CN108828681B

CN108828681B - Method and device for determining formation resistivity and polarizability

Info

Publication number: CN108828681B
Application number: CN201810861187.2A
Authority: CN
Inventors: ***; 刘雪军; 张�林
Original assignee: China National Petroleum Corp; BGP Inc
Current assignee: China National Petroleum Corp; BGP Inc
Priority date: 2018-08-01
Filing date: 2018-08-01
Publication date: 2020-01-07
Anticipated expiration: 2038-08-01
Also published as: CN108828681A

Abstract

The embodiment of the application provides a method and a device for determining formation resistivity and polarizability, wherein the method comprises the following steps: acquiring time-frequency electromagnetic observation data and geological background data of a target area; determining a first parameter solution and searching track parameters according to geological background data; determining a second parameter solution according to the first parameter solution and the search track parameter; according to the method, the search track parameters are modified according to a first parameter solution, a second parameter solution and time-frequency electromagnetic observation data, the formation resistivity and the polarizability of the target area are determined according to the modified search track parameters, and because the scheme correspondingly modifies the search track parameters according to the second parameter solution determined based on the first parameter solution and the search track parameters by utilizing a random differential algorithm mechanism, and then the formation resistivity and the polarizability of the target area are searched and determined according to the modified search track parameters, the technical problems of low processing speed and poor accuracy in the prior art are solved.

Description

Method and device for determining formation resistivity and polarizability

Technical Field

The application relates to the technical field of oil and gas exploration, in particular to a method and a device for determining formation resistivity and polarizability.

Background

In the oil and gas exploration process, the formation resistivity and the polarizability of a target area are often determined, and then an area possibly storing oil and gas is found from the area according to the difference condition of the formation resistivity and the polarizability of different areas in the target area. For example, the difference in polarization characteristics between the region where hydrocarbons are stored and the surrounding rock is typically significantly less than the polarization characteristics between the region where metal deposits are stored and the surrounding rock.

At present, in order to determine the formation resistivity and the polarizability of a target region, an optimization objective function method is often used to perform optimization solution on the acquired time-frequency electromagnetic observation data so as to obtain data meeting requirements as the formation resistivity and the polarizability. However, the method is limited by the mechanism of the optimization solution, and when the specific solution is performed based on the existing method, the method is prone to be involved in solving a local minimum value, and cannot search and determine a global minimum value, so that the accuracy of finally obtained result data is often relatively poor. In addition, the existing methods (such as an annealing inversion method and the like) have complex algorithm structures and slow convergence, and show that the processing speed is relatively slow in implementation. In summary, the existing method often has the technical problems of slow processing speed and poor accuracy in implementation.

In view of the above problems, no effective solution has been proposed.

Disclosure of Invention

The embodiment of the application provides a method and a device for determining formation resistivity and polarizability, so that the technical problems of low processing speed and poor accuracy in the existing method are solved, and the technical effects of considering both processing efficiency and accurately determining the formation resistivity and polarizability of a target region are achieved.

The embodiment of the application provides a method for determining formation resistivity and polarizability, which comprises the following steps:

acquiring time-frequency electromagnetic observation data and geological background data of a target area;

determining a first parameter solution and a search track parameter according to the geological background data, wherein the search track parameter at least comprises: searching direction derivative vectors, time integral step length and change increment;

determining a second parameter solution according to the first parameter solution and the search track parameter;

and modifying the search track parameter according to the first parameter solution, the second parameter solution and the time-frequency electromagnetic observation data, and determining the formation resistivity and the polarizability of the target area according to the modified search track parameter.

In one embodiment, determining search trajectory parameters based on the geological context, comprises:

determining the number of stratum layers of a target area according to the geological background data;

generating the search direction derivative vector by using a Gaussian distribution function, wherein the vector length of the search direction derivative vector is equal to the number of stratum layers of the target area;

and determining the time integration step length and the change increment according to the number of stratum layers of the target area.

In one embodiment, determining a second parameter solution according to the first parameter solution and the search trajectory parameter includes:

determining data in the solution of the second parameter according to the following formula:

X₁(i)＝X₀(i)+dx*W(i)

wherein, X₁(i) For data numbered i in the second parametric solution, X₀(i) Data numbered i in the first parametric solution, dx is the increment of change, w (i) is data numbered i in the search direction derivative vector, and i is the number of data in the first parametric solution.

In one embodiment, modifying the search trajectory parameter according to the first parameter solution, the second parameter solution, and the time-frequency electromagnetic observation data includes:

determining first objective function data according to the first parameter solution and the time-frequency electromagnetic observation data; determining second objective function data according to the second parameter solution and the time-frequency electromagnetic observation data;

determining an objective function derivative according to the first objective function data and the second objective function data;

determining a third parameter solution according to the objective function derivative, the first parameter solution, the search direction derivative vector and the time integration step length;

and modifying the search track parameters according to the third parameter solution and the objective function derivative.

In one embodiment, determining first objective function data according to the first parameter solution and the time-frequency electromagnetic observation data includes:

determining first objective function data according to the following formula:

wherein, F₁(X₀(i) X) is the objective function data of the data numbered i in the first parameter solution in the first objective function data₀(i) Is the data with the number i in the first parameter solution, i is the number of the data in the first parameter solution, x_jIs the element numbered j in the data numbered i, j is the number of the element in the data numbered i, d_jIs observation data with the number of j in time-frequency electromagnetic observation data, f (x)_j) The observation data of the element numbered j in the data numbered i, m is the number of the observation data, and std is the relative noise coefficient of the observation data.

In one embodiment, determining a third parameter solution from the objective function derivative, the first parameter solution, the search direction derivative vector, and the time integration step comprises:

determining data in the solution of the third parameter according to the following formula:

X₂(i)＝X₀(i)-h*W(i)*dF₀₁*N

wherein, X₂(i) For data numbered i in the third parametric solution, X₀(i) Data numbered i in the first parametric solution, h is the time integration step, W (i) is data numbered i in the search direction derivative vector, i is the number of data in the first parametric solution, dF₀₁For the objective function derivative, N is the vector length of the search direction derivative vector.

In one embodiment, modifying the search trajectory parameter according to the third parameter solution and the objective function derivative includes:

determining third objective function data according to the third parameter solution;

determining an objective function characteristic parameter according to the first objective function data and the objective function derivative;

and modifying the time integration step length and the change increment in the search track parameter according to the third target function data and the target function characteristic parameter to obtain the modified time integration step length and the modified change increment.

In one embodiment, determining an objective function characteristic parameter from the first objective function data, the objective function derivative, comprises:

determining the characteristic parameters of the objective function according to the following formula:

F_vs＝F₀+dx*abs(dF₀₁)

wherein, F_vsAs characteristic parameters of the objective function, F₀For the first objective function data, dx is the delta of change, dF₀₁Is the objective function derivative.

In one embodiment, modifying the time integration step in the search trajectory parameter according to the third objective function data and the objective function characteristic parameter includes:

comparing the third objective function data with the magnitude of the objective function characteristic parameter;

reducing the time integration step size in the case that the third objective function data is determined to be greater than or equal to the objective function characteristic parameter;

increasing the time integration step size if it is determined that the third objective function data is less than the objective function characteristic parameter.

In one embodiment, modifying the delta change in the search trajectory parameter based on the third objective function data, the objective function characteristic parameter, comprises:

calculating a modification indicating parameter according to the third target function data and the target function characteristic parameter;

comparing the modification indication parameter to a size of 0;

in an instance in which it is determined that the modification indication parameter is greater than 0, decreasing the delta change;

in an instance in which it is determined that the modification indication parameter is less than 0, increasing the delta change;

in the case where it is determined that the modification indication parameter is equal to 0, the value of the change increment is kept unchanged.

In one embodiment, calculating a modification indication parameter according to the third objective function data and the objective function characteristic parameter includes:

calculating the modification indicating parameter according to the following formula:

wherein G is a modification indicating parameter, F_vsAs characteristic parameters of the objective function, F₂Is the third objective function data.

In one embodiment, determining the formation resistivity and polarizability of the target region based on the modified search trajectory parameters includes:

generating a random vector by using a Gaussian distribution function, wherein the vector length of the random vector is the same as the vector length of the search direction derivative vector;

and determining a fourth parameter solution according to the third parameter solution and the modified search track parameter, and taking the fourth parameter solution as the formation resistivity and the polarizability of the target area.

In one embodiment, determining a fourth parameter solution according to the third parameter solution and the modified search track parameter includes:

determining data in the solution of the fourth parameter according to the following formula:

X₃(i)＝X₂(i)-noise*sqrt(h′)*W(i)

wherein, X₃(i) For data numbered i in the fourth parametric solution, X₂(i) The data numbered i in the third parameter solution, h' is the modified time integral step length, W (i) is the data numbered i in the search direction derivative vector, i is the number of the data in the first parameter solution, and noise is the white noise coefficient.

In one embodiment, after determining the fourth parametric solution, the method further comprises:

determining fourth objective function data according to the fourth parameter solution;

determining an accuracy parameter according to the fourth objective function data and the first objective function data;

according to the accuracy parameters, second modification is carried out on the search track parameters;

and determining the formation resistivity and the polarizability of the target area according to the second modified search track parameter.

In one embodiment, determining an accuracy parameter from the fourth objective function data, the first objective function data, comprises:

the accuracy parameter is determined according to the following formula:

G′＝F₃-F₀-100*noise²

wherein G' is an accuracy parameter, F₃Is the third objective function data, F₀For the first objective function data, noise is the white noise coefficient.

In one embodiment, the second modification of the search trajectory parameters according to the accuracy parameters comprises:

comparing the accuracy parameter to a magnitude of 0;

in a case where it is determined that the accuracy parameter is greater than 0, reducing a time integration step in the search trajectory parameter.

In one embodiment, after determining the formation resistivity and polarizability of the target region based on the modified search trajectory parameters, the method further comprises:

determining a region with the difference degree of the formation resistivity and the polarizability larger than a threshold degree in the target region as an oil-gas region according to the formation resistivity and the polarizability of the target region;

and carrying out oil and gas exploration on the oil and gas area.

The embodiment of the application also provides a device for determining the formation resistivity and the polarizability, which comprises:

the acquisition module is used for acquiring time-frequency electromagnetic observation data and geological background data of a target area;

a first determining module, configured to determine a first parameter solution and a search trajectory parameter according to the geological background data, where the search trajectory parameter at least includes: searching direction derivative vectors, time integral step length and change increment;

the second determining module is used for determining a second parameter solution according to the first parameter solution and the search track parameter;

and the modification module is used for modifying the search track parameter according to the first parameter solution, the second parameter solution and the time-frequency electromagnetic observation data, and determining the formation resistivity and the polarizability of the target area according to the modified search track parameter.

The embodiment of the application also provides a computer readable storage medium, which stores computer instructions, and when the instructions are executed, the instructions realize the acquisition of time-frequency electromagnetic observation data and geological background data of a target area; determining a first parameter solution and a search track parameter according to the geological background data, wherein the search track parameter at least comprises: searching direction derivative vectors, time integral step length and change increment; determining a second parameter solution according to the first parameter solution and the search track parameter; and modifying the search track parameter according to the first parameter solution, the second parameter solution and the time-frequency electromagnetic observation data, and determining the formation resistivity and the polarizability of the target area according to the modified search track parameter.

In the embodiment of the application, by utilizing a mechanism of a random differential algorithm, the search track parameter is modified according to a second parameter solution determined based on the first parameter solution and the search track parameter, and then the formation resistivity and the polarizability of the target area are determined according to the modified search track parameter, so that the technical problems of low processing speed and poor accuracy in the existing method are solved, and the technical effects of considering both the processing efficiency and accurately determining the formation resistivity and the polarizability of the target area are achieved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.

FIG. 1 is a process flow diagram of a method of determining formation resistivity and polarizability provided in accordance with an embodiment of the present application;

FIG. 2 is a block diagram of the components of an apparatus for determining formation resistivity and polarizability provided in accordance with an embodiment of the present application;

FIG. 3 is a schematic diagram of an electronic device structure based on a method for determining formation resistivity and polarizability provided by an embodiment of the present application;

FIG. 4 is a schematic cross-sectional view of formation resistivity obtained by applying the method and apparatus for determining formation resistivity and polarizability provided by embodiments of the present application in an example scenario;

FIG. 5 is a schematic cross-sectional view of formation polarizability obtained by applying the method and apparatus for determining formation resistivity and polarizability provided by embodiments of the present application in one example scenario.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Considering that the existing method for determining the formation resistivity and the polarizability is to determine an optimal solution as the formation resistivity and the polarizability by solving a linear equation system step by step through an optimization objective function method. However, the method is limited by the implementation mechanism of the existing method, and during specific solution, the method is easy to fall into solving a local minimum value, and cannot search and determine a global minimum value, so that the accuracy of result data obtained by final solution is often relatively poor. In addition, the algorithm structure adopted by the existing method is complex, and convergence is relatively slow, so that the processing speed is relatively slow in implementation. Aiming at the root cause of the technical problem, the method considers the relevant mechanism of the random differential algorithm and determines a second parameter solution by utilizing an initial first parameter solution and a search track parameter; and then, the search track parameters are correspondingly modified according to the second parameter solution and the related derivative information, so that track parameters which are relatively better in effect, higher in accuracy and easier to converge are obtained to determine the formation resistivity and the polarizability of the target area, the technical problems of low processing speed and poor accuracy in the conventional method are solved, and the technical effects of considering both the processing efficiency and accurately determining the formation resistivity and the polarizability of the target area are achieved.

Based on the thought, the embodiment of the application provides a method for determining formation resistivity and polarizability. Specifically, refer to fig. 1, which is a process flow diagram illustrating a method for determining formation resistivity and polarizability according to an embodiment of the present application. The method for determining the formation resistivity and the polarizability provided by the embodiment of the application can be implemented specifically by the following steps.

In the embodiment, in the inversion solving process, the inversion itself is an underdetermined problem, so that the obtained solution is often non-unique and a multi-solution problem exists in consideration of the existing determination method for the formation resistivity and the polarizability. In the existing method, when a specific inversion is solved, the inversion is generally approximated to a linear problem, and then a linear optimization algorithm is adopted to solve the inversion, so that the local minimum is easy to fall into, and the difference between the solution obtained by the inversion and real data is relatively large. Certainly, in the existing method, a nonlinear optimization algorithm (for example, a linearization iteration method, a conjugate gradient method, a genetic algorithm, a simulated annealing algorithm, and the like) is also used for performing inversion solution, so that although global optimization can be performed unlike a linear algorithm, the solution obtained by inversion also has uncertainty due to some uncertain factors, such as random factors, existing in the inversion process, and the solution accuracy is reduced. Further, when the formation resistivity and the polarizability are solved by inversion, in the process of inverting parameters with abnormal polarization or resistance by using the acquired time-frequency electromagnetic observation data of the target region to determine the oil-gas region, the non-uniqueness and uncertainty existing in the existing inversion method are more obvious, so that the difficulty in acquiring the accurate formation resistivity and polarizability is higher. In order to reduce the uncertainty and uniqueness existing when the time-frequency electromagnetic observation data is used for inverting the formation resistivity and the polarizability and improve the inversion precision, a search track used in the inversion process is generated or modified through a first-order random differential equation based on a random differential mechanism so as to obtain a search track with a better search effect, and then inversion solution is carried out according to the new search track so as to efficiently and accurately search and determine a global optimal solution as the formation resistivity and the polarizability.

S11: and acquiring time-frequency electromagnetic observation data and geological background data of the target area.

In this embodiment, the time-frequency electromagnetic observation data (also referred to as measured data) of the target area may be specifically understood as measured time-frequency electric field data and/or time-frequency magnetic field data of the target area acquired by a high-power time-frequency electromagnetic method.

In one embodiment, the time-frequency electromagnetic observation data of the target area is obtained by a high-power time-frequency electromagnetic method, and the specific implementation may include the following contents: exciting on the ground of a target area to generate square waves with various frequencies through a lead source pre-arranged in the target area; and acquiring time-frequency electric field data (marked as Ex) and/or time-frequency magnetic field data (marked as Hz) formed on the basis of the square waves through measuring points on measuring lines parallel to the lead source. The wire source may be a horizontally long wire source.

