38 results about "Mathematical relationship" patented technology

The invention discloses an equivalent calculation method for quantitative evaluation of the residual life of an existing pavement and a storage medium, and the method comprises the steps: firstly, determining a bearing threshold value of a lossless pavement structure based on a dual-modulus elastic layered system theory; secondly, a reduction coefficient of typical diseases to the structural strength is quantified through finite element simulation; thirdly, establishing a mathematical relationship model of the maximum effective stress and the fatigue life; then, actual disease information is accurately obtained by combining nondestructive testing technologies such as ground penetrating radar and three-dimensional laser scanning; then, correcting the maximum allowable equivalent stress in a lossless state according to the disease data; and finally, fusing the theoretical model and the traffic load history, and calculating the remaining service life. According to the method, three-dimensional and quantitative analysis on the influence of the diseases is realized through a mechanical response equivalence principle, the accuracy, objectivity and engineering application efficiency of residual life evaluation are remarkably improved, and a reliable basis is provided for scientifically making a road maintenance decision.

The invention relates to the technical field of down-the-hole drill ball tooth drill bit wear measurement, in particular to a down-the-hole drill ball tooth drill bit wear value real-time measurement method and system, and the method comprises the steps: carrying out the optimization and registration of an initial three-dimensional model, and obtaining an overall wear quantized value of a down-the-hole drill ball tooth drill bit; analyzing a mapping relation between the while-drilling parameters and the overall wear quantized value, and constructing a database between the while-drilling parameters and the drill bit wear value; deriving a dimensionless variable according to a dimensional analysis method and a database, and performing combined screening on the dimensionless variable, a second-order polynomial and a cross term to determine a dimensionless variable combination influenced by drill bit wear; and substituting the dimensionless variable combination into the multiple linear regression model to establish a mathematical relationship model between the drill bit wear and the while-drilling parameters, thereby realizing the real-time measurement of the wear value of the ball tooth drill bit of the down-the-hole drill. According to the method, non-dimensional variables of the while-drilling parameters are obtained based on dimensional analysis, the model is built in combination with multiple linear regression, the wear value of the ball tooth drill bit of the down-the-hole drill is measured in real time, and construction efficiency and safety are improved.

The invention relates to the technical field of machining, and discloses a chamfering tool metal dead zone shape prediction method based on a slip line theory. The method comprises the steps that firstly, a chamfering cutting edge right-angle cutting slip line field model is constructed, a right-angle cutting coordinate system is established with an S1 point as an original point, then an S1 point Moire circle model is established based on the plastic deformation theory, and the size of an included angle omega 1 formed by a metal dead zone boundary S1S3 and a chamfering S1S2 is solved in combination with the Coulomb friction theorem; and then determining a slope relational expression of the line segment S2S3 and the line segment DN through a geometrical relationship, establishing an equation to solve the height of a shunt point, and finally solving the length 1 of the lower boundary of the metal dead zone, thereby realizing prediction of the shape of the metal dead zone. According to the method, the mathematical relationship between the parameters of the cutting edge of the chamfering tool and the shape of the metal dead zone is established particularly for the shape of the dead zone of the cutting edge of the chamfering tool, so that the boundary of the dead zone can be represented according to the parameters of the cutting edge of the chamfering tool, and the prediction effect of the shape of the metal dead zone of the chamfering tool is achieved.

The invention discloses a blasting lumpiness overall distribution curve prediction method considering blasting in-situ blocks. The method comprises the following steps: obtaining structural surface distribution characteristics of a rock mass in a to-be-blasted area; constructing a three-dimensional numerical model of the rock mass based on the distribution characteristics of the structural surface; blasting design parameters are introduced into the three-dimensional numerical model, and the segmentation characteristics of the rock mass under the combined action of the structural plane and blast hole arrangement are analyzed; according to the segmentation features, blasting in-situ block information is extracted, and the size is counted; defining the maximum size of the blasting in-situ block as the size upper limit of an R-R distribution function; establishing a mathematical relationship between the average size of the blasting in-situ blocks and the characteristic curve parameters in the R-R distribution function; based on the size upper limit and the mathematical relationship, constructing a prediction model of the overall distribution curve of the rock lumpiness after blasting; and predicting the blasting fragmentation overall distribution curve according to the prediction model to obtain a prediction result. According to the method, the accuracy and practicability of blasting lumpiness overall distribution prediction are improved.

