51 results about "Nonlinear inversion" patented technology

A method for processing a signal propagated through a nonlinear channel is disclosed. The method comprises modeling the channel characteristics to produce a linearized channel model, wherein the linearized channel model has a linearized transfer function that includes a plurality of first order polynomials and nonlinear operators. The method further comprises deriving an inverse linearized channel model from the linearized channel model and filtering the signal using the inverse linearized channel model.

The invention provides a nonlinear optimization based time-space domain staggered grid finite difference method and device. The method includes: determining finite difference coefficients; optimizing the finite difference coefficients on the basis of time-space domain dispersion relation and a nonlinear inversion algorithm; utilizing the optimized finite difference coefficients to perform elastic wave forward modeling. By the method and device, the technical problems of high middle-high frequency dispersion and low simulation precision caused by the fact that a finite difference method of taylor series expansion and space domain dispersion relation is utilized to acquire the finite difference coefficients so as to perform elastic wave forward modeling are solved, dispersion of middle and high frequency is achieved, and technical effect of simulation precision is improved.

The invention provides a nonlinear model-based multispectral remote sensing water depth inversion method and an apparatus thereof. The method comprises the following steps: acquiring the multispectral remote sensing image of a preset area and the actually measured control point water depth of a preset water area, and preprocessing the multispectral remote sensing image to obtain a preset area reflectivity; carrying out water-land separation on the preset area reflectivity through a near infrared waveband spectrum characteristic-based threshold technique to obtain the reflectivity of the water surface of the preset water area; establishing a nonlinear inversion model corresponding to the preset water area according to the water surface reflectivity and the actually measured control point water depth; and regressing the nonlinear inversion model through a stepwise regression algorithm, and inversing according to the regressed nonlinear inversion model to obtain the water depth of the preset water area. The highly-precise water depth of the island reef water area far from the land is rapidly obtained according to the nonlinear inversion model on the basis of the actually measured water depth, model establishing and the solving process are simple, and the nonlinear inversion model is suitable for various types of water depth inversion engineering and has good portability.

The present invention relates to an AUV inversion docking control method, belonging to the technical field of underwater vehicle recovery and docking. The method is characterized in that the head of an AUV is equipped with a USBL transceiver, two sides of a recovery station is equipped with two USBL transponders B1 and B2; in the process that the AUV approaches a docking station, the AUV obtains the positions of the transponders in a body coordinate system through a USBL positioning system, time derivation is carried out by an AUV transponder position measurement equation, and a docking error is defined in the AUV body coordinate system. In the docking process, the AUV is in a full driving navigation mode, for a docking error, a nonlinear inversion controller is designed, thus the AUV navigates along an expected straight line trajectory until reaching the docking station. According to the method, the inversion adapted speed tracking has good speed tracking performance in a condition of parameter uncertainty, and the docking effect is good.

The invention discloses a micro earthquake monitoring and positioning method. The method comprises the steps as follows: seismogenic azimuth angles, where a micro earthquake happens, detected by all detectors are calculated; a first objective function is established according to the azimuth angles, where the micro earthquake happens, detected by all detectors; an initial position (X0, Y0 and Z0) of a micro earthquake incident is estimated on the basis of the inversion of the first objective function; a second objective function is established according to the range from a P wave first arrival and an S wave first arrival of the micro earthquake incident near the initial position (X0, Y0 and Z0); and nonlinear inversion is performed on the second objective function, so that accurate x, y and z coordinates of a focus of the micro earthquake incident are obtained. According to the micro earthquake monitoring and positioning method, the micro earthquake incident positioning problem of the detectors located at a highly-deviated well section can be effectively inversed, and the method has the advantages that the calculation speed is high, an inversion operator is stable, and the like.

The invention relates to a vertical wind profile nonlinear inversion method based on a Doppler weather radar. The method includes the following steps that (1) an actual horizontal wind field in a certain height is selected at will and shown in a Taylor polynomial expansion mode; (2) the radar speed observation is represented by rVd; (3)the polynomial in the step (1) is plugged into a rVd expression in the step (2) to obtain a rVd theoretical expression of a nonlinear downstream wind field; (4) arithmetic product of Doppler data Vd of each observation point of the radar and radial distance r between the observation point and the radar is calculated to obtain an actual physical quantity of the rVd; (5) the observed actual physical quantity rVd in the step (4) is plugged into the rVd theoretical expression in the step (3), and the mathematical expression is subjected to polynomial fitting so as to figure out horizontal wind speed of the height; (6) data of different heights are selected, the process from the step (1) to the step (5) is repeated, and thereby, a vertical wind profile can be obtained. By means of the vertical wind profile nonlinear inversion method based on the Doppler weather radar, inversion of the horizontal wind field and the vertical wind profile can be well performed, and the problem that the calculation is not stable due to non-uniform data distribution by traditional methods is solved.

The invention relates to a tomography method for travel times of three preliminary waves of offshore cross-well TTI medium. The method comprises the following steps: (1) establishing a TTI medium straight-well model containing faults and acquiring an elastic parameter of the straight-well model; (2) dividing the straight-well model into a plurality of independent calculation regions; (3) carrying out model parametrization on divided straight-well model areas one by one; (4) implementing discretization on interfaces of the divided straight-well model one by one; (5) acquiring actual observation travel times of preliminary waves qP, qSV and qSH; (6) setting an initial model for inversion, and calculating theoretical travel times of the preliminary waves qP, qSV and qSH as well as corresponding ray paths by virtue of zoning multi-step improved shortest path algorithm; (7) calculating corresponding Jacobian derivative matrix elements; and (8) solving a constrained damped least square question by virtue of a conjugate gradient method for nonlinear inversion, and judging a result: when meeting minimum travel time residual, ending the inversion; otherwise, updating the model for inversion, and turning to step (6).

The invention provides a method and system for simultaneously obtaining low-frequency elastic property and density of reservoir rock. The method comprises the steps of: obtaining a reservoir rock sample S to be measured, a first standard sample Al and a second standard sample Lu with known elastic properties, wherein the compression coefficient and the density of the first standard sample are kappaal and Rhoal, the compression coefficient and the density of the second standard sample are kappalu and Rholu; measuring and obtaining a volume Val of the first standard sample and a volume Vlu of the second standard sample as well as a volume Vs of the reservoir rock sample to be measured; measuring and obtaining a resonance frequency f0 of an acoustic resonance cavity of a difference resonance acoustic spectrum device; measuring resonance frequencies in N positions in the difference resonance acoustic spectrum device: fal, i(i=1, 2...N), flu, i(i=1, 2...N) and fs, i(i=1, 2...N); and by using the parameters, simultaneously obtaining the compression coefficient and the density of the reservoir rock to be measured, which are respectively kappas and Rhos, by using a least square method nonlinear inversion method. According to the method, the high-precision low-frequency elastic property and the high-precision density of the reservoir rock can be simultaneously obtained.

The embodiment of the invention discloses a computer device, apparatus and method for determining structural parameters of a high-voltage basin-type insulator. The computer device comprises a performance collection module used for acquiring material performance paramaters of a pot insulator body to acquire a performance parameter collection module in a nonlinear relationship between performance parameters; an electro-thermal-machine performance coupling calculation module used for acquiring electric field distribution, temperature distribution and stress distribution of a basin insulator by using a coupling calculation model of electro-thermal-machine performance based on nonlinear relationship between finite element method and performance parameters; a multi-physical field decoupling calculation module used for simulation calculation by a three-dimensional definite element model in an electric field, a temperature field and a stress field; and a structure parameter determination module used for acquiring best structure parameters by nonlinear inversion through the deep learning network model. The application can effectively guide structure design of the high-voltage basin-type insulator.