In this embodiment, it should be noted that, in specific implementation, the time-frequency electric field data and the time-frequency magnetic field data collected by the measuring points on the measuring line may be used together as the time-frequency electromagnetic data of the target area; one of the time-frequency electric field data and the time-frequency magnetic field data collected by the measuring points on the measuring lines can be used as the time-frequency electromagnetic data of the target area according to specific conditions and requirements. The present application is not limited thereto.

In an embodiment, after the time-frequency electromagnetic data of the target area is acquired, in order to further improve the accuracy of the subsequent processing, the acquired time-frequency electromagnetic data of the target area may be intercepted first according to specific situations. Specifically, after the time-frequency electromagnetic observation data of the target area is acquired, the method may further include the following steps: and intercepting data in a specified frequency range from the time-frequency electromagnetic observation data as the time-frequency electromagnetic observation data of the target area, wherein the specified frequency range is more than or equal to 0.01Hz and less than or equal to 100 Hz. It should be understood that the above listed specified frequency ranges are only for better illustration of the embodiments of the present application. In specific implementation, other frequency ranges can be selected as the designated frequency range according to specific situations and construction requirements. The present application is not limited thereto.

In the present embodiment, the geological background data may be specifically understood as geological data records of the target area, well log data of the target area, seismic data of the target area, and the like. Of course, the geological background of the target area is only given to better illustrate the embodiments of the present application. The specific content of the geological background information is not limited in the application.

S12: determining a first parameter solution and a search track parameter according to the geological background data, wherein the search track parameter at least comprises: searching for directional derivative vectors, time integration step sizes, and change increments.

In this embodiment, the first parameter solution may be specifically understood as an initial solution of the inversion solving process. The first parameter solution may specifically include a plurality of data (or model parameters), each of which includes a plurality of elements, and each of the elements corresponds to the formation resistivity and the polarizability (parameters) at a measurement point position in the target region.

In this embodiment, the above-mentioned search trajectory parameters may be specifically understood as a direction basis for gradually searching a near-accurate global optimal solution, that is, the formation resistivity and the polarizability of the target region based on the first parameter solution.

In this embodiment, the search trajectory parameters include at least the following parameters: search for directional derivative vectors, time integration step size (i.e., h), delta change (i.e., dx), and so on. Of course, it should be noted that the above listed parameters are only illustrative. In specific implementation, other types of parameters can be introduced as the search track parameters according to specific situations and construction requirements. The present application is not limited thereto.

In an embodiment, the determining of the search trajectory parameter according to the geological background data may include the following steps:

s1: determining the number of stratum layers (N) in the target area according to the geological background data;

s2: generating the search direction derivative vector by using a Gaussian distribution function, wherein the vector length of the search direction derivative vector is equal to the number of stratum layers of the target area;

s3: and determining the time integration step length and the change increment according to the number of stratum layers of the target area.

In this embodiment, the value range of the time integration step h may be specifically set to 10 according to the number of stratum layers of the concerned target area^-9To 10^-7In between, the value range of the change increment dx can be specifically set to 10^-9To 10^-7In the meantime. Of course, it should be noted that the above-listed value ranges of the time integration step size and the value range of the change increment are only schematic illustrations. During specific implementation, other suitable numerical value ranges can be selected according to specific conditions and construction requirements as the value range of the time integration step length and the value range of the change increment.

In this embodiment, the generating the search direction derivative vector by using the gaussian distribution function may specifically include: a vector W having a vector length equal to the number of formation layers (i.e., N) of the target zone is generated as the search direction derivative vector (also referred to as an initial search reverse derivative vector) using a gaussian distribution function.

In an embodiment, the determining a first parameter solution according to the geological background data may include the following steps: determining the number of parameters in an initial solution (namely the number of parameters of unknown parameters to be inverted and solved) according to the stratum number of the target area; generating corresponding initial solution X according to the number of parameters in the initial solution₀As the first parametric solution.

In one embodiment, after determining a first parameter solution and searching for trajectory parameters according to the geological background data, the method further comprises: and determining other solving parameters according to the geological background data. Wherein the other solution parameters may include at least one of: number of iterations N of the inversion loop_iAnd the number of search paths N is inverted_trajWhite noise coefficient (or called initial white noise coefficient) noise, relative error tolrel of single iteration stop, absolute error tolabs of single iteration stop, maximum of parameter solution (or called maximum of model parameter) X_maxMinimum value of parameter solution (or minimum value of model parameter) X_minModel parameter matrix X_ntrajThe objective function matrix Fun_ntrajSearch path loop number id, inversion loop iteration number it, and so on. Of course, it should be noted that the other solution parameters listed above are only an illustrative example. In particular, other types of parameters may be introduced according to specific situations and requirements. The present application is not limited thereto.

In an embodiment, in practical implementation, the range of the number of iterations of the inversion loop may be set to be between 20 and 50. The value range of the inversion search path number may be set to be between 3 and 20. The white noise coefficient may be set to 1. The above-mentioned relative error for the single iteration stop may be set to a value in the range of 0.01 to 0.05. The value range of the absolute error of the single iteration stop can be set asBetween 0.001 and 0.005. The first parametric solution may be a vector with a length N. Accordingly, the maximum value of the parameter solution and the minimum value of the parameter solution may be specifically a vector with a length of N, and the dimension of the model parameter matrix may be expressed as N × N_trajThe dimension of the objective function matrix may be expressed as N_traj. Initially, the number of search path cycles may be set to 1, and the number of iterations of the inversion loop may be set to 1. It should be understood that the numerical ranges given above are merely illustrative and should not be construed as unduly limiting the present application.

S13: and determining a second parameter solution according to the first parameter solution and the search track parameter.

In an embodiment, the determining the second parameter solution according to the first parameter solution and the search track parameter may specifically be understood as taking the initial solution of the first parameter solution as an initial value, and obtaining a next more accurate numerical solution as the second parameter solution according to an inversion solution of parameters such as a search direction derivative vector, a time integral step length, a change increment, and the like in the search track parameter.

In an embodiment, the determining a second parameter solution according to the first parameter solution and the search trajectory parameter may include:

X₁(i)＝X₀(i)+dx*W(i)

wherein, X₁(i) Specifically, the parameter can be expressed as data with the number i in the second parameter solution, X₀(i) Specifically, the number i of the first parameter solution, dx of the first parameter solution, w (i) of the search direction derivative vector, and i of the search direction derivative vector may be represented as the number i of the first parameter solution.

S14: and modifying the search track parameter according to the first parameter solution, the second parameter solution and the time-frequency electromagnetic observation data, and determining the formation resistivity and the polarizability of the target area according to the modified search track parameter.

In this embodiment, the formation resistivity and polarizability of the target region determined may be specifically understood as the formation resistivity and polarizability at the site positions in the target region.

In one embodiment, in order to perform global search more quickly and accurately to find the global minimum parameter solution as the formation resistivity and the polarizability of the target region, relevant parameters such as a search direction derivative vector, a time integration step length, a change increment and the like in the search track parameter may be modified and adjusted correspondingly according to the determined second parameter solution in combination with the first parameter solution and the time-frequency electromagnetic observation data, so that the modified and adjusted search track parameter may be used to determine the optimal solution as the formation resistivity and the polarizability more efficiently and accurately.

In an embodiment, the modifying the search track parameter according to the first parameter solution, the second parameter solution, and the time-frequency electromagnetic observation data may include the following steps:

s1: determining first objective function data according to the first parameter solution and the time-frequency electromagnetic observation data; determining second objective function data according to the second parameter solution and the time-frequency electromagnetic observation data;

s2: determining an objective function derivative according to the first objective function data and the second objective function data;

s3: and modifying the search track parameters according to the third parameter solution and the objective function derivative.

In this embodiment, the first objective function data may be specifically used for a degree of difference between the first parameter solution and related data (forward observation data) obtained based on observation data (or actual measurement data) in the video electromagnetic observation data. The second objective function data may be specifically used for the difference degree between the second parameter solution and the related data obtained based on the observation data (or the measured data) in the video electromagnetic observation data.

In an embodiment, the determining the first objective function data according to the first parameter solution and the time-frequency electromagnetic observation data may include the following steps:

determining first objective function data according to the following formula:

wherein, F₁(X₀(i) X) can be specifically expressed as the objective function data of the data numbered i in the first parameter solution in the first objective function data₀(i) Specifically, i may be represented as data with a number i in the first parametric solution, and i may be specifically represented as a number x of data in the first parametric solution_jSpecifically, the number of the element with the number j in the data with the number i can be represented, j specifically can be represented as the number of the element in the data with the number i, d_jThe method can be specifically expressed as the observation data with the number of j in the time-frequency electromagnetic observation data, f (x)_j) Specifically, the measurement may be represented as an observation data measurement of an element numbered j in the data numbered i, m may be specifically represented as the number of observation data, and std may be specifically represented as a relative noise coefficient of the observation data.

In an embodiment, the determining second objective function data according to the second parameter solution and the time-frequency electromagnetic observation data may include the following steps:

determining second objective function data according to the following formula:

wherein, F₂(X₁(i) X) can be specifically expressed as the objective function data of the data numbered i in the second parameter solution in the second objective function data₁(i) Specifically, i may be represented as the number i of the second parametric solution, and i may be specifically represented as the number x of the data in the second parametric solution_j' in particular can be expressed asThe element numbered j in the data numbered i can be specifically represented as the number of the element in the data numbered i, d_jThe method can be specifically expressed as the observation data with the number of j in the time-frequency electromagnetic observation data, f (x)_j') may specifically be represented as the observation data measure of the element numbered j within the data numbered i, m may specifically be represented as the number of observation data, std may specifically be represented as the relative noise figure of the observation data.

In an embodiment, the determining a third parameter solution according to the objective function derivative, the first parameter solution, the search direction derivative vector, and the time integration step may include the following steps:

X₂(i)＝X₀(i)-h*W(i)*dF₀₁*N

wherein, X₂(i) Specifically, the parameter can be expressed as data with the number i in the third parameter solution, X₀(i) Specifically, the parameter may be represented as data numbered i in the first parameter solution, h may be represented as a time integration step length, w (i) may be represented as data numbered i in the search direction derivative vector, i may be represented as data numbered i in the first parameter solution, and dF may be represented as₀₁In particular, it may be expressed as an objective function derivative, and N may be expressed specifically as a vector length of the search direction derivative vector.

In one embodiment, the derivative of the objective function dF is as described above₀₁The determination may be specifically determined according to the first objective function data and the second objective function data. In specific implementation, the derivative of the objective function may be calculated according to the following formula:

wherein dF₀₁It can be expressed in particular as the derivative of the objective function, F₁It can be expressed in particular as first objective function data, F₂And may specifically be represented as second objective function data, and dx may specifically be represented as a delta change.

In an embodiment, the modifying the search trajectory parameter according to the third parameter solution and the objective function derivative may include the following steps:

s1: determining third objective function data according to the third parameter solution;

s2: determining an objective function characteristic parameter according to the first objective function data and the objective function derivative;

s3: and modifying the time integration step length and the change increment in the search track parameter according to the third target function data and the target function characteristic parameter to obtain the modified time integration step length and the modified change increment.

In an embodiment, the determining the characteristic parameter of the objective function according to the first objective function data and the derivative of the objective function may include:

F_vs＝F₀+dx*abs(dF₀₁)

wherein, F_vsIt can be expressed in particular as an objective function characteristic parameter, F₀In particular, may be represented as first objective function data, dx in particular may be represented as delta of change, dF₀₁In particular as the objective function derivative.

In an embodiment, the modifying the time integration step length in the search trajectory parameter according to the third objective function data and the objective function characteristic parameter may include the following steps: comparing the third objective function data with the magnitude of the objective function characteristic parameter; reducing the time integration step size in the case that the third objective function data is determined to be greater than or equal to the objective function characteristic parameter; increasing the time integration step size if it is determined that the third objective function data is less than the objective function characteristic parameter.

In an embodiment, the modifying the change increment in the search trajectory parameter according to the third objective function data and the objective function characteristic parameter may include the following steps: calculating a modification indicating parameter according to the third target function data and the target function characteristic parameter; comparing the modification indication parameter to a size of 0; in an instance in which it is determined that the modification indication parameter is greater than 0, decreasing the delta change; in an instance in which it is determined that the modification indication parameter is less than 0, increasing the delta change; in the case where it is determined that the modification indication parameter is equal to 0, the value of the change increment is kept unchanged.

In an embodiment, the calculating a modification indication parameter according to the third objective function data and the objective function characteristic parameter may include:

wherein G may be specifically denoted as modification indication parameter, F_vsIt can be expressed in particular as an objective function characteristic parameter, F₂And may specifically be represented as third objective function data.

In this embodiment, it should be noted that, by the above method, parameters such as a time integral step length and/or a change increment in an initial search trajectory parameter may be modified and adjusted based on a second parameter solution in combination with a first parameter solution, time-frequency electromagnetic data, and the like, so as to obtain a modified search trajectory parameter that has a better effect and can more quickly converge to a more accurate global optimal solution, and then, the formation resistivity and the polarizability of a target region may be more quickly and accurately determined according to the modified search trajectory parameter.

In one embodiment, the determining the formation resistivity and the polarizability of the target region according to the modified search track parameters may be implemented by the following steps:

s1: generating a random vector (noted as U) by using a Gaussian distribution function, wherein the vector length of the random vector is the same as the vector length of the search direction derivative vector;

s2: and determining a fourth parameter solution according to the third parameter solution and the modified search track parameter, and taking the fourth parameter solution as the formation resistivity and the polarizability of the target area.

In an embodiment, the determining a fourth parameter solution according to the third parameter solution and the modified search trajectory parameter may include:

X₃(i)＝X₂(i)-noise*sqrt(h′)*W(i)

wherein, X₃(i) Specifically, the parameter can be expressed as data with the number i in the fourth parameter solution, X₂(i) Specifically, the parameter may be represented as data numbered i in the third parameter solution, h' may be represented as a modified time integration step length, w (i) may be represented as data numbered i in the search direction derivative vector, i may be represented as a number of data in the first parameter solution, and noise is a white noise coefficient.

In this embodiment, a global minimum value or a global optimal solution with relatively high accuracy, that is, a fourth parameter solution, can be obtained by performing inversion solving in the above manner. The difference degree between the fourth parameter solution and forward observation data obtained based on actually measured time-frequency electromagnetic data is relatively small, so that the fourth parameter solution can be determined as the formation resistivity and the polarizability of the target area.

In the embodiment of the application, compared with the existing method, the search track parameter is modified according to the second parameter solution determined based on the first parameter solution and the search track parameter by utilizing the mechanism of the random differential algorithm, and the formation resistivity and the polarizability of the target area are determined according to the modified search track parameter, so that the technical problems of low processing speed and poor accuracy in the existing method are solved, and the technical effects of considering both the processing efficiency and accurately determining the formation resistivity and the polarizability of the target area are achieved.

In an embodiment, in a case that it is determined that the third objective function data is greater than or equal to the objective function characteristic parameter, the reducing the first time integration step size may include, in a specific implementation:

reducing the first time integration step size in the following manner:

h′＝h*0.5

specifically, h' may be represented as a modified first time integration step, and h may be represented as a first time integration step before modification.

In an embodiment, in a case that it is determined that the third objective function data is smaller than the objective function characteristic parameter, increasing the first time integration step size may include, in a specific implementation:

increasing the first time integration step size in the following manner:

h′＝h*2

In an embodiment, in a case where it is determined that the modification indication parameter is greater than 0, the reducing the first change increment may include, in specific implementation:

reducing the first delta change in the following manner:

dx′＝dx*0.5

specifically, dx' may be represented as the first change increment after modification, and dx may be represented as the first change increment before modification.

