CN114526063B

CN114526063B - Method and device for obtaining structural parameters of edge detection electromagnetic wave logging instrument

Info

Publication number: CN114526063B
Application number: CN202210134146.XA
Authority: CN
Inventors: 唐章宏; 张思赐; 王轶男; 王群; 王澈; 李永卿
Original assignee: Beijing University of Technology
Current assignee: Beijing University of Technology
Priority date: 2022-02-14
Filing date: 2022-02-14
Publication date: 2024-07-12
Anticipated expiration: 2042-02-14
Also published as: CN114526063A

Abstract

The invention provides a method and a device for acquiring structural parameters of an edge detection electromagnetic wave logging instrument, wherein the method comprises the following steps: acquiring at least one set of initial optimization parameters of the edge-detecting electromagnetic wave logging instrument; according to at least one set of initial optimization parameters and a preset first threshold value, determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters through a rapid calculation method; determining at least one overall objective function corresponding to the at least one set of initial optimization parameters; and respectively evaluating at least one group of initial optimization parameters through at least one corresponding overall objective function, and judging an evaluation result to determine the objective optimization parameters. The optimization efficiency of the instrument structure is improved, and the defect of large calculation amount caused by the fact that forward modeling is applied in a large amount when the edge detection distance is calculated is overcome.

Description

Method and device for obtaining structural parameters of edge detection electromagnetic wave logging instrument

Technical Field

The invention relates to the field of logging while drilling, in particular to a method and a device for acquiring structural parameters of an electromagnetic wave logging instrument while probing.

Background

In the current trend of horizontal wells and highly deviated wells, maintaining the drilling of logging instruments in the middle of reservoirs is a popular subject of current research in order to improve the oil recovery rate. This requires that the instrument has good edge detection performance, and good edge detection logging instruments (e.g., edge detection electromagnetic wave logging instruments, hereinafter referred to as instruments) can detect distances of more than several tens of meters around. The structural parameters of each electrode of the edge detection electromagnetic wave logging instrument, the frequency of the emitted signal and the like determine the edge detection characteristics of the instrument.

The electrode system structure of the instrument has a great influence on the edge detection performance, and the selection and optimization of the electrode system structure parameters directly influence the quality of the edge detection characteristics. In addition, in the research process of the instrument edge detection performance, the rapid calculation of the edge detection distance under different instrument structure parameter models is also a core for improving the instrument optimization efficiency. The edge detection distance of the current instrument is judged by calculating the intersection point of a response curve obtained by simulating calculation signals at a large number of different boundary distances and the minimum signal threshold identifiable by the instrument, and the response curve of the instrument can be obtained only by carrying out a large number of forward calculations, so that the calculated amount is greatly increased, and the optimization efficiency is low.

Disclosure of Invention

The invention provides a method, a device, equipment, a medium and a product for acquiring structural parameters of an edge detection electromagnetic wave logging instrument. The invention aims to improve the optimization efficiency of the instrument structure and overcome the defect of large calculated amount caused by the fact that forward modeling is largely applied when the edge detection distance is calculated.

In a first aspect, the present invention provides a method for obtaining structural parameters of an edge-detecting electromagnetic wave logging instrument, including: acquiring at least one set of initial optimization parameters of the edge-detecting electromagnetic wave logging instrument, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil; determining at least one target edge detection distance corresponding to the at least one initial optimization parameter by a rapid calculation method according to the at least one initial optimization parameter and a preset first threshold, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by an edge detection electromagnetic wave logging instrument under the corresponding initial optimization parameter; for each set of initial optimization parameters, constructing at least one corresponding objective function according to the corresponding target edge detection distance, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters; evaluating at least one group of initial optimization parameters through the corresponding at least one overall objective function respectively, judging whether an evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and re-determining the target edge detection distance of the at least one group of updated optimization parameters; and if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in the at least one group of initial optimization parameters according to the evaluation result.

Further, the preset optimizing termination conditions comprise a preset first optimizing termination condition and a preset second optimizing termination condition, the first optimizing termination condition comprises judging whether the current optimizing times reach a preset maximum optimizing times, and if the current optimizing times reach the preset maximum optimizing times, determining target optimizing parameters according to the current evaluation result; the second optimization termination condition is to judge whether the difference value between the current evaluation result and the evaluation result of the preset times meets a preset second threshold value, and if so, determining a target optimization parameter according to the current evaluation result; and judging whether the evaluation result meets a preset optimization termination condition, including: and judging whether the evaluation result meets a preset first optimization termination condition or a preset second optimization termination condition.

Further, the constructing a global objective function from the at least one objective function includes: the overall objective function is constructed from a first objective function representing the ability of the edge-penetrating electromagnetic wave logging instrument to resolve a formation boundary, a second objective function representing the resolution of the edge-penetrating electromagnetic wave logging instrument, a range of maximum distances between a preset transmitting coil and a receiving coil, a frequency range of the preset transmitting coil, an inclination angle range of the preset receiving coil, a turn number range of the preset transmitting coil, a turn number range of the preset receiving coil, and a range of minimum signals receivable by the preset edge-penetrating electromagnetic wave logging instrument.

Further, before determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters through a fast calculation method according to the at least one set of initial optimization parameters and a preset first threshold value, the method further comprises: determining a first sampling point and a preset second sampling point of the edge detection electromagnetic wave logging instrument at a stratum interface, and determining an initial edge detection distance according to the first sampling point and the second sampling point; and determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters through a rapid calculation method according to the at least one set of initial optimization parameters and a preset first threshold, wherein the method comprises the following steps: acquiring a preset first threshold value; determining whether the difference value between the simulation calculation signal of each group of initial optimization parameters and the first threshold value meets a preset third optimization termination condition or not under the initial edge detection distance, and determining the initial edge detection distance as a target edge detection distance if the difference value meets the preset third optimization termination condition; if the preset third optimization termination condition is not met, updating the first sampling point and the second sampling point, determining an updated edge detection distance according to the updated first sampling point and the updated second sampling point, and determining whether the difference value between the simulation calculation signal of each group of initial optimization parameters and the first threshold value meets the preset third optimization condition or not under the updated edge detection distance.