The invention provides a magnetotelluric two-dimensional inversion method for optimizing a neural network based on a genetic algorithm. The method comprises the following steps of: firstly, establishing a BP neural network basic framework for a magnetotelluric two-dimensional geoelectric model for learning training, wherein the network input is the apparent resistivity parameter of a known geoelectric model, and the output is the geoelectric model parameter; optimizing a neural network learning and training process by utilizing a genetic algorithm, and calculating optimal solutions of networkconnection weights and thresholds of various geoelectric models; and finally, performing inversion test on the unknown model by using the optimal connection weight and the threshold, the network inputbeing the apparent resistivity parameter of the unknown geoelectric model, and the output being the parameter of the geoelectric model. The magnetotelluric detection nonlinear inversion method can effectively improve magnetotelluric detection nonlinear inversion precision and speed, and is high in adaptability.

The invention relates to a transient electromagnetic data processing method and belongs to the technical field of geophysical exploration, in particular to a method for processing full-space transientelectromagnetic data of a mine. According to the method, an inversion processing technology is introduced into mine transient electromagnetic data processing, thereby improving the data processing quality. According to the method in the invention, a combined inversion method is adopted so that not only the problem that an initial model needs to be manually provided for a damping least square method is solved, but also the advantage that a particle swarm can be subjected to global optimization is fully utilized; a combined algorithm is used for providing an initial model for the damping leastsquare method by means of a particle swarm algorithm; and the characteristics of nonlinear inversion of the particle swarm algorithm and the advantage of high damping least square optimization efficiency are taken into account.

The invention discloses a seafloor seismograph position and orientation inversion method based on water wave first arrival polarization orientation. A nonlinear inversion method is adopted. For a submarine seismograph to be corrected, the difference of the water wave first arrival polarization azimuth residuals is constructed. The position of the seismograph which minimizes an objective function is acquired. After the exact position of the seismograph is acquired, the actual orientation of the seismograph is acquired by using the difference between the shot point orientation and the polarization orientation. In particular, the sum of the squares of the difference of pairs of water wave first arrival polarization azimuth residuals is taken as the objective function. A DE optimization methodis used to acquire the position of the seismometer which minimizes the objective function. The influence of the seismograph orientation is eliminated in the objective function. The method has the advantages of faster convergence speed and better stability, and has better accuracy than a linear method.

The invention provides a full-waveform inversion method and device, and electronic equipment. The method comprises the steps of obtaining initial physical parameters, wherein the initial physical parameters are speed parameters of the underground structure; performing parameterization processing on the initial physical parameters to obtain physical parameters, and inputting the physical parametersinto a pre-trained machine learning model to enable the machine learning model to output a full-waveform inversion result according to the physical parameters, wherein the full-waveform inversion result and the weight coefficient of the machine learning model satisfy a preset relationship; and reconstructing a speed structure chart of the underground structure according to the full-waveform inversion result. According to the invention, the initial physical parameters are parameterized through the weight coefficient of the machine learning model; therefore, the full-waveform inversion problemis converted into the reconstruction problem of machine learning model network parameters, the problems that the existing full-waveform inversion cannot solve the nonlinear inversion problem and a large amount of calculation exists are solved, the calculation efficiency is improved, and the beneficial effect of high-precision inversion of a complex underground structure is achieved.

The invention provides a porosity inversion method for improving resolution. The method comprises the steps: (1), deducing a fast longitudinal wave reflection coefficient approximate expression whichis vertically incident to a fluid-containing pore medium interface, and building a direct quantitative relation between porosity and a seismic record based on a rock physics theory; (2), constructinga nonlinear inversion objective function by taking the logging porosity and the logging reflection coefficient as prior constraints according to a relationship between the porosity and the seismic record; (3), calculating a porosity adjustment parameter by utilizing logging data information, and giving prior information such as a constraint parameter, a maximum inversion iteration frequency and aporosity initial solution; and (4), substituting the known parameters into the nonlinear inversion objective function, and realizing direct quantitative inversion of the porosity by utilizing a simulated annealing algorithm. The method has the advantages that the limitation that the traditional method depends on single-phase medium and equivalent medium theories is broken through, and the direct quantitative relation between the porosity and the seismic record is fundamentally established, so that the resolution of porosity inversion is improved.