This invention relates to the field of semiconductor manufacturing process monitoring technology, and discloses an online pH monitoring system for polishing slurry based on ultrasonic stirring. The system includes: an ultrasonic stirring module for uniformly stirring the polishing slurry and acquiring acoustic signals, extracting acoustic feature vectors through Fourier transform and wavelet analysis; a multi-sensor data acquisition module for acquiring pH, temperature, turbidity, and redox potential data; an anomaly detection module for constructing an LSTMAutoencoder model, calculating reconstruction errors, and triggering early warnings; a causal analysis module for constructing a causal network of pH changes; a rule generation module for extracting mathematical relationships using symbolic regression and converting them into predictive rules; and an intervention control module for calculating the effectiveness of intervention measures, generating and executing optimal control operations. Through structural causal models and counterfactual reasoning, this invention can accurately identify key factors leading to pH anomalies and their contribution, shortening troubleshooting time.

The application discloses a multi-layer adhesive precise structure and function device processing release film removing device and method, and the removing device comprises a sampling module, a testing module, an analyzing module, a control module and a processing unit. The device samples are randomly sampled, the obtained device samples are subjected to warming test and release performance test, the peeling force parameter values of the device samples and the warming temperature values corresponding to the peeling force parameter values are obtained, the obtained data is fitted, a mathematical relation model corresponding to the peeling force parameter values and the warming temperature values is constructed, the warming temperature and the peeling force size setting in the processing of removing the release film on the surface of the function device in the running process of the processing unit are controlled, and the function device is processed, so that the release film on the surface of the function device is efficiently removed.

The invention provides a wellbore scale upgrading method and system based on acid gas reservoir meter-level well section numerical simulation, and the method comprises the steps: building an apparent phase slippage speed calculation model and a wellbore wall surface friction calculation model through recognizing a multiphase fluid flow state mode; and finally, determining the mathematical relationship among the fluid flow state, the interphase slippage speed, the shaft wall friction, the temperature, the pressure and the liquid holdup, and embedding the meter-scale operation model into the macroscopic shaft model to realize the multi-scale accurate fluid flow simulation of the acid gas reservoir shaft. According to the scheme, the problems that in the prior art, factors are not considered comprehensively, and calculation accuracy is insufficient are solved, a full-wellbore numerical simulation control system considering fluid characteristics of the acid gas reservoir is established, meter-scale gas-liquid flow and distribution rules of the sulfur-containing gas reservoir can be accurately described, and calculation accuracy is improved. And shaft macroscopic parameter indexes suitable for gas reservoir development are reliably calculated, and theoretical support is provided for economic and efficient development of acid gas reservoirs.

The application relates to the medical field and can be applied to doctor-patient intelligent question answering, and discloses a text similarity discrimination method, wherein the method comprises the following steps: constructing a cost matrix according to token embedding of two to-be-discriminated sentences; constructing a first mathematical relationship corresponding to a total cost, a cost matrix, an optimal transmission matrix and an optimal transmission distance in a transmission process of the two to-be-discriminated sentences; defining state vectors of the two to-be-discriminated sentences as all-1 vectors normalized by lengths of the own sentences respectively; the all-1 vectors comprise a first constraint condition and a second constraint condition; removing any one of the first constraint condition and the second constraint condition in the all-1 vectors to obtain a relaxed equation; combining the relaxed equation with the first mathematical relationship to derive a relaxed optimal transmission distance, and utilizing the relaxed optimal transmission distance to discriminate the similarity of the two to-be-discriminated sentences, so that the text similarity can be discriminated simply and accurately.

The application discloses a relative photometry improvement method for an oversaturated detection image, belongs to the technical field of astronomical image photometry, and aims at solving the problem that the nonlinear truncation of the observed light flux is caused by the oversaturation of the gray value of a star in an existing astronomical image, and the systematic deviation exists in a classical relative photometry model in a star apparent magnitude estimation method. The method comprises the following steps: based on a point spread function model of saturation truncation, a mathematical relationship between the total light flux of a star and the observed light flux of the star in an astronomical oversaturated detection image is established; according to the mathematical relationship, a relative photometry improvement model is established; based on the observed light fluxes of a plurality of known stars and corresponding reference apparent magnitudes, an iterative optimization algorithm is adopted to iteratively optimize the relative photometry improvement model, and the optimal model parameter in the model is solved; and based on the optimal model parameter and the observed light flux of a target to be measured, the apparent magnitude estimation value of the target in the astronomical oversaturated detection image is obtained through the relative photometry improvement model.

