43 results about "Geophysical inversion" patented technology

A model-based approach to estimating wall positions for a building is developed and tested using simulated data. It borrows two techniques from geophysical inversion problems, layer stripping and stacking, and combines them with a model-based estimation algorithm that minimizes the mean-square error between the predicted signal and the data. The technique is designed to process multiple looks from an ultra wideband radar array. The processed signal is time-gated and each section processed to detect the presence of a wall and estimate its position, thickness, and material parameters. The floor plan of a building is determined by moving the array around the outside of the building. In this paper we describe how the stacking and layer stripping algorithms are combined and show the results from a simple numerical example of three parallel walls.

The present invention discloses a geologic body three-dimensional visualization method based on geophysical field data. Said method includes the following steps: (A), fetching collected geophysical field data, making fetched data be stored as object array, and statistically analyzing the fetched data so as to obtain space distribution characteristics of fetched data; (B), according to the space distribution characteristics of data combining data points in the object array and constructing them into concrete space polygonal mode; and (c), drawing and displaying said constructed space polygonal model, and making said space polygonal model undergo the process of visualization operation treatment.

The invention is an entirely new application of domain characterization generated by Voronoi tessellation, which is very close to realistic geology and computation of gravity response of such domain, which has three dimensional fractal basin structure, and is favorable for oil exploration. In this work the interfaces or tessellating domains are represented by a set of parameters, which are referred as Voronoi centers. These parameters can be perturbed by any amount without getting into representational problems as faced by the conventional techniques. To accomplish such representation Voronoi tessellation is used, which in two dimensional space consists of enclosing every Voronoi center by a Voronoi polygon such that the common edge of adjacent polygons is perpendicular bisector to the line joining the Voronoi centers on both the sides of that edge. In this invention instead of using conventional Euclidian distances, the notion of Voronoi tessellation is generalized by using Ldistances, where p can hold any real value so that Voronoi domains are not necessarily polygonal. Desired fractal subsurface is generated using this approach that is quite close to the natural settings than the conventional planer or polygonal representation. Next, the gravity response due to this fractal subsurface structure has been computed. The new invention has a significant advantage over the conventional methods especially in geophysical inversion where initial model parameters are updated in each iteration, which can be done more easily and efficiently by Voronoi tessellation merely by changing Voronoi centers.

The invention discloses a structural constraint-based normalized gravity-magnetic-electric-seismic joint inversion method. The method includes the following steps that: S1, a normalized joint inversion objective function is established; S2, an initial model is established; S3, forward calculation and Jacobian matrix solving are carried out; S4, a normalized cross-gradient partial derivative and Lagrangian operator are calculated; S5, an iterative model is calculated; and S6, forward calculation is performed on the obtained iterative model, and the fitting difference of calculation results andobservation data is solved, if the fitting difference increases, the maximum number of iterations is reached, or the fitting difference reaches a threshold, loop inversion is stopped, and a normalizedjoint inversion model is outputted, otherwise S3 is executed. With the structural constraint-based normalized gravity-magnetic-electric-seismic joint inversion method of the invention adopted, the limitations of a single method are eliminated, the non-uniqueness of the inversion of geophysical inversion is decreased; and wrong inversion results caused by inversion based on the direct coupling ofphysical property parameters with large differences in order of magnitudes can be avoided. The method does not rely on the physical property relations of rock.

Method for reducing the time needed to perform geophysical inversion by using simultaneous encoded sources in the simulation steps of the inversion process. The geophysical survey data are prepared by encoding (3) a group of source gathers (1), using for each gather a different encoding signature selected from a set (2) of non-equivalent encoding signatures. Then, the encoded gathers are summed (4) by summing all traces corresponding to the same receiver from each gather, resulting in a simultaneous encoded gather. (Alternatively, the geophysical data are acquired from simultaneously encoded sources.) The simulation steps needed for inversion are then calculated using a particular assumed velocity (or other physical property) model (5) and simultaneously activated encoded sources using the same encoding scheme used on the measured data. The result is an updated physical properties model (6) that may be further updated (7) by additional iterations.

A model-based approach to estimating wall positions for a building is developed and tested using simulated data. It borrows two techniques from geophysical inversion problems, layer stripping and stacking, and combines them with a model-based estimation algorithm that minimizes the mean-square error between the predicted signal and the data. The technique is designed to process multiple looks from an ultra wideband radar array. The processed signal is time-gated and each section processed to detect the presence of a wall and estimate its position, thickness, and material parameters. The floor plan of a building is determined by moving the array around the outside of the building. In this paper we describe how the stacking and layer stripping algorithms are combined and show the results from a simple numerical example of three parallel walls.

The invention provides a method for detecting a solution leaching scope and a groundwater pollution scope of acid in-situ leaching of uranium. The method comprises the steps of: (a) distributing measuring lines in a detecting area and setting measuring points on the measuring lines; (b) transmitting signals of different frequencies through a transmitter, receiving signals of electric field and magnetic field which are coupled via the ground through a receiver, and converting the signals into collection data after the signals are subjected to calibration of scale values; (c) sequentially subjecting the collected date to curve smoothing, near field correction, one-dimensional inversion, two-dimensional inversion and electric property geological integrated interpretation to form a geophysical inversion result and a geological interpretation map of every measuring line; (d) subjecting the detecting area to three-dimensional geological modeling and subjecting the model to slicing display of different depths; and (e) combined with physical property data of the detecting target area, obtaining the solution leaching scope and the groundwater pollution scope of the acid in-situ leaching of uranium and the points where leakage occurs. The method for detecting the solution leaching scope and the groundwater pollution scope of the acid in-situ leaching of uranium is quick, economical, effective and simple to operate, and does not need constructing monitoring well and sampling analysis.

A wave impedance inversion method based on an improved damped least square method belongs to the field of geophysical inversion, and particularly relates to wave impedance inversion technology in oiland gas geophysical exploration. The invention aims to provide an improved wave impedance inversion method, which is used to establish a wave impedance inversion objective function in the sense of least squares and reduce the calculation cost of the Jacobian matrix in the traditional least square method, and can solve the non-positive singular problems of the Jacobian matrix to optimize the iterative method of damping coefficients, so that the algorithm has better stability and global convergence, and the inversion results are more reliable. The implementation process comprises the following steps of (1) constructing an inversion objective function according to the convolution model and the sparsely constrained pulse inversion theory; (2) establishing an initial model based on the log dataand horizon Information; (3) setting the algorithm and model parameters; (4) putting the initial model into the objective function to iterate; (5) obtaining the best matching reflection coefficient under the comprehensive constraint of three data bodies of model constraint, sparse constraint and seismic data constraint; (6) solving the wave impedance by using the recursive method; and (7) addinghigh and low frequency compensation to get the broadband wave impedance value.

The invention discloses a seismic inversion method based on hybrid high order and fractional order Anisotropic Total p-variation (ATpV) sparse regularization, belongs to the field of geophysical inversion and oil and gas reservoir forecasting, and solves the problems caused by existing calculation of a total variation by adopting a first-order difference. The seismic inversion method comprises thefollowing steps: preprocessing a seismic record, extracting horizon position, and then acquiring an initial model of a parameter to be inversed according to well-logging data after the horizon position is extracted; calculating an initial wave impedance logarithm based on the initial model of the parameter to be inversed and the preprocessed seismic record, and then building an inversion model based on the hybrid high order and fractional order ATpV sparse regularization; updating the initial wave impedance logarithm based on the seismic record and a seismic wavelet by combining an alternating direction multiplier method and a forward model to obtain an updated wave impedance logarithm and a parameter for updating a next wave impedance logarithm; and determining whether a not updated value and an updated value meet conditions, if YES, updating the next wave impedance logarithm, and if NO, acquiring the parameter to be inversed. The method is used for seismic inversion.

In general all the geophysical data sets are non-linear in nature and should be tackled in non-linear manner in order to preserve the subtle information, contained in the data. It was customary to linearize non-linear problems for mathematical simplicity and to avoid tedious computations. A method solves a non-linear inversion problem in non-linear manner and avoids cumbersome mathematical computations without losing any information contained in the data. The efficacy is demonstrated on synthetic and field resistivity data, but it can be used for non-linear inversion of any geophysical data, as the general approach of the geophysical inversion is same for any data set.

The present invention relates to an electromagnetic ground lens detection method and device used for detection of downhole electricity anomalous body. The device comprises: an electromagnetic excitation source applying a low-frequency current as an excitation source, by employing borehole casing pipe, used to excite electricity anomalous body secondary inductive electromagnetic field; and electromagnetic data collection probes, wherein the array electromagnetic data collection probes with a certain quantity are arranged on the ground to obtain a three-component electric field and a magnetic field data used for downhole electricity anomalous body and fining description. The electricity anomalous body lens imaging device and method employ a physical geography inversion method to perform inversion imaging processing of the obtained electromagnetic response data through collection to obtain conductivity parameters and geometrical parameters of the downhole electricity anomalous body through inversion. The electricity anomalous body lens imaging device and method can achieve effective identification and fining lens imaging of the downhole electricity anomalous body based on the electromagnetic theory.

Domain characterization generated by Voronoi tessellation, which is very close to realistic geology and computation of gravity response of such domain, has a three dimensional fractal basin structure, and is favorable for oil exploration. Interfaces or tessellating domains are represented by a set of parameters, which are referred as Voronoi centers. These parameters can be perturbed by any amount without getting into representational problems. To accomplish such representation Voronoi tessellation is used, which in two dimensional space involves enclosing every Voronoi center by a Voronoi polygon such that the common edge of adjacent polygons is a perpendicular bisector to the line joining the Voronoi centers on both the sides of that edge. Instead of using conventional Euclidian distances, the notion of Voronoi tessellation is generalized by using Lp distances, where p can hold any real value so that Voronoi domains are not necessarily polygonal. A desired fractal subsurface is generated using this approach that is quite close to the natural settings. Next, the gravity response due to this fractal subsurface structure is computed. A significant advantage is provided especially in geophysical inversion where initial model parameters are updated in each iteration, which can be done more easily and efficiently by Voronoi tessellation merely by changing Voronoi centers.

The invention discloses a pre-stack seismic AVA inversion method based on cross gradient regularization constraint. The method comprises the steps of extracting angle seismic wavelets, establishing aninversion objective function, constructing an initial model and a prior constraint model, and solving by a gradient descent algorithm. According to the method, multiple disciplines such as a geophysical inversion theory and method, an optimization method and geostatistics are integrated, a pre-stack seismic AVA inversion technology, a gradient descent algorithm and a Kriging interpolation methodare organically combined, the stability of a pre-stack seismic AVA inversion result is effectively improved, and the method is suitable for multiple important links such as reservoir prediction and description and fluid identification.

The invention discloses a Bayesian seismic inversion method based on [tau] distribution, and relates to the geophysical inversion and oil and gas reservoir prediction field. The method comprises the following steps: 1, inputting data to obtain an initial model of parameters to be inverted and determining parameters of [tau] distribution; 2, selecting an initial model of the t-th channel parameteras an iteration initial model, determining a prior probability density distribution function by parameterized [tau] distribution, inputting data to obtain posterior probability density function and performing MCMC inversion to obtain an inversion result; and 3, determining whether t is greater than seismic data in the input data, if yes, ending inversion to obtain a to-be-inverted wave impedance profile based on the inversion result, and if not, accumulating t and jumping to the step 2 for continuous inversion. The method solves the problem that the existing seismic inversion uses the Gaussiandistribution to simulate the seismic reflection coefficient distribution, resulting in the low precision and resolution of inversion physical parameters, and achieves the effect of improving the accuracy and resolution of the inversion physical parameters.

The invention relates to a direct ray tracking algorithm for geological radar chromatography detecting and belongs to the field of physical geography inversion algorithms. The method comprises the following steps that a plane right-angle relative coordinate system is established; a section is subjected to mesh generation and numbering; the left-right marking point coordinates of each mesh are determined; the coordinates of an emitting point and a receiving point are determined; ray parameters are computed; the lengths of the rays in the meshes are computed; the computing results are checked; and the computing results are subjected to sparse storage. According to three parameters of the left intercept, the right intercept and the slope of the rays, the ray trend is tracked, only the meshes through which the rays pass need to be computed, compared with a traditional algorithm in which all the meshes are traversed, consumption on internal storage and time is greatly lowered, the efficiency and the accuracy of the algorithm are improved, finally the computing results are stored in a sparse format, storage space can be saved, and the distribution status of the rays can be visually displayed.

The invention provides an anisotropy parameter inversion method based on a transmission equation, and belongs to the field of physical geography inversion. The method comprises the steps: (1) selecting post-stack seismic data volumes corresponding to any three different azimuth angles, calculating and obtaining reflection coefficients corresponding to the three different azimuth angles through employing a sparse pulse inversion method; (2) respectively calculating transmission coefficients corresponding to the three reflection coefficients; (3) analyzing a pre-stack azimuth path set, and obtaining incident angle information, wherein the incident angle information comprises a maximum incident angle i2, a maximum incident angle i1, and an interval; (4) calculating and obtaining anisotropy parameters delta epsilon (V) and delta delta (V) through the azimuth angle information and the transmission coefficient information.

A two-stage method for iteratively inverting geophysical data for the purpose of subsurface imaging, including: obtaining at least one geophysical dataset and an initial subsurface model; representing subsurface such that a geometry of a geobody is defined using a set of basis functions, and a number of such basis functions is significantly smaller than the number of cells used in cell-based geobody representations, wherein an order of magnitude reduction is two or more for 2-D domains and 3 or more for 3-D domains; in a first stage, successively updating the initial subsurface model, only for the geobody, by performing iterative low-dimensional geophysical inversion based on minimizing a misfit between simulated geophysical data and the geophysical dataset, wherein the simulated geophysical data is generated from a current subsurface model at each iteration; generating a subsurface image from a final updated subsurface model obtained via the low-dimensional geophysical inversion, wherein the subsurface image includes an inverted geobody; in a second stage, successively updating the subsurface model with the inverted geobody by performing iterative cell-based geophysical inversion based on minimizing a misfit between simulated geophysical data and the geophysical dataset, wherein the simulated geophysical data is generated from a current subsurface model at each iteration.

The invention discloses a geophysics inversion method based on a generic function reconstruction under a modified total variation model constraint. The method comprises the following steps: (1) constructing an inversion objective function aiming at the problem of regularized inversion of the modified total variation model constraint; (2) performing a generic function reconstruction on stable function terms of the modified total variation; (3) iteratively solving a calculation formula of a new model on the model itself according to an objective function minimization equation; and (4) setting inversion parameters, repeating the iteration to obtain a desired model result, and the result is used for inferring geological structures or positioning geological anomaly bodies. According to the geophysics inversion method based on the generic function reconstruction under the modified total variation model constraint, a generic function reconstruction method is innovatively provided, and the constraint property of the stable function term on the model is reserved, thereby greatly simplifying the numerical calculation difficulty caused by the high nonlinearity to the inversion; the inversionadopts a solution mode which is iterative to the model itself, and compared with a solution mode which is iterative to the correction amount of the model, the regularization directly applies a stablefunction constraint on the model, thereby obtaining a more reasonable model result.

Method for reducing the time needed to perform geophysical inversion by using simultaneous encoded sources in the simulation steps of the inversion process. The geophysical survey data are prepared by encoding (3) a group of source gathers (1), using for each gather a different encoding signature selected from a set (2) of non-equivalent encoding signatures. Then, the encoded gathers are summed (4) by summing all traces corresponding to the same receiver from each gather, resulting in a simultaneous encoded gather. (Alternatively, the geophysical data are acquired from simultaneously encoded sources.) The simulation steps needed for inversion are then calculated using a particular assumed velocity (or other physical property) model (5) and simultaneously activated encoded sources using the same encoding scheme used on the measured data. The result is an updated physical properties model (6) that may be further updated (7) by additional iterations.

The invention discloses an inversion model updating method based on M-H sampling of Gaussian distribution and relates to the technical field of geophysical inversion. The method comprises the following steps of: step 1, pre-processing earthquake information to obtain an initial model of the parameters to be inverted; step 2, selecting the initial model of the t-th parameter to be inverted to calculate an initial wave impedance logarithm L1; step 3, calculating the variance of the initial wave impedance logarithm L1, establishing a state transition function obeying a Gaussian distribution, andrepeatedly updating the initial wave impedance logarithm L1 according to the state transition function; and step 4, determining whether t is greater than the seismic trace in the earthquake information; if so, ending the update; and if not, causing t=t+1 and jumping to step 2 to continue the inversion. The inversion model updating method based on M-H sampling of Gaussian distribution solves the problems of a too large convergence value, slow convergence speed, and local optimum due to the lack of the analysis of actual data when adopting M-H sampling based on uniform distribution in the priorinversion model updating, thereby minimizing the scope of convergence values, and being capable of quickly finding the optimum.

The invention relates to the technical field of geophysical inversion, in particular to a magnetotelluric frequency division tomography inversion method. The method comprises the following steps: estimating an effective exploration depth according to frequency point data of an observation point; grouping the frequency point data; establishing a gridding model; constructing an initial resistivity model; performing frequency division tomography inversion; and evaluating an inversion result. According to the method, the magnetotelluric data are grouped according to the frequency, inversion is performed layer by layer from the shallow layer to the deep layer, the discomfort of inversion is improved, effective information of the magnetotelluric data, especially low-frequency data, is fully excavated, the resolution of the deep layer is improved, and the problem that existing magnetotelluric inversion is low in resolution of the deep layer is solved.

The invention provides a wavelet transform model parameter disturbance method, which specifically comprises the following steps of: centralizing disturbance of a geophysical model obtained after transform on a local tree-shaped structure sub-node (with larger depth) to express as high-frequency detail information of the model; expressing a tree-shaped structure root node (with smaller depth) covering the whole model area by disturbance of the geophysical model obtained after transformation as low-frequency approximate information of the model, and transforming the tree-shaped structure and thegeophysical model through wavelet transformation so as to achieve decomposition or reconstruction of the geophysical model. According to the method provided by the invention, accurate local disturbance on different scales and different regions of the geophysical model can be correctly achieved by increasing nodes, reducing node values, disturbance node values and the like. The method provides necessary technical conditions for development based on wavelet domain geophysical inversion, and has a wide application prospect.

The invention belongs to the technical field of mine geophysical exploration, relates to a three-dimensional visualization method for a mine direct current method. The method comprises the following steps: firstly, researching the advantages and disadvantages of a Slicer Dicer three-dimensional visual formation graph; analyzing data structure characteristics of the readable file of the software, determining a three-dimensional mapping mode of the software, and converting the three-dimensional inversion data into readable data of the software through programming, thereby realizing a three-dimensional visual mapping technology of the mine geophysical inversion data, and making slice maps of different layers so as to meet requirements of engineering personnel; the method is simple, is convenient to operate, can directly read data in various formats, realizes three-dimensional visualization of inversion data of a mine direct current method, and has a very good practical application value.

The invention relates to the technical field of test methods, in particular to a method for predicting an abnormal stratum pressure. The method comprises the steps of arranging abnormal pressure dataof a stratum; analyzing logging response characteristics of the abnormal pressure data of the stratum; building a stratum pressure calculation model through the logging response characteristics; and measuring stratum pressure data by utilizing the stratum pressure calculation model. The abnormal stratum pressure data actually measured by drilling is subjected to statistics; response characteristicanalysis of each logging curve is performed; then, the logging curve with relatively good correlation with the abnormal stratum pressure data is selected to build an abnormal pressure identificationfactor model; further, a new stratum pressure calculation formula is obtained in combination with the measured stratum pressure data; and finally, parameter data bodies in the formula are obtained byutilizing geophysical inversion based on pre-stack and post-stack seismic data, and a stratum pressure data body can be obtained by substituting the parameter data bodies into the new stratum pressurecalculation formula, so that spatial distribution characteristics of the stratum pressure are obtained, and exploration and development of abnormal pressure oil and gas reservoirs are facilitated.