The invention discloses a prestack hybrid nonlinear inversion method and a computer readable storage medium. The method may include the following steps that: prestack linear inversion is performed onprestack seismic data so as to obtain the initial value of a transverse wave reflection coefficient and the initial value of a transverse wave velocity-to-longitudinal wave velocity ratio; a combinedelastic parameter is constructed based on the transverse wave reflection coefficient, the transverse wave velocity-to-longitudinal wave velocity ratio, and a density gradient; a prestack longitudinalwave reflection coefficient formula is expressed as a linear equation about the density gradient, a longitudinal wave reflection coefficient and the combined elastic parameter, linear solution is performed on the prestack longitudinal wave reflection coefficient formula, so that the density gradient, the longitudinal wave reflection coefficient and the combined elastic parameter are obtained; andan objective function about the transverse wave reflection coefficient and the transverse wave velocity-to-longitudinal wave velocity ratio is constructed, and linear solution is performed on the objective function, so that a final transverse wave reflection coefficient and a final transverse wave velocity-to-longitudinal wave velocity ratio are obtained. According to the prestack hybrid nonlinearinversion method and the computer readable storage medium of the invention adopted, a traditional four-parameter nonlinear problem is degraded into a two-parameter nonlinear problem, and therefore, various elastic parameters can be obtained with high efficiency and high precision.

The invention discloses a multi-wave combined pre-stack waveform inversion method. The pre-stack seismic inversion method mainly comprises two major types of a forward operator based on ray tracing and a forward operator based on wave equations, wherein the forward operator based on ray tracing is pre-stack AVO inversion with the widest application, and the forward operator based on wave equationsis called pre-stack waveform inversion. Different from the pre-stack AVO inversion, the pre-stack waveform inversion method can better apply complex wave field response in input data, reduce the processing difficulty of the input data, and improve the sensitivity of seismic records to target inversion parameters. At present, a nonlinear inversion strategy is mostly adopted for the pre-stack waveform inversion, and the calculation efficiency is too low. The invention provides a linear strategy pre-stack inversion method so as to reduce the calculation time. Meanwhile, in order to improve the inversion precision and stability, a PP and PS multi-wave data joint inversion strategy is adopted, and the method can effectively improve the inversion precision of three parameters, especially for transverse wave speed and density estimation. A logging model test verifies the effectiveness of the method.

The invention provides a method for determining a fluid density and a solid skeletal density in a storage layer, and determining the fluid density and the solid skeletal density of a three dimensional area. The method for determining the fluid density in the storage layer comprises the steps of: collecting logging data aiming at the storage layer; obtaining storage layer density data rho i and porosity data phi i at each sampling point of n sampling points in the storage layer from the logging data aiming at the storage layer, wherein i = 1, 2, ..., n; and determining the fluid density rho f in the storage layer through a formula. Through the method provided by the invention, the fluid density and the solid skeletal density in the storage layer can be determined by using the density data and the porosity data of the storage layer obtained by the logging data; the fluid density and the solid skeletal density can be spread to the whole three dimensional data space through a nonlinear inversion method in combination with a three dimensional seismic data volume; and the three dimensional space data obtained through inversion can be used for storage layer forecasting, gas and water identification, oil and gas accumulation description and the like.

The invention provides a simulated annealing-based quality factor Q nonlinear inversion method and system. The method includes the following steps that: a dual-well micro logging observation system isutilized to obtain micro logging data; direct waves excited by the same shot are extracted from the micro logging data, and an attenuation curve is calculated; the prior information of the change ofa quality factor Q with a frequency is introduced, a nonlinear objective function is established based on the attenuation curve; a simulated annealing method is adopted to obtain parameters in the objective function by means of nonlinear inversion, so that the value of the quality factor Q which changes with the frequency is obtained. Compared with the prior art, a constant Q hypothesis is avoided, and the value of the frequency-dependent quality factor Q is directly obtained; and therefore, the accurate compensation of energy lost in formation absorption can be benefitted, and a data foundation is provided for high-precision imaging. With the method adopted, error introduced by a constant Q hypothesis-based inversion method in traditional methods can be eliminated, so that the accuracy ofthe calculation of the value of the quality factor Q can be improved; and the micro logging data are adopted, so that the accuracy and stability of results can be improved.