The invention discloses a passive density correction method applied to coal seam measurement, and belongs to the technical field of petroleum and natural gas development. The method comprises the following steps: firstly, obtaining the influence of coal seams with different densities on a passive density measurement result through a numerical simulation method; then, calculating the apparent density of the coal seam by utilizing an existing density data processing method, and calculating a passive density error caused by the coal seams with different densities according to the difference between the apparent density and the real density; secondly, establishing a mathematical relationship between the passive apparent density and a passive density error, and forming a passive density coal seam argillaceous correction formula; and finally, substituting the apparent density of the coal seam into a coal seam density correction formula to obtain a density correction value, and superposing the density correction value to a passive density result to obtain relatively accurate coal seam density. According to the method, the measurement precision of passive density logging in the coal seam is improved, and the application scene of the method in the coal seam is expanded.

The present disclosure relates to a method for measuring a sample based on an ellipsometer and an ellipsometric measuring device. The method for measuring a sample based on an ellipsometer comprises: collecting a first measurement Mueller spectrum corresponding to a reference light spot position, and obtaining a first Mueller matrix; moving a cylindrical body along a direction perpendicular to an incident plane by a first preset distance to form a measurement light spot, collecting a second measurement Mueller spectrum corresponding to the measurement light spot position, and obtaining a second Mueller matrix; determining a mathematical relationship between the second Mueller matrix and the first Mueller matrix; representing the second Mueller matrix as a first function of an incident light wavelength, a film thickness, and an included angle based on a Fresnel equation and the mathematical relationship; fitting the second measurement Mueller spectrum based on the first function using a nonlinear regression algorithm to obtain a measured value of the film thickness and the included angle; and calculating a radius of the cylindrical body based on the first preset distance and the measured value of the included angle. The method realizes rapid and non-destructive measurement of the radius of the cylindrical sample.

This invention relates to the field of down-the-hole (DH) drill bit wear measurement technology, specifically a method and system for real-time measurement of DH drill bit wear values. The method involves optimizing and registering an initial three-dimensional model to obtain the overall quantitative wear value of the DH drill bit; analyzing the mapping relationship between drilling parameters and the overall quantitative wear value, and constructing a database of drilling parameters and drill bit wear values; deriving dimensionless variables based on dimensional analysis methods and the database, and combining and filtering these variables with second-order polynomials and cross terms to determine the combination of dimensionless variables affecting drill bit wear; and substituting this combination of dimensionless variables into a multiple linear regression model to establish a mathematical relationship model between drill bit wear and drilling parameters, thereby achieving real-time measurement of the DH drill bit wear value. This invention, based on dimensional analysis to obtain dimensionless variables of drilling parameters and combined with multiple linear regression to construct a model for real-time measurement of DH drill bit wear values, improves construction efficiency and safety.

The invention provides a model and a method for predicting the water-gas ratio and the water yield of formation water of a fracture-vug type water-producing gas well. The model establishment method comprises the following steps: screening out abnormal fluctuation data from gas field production dynamic data to obtain daily output data; calculating the accumulated gas production and formation water-gas ratio of the water-producing gas well according to the daily output data; establishing a formation water-gas ratio calculation model of the water-producing gas well, wherein the model is a mathematical relationship between the formation water-gas ratio and cumulative gas production and contains a plurality of undetermined indexes; the accumulated gas production of the water-producing gas well and the water-gas ratio of the formation water are used for fitting to determine the value of each index, and then a prediction model of the water-gas ratio of the formation water is obtained. The water yield prediction model is established based on the formation water-gas ratio model. According to the prediction method, the future daily water yield can be predicted according to the water yield prediction model. According to the method, the labor cost of a large number of professionals is effectively reduced, the timeliness and convenience are improved, and the method has good applicability and popularization prospects in field practical application.

The invention provides a method for determining the size of a tubular grain for testing the burning rate through the impulse method, and the method comprises the following steps: establishing a relationship between the pressurization rate and the burning characteristic of a propellant and a mathematical relationship between the pressurization rate and a tubular charging size parameter, and revealing the influence of the inner hole burning tubular charging size on the pressure intensity change. Different requirements of impulse method combustion rate tests of propellants with different combustion characteristics on the sizes of the explosive types are determined. And in combination with constraints such as pressurization rate limitation, pressure intensity test range and erosion-resistant combustion, a tubular charging design criterion considering both test precision and safety is provided.