Further, the determining the simulated computing signal for each set of initial optimization parameters includes: according to the forward computing method, simulation computing signals of each group of initial optimization parameters are respectively determined.

Further, the perturbing the at least one set of initial optimization parameters according to a preset rule includes: and carrying out random disturbance and/or directional disturbance on the at least one group of initial optimization parameters according to a preset rule.

In a second aspect, the present invention further provides a device for obtaining structural parameters of an edge-detecting electromagnetic wave logging instrument, including: the first processing module is used for acquiring at least one set of initial optimization parameters of the edge detection electromagnetic wave logging instrument, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil; the second processing module is used for determining at least one target edge detection distance corresponding to the at least one initial optimization parameter through a rapid calculation method according to the at least one initial optimization parameter and a preset first threshold value, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by the edge detection electromagnetic wave logging instrument under the corresponding initial optimization parameter; the third processing module is used for constructing at least one corresponding objective function according to the corresponding target edge detection distance for each set of initial optimization parameters, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters; the fourth processing module is used for evaluating at least one group of initial optimization parameters through the corresponding at least one overall objective function respectively, judging whether the evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and redetermining the objective edge detection distance of the at least one group of updated optimization parameters; and if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in the at least one group of initial optimization parameters according to the evaluation result.

In a third aspect, the present invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method for obtaining structural parameters of a side-finding electromagnetic wave logging instrument as described in any one of the above when the program is executed.

In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of a method of obtaining structural parameters of a side-finding electromagnetic wave logging instrument as described in any of the above.

In a fifth aspect, embodiments of the present invention also provide a computer program product having stored thereon executable instructions that, when executed by a processor, cause the processor to implement the steps of the method of obtaining structural parameters of an edge-detecting electromagnetic wave logging instrument of the first aspect.

The invention provides a method, a device, equipment, a medium and a product for acquiring structural parameters of an edge detection electromagnetic wave logging instrument, wherein at least one group of initial optimization parameters of the edge detection electromagnetic wave logging instrument are acquired, and each group of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil; determining at least one target edge detection distance corresponding to the at least one initial optimization parameter by a rapid calculation method according to the at least one initial optimization parameter and a preset first threshold, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by an edge detection electromagnetic wave logging instrument under the corresponding initial optimization parameter; for each set of initial optimization parameters, constructing at least one corresponding objective function according to the corresponding target edge detection distance, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters; evaluating at least one group of initial optimization parameters through the corresponding at least one overall objective function respectively, judging whether an evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and re-determining the target edge detection distance of the at least one group of updated optimization parameters; and if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in the at least one group of initial optimization parameters according to the evaluation result. It can be seen that the number of forward calculation times in the optimization process can be greatly reduced on the premise of ensuring calculation accuracy by constructing the overall objective function, and the instrument optimization efficiency is greatly improved. And constructing at least one corresponding objective function according to the corresponding target edge detection distance, so that the appropriate objective function is quickly constructed, the measured value is more similar to the true value, and the optimization efficiency is improved.

Drawings

In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of some embodiments of a method for obtaining structural parameters of a side-finding electromagnetic wave logging instrument according to the present invention;

FIG. 2 is a schematic diagram of a structural model and a formation model of a side-finding electromagnetic wave logging instrument;

FIG. 3 is a graph of voltage geologic signals versus different boundary distances;

FIG. 4-1 is a diagram of a fast forward calculation model of a parallel green's function in a formation coordinate system;

FIG. 4-2 is a diagram of a fast forward calculation model of the parallel green's function in the instrument coordinate system;

FIG. 5 is a schematic diagram of some embodiments of an apparatus for obtaining structural parameters of a side-finding electromagnetic wave logging instrument according to the present invention;

fig. 6 is a schematic structural diagram of an electronic device provided according to the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the invention and features of the embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like herein are merely used for distinguishing between different devices, modules, or units and not for limiting the order or interdependence of the functions performed by such devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those skilled in the art will appreciate that "one or more" is intended to be construed as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of such messages or information.

The invention will be described in detail below with reference to the drawings in connection with embodiments.

Referring to fig. 1, fig. 1 is a flowchart illustrating some embodiments of a method for obtaining structural parameters of an edge-detecting electromagnetic wave logging apparatus according to the present invention. As shown in fig. 1, the method comprises the steps of:

step 101, at least one set of initial optimization parameters of the edge-detecting electromagnetic wave logging instrument are obtained, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil.

As an example, each set of initial optimization parameters corresponds to a structural parameter of the instrument (structural parameters i.e., transmit coil tilt angle, receive coil tilt angle, distance between transmit and receive coils, and transmit frequency of the transmit coil).

Step 102, determining at least one target edge detection distance corresponding to at least one set of initial optimization parameters by a rapid calculation method according to at least one set of initial optimization parameters and a preset first threshold, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by the edge detection electromagnetic wave logging instrument under the corresponding set of initial optimization parameters.

As an example, the preset first threshold may be a minimum signal threshold of the instrument identification interface, the setting of which includes two cases: in the first case, for the edge detection distance defined by the voltage geological signal, the minimum signal threshold is the minimum voltage value recognizