construct the LM incremental equation and solve for the iterative update of the incremental step size; Physical boundary constraints are introduced to determine the updated parameters. If the updated sound speed exceeds the set upper and lower limits of the physical sound speed, it is forcibly truncated to the boundary extreme value.

[0012] Furthermore, the adaptive adjustment of the algorithm damping factor based on the overall residual change trend of the system before and after the trial update specifically includes: Calculate the new population residual norm corresponding to the trial parameters. If the new residual norm is less than the old residual norm, the convergence direction is determined to be correct. Then, accept this parameter update and reduce the damping factor proportionally. If the new residual norm is greater than the old residual norm, the convergence direction is determined to be off, the parameter update is rejected, and the damping factor is increased exponentially.

[0013] According to a second aspect of the present invention, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the method for estimating the sound velocity and dip angle of non-uniform thickness sedimentary layers as described above.

[0014] According to a third aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, the computer program being used to cause the computer to perform the sound velocity and formation dip angle estimation method for non-uniform thickness sedimentary layers as described above.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention provides a method for estimating the sound velocity and dip angle of sedimentary layers with non-uniform thickness. By constructing a physical residual barrier, the objective function of the error is defined as the physical time residual, which forces the unknown sound velocity to be located in the denominator of the formula. This form ensures from a mathematical mechanism that when the parameters undergo non-physical degradation, a large residual will be generated, which effectively avoids the nonlinear algorithm from getting stuck in the trivial solution where the sound velocity tends to zero. 2. This invention solves the problem of easy divergence in multi-parameter inversion under low signal-to-noise ratio. In the face of the strong coupling problem of multi-parameters caused by inclined strata, this invention uses the multi-directional electronic scanning characteristics of multi-beam shallow profiling sonar to construct a multi-beam overdetermined nonlinear equation system. Through redundant observation at the macroscopic spatial scale, the interference of local microscopic random errors is greatly suppressed, so that the method has high robustness and high accuracy in complex environments and low signal-to-noise ratio conditions. 3. This invention has extremely high engineering feasibility. It uses the finite difference method to approximate the Jacobian matrix, which completely avoids the tedious analytical differentiation for complex seabed topography models. At the same time, by combining physical boundary constraints with the adaptive damping adjustment of the LM algorithm, it effectively improves the global stability and convergence speed of the calculation. The algorithm has low overall resource consumption and a tight logical closed loop, making it easy to directly integrate into the embedded digital signal processor (DSP) of underwater sonar. Attached Figure Description

[0016] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart illustrating the method for estimating the sound velocity and dip angle of sedimentary layers with non-uniform thickness as described in this invention. Figure 2 This is a schematic diagram of the physical geometric model of multidirectional sound propagation in the method for estimating sound velocity and dip angle of non-uniform thickness sedimentary layers described in this invention; Figure 3 This is a parameter iteration convergence curve diagram in the method for estimating sound velocity and dip angle of non-uniform thickness sedimentary layers according to the present invention; Figure 4 This is a percentage relative error analysis chart of 1000 Monte Carlo runs under different signal-to-noise ratio conditions according to the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other, and the described embodiments are only some embodiments of the present invention, not all embodiments.

[0018] Figure 1 This is a schematic flowchart of a method for estimating the sound velocity and dip angle of sedimentary layers with non-uniform thickness, as described in this invention.

[0019] like Figure 1 As shown, the method for estimating the sound velocity and dip angle of this non-uniform thickness sedimentary layer includes the following steps: In step S1, shallow seabed echo data from multi-directional detection are acquired, and the echo time difference between the seabed and sedimentary layer corresponding to each directional beam is extracted.

[0020] In some embodiments, the acquisition of shallow subsurface echo data from multi-directional detection and the extraction of the echo time difference between the seabed and sedimentary layer corresponding to each beam direction specifically include: Multibeam shallow profile sonar Synchronous or time-division electronic scanning is performed on each beam angle. This includes... Each independent normal beam has an emission deflection angle. Set as negative seabed tilt angle This ensures that it is perpendicularly incident on the seabed surface in seawater; it also includes... A conventional scanning beam, in this embodiment Scanning angle coverage to Step length .