The invention relates to a pre-stack seismic inversion method based on hybrid drive regularization, and belongs to the technical field of geophysical inversion. The method comprises the following steps: 1) acquiring data, and inputting an observation data set; 2) carrying out unconstrained inversion on the data to obtain an initial inversion result set; 3) calculating the spatial gradient of the initial inversion result in the step 2); 4) classifying the spatial gradients in the step 3) to obtain two types of spatial positions of the spatial gradients; 5) calculating a distribution characteristic function of a to-be-inverted result according to the initial inversion result in the step 2) and the position information in the step 4); 6) solving a regularization item according to the initial inversion result in the step 2) and the distribution characteristic function in the step 5); and 7) solving the objective function to obtain a final result. Regularization constraint is carried out on the inversion process by simultaneously utilizing the characteristics of the to-be-inverted parameters and the model hypothesis of the inversion error, so that the stability of the inversion result is improved, and the detail characteristics of the inversion result are protected at the same time.

The invention belongs to the technical field of geophysical inversion, and discloses a gravity anomaly inversion method based on a convolutional neural network, and the method comprises the steps: constructing two-dimensional density models of different shapes, carrying out the forward modeling to obtain gravity anomaly data, and constructing a sample data set based on the obtained gravity anomaly data; constructing a gravity anomaly inversion network, namely AlexNet-Gra; preprocessing and dividing the constructed sample data set; utilizing the processed sample data set to train, optimize and verify the constructed AlexNet-Gra network, and obtaining a trained AlexNet-Gra network; and inputting the gravity abnormal data into the trained AlexNet-Gra network, so that an inversion result can be obtained. According to the method, after a large amount of data is obtained through forward modeling by means of models designed into different shapes, the position and density of the gravity anomaly body can be accurately inverted, and the gravity anomaly inversion problem can be effectively solved.

The invention provides a gravity gradient data joint inversion method, relates to the technical field of geophysical inversion, and aims to introduce a gradient depth weighting function, physical property constraints based on pair / index transformation and other methods on the basis of focusing inversion in order to solve the problems of insufficient spatial resolution and the like of gravity gradient data inversion at present. Six components are combined in the full-tensor gradient data, and three-dimensional density inversion is achieved by using a nonlinear conjugate gradient method. Meanwhile, in order to improve the visualization effect and operability of inversion, a software platform with a visualization function is developed on the basis of Python language, PyQt, Matplotlib and other toolkits as proposed inversion methods, and the distinguishing capability of near geologic bodies and the longitudinal space imaging capability of target bodies are effectively improved. A softwareplatform and a development method thereof have the advantages of being easy to use, practical and the like.

The invention discloses a geophysics inversion method based on a generic function reconstruction under a modified total variation model constraint. The method comprises the following steps: (1) constructing an inversion objective function aiming at the problem of regularized inversion of the modified total variation model constraint; (2) performing a generic function reconstruction on stable function terms of the modified total variation; (3) iteratively solving a calculation formula of a new model on the model itself according to an objective function minimization equation; and (4) setting inversion parameters, repeating the iteration to obtain a desired model result, and the result is used for inferring geological structures or positioning geological anomaly bodies. According to the geophysics inversion method based on the generic function reconstruction under the modified total variation model constraint, a generic function reconstruction method is innovatively provided, and the constraint property of the stable function term on the model is reserved, thereby greatly simplifying the numerical calculation difficulty caused by the high nonlinearity to the inversion; the inversionadopts a solution mode which is iterative to the model itself, and compared with a solution mode which is iterative to the correction amount of the model, the regularization directly applies a stablefunction constraint on the model, thereby obtaining a more reasonable model result.

The invention provides an anisotropic parameter inversion method based on a transmission equation, which belongs to the field of geophysical inversion. The method includes: (1) selecting post-stack seismic data volumes corresponding to any three different azimuth angles, calculating the reflection coefficients corresponding to the three different azimuth angles through sparse pulse inversion method; (2) calculating three different azimuth angles respectively. The transmission coefficient corresponding to the reflection coefficient of the azimuth angle (3) analyze the pre-stack azimuth gather to obtain the incident angle information, the incident angle information includes the maximum incident angle i2, the minimum incident angle i1 and the interval; (4) use the azimuth information transmission coefficient The information is calculated to obtain the anisotropy parameters Δε(V) and Δδ(V).