In an embodiment, in a case where it is determined that the modification indication parameter is smaller than 0, increasing the first change increment may include, in particular:

increasing the first delta change in the following manner:

dx′＝dx*2

In one embodiment, in order to further improve the accuracy of the determined formation resistivity and polarizability of the target region, after determining the fourth parameter solution, the method may further include, when embodied:

s1: determining fourth objective function data according to the fourth parameter solution;

s2: determining an accuracy parameter according to the fourth objective function data and the first objective function data;

s3: according to the accuracy parameters, second modification is carried out on the search track parameters;

s4: and determining the formation resistivity and the polarizability of the target area according to the second modified search track parameter.

In the present embodiment, the accuracy parameter may be understood as an indication parameter for indicating whether further modification of the modified search trajectory parameter is required.

In an embodiment, the determining an accuracy parameter according to the fourth objective function data and the first objective function data may include:

the accuracy parameter is determined according to the following formula:

G′＝F₃-F₀-100*noise²

wherein G' may be expressed specifically as an accuracy parameter, F₃Can be expressed in particular as third objective function data, F₀Specifically, the first objective function data may be represented, and the noise may be specifically represented as a white noise coefficient.

In an embodiment, the second modification of the search track parameter according to the accuracy parameter may include the following steps: comparing the accuracy parameter to a magnitude of 0; in a case where it is determined that the accuracy parameter is greater than 0, reducing a time integration step in the search trajectory parameter.

In one embodiment, in a case that it is determined that the accuracy parameter is greater than 0, decreasing the first time integration step in the first search trajectory parameter may include, in specific implementation:

reducing the first time integration step size in the following manner:

h″＝h′*0.1

wherein h "may be specifically represented as a first time integration step after the second modification, and h' may be specifically represented as a first time integration step before the second modification.

In this embodiment, it should be noted that after the formation resistivity and the polarizability are obtained by using the modified search trajectory parameters according to the above method, further, the above operations may be repeated for multiple times to obtain multiple sets of formation resistivity and polarizability; and calculating target function data corresponding to the multiple groups of formation resistivities and polarizabilities, and selecting the group of formation resistivity and polarizability with the minimum target function data as the final formation resistivity and polarizability of the target region. This may result in higher accuracy of formation resistivity and polarizability.

In one embodiment, after determining the formation resistivity and polarizability of the target region according to the modified search track parameters, the method may further include the following steps:

s1: determining a region with the difference degree of the formation resistivity and the polarizability larger than a threshold degree in the target region as an oil-gas region according to the formation resistivity and the polarizability of the target region;

s2: and carrying out oil and gas exploration on the oil and gas area.

In the present embodiment, the region where the formation resistivity and the polarizability are abnormal in the peripheral region in the target region, that is, the region having a large difference degree is often a region where hydrocarbons may be stored, and therefore, the region may be determined as a hydrocarbon region for further more specific hydrocarbon exploration.

In this embodiment, the threshold degree may be flexibly set according to specific conditions and construction requirements. The present application is not limited thereto.

From the above description, it can be seen that the method for determining the formation resistivity and the polarizability provided in the embodiment of the present application modifies the search track parameter according to the second parameter solution determined based on the first parameter solution and the search track parameter by using the mechanism of the random differential algorithm, and then determines the formation resistivity and the polarizability of the target region according to the modified search track parameter, thereby solving the technical problems of low processing speed and poor accuracy in the existing method, and achieving the technical effects of considering both the processing efficiency and accurately determining the formation resistivity and the polarizability of the target region; and the search track parameters are modified for multiple times to obtain the search track parameters with better effect, so that the accuracy of the formation resistivity and the polarizability determined on the basis of the search track parameters modified for multiple times is further improved.

Based on the same inventive concept, the embodiment of the present invention also provides a device for determining formation resistivity and polarizability, as described in the following embodiments. Because the principle of solving the problems of the determination device for the formation resistivity and the polarizability is similar to the determination method for the formation resistivity and the polarizability, the implementation of the determination device for the formation resistivity and the polarizability can refer to the implementation of the determination method for the formation resistivity and the polarizability, and repeated details are omitted. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated. Referring to fig. 2, a structural diagram of an apparatus for determining formation resistivity and polarizability according to an embodiment of the present application is shown, where the apparatus may specifically include: the obtaining module 201, the first determining module 202, the second determining module 203, and the modifying module 204, which will be described in detail below.

The obtaining module 201 may be specifically configured to obtain time-frequency electromagnetic observation data and geological background data of a target area;

the first determining module 202 may be specifically configured to determine a first parameter solution and a search trajectory parameter according to the geological background data, where the search trajectory parameter at least includes: searching direction derivative vectors, time integral step length and change increment;

the second determining module 203 may be specifically configured to determine a second parameter solution according to the first parameter solution and the search trajectory parameter;

the modifying module 204 may be specifically configured to modify the search trajectory parameter according to the first parameter solution, the second parameter solution, and the time-frequency electromagnetic observation data, and determine the formation resistivity and the polarizability of the target region according to the modified search trajectory parameter.

In an embodiment, in order to determine the search trajectory parameter according to the geological background data, the first determining module 202 may specifically include the following structural units:

the first determining unit may be specifically configured to determine the number of stratum layers of the target area according to the geological background data;

the first generating unit may be specifically configured to generate the search direction derivative vector by using a gaussian distribution function, where a vector length of the search direction derivative vector is equal to the number of formation layers of the target region;

the second determining unit may be specifically configured to determine the time integration step length and the change increment according to the number of formation layers in the target region.

In an embodiment, when the second determining module 203 is implemented, the data in the solution of the second parameter may be determined according to the following formula:

X₁(i)＝X₀(i)+dx*W(i)

wherein, X₁(i) Specifically, the parameter can be expressed as data with the number i in the second parameter solution, X₀(i) Specifically, the number i of the first parameter solution, dx of the first parameter solution, w (i) of the search direction derivative vector, and i of the search direction derivative vector may be represented.

In an embodiment, in order to modify the search trajectory parameter according to the first parameter solution, the second parameter solution, and the time-frequency electromagnetic observation data, the modifying module 204 may specifically include the following structural units:

the third determining unit may be specifically configured to determine first objective function data according to the first parameter solution and the time-frequency electromagnetic observation data; determining second objective function data according to the second parameter solution and the time-frequency electromagnetic observation data;

a fourth determining unit, which may be specifically configured to determine an objective function derivative according to the first objective function data and the second objective function data;

a fifth determining unit, which may be specifically configured to determine a third parameter solution according to the objective function derivative, the first parameter solution, the search direction derivative vector, and the time integration step;

the modifying unit may be specifically configured to modify the search trajectory parameter according to the third parameter solution and the objective function derivative.

In an embodiment, when the third determining unit is implemented, the first objective function data may be determined according to the following formula:

In an embodiment, when the third determining unit is implemented, the second objective function data may be determined according to the following formula:

wherein, F₂(X₁(i) X) can be specifically expressed as the objective function data of the data numbered i in the second parameter solution in the second objective function data₁(i) Specifically, i may be represented as the number i of the second parametric solution, and i may be specifically represented as the number x of the data in the second parametric solution_j' may specifically be represented as an element numbered j within data numbered i, j may specifically be represented as a number of an element within data numbered i, d_jThe method can be specifically expressed as the observation data with the number of j in the time-frequency electromagnetic observation data, f (x)_j') may specifically be represented as the observation data measure of the element numbered j within the data numbered i, m may specifically be represented as the number of observation data, std may specifically be represented as the relative noise figure of the observation data.

In an embodiment, when the fifth determining unit is implemented, the data in the solution of the third parameter may be determined according to the following formula:

X₂(i)＝X₀(i)-h*W(i)*dF₀₁*N

In one embodiment, in order to modify the search trajectory parameter according to the third parameter solution and the objective function derivative, the modifying unit may include the following structural sub-units:

the first determining subunit is specifically configured to determine third objective function data according to the third parameter solution;

the second determining subunit is specifically configured to determine an objective function characteristic parameter according to the first objective function data and the objective function derivative;

the modifying subunit is specifically configured to modify the time integration step length and the change increment in the search trajectory parameter according to the third objective function data and the objective function characteristic parameter, so as to obtain a modified time integration step length and a modified change increment.

In an embodiment, when the second determining subunit is implemented, the objective function characteristic parameter may be determined according to the following formula:

F_vs＝F₀+dx*abs(dF₀₁)

In an embodiment, in order to modify the time integration step in the search trajectory parameter according to the third objective function data and the objective function characteristic parameter, the modifying subunit may be implemented according to the following procedure: comparing the third objective function data with the magnitude of the objective function characteristic parameter; reducing the time integration step size in the case that the third objective function data is determined to be greater than or equal to the objective function characteristic parameter; increasing the time integration step size if it is determined that the third objective function data is less than the objective function characteristic parameter.

In an embodiment, in order to modify the change increment in the search trajectory parameter according to the third objective function data and the objective function characteristic parameter, the modifying subunit may be implemented according to the following procedure: calculating a modification indicating parameter according to the third target function data and the target function characteristic parameter; comparing the modification indication parameter to a size of 0; in an instance in which it is determined that the modification indication parameter is greater than 0, decreasing the delta change; in an instance in which it is determined that the modification indication parameter is less than 0, increasing the delta change; in the case where it is determined that the modification indication parameter is equal to 0, the value of the change increment is kept unchanged.

In an embodiment, when the modification subunit is implemented, the modification indication parameter may be calculated according to the following formula:

In one embodiment, in order to determine the formation resistivity and the polarizability of the target region according to the modified search track parameters, the modification module may further include the following structural units:

the second generating unit may be specifically configured to generate a random vector by using a gaussian distribution function, where a vector length of the random vector is the same as a vector length of the search direction derivative vector;

the sixth determining unit may be specifically configured to determine a fourth parameter solution according to the third parameter solution and the modified search trajectory parameter, and use the fourth parameter solution as the formation resistivity and the polarizability of the target region.

In an embodiment, when the sixth determining unit is implemented, the data in the solution of the fourth parameter may be determined according to the following formula:

X₃(i)＝X₂(i)-noise*sqrt(h′)*W(i)

wherein, X₃(i) Specifically, the parameter can be expressed as data with the number i in the fourth parameter solution, X₂(i) It can be specifically represented as data numbered i in the third parameter solution, h' can be specifically represented as a modified time integration step, and w (i) can be specifically represented as data numbered i in the search direction derivative vectorThe data i may be specifically represented as a number of data in the first parameter solution, and noise is a white noise coefficient.

In an embodiment, in order to obtain a more accurate formation resistivity and polarizability of the target region, in a specific implementation, the apparatus may further include a second-order modification module, which is specifically configured to determine fourth objective function data according to a fourth parameter solution after determining the fourth parameter solution; determining an accuracy parameter according to the fourth objective function data and the first objective function data; according to the accuracy parameters, second modification is carried out on the search track parameters; and determining the formation resistivity and the polarizability of the target area according to the second modified search track parameter.

In one embodiment, when the secondary modification module is implemented, the accuracy parameter may be determined according to the following formula:

G′＝F₃-F₀-100*noise²

In one embodiment, in order to perform the second modification on the search track parameter according to the accuracy parameter, the second modification module may be implemented according to the following procedures: comparing the accuracy parameter to a magnitude of 0; in a case where it is determined that the accuracy parameter is greater than 0, reducing a time integration step in the search trajectory parameter.

In one embodiment, in order to perform more effective oil and gas exploration on a target region, in specific implementation, the apparatus may further include a construction module, where the construction module may be specifically configured to determine, according to the formation resistivity and the polarizability of the target region, a region in the target region, where a difference degree between the formation resistivity and the polarizability is greater than a threshold degree, as an oil and gas region; and carrying out oil and gas exploration on the oil and gas area.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

It should be noted that, the systems, devices, modules or units described in the above embodiments may be implemented by a computer chip or an entity, or implemented by a product with certain functions. For convenience of description, in the present specification, the above devices are described as being divided into various units by functions, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.

Moreover, in the subject specification, adjectives such as first and second may only be used to distinguish one element or action from another element or action without necessarily requiring or implying any actual such relationship or order. References to an element or component or step (etc.) should not be construed as limited to only one of the element, component, or step, but rather to one or more of the element, component, or step, etc., where the context permits.

From the above description, it can be seen that the determining apparatus for formation resistivity and polarizability provided in the embodiment of the present application considers the mechanism of the random differential algorithm, modifies the search trajectory parameter according to the second parameter solution determined based on the first parameter solution and the search trajectory parameter through the second determining module and the modifying module, and determines the formation resistivity and polarizability of the target region according to the modified search trajectory parameter through the modifying module, so that the technical problems of slow processing speed and poor accuracy in the existing method are solved, the technical effects of considering both processing efficiency and accurately determining the formation resistivity and polarizability of the target region are achieved; and the search track parameters are modified for multiple times through the secondary modification module to obtain the search track parameters with better effect, and the accuracy of the formation resistivity and the polarizability determined based on the search track parameters modified for multiple times is further improved.

The embodiment of the present application further provides an electronic device, which may specifically refer to a schematic structural diagram of the electronic device shown in fig. 3 based on the method for determining the formation resistivity and the polarizability provided in the embodiment of the present application, where the electronic device may specifically include an input device 31, a processor 32, and a memory 33. The input device 31 may be specifically configured to input time-frequency electromagnetic observation data and geological background data of the target area. The processor 32 may be specifically configured to determine a first parameter solution and a search trajectory parameter according to the geological background data, where the search trajectory parameter at least includes: searching direction derivative vectors, time integral step length and change increment; determining a second parameter solution according to the first parameter solution and the search track parameter; and modifying the search track parameter according to the first parameter solution, the second parameter solution and the time-frequency electromagnetic observation data, and determining the formation resistivity and the polarizability of the target area according to the modified search track parameter. The memory 33 may be specifically configured to store time-frequency electromagnetic observation data and geological background data of the target area input via the input device 31, and intermediate data generated by the processor 32.

In this embodiment, the input device may be one of the main apparatuses for information exchange between a user and a computer system. The input device may include a keyboard, a mouse, a camera, a scanner, a light pen, a handwriting input board, a voice input device, etc.; the input device is used to input raw data and a program for processing the data into the computer. The input device can also acquire and receive data transmitted by other modules, units and devices. The processor may be implemented in any suitable way. For example, the processor may take the form of, for example, a microprocessor or processor and a computer-readable medium that stores computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, an embedded microcontroller, and so forth. The memory may in particular be a memory device used in modern information technology for storing information. The memory may include multiple levels, and in a digital system, the memory may be any memory as long as it can store binary data; in an integrated circuit, a circuit without a physical form and with a storage function is also called a memory, such as a RAM, a FIFO and the like; in the system, the storage device in physical form is also called a memory, such as a memory bank, a TF card and the like.

In this embodiment, the functions and effects specifically realized by the electronic device can be explained by comparing with other embodiments, and are not described herein again.

There is also provided in an embodiment of the present application a computer storage medium based method for determining formation resistivity and polarizability, the computer storage medium storing computer program instructions that, when executed, implement: acquiring time-frequency electromagnetic observation data and geological background data of a target area;

determining a first parameter solution and a search track parameter according to the geological background data, wherein the search track parameter at least comprises: searching direction derivative vectors, time integral step length and change increment; determining a second parameter solution according to the first parameter solution and the search track parameter; and modifying the search track parameter according to the first parameter solution, the second parameter solution and the time-frequency electromagnetic observation data, and determining the formation resistivity and the polarizability of the target area according to the modified search track parameter.

In the present embodiment, the storage medium includes, but is not limited to, a Random Access Memory (RAM), a Read-Only Memory (ROM), a Cache (Cache), a Hard Disk Drive (HDD), or a Memory Card (Memory Card). The memory may be used to store computer program instructions. The network communication unit may be an interface for performing network connection communication, which is set in accordance with a standard prescribed by a communication protocol.

In this embodiment, the functions and effects specifically realized by the program instructions stored in the computer storage medium can be explained by comparing with other embodiments, and are not described herein again.

In a specific implementation scenario example, the method and the device for determining the formation resistivity and the polarizability provided by the embodiment of the application are applied to determine the formation resistivity and the polarizability of a certain region, and then a determined oil and gas region possibly storing oil and gas is searched from the region according to the determined formation resistivity and polarizability. The following can be referred to as a specific implementation process.

S1: acquiring time-frequency electromagnetic data (or called actual measurement time-frequency electromagnetic data) of a target area, and selecting the time-frequency electromagnetic data (namely intercepting the time-frequency electromagnetic data in a specified frequency range) to participate in inversion according to the distribution range and the component type of the emission frequency of the actual measurement time-frequency electromagnetic data.

In this embodiment, the range of the emission frequency of the time-frequency electromagnetic data participating in the inversion may be specifically 0.01Hz to 100 Hz. The components of the time-frequency electromagnetic data participating in inversion may specifically include: electric field component data Ex parallel to the field source and/or magnetic field component data Hz perpendicular to the field source.

S2: and determining initial data such as inversion unknowns (namely the resistivity and polarizability of the stratum to be solved), track parameters and the like.

In this embodiment, in specific implementation, the number of inverted unknowns may be determined to be N according to the geological data record of the target region. Similarly, the iteration number N of other initial data inversion loop can be determined_iAnd the number N of paths for inverting the search trajectory_trajInitial white noise coefficient noise, initial time integral step length (i.e. time integral step length) h, model parameter change increment (i.e. change increment) dx, relative error tolrel of single iteration stop, absolute error tolabs of single iteration stop, initial model parameter X₀Maximum value X of model parameter_maxMinimum value X of model parameter_minModel parameter matrix X_ntrajSimulating an objective function value matrix Fun_ntrajThe initial search path cycle number id and the initial inversion cycle iteration number it.

In this embodiment, it should be noted that the number of the inverted unknowns may specifically be determined according to the stratum to be invertedThe number N is determined. Number of iterations N of the inversion loop_iThe value range can be specifically expressed as 20-50. The number of paths N of the inverted search trace_trajThe value range can be specifically expressed as 3 to 20. The value range of the initial white noise coefficient noise may be equal to 1. The value range of the time integration step h can be specifically expressed as 10^-9To 10^-7. The value range of the model parameter change increment dx can be specifically expressed as 10^-9To 10^-7. The value range of the relative error tolrel of the single iteration stop can be specifically represented as 0.01-0.05. The range of the absolute error tolabs of the single iteration stop can be specifically expressed as 0.001-0.005. Furthermore, the initial model parameter X₀Maximum value X of model parameter_maxAnd minimum value X of model parameter_minAnd the like can be specifically a vector with the vector length of N; model parameter matrix X_ntrajMay be particularly N × N_traj(ii) a Model parameter objective function value Fun_ntrajMay be specifically N_traj(ii) a The initial search path cycle number id may be specifically 1; the initial inversion loop iteration number it may specifically be 1.

S3: generating model parameter search direction derivative vector (i.e. search direction derivative vector) W with vector length N by using Gaussian distribution function, and searching according to X₀(i.e., the first parametric solution), dx (i.e., the delta change), and W calculate a new model parameter vector X₁(i.e., the second parametric solution). Wherein, X₁Is used to calculate the objective function derivative of the model parameters. So that the time integration step length, the change increment and other parameters in the search track parameters can be correspondingly modified and adjusted according to the objective function derivative.

In particular, the vector X for the model parameters can be calculated separately₀And X₁Is the objective function value F₀(i.e., first objective function data) and F₁(second objective function data). And may further be according to F₀、F₁Calculating the derivative dF of the model parameter vector objective function value₀₁。

In the present embodiment, the new model parameter vector X is₀And X₁Objective function value F of model parameter₀And F₁And the objective function value derivative dF₀₁Specifically, the calculation can be performed according to the following formula:

X₁(i)＝X₀(i)+dx*W(i) (1)

Wherein, F can be specifically expressed as the target function data with the number of j in the first or second target function data, x_jSpecifically, the number of the element with the number j in the data with the number i can be represented, j specifically can be represented as the number of the element in the data with the number i, d_jThe method can be specifically expressed as the observation data with the number of j in the time-frequency electromagnetic observation data, f (x)_j) In particular, the element x with the number j in the data with the number i can be expressed_jM may be specifically represented by the number of observed data, and std may be specifically represented by the relative noise figure of the observed data. Wherein, the value range of j can be more than or equal to 1 and less than or equal to N.

dF₀₁＝(F₁-F₀)/dx (3)

S4: according to X₀、h、dF₀₁And W calculates a new model parameter vector (i.e., a third parametric solution) X₂And calculating a model parameter vector X₂An objective function value (i.e., third objective function data) F of₂From the parameter vector X₂To do (1)And the scalar value is used for correspondingly modifying the integral step length (namely time integral step length) and the model parameter change increment (namely change increment) in the search track parameter.

In the present embodiment, specifically, the objective function value F can be calculated₀Objective function value F of derivative vector W along search direction_vs(i.e., the characteristic parameters of the objective function). Further, the judgment and processing can be performed according to the following rules: if F_vsLess than F₂Then the integration step size becomes smaller, for example, the integration step size is decreased according to the following equation: h is 0.5; if F_vsLess than F₂The product step length is increased, for example, the integration step length is increased according to the following formula: h ═ h × 2; if abs (F)_vs-F₂) Greater than abs (F)_vs+F₂)*10^-5And/2, the model parameter change increment dx is decreased, for example, according to the following formula: dx ═ dx 0.5; if abs (F)_vs-F₂) Less than abs (F)_vs+F₂)*10^-11And/2, the model parameter change increment dx becomes larger, for example, the model parameter change increment is increased according to the following formula: dx-dx 2; otherwise dx is not updated and not modified.

In this embodiment, the method is used to calculate the new model parameter vector X₂The formula (c) can be expressed in the form:

X₂(i)＝X₀(i)-h*W(i)*dF₀₁*N (4)

In the present embodiment, the objective function value F₂Can be calculated by the formula (2), and the value of the objective function F₀Objective function of derivative vector W along search directionValue F_vsThe calculation formula may be specifically expressed as follows:

F_vs＝F₀+dx*abs(dF₀₁)。

s5: generating a random vector U with a vector length N by using a Gaussian distribution function, and then generating a random vector U according to X₂The noise, h and U calculate a new model parameter vector (i.e., the fourth parametric solution) X₃And a model parameter vector X₃An objective function value (i.e., fourth objective function data) F of₃According to the above F₃、F₀The search track parameters are modified again.

In the present embodiment, specifically, if F₃-F₀If > 100 × noise, the integration step becomes smaller, for example, the integration step h — h 0.1 may be reduced according to the following formula, and X may be set to X₃Is assigned to X₀Is mixing X₀Is assigned to X_ntraj，X_ntraj(:,id)＝X₀Will F₃Assign value to Fun_ntraj，Fun_ntraj(id)＝F₃. Meanwhile, the search path cycle number id is increased by 1, id +1, and the process proceeds to S3. If id is greater than N_trajThen set id equal to zero and jump to S6.

In the present embodiment, the new model parameter vector X is₃The calculation formula may be specifically expressed as follows:

X₃(i)＝X₂(i)-noise*sqrt(h′)*W(i) (6)

Wherein the objective function value F₃Specifically, the calculation can be performed by using formula (2).

S6: for model parameter objective function value Fun_ntrajAre sorted in increasing order and Fun is extracted_ntrajExtracting Fun from serial number i corresponding to the intermediate value of the matrix_ntrajNumber j corresponding to the maximum value of the matrix, X_ntraj(i) assigning a value to X_ntraj(:,j)，X_ntraj(:,j)＝X_ntraj(: i). Meanwhile, the iteration time it of the inversion loop is increased by 1, namely it is equal to it +1, and S3 is skipped; if it is greater than N_iAnd jumps to S7.

S7: extracting model objective function values Fun_ntrajThe number i corresponding to the minimum value in the matrix is set to X_ntrajAnd (i) if the global minimum of the inversion algorithm is adopted, and the corresponding solution is the optimal solution to be solved (namely the formation resistivity and the polarizability of the target area), the optimization process is stopped, and the inversion of the resistivity or the polarizability is completed.