[0021] The system collects all of the above. The echo signals of each beam are processed by a signal processing front-end to extract the first echo travel time of the seabed interface corresponding to each detection beam. Second echo travel time at the bottom interface of the sedimentary layer Then, the observation echo time difference of the normal beam is calculated. Time difference between observation echoes and each scanning beam .

[0022] like Figure 2 As shown, in step S2, a multi-directional sound propagation geometric model is established based on ray acoustics theory, and a nonlinear objective function is constructed with physical time residual as the core, forming a physical residual barrier against degradation in the solution space.

[0023] In actual implementation, the speed of sound in seawater is assumed to be a known constant. The true sound velocity of the sedimentary layer to be inverted is When a phased array sonar emits a detection beam toward the seabed, let the angle of incidence of the beam in the seawater be θ. .

[0024] The refraction effect of sound waves is calculated according to Snell's Law, which determines the angle of refraction of sound waves within the sedimentary layer. The following physical equations must be satisfied: First, the actual observed echo time difference is extracted using a normal beam emitted perpendicular to the seabed surface. Establish a reference layer thickness in the normal direction. Adaptive decoupling relationship: Using the lateral horizontal offset of the probe beam relative to the normal beam contact point with the dip angle of the strata Determine the local deposition layer thickness corresponding to the incident point of the beam: Furthermore, based on the sine theorem of triangles, the one-way slant range of an arbitrary probe beam propagating within the sedimentary layer is derived. The specific expression is: in, The sound velocity of the sedimentary layer to be inverted; This represents the one-way slant distance of the acoustic beam propagating within the sediment layer. This represents the local deposition layer thickness corresponding to the incident point of the beam. The angle of refraction of the sound wave within the sediment layer; This indicates the dip angle of the sedimentary strata.

[0025] The theoretical physical time difference of the sound wave's round-trip propagation within the sediment layer is: in, This represents the one-way slant distance of the acoustic beam propagating within the sediment layer. To determine the true sound velocity of the sedimentary layer to be inverted, This indicates the dip angle of the sedimentary strata.

[0026] The theoretical travel time described above is compared with the actual observed echo time difference of the beam extracted in step 1. Subtraction constructs a nonlinear objective function with the physical time residual as its core, the specific expression of which is: The residual function will determine the sound velocity of the sediment layer to be inverted. This is placed in the denominator, thus forming a physical residual potential barrier in the solution space. The mathematical mechanism lies in: during the iteration process... When the residual approaches zero (i.e., falls into a trivial solution), The value of the objective function will tend to infinity, causing it to increase dramatically, thus effectively guiding the optimization algorithm away from the non-physical degenerate region.

[0027] In step S3, the actual observed echo time difference of each beam is substituted into the nonlinear objective function to construct an overdetermined nonlinear equation set concerning the sound velocity of the sedimentary layer and the dip angle of the strata.

[0028] In some embodiments, the actual observed echo time difference of each beam is substituted into the nonlinear objective function to simultaneously construct an overdetermined set of nonlinear equations concerning the sound velocity of the sedimentary layer and the dip angle of the formation, specifically including: Select more parameters than the parameters to be estimated Each probe beam and an independent normal beam are used to obtain the actual observed echo time difference for each beam. It is an integer greater than or equal to 2; For the One beam, By utilizing geometric constraints to calculate the local sedimentary layer thickness variation caused by the stratum dip angle, and combining this with Snell's law to determine the acoustic wave refraction angle, the physical time residual function corresponding to the beam is then calculated. ; The residual functions of N beams are stacked and combined into a column vector, and an overdetermined nonlinear equation system is constructed for the sound velocity of the sedimentary layer and the dip angle of the strata.