This application relates to apparatus and methods for generating, and executing, surrogate models. In some examples, a computing device generates and evaluates correlations between input and output variables for a system to identify highly correlated input and output parameters. In addition, weights for one or more of the parameters may be determined. The computing device identifies a mathematical relationship between input and output variables to generate a physics model. The computing device may also identify other features not captured by the physical relationship that are highly correlated to each other, and generates a feature model that is based on the highly correlated features. The computing device may optimize the feature model based on a culling process that reduces the computational resources required to execute the feature model. The physics model is then combined with the feature model to generate a system output model that can simulate the system.

The invention discloses a multi-station signal time difference positioning system in a complex environment, and relates to the technical field of wireless signal positioning, and the method comprises the steps: S1, building a measurement model based on a TDOA positioning principle; s2, deriving a mathematical relationship between measurement data and an error introduced by measurement noise by using the measurement model; s3, correcting measurement data according to the mathematical relationship so as to reduce an error term introduced by measurement noise; s4, performing iterative correction on the corrected measurement data to enable the measurement data to gradually approach a theoretical value; s5, judging and terminating iteration by utilizing constraint conditions to obtain final corrected measurement data, solving a target position by adopting a least square method to obtain a positioning result with higher precision, and obtaining a solving process of the method; a measurement model between a signal source and each receiving station is established based on a TDOA positioning principle, and a mathematical equation reflecting a relation between a signal propagation path difference and a target position is established through observation data.

The invention provides a driving-driven gear type one-way conveying particle type material 3D printing gear assembly and a design method thereof, and belongs to the technical field of 3D printing. A flow control assembly for meshing transmission of a driving gear and a driven gear is arranged in a storage shell, and the mathematical relation of the number of teeth, the rotating speed and the diameter is established through a gear transmission ratio calculation equation; an output matching equation is adopted to determine the inner diameter size of an output pipe, a containing groove depth optimization equation is matched to determine the gear embedding depth, the screw pitch of a conveying screw and parameters of a flow control assembly are coordinated through a screw pitch optimization equation, and a complete transmission chain from particle material conveying to liquid flow control is constructed. Accurate control over the rotating speed of the driven gear through rotating speed adjustment of the driving gear is achieved, the matching relation between the liquid conveying rate and the size of an output channel is guaranteed, and the technical problem that in the 3D printing particle material conveying process, liquid flow control precision is insufficient is solved.

The application discloses a kind of temperature control load participation based on model predictive control's distribution network double-layer dispatching method, and the technical scheme steps of application include: first, design the objective function and constraint condition of temperature control load distribution network dispatching, form day-ahead optimal dispatching plan based on particle swarm;Based on the heat balance equation of building, the quantitative mathematical relationship between indoor temperature and refrigeration power and external environment is constructed, and the heat dynamic characteristic model considering is established;Finally, according to the day-ahead temperature control load dispatching plan and building heat dynamic characteristic model, based on model predictive control, single air conditioner control strategy is established, system stability and regulation economy are considered in a larger range, and the economy of distribution network day-ahead optimal dispatching is further improved.

A multi-time-layer differential scheme for implicit heat transfer calculation using moving particles is presented, with the following specific steps: 1. Before calculation, virtual particles are arranged at the boundary to implement boundary layout, using virtual particles to arrange the first, second, and third types of boundaries for heat transfer calculation, as well as symmetric and periodic geometric boundary conditions; 2. During heat transfer calculation, the physical and mathematical relationships between different particles are given according to the input boundary conditions; 3. The distances between particle i and its neighboring particle j from the boundary surface formed by the boundary particles are calculated, and boundary conditions are applied; 4. The particle properties are given according to the initial input temperature, and the calculation time step length is given according to the stability condition; 5. The coefficient matrix and source terms of the multi-time-layer scheme of the heat diffusion equations are combined to solve the energy equation for temperature; 6. A consistent solution is performed using relevant solving algorithms to solve for the next temperature and determine whether convergence has occurred; 7. After all MPS calculations for a single time step are completed, the next time step is initiated.