In this embodiment, the above steps S3, S4, S5, S6 and the like may be repeated, and when the number of iterations or the fitting error reaches a set standard, the time-frequency electromagnetic inversion technique based on the stochastic differential algorithm is implemented.

According to the obtained stratum resistivity and polarizability of the target area, a resistivity profile schematic diagram and a polarizability profile schematic diagram can be respectively established, and further, the oil and gas area in the target area can be locked according to the resistivity profile schematic diagram and the polarizability profile schematic diagram so as to perform specific oil and gas exploration.

Specifically, a schematic cross-sectional view of the formation resistivity (in the figure, Res represents resistivity, Elevation represents vertical height, i.e., y coordinate, and Distance represents horizontal Distance, i.e., x coordinate) obtained by applying the method and the device for determining the formation resistivity and the polarizability provided by the embodiment of the present application in one scenario example shown in fig. 4, and a schematic cross-sectional view of the formation polarizability (in the figure, Chargeability represents polarizability, Elevation represents vertical height, i.e., y coordinate, and Distance represents horizontal Distance, i.e., x coordinate) obtained by applying the method and the device for determining the formation resistivity and the polarizability provided by the embodiment of the present application in one scenario example shown in fig. 5 can be referred to. In the figure 4, the x coordinate is 6000km (the measurement point number is 161 point position), the earthquake with the depth of 4500-5000m is predicted to be favorable trap, and a drilling well is designed at the position. But then the time-frequency electromagnetic survey results show that the area is a non-oil-containing favorable area and drilling is not recommended. By combining the graphs of fig. 4 and fig. 5, it can be seen that in the region range of 4500-5000m depth and 6km horizontal distance, the characteristic of low resistivity and low polarizability is presented, and the target is predicted to be a non-favorable oil and gas target. And then, the drilling result shows that an oil-containing oil layer is not drilled at the depth, and the result is consistent with the predicted result, which shows that the treatment effect of the treatment technology is very good.

Compared with the prior art, the method has the following advantages: the method for determining the formation resistivity and the polarizability is a time-frequency electromagnetic inversion technology based on a random differential algorithm, the measured electromagnetic data (instant frequency electromagnetic data) is processed, the resistivity and the polarizability distribution of the underground medium below a measuring line after repeated iterative inversion are obtained, the resistivity and the polarizability information can provide favorable information for the explanation of the structure, the fault and the trap, and meanwhile the oil-gas trap oil-gas containing property can be evaluated by utilizing the resistivity and the polarizability information. The search direction of the time-frequency electromagnetic inversion technology based on the random differential algorithm is determined by a difference method, and the search step length is automatically adjusted, so that the defect of long search time of the simulated annealing inversion technology is overcome, and the defect that the genetic algorithm is easy to fall into local minimum is also overcome, so that the time-frequency electromagnetic inversion technology based on the random differential algorithm has the characteristic of high calculation speed. The method is successfully applied to actual measured data processing, promotes the progress of the processing technology of the time-frequency electromagnetic exploration technology, provides a new means and method for extracting resistivity and polarizability information from the actual measured data of the time-frequency electromagnetic method, and can also be used in the research of inversion problems of magnetotelluric methods, audio magnetotelluric methods and other methods.

Through the scene example, the method and the device for determining the formation resistivity and the polarizability provided by the embodiment of the application are verified, the search track parameter is modified according to the second parameter solution determined based on the first parameter solution and the search track parameter by utilizing the mechanism of the random differential algorithm, and the formation resistivity and the polarizability of the target area are determined according to the modified search track parameter, so that the technical problems of low processing speed and poor accuracy in the conventional method are solved.

Although various specific embodiments are mentioned in the disclosure of the present application, the present application is not limited to the cases described in the industry standards or the examples, and the like, and some industry standards or the embodiments slightly modified based on the implementation described in the custom manner or the examples can also achieve the same, equivalent or similar, or the expected implementation effects after the modifications. Embodiments employing such modified or transformed data acquisition, processing, output, determination, etc., may still fall within the scope of alternative embodiments of the present application.

Although the present application provides method steps as described in an embodiment or flowchart, more or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an apparatus or client product in practice executes, it may execute sequentially or in parallel (e.g., in a parallel processor or multithreaded processing environment, or even in a distributed data processing environment) according to the embodiments or methods shown in the figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded.

The devices or modules and the like explained in the above embodiments may be specifically implemented by a computer chip or an entity, or implemented by a product with certain functions. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the present application, the functions of each module may be implemented in one or more pieces of software and/or hardware, or a module that implements the same function may be implemented by a combination of a plurality of sub-modules, and the like. The above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical division, and other divisions may be realized in practice, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed.

Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may therefore be considered as a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, or the like, and includes several instructions for enabling a computer device (which may be a personal computer, a mobile terminal, a server, or a network device) to execute the method according to the embodiments or some parts of the embodiments of the present application.

The embodiments in the present specification are described in a progressive manner, and the same or similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.

While the present application has been described by way of examples, those of ordinary skill in the art will appreciate that there are numerous variations and permutations of the present application that do not depart from the spirit of the present application and that the appended embodiments are intended to include such variations and permutations without departing from the present application.

Claims

1. A method for determining formation resistivity and polarizability, comprising:

2. The method of claim 1, wherein determining search trajectory parameters based on the geological context, comprises:

3. The method of claim 1, wherein determining a second parameter solution according to the first parameter solution and the search trajectory parameter comprises:

X₁(i)＝X₀(i)+dx*W(i)

4. The method of claim 2, wherein modifying the search trajectory parameters according to the first parameter solution, the second parameter solution, and the time-frequency electromagnetic observation data comprises:

5. The method of claim 4, wherein determining first objective function data from the first parameter solution and the time-frequency electromagnetic observation data comprises:

determining first objective function data according to the following formula:

6. The method of claim 4, wherein determining a third parametric solution based on the objective function derivative, the first parametric solution, the search direction derivative vector, and the time integration step comprises:

X₂(i)＝X₀(i)-h*W(i)*dF₀₁*N

7. The method of claim 4, wherein modifying search trajectory parameters based on the third parameter solution, the objective function derivative, comprises:

8. The method of claim 7, wherein determining an objective function characterization parameter from the first objective function data, the objective function derivative, comprises:

F_vs＝F₀+dx*abs(dF₀₁)

9. The method of claim 7, wherein modifying the time integration step in the search trajectory parameters according to the third objective function data, the objective function characteristic parameters, comprises:

10. The method of claim 7, wherein modifying the delta change in the search trajectory parameters based on the third objective function data, the objective function characteristic parameters, comprises:

comparing the modification indication parameter to a size of 0;

11. The method of claim 10, wherein calculating a modification indication parameter based on the third objective function data and the objective function characteristic parameter comprises:

12. The method of claim 7, wherein determining the formation resistivity and polarizability of the target region based on the modified search trajectory parameters comprises:

13. The method of claim 12, wherein determining a fourth parametric solution based on the third parametric solution and the modified search trajectory parameters comprises:

X₃(i)＝X₂(i)-noise*sqrt(h′)*W(i)

14. The method of claim 13, wherein after determining a fourth parametric solution, the method further comprises:

15. The method of claim 14, wherein determining an accuracy parameter from the fourth objective function data, the first objective function data, comprises:

the accuracy parameter is determined according to the following formula:

G′＝F₃-F₀-100*noise²

16. The method of claim 14, wherein modifying the search trajectory parameters a second time according to the accuracy parameters comprises:

comparing the accuracy parameter to a magnitude of 0;

in the event that it is determined that the accuracy parameter is greater than 0, reducing a time integration step in the search trajectory parameter;

and keeping the time integration step size in the search track parameter unchanged under the condition that the accuracy parameter is less than or equal to 0.

17. The method of claim 1, wherein after determining the formation resistivity and polarizability of the target region based on the modified search trajectory parameters, the method further comprises:

and carrying out oil and gas exploration on the oil and gas area.

18. An apparatus for determining formation resistivity and polarizability, comprising:

19. A computer-readable storage medium having computer instructions stored thereon which, when executed, implement the steps of the method of any one of claims 1 to 17.