[0029] In actual execution, using the detection data from the aforementioned N+1 scanning beams, the deflection angle is first extracted from the scanning sequence. Normal beam observation echo time difference Based on the perpendicular geometric relationship between the normal beam and the seabed, the reference layer thickness perpendicular to the seabed surface is obtained through decoupling. Subsequently, for the remaining incident angles... The detection beam utilizes the normal distance from the array to the seabed surface. The lateral horizontal offset relative to the normal beam contact point is calculated using geometric projection: Based on this, combined with the reference layer thickness Horizontal offset and the dip angle of the strata to be estimated Determine the local sedimentary layer thickness corresponding to each detection point. Then, by substituting various geometric constraints into the physical forward modeling process, a model for the sound velocity of the sedimentary layer is constructed. with the dip angle of the strata nonlinear objective function ; Stack the residual functions of N beams together to form a column vector: An overdetermined set of nonlinear equations relating the sound velocity in sedimentary layers to the dip angle of the formation is constructed simultaneously. Redundant observations at the macroscopic spatial scale significantly suppress the interference of local microscopic random errors, enabling this method to exhibit high robustness and accuracy in complex environments and under low signal-to-noise ratio conditions.

[0030] In step S4, the Jacobian matrix of the overdetermined nonlinear equation system is approximately solved using the finite difference method, and the damping LM iterative algorithm is initialized.

[0031] In some embodiments, the step of approximating the Jacobian matrix of the overdetermined nonlinear equation system using the finite difference method specifically includes: Preset small perturbations are applied to the sound velocity of the sedimentary layer and the dip angle of the strata, respectively. By calculating the rate of change of the system residuals before and after the perturbation, the partial derivative of the Jacobian matrix is ​​approximately approximated.

[0032] In actual implementation, the initial iterative values ​​of the parameters to be estimated and the initial damping factor of the LM algorithm are set. In this embodiment, the initial value of the sound velocity is set to 1500 m / s, and the initial value of the tilt angle is set to 0°. The value is 0.01; the sound velocity of the sedimentary layer is respectively... and the dip angle of the strata In this embodiment, the sound velocity of the deposition layer is determined by a preset small perturbation. Preset small perturbation amount m / s, stratigraphic dip Preset small perturbation amount rad; By calculating the rate of change of the system residuals before and after the perturbation, the partial derivative of the Jacobian matrix J is approximately approximated, i.e.: In step S5, the LM incremental equation is solved to obtain the parameter update step size, and the updated ground acoustic parameters are constrained and truncated in combination with physical boundary conditions.

[0033] In some embodiments, the step size for obtaining parameter update by solving the LM incremental equation, and the constraint truncation of the experimentally updated ground acoustic parameters in combination with physical boundary conditions, specifically includes: Construct the LM incremental equation and solve for the iterative update of the incremental step size; Physical boundary constraints are introduced to determine the updated parameters. If the updated sound speed exceeds the set upper and lower limits of the physical sound speed, it is forcibly truncated to the boundary extreme value.

[0034] In actual implementation, the LM incremental equation is constructed, and its expression is as follows: And solve for the incremental step size of the iterative update. ; Introducing physical boundary constraints to update the parameters after trial and error A decision is made if the updated speed of sound exceeds the set upper and lower limits of the physical speed of sound. In this embodiment, the set upper and lower limits of the physical speed of sound are in the range of 1000m / s to 3000m / s, then it is forcibly truncated to the boundary extreme value.

[0035] In step S6, based on the trend of the overall residual change of the system before and after the trial update, the algorithm damping factor is adaptively adjusted and iterated until the convergence condition is met, and finally the estimated value is output.

[0036] In some embodiments, the algorithm damping factor is adaptively adjusted based on the overall residual change trend of the system before and after the trial update, specifically including: Calculate the new population residual norm corresponding to the trial parameters. If the new residual norm is less than the old residual norm, the convergence direction is determined to be correct. Then, accept this parameter update and reduce the damping factor proportionally. If the new residual norm is greater than the old residual norm, the convergence direction is determined to be off, the parameter update is rejected, and the damping factor is increased exponentially.