The present application belongs to the technical field of oil and gas pipeline internal detection, and particularly relates to a pipeline magnetic flux leakage detection data wall thickness quantification method, aiming at solving the problem that the prior art cannot quantize the pipeline wall thickness with high precision in the pipeline magnetic flux leakage internal detection. The method comprises: obtaining simulation data of oil and gas pipeline magnetic flux leakage detection as a base value; only considering the relationship between the base value and the wall thickness, constructing a univariate model of the pipeline wall thickness and the base value of different diameters, then modeling and fitting the mathematical relationship between the wall thickness and the base value, determining the mathematical model of the wall thickness and the base value based on the fitting result as a first model; introducing a speed influence factor in the first model to establish a wall thickness quantification model with the speed factor, as a second model, that is, the final mathematical model of the wall thickness and the base value; obtaining the base value data, and obtaining the wall thickness quantification result through the final mathematical model of the wall thickness and the base value. The present application realizes high-precision quantification of the pipeline magnetic flux leakage detection wall thickness.

The invention discloses a casing monitoring method and device based on secondary gamma-ray energy spectrum inversion, and the method comprises the steps: measuring a plurality of scale wells containing different preset casing sizes through a neutron gamma-ray energy spectrum instrument, obtaining capture gamma-ray energy spectrums under the different preset casing sizes, carrying out the inversion of the capture gamma-ray energy spectrums under the different preset casing sizes, and carrying out the inversion of the capture gamma-ray energy spectrums under the different preset casing sizes. According to a preset casing thickness calculation formula, the iron element yield is calculated, the casing thickness is obtained, and the preset casing thickness calculation formula is determined according to the mathematical relationship between the casing thickness under different casing inner diameters and the iron element yield and the function coefficient; the function coefficient is a function coefficient related to the inner diameter of the casing under different preset casing sizes, and performing casing damage monitoring according to the casing thickness.

This invention relates to a method for calibrating IQ unbalanced image leakage, comprising the following steps: establishing a mathematical relationship model between image leakage power and system IQ unbalance parameters and external compensation; acquiring multi-point measurement data; constructing a nonlinear residual equation system; using a nonlinear least squares algorithm to iteratively solve for the optimal parameters; and calculating the optimal amplitude compensation factor and the optimal phase compensation amount. By employing the method, system, device, processor, and computer-readable storage medium of this invention for calibrating IQ unbalanced image leakage, and by establishing an accurate mathematical model of image leakage, only a small amount of image power data under different compensation conditions needs to be collected. Through an efficient numerical solution algorithm, the inherent amplitude and phase unbalance of the system can be calculated accurately in one step, directly determining the optimal compensation value.

This application discloses a method for solving damage evolution parameters in a damage constitutive model, belonging to structural mechanics and fracture mechanics. The method includes: establishing a mathematical relationship between damage variables and associated variables based on thermodynamic principles, and obtaining an integral expression for the energy dissipation potential per unit volume by combining damage evolution criteria; simplifying the integral expression for the energy dissipation potential per unit volume based on the principle of equivalent strain, obtaining a scalar analytical expression; numerically integrating the scalar analytical expression using the three-point Newton-Cotes integration algorithm, and iteratively solving for the damage evolution parameters using the secant method. This method transforms complex tensor operations into simple scalar analysis, reducing the computational burden. Furthermore, the use of the Newton-Cotes integration method and the secant method iterative solution strategy ensures accurate calculation of damage parameters, enhances computational stability and reliability, and significantly improves the efficiency and accuracy of the solution.

The application discloses a DC system fault location method based on complex domain analysis, comprising the following steps: converting a preliminary fitting exponential function into Z domain for analysis to obtain the converted preliminary fitting exponential function; calculating and solving based on least square method rational approximation to determine the parameters of the preliminary fitting exponential function; calculating the Pearson correlation coefficient to measure the linear relationship between the candidate step length and the minimum fitting error, and optimizing the Pearson correlation coefficient through a particle swarm algorithm to select the best step length; obtaining the final fitting exponential function according to the parameters of the preliminary fitting exponential function and the best step length, solving the mathematical relationship between the distribution characteristics of system poles and the natural oscillation frequency; and calculating the inductance value in the fault line to estimate the fault distance by using the mathematical relationship and combining the inductance value per unit length, so as to realize fault location. The application can realize accurate fault location and meet the speed requirement of fault location.