[0037] In actual implementation, the new population residual norm corresponding to the trial parameters is calculated. If the new residual norm is less than the old residual norm, the convergence direction is determined to be correct, and the parameter update is accepted. The damping factor is then adjusted accordingly. Scaling down proportionally, in this embodiment the scaling down ratio is... To take advantage of the fast convergence property of the Gauss-Newton method; If the new residual norm is greater than the old residual norm, the convergence direction is considered to have deviated, the parameter update is rejected, and the damping factor is increased exponentially. In this embodiment, the increase ratio is 1. This causes the algorithm to degenerate into a globally stable gradient descent method; Repeat steps S4 to S6 until the residual norm is less than the preset accuracy threshold or the maximum number of iterations is reached.

[0038] like Figure 3 The figure shows the convergence curve of the parameter iteration; Figure 4 The figure shows the relative error analysis of 1000 Monte Carlo simulations conducted in the signal-to-noise ratio range of 5dB to 20dB. The results show that when the environmental signal-to-noise ratio is greater than 8dB, the relative error of dip angle estimation can be controlled within 5%, and the relative error of sound velocity estimation is less than 2%. The final output is a high-precision estimate of the sound velocity and dip angle of the non-uniform thickness sedimentary layer.

[0039] The method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness proposed in this invention has the following advantages: (1) By constructing a physical residual barrier, the objective function of the error is defined as the physical time residual, and the unknown speed of sound is forced to be in the denominator of the formula. This form ensures from a mathematical mechanism perspective that when the parameters undergo non-physical degradation, a large residual will be generated, which effectively avoids the nonlinear algorithm from falling into the trivial solution where the speed of sound tends to zero. (2) This invention solves the problem of easy divergence in multi-parameter inversion under low signal-to-noise ratio. In the face of the problem of strong coupling of multiple parameters caused by tilted strata, this invention uses the multi-directional electronic scanning characteristics of multi-beam shallow profiling sonar to construct a multi-beam overdetermined nonlinear equation set. Through redundant observation at the macroscopic spatial scale, the interference of local microscopic random errors is greatly suppressed, so that the method has high robustness and high accuracy in complex environment and low signal-to-noise ratio conditions. (3) It has extremely high engineering feasibility. It uses the finite difference method to approximate the Jacobian matrix, which completely avoids the tedious analytical differentiation for complex seabed topography models. At the same time, it combines physical boundary constraints with the adaptive damping adjustment of the LM algorithm, which effectively improves the global stability and convergence speed of the calculation. The algorithm has low overall resource consumption and a tight logical closed loop, making it easy to directly integrate into the embedded digital signal processor (DSP) of underwater sonar.

[0040] This invention proposes an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the method for estimating the sound velocity and dip angle of the non-uniform thickness sedimentary layer.

[0041] This invention proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the method for estimating the sound velocity and dip angle of the non-uniform thickness sedimentary layer.

[0042] The memory in this application embodiment can be volatile memory or non-volatile memory, or it can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DRRAM). It should be noted that the memory used in the methods described in this invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0043] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs (DVDs)), or semiconductor media (e.g., solid-state drives (SSDs)).

[0044] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0045] It should be noted that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuitry in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0046] The above provides a detailed description of the method for estimating the sound velocity and dip angle of non-uniform thickness sedimentary layers proposed in this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness, characterized in that: Includes the following steps: Acquire shallow subsurface echo data from multiple directions and extract the echo time difference between the seabed and sedimentary layer corresponding to each beam direction; A multi-directional sound propagation geometric model is established based on ray acoustics theory, and a nonlinear objective function is constructed with physical time residual as the core, forming a physical residual barrier against degradation in the solution space. Substitute the actual observed echo time difference of each beam into the nonlinear objective function to construct an overdetermined nonlinear equation set concerning the sound velocity of the sedimentary layer and the dip angle of the strata. The Jacobian matrix of the overdetermined nonlinear equation system is approximated by the finite difference method, and the damping LM iterative algorithm is initialized. Solve the LM incremental equation to obtain the parameter update step size, and combine the physical boundary conditions to constrain and truncate the experimentally updated ground acoustic parameters; Based on the trend of the overall residual change of the system before and after the trial update, the damping factor of the algorithm is adaptively adjusted, and the iteration is repeated until the convergence condition is met, and finally the estimated value is output.

2. The method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness according to claim 1, characterized in that: The acquisition of shallow subsurface echo data from multiple directions, and the extraction of the echo time difference between the seabed and sedimentary layer corresponding to each beam direction, specifically includes: Multibeam shallow-profile sonar emits and collects a set of signals consisting of a normal beam and a sonar beam within a single detection cycle. A multidirectional echo signal composed of conventional scanning beams, where N is an integer greater than or equal to 2; Envelope detection and time delay estimation were performed on the acquired echo signals of each beam, and the observation echo time difference corresponding to the normal beam was extracted respectively. and the observation echo time difference corresponding to each scanning beam ,in, The travel time of the first echo from the seabed interface corresponding to each detection beam. This is the second echo travel time at the bottom interface of the sedimentary layer.

3. The method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness according to claim 1, characterized in that: The specific expression for the multidirectional sound propagation geometric model is as follows: in, The one-way slant distance of the acoustic beam propagating within the sediment layer. ， The vertical thickness of the local deposition layer corresponding to the incident point of the acoustic beam; The angle of refraction of the sound wave within the sediment layer; This indicates the dip angle of the sedimentary strata.

4. The method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness according to claim 1, characterized in that: The specific expression for the nonlinear objective function is as follows: in, The theoretical physical echo time difference of a sound wave traveling back and forth within the sediment layer is expressed as follows: , This represents the one-way slant distance of the acoustic beam propagating within the sediment layer. To determine the true sound velocity of the sedimentary layer to be inverted, Indicates the dip angle of the sedimentary strata. This indicates the actual observed echo time difference.

5. The method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness according to claim 1, characterized in that: The step of substituting the actual observed echo time difference of each beam into the nonlinear objective function to simultaneously construct an overdetermined nonlinear equation system concerning the sound velocity of the sedimentary layer and the dip angle of the formation specifically includes: N probe beams, which are more than the number of parameters to be estimated, and an independent normal beam are selected to obtain the actual observed echo time difference of each beam, where N is an integer greater than or equal to 2. For the One beam, By utilizing geometric constraints to calculate the local sedimentary layer thickness variation caused by the stratum dip angle, and combining this with Snell's law to determine the acoustic wave refraction angle, the physical time residual function corresponding to the beam is then calculated. ; The residual functions of N beams are stacked and combined into a column vector, and an overdetermined nonlinear equation system is constructed for the sound velocity of the sedimentary layer and the dip angle of the strata.

6. The method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness according to claim 1, characterized in that: The method of approximating the Jacobian matrix of the overdetermined nonlinear equation system using the finite difference method specifically includes: Preset small perturbations are applied to the sound velocity of the sedimentary layer and the dip angle of the strata, respectively. By calculating the rate of change of the system residuals before and after the perturbation, the partial derivative of the Jacobian matrix is ​​approximately approximated.

7. The method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness according to claim 1, characterized in that: The step size for parameter update is obtained by solving the incremental LM equation, and the updated ground acoustic parameters are constrained and truncated in combination with physical boundary conditions. Specifically, this includes: Construct the LM incremental equation and solve for the iterative update of the incremental step size; Physical boundary constraints are introduced to determine the updated parameters. If the updated sound speed exceeds the set upper and lower limits of the physical sound speed, it is forcibly truncated to the boundary extreme value.

8. The method for estimating sound velocity and dip angle of sedimentary layers with non-uniform thickness according to claim 1, characterized in that: Based on the overall residual change trend of the system before and after the trial update, the damping factor of the adaptive algorithm is adjusted, specifically including: Calculate the new population residual norm corresponding to the trial parameters. If the new residual norm is less than the old residual norm, the convergence direction is determined to be correct. Then, accept this parameter update and reduce the damping factor proportionally. If the new residual norm is greater than the old residual norm, the convergence direction is determined to be off, the parameter update is rejected, and the damping factor is increased exponentially.

9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, the processor executing the program to implement a method for estimating the sound velocity and dip angle of a non-uniform thickness sedimentary layer as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, It stores a computer program that enables the computer to execute a method for estimating the sound velocity and dip angle of a non-uniform thickness sedimentary layer as described in any one of claims 1-8.

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