The invention belongs to the technical field of tire detection, and particularly relates to a rolling resistance prediction method and device based on a tire dynamic load, and the method comprises the steps: obtaining the three-dimensional shape data of the surface of a tire, extracting the key parameters such as the average wear depth, the maximum wear depth and the wear variance, and representing the wear state of the tire in combination with a pattern depth index. And then, on the basis of simulating the vertical deformation of the tire and the change of a contact area under the action of a dynamic load, further calculating the distribution of shear stress, and finally establishing a mathematical relationship among the rolling resistance, the wear degree and the load, so as to realize the accurate prediction of the rolling resistance. The change trend of the rolling resistance can be accurately predicted under different load conditions according to the actual wear state of the tire, and more reliable data support is provided for vehicle energy consumption management.

The invention provides a three-phase asynchronous motor modeling size calculation method and system. The method comprises the steps of obtaining a first geometric size and a preset mathematical relationship model of a three-phase asynchronous motor; determining a second geometric dimension of the three-phase asynchronous motor according to the first geometric dimension of the three-phase asynchronous motor and a preset mathematical relationship model; and taking the second geometric dimension of the three-phase asynchronous motor as the modeling dimension of the three-phase asynchronous motor. According to the technical scheme provided by the invention, other required modeling sizes can be quickly obtained, the parameter calculation time in the modeling process is greatly shortened, and parametric modeling of the motor under the limited data condition becomes possible.

This invention provides a multi-sensor data processing method, apparatus, and system with the following advantages: Monitoring data is grouped according to data elements to obtain multiple data groups, where each data element includes multiple physical parameters; these data groups are fitted separately, and the data with the smallest fitting error is selected from each group to form a training set; the mathematical relationship between the data elements is calculated using the training set. This invention groups sensor data for processing, uses high-precision sensor data for fitting calculations, shields against data noise interference, and effectively improves the accuracy of sensor data processing.

The embodiment of the present application provides a kind of based on the determination method of induced voltage of split conductor of sub-conductor fracture.The method comprises: obtaining the attribute parameter of transmission line, and according to attribute parameter, construct geometric model;Wherein, attribute parameter includes the structural parameter of tower, the physical parameter of conductor, broken line position parameter, conductor includes ground wire, broken sub-conductor and perfect sub-conductor;According to the geometric model, determine potential coefficient matrix, and according to potential coefficient matrix, construct coupling equation;Wherein, potential coefficient matrix represents the electrostatic coupling strength between each conductor, and coupling equation represents the mathematical relationship between the voltage of conductor and charge amount;Solve coupling equation, obtain the electrostatic induction voltage of broken sub-conductor, and according to the electrostatic induction voltage of broken sub-conductor, determine the induced voltage of split conductor to which it belongs.The method is used to improve the effect of the accuracy of determining the induced voltage of split conductor.

The invention discloses a zinc hydrometallurgy cobalt ion concentration prediction method and system based on model compensation TCN input optimization, and belongs to the field of non-ferrous metal wet refining. Identifying abnormal values through forward filling of missing data and a 3 principle, and reducing data noise through wavelet denoising; a mathematical relationship model of historical input and current cobalt ion concentration is established based on a material conservation principle and a Taylor expansion approximation idea, fitting estimation is performed on unknown coefficients in the mathematical model through a particle swarm optimization (PSO) algorithm, and a hybrid model STCN based on a time convolutional network (TCN) and fused with a one-dimensional convolutional mapping module is constructed. And deep features are fully excavated, so that the prediction precision is further improved. According to the method, the mathematical model and the deep learning model are combined, a reliable cobalt ion concentration prediction result can be provided, the interpretability of the whole model can be improved by introducing the mathematical model, and a reliable basis is provided for next-step zinc powder adding and other operations of field workers.

The invention discloses a brine reservoir enrichment zone determination method and device. The method comprises the steps that logging data, rock matrix elastic parameters and angle gather seismic data are acquired; according to the angle gather seismic data, a pre-stack random inversion technology is adopted for inversion to obtain stratum longitudinal wave impedance and stratum transverse wave impedance; according to the logging data, the mathematical relation between the stratum longitudinal wave impedance and the porosity is determined; determining a density attribute corresponding to the to-be-measured seismic data volume according to a mathematical relationship between the stratum density and the stratum longitudinal wave impedance and the stratum transverse wave impedance; and according to the density attribute corresponding to the to-be-measured seismic data volume, determining a brine reservoir enrichment zone meeting a preset condition. According to the method, the brine reservoir enrichment zone can be effectively obtained, and the exploration and development risk of the brine reservoir is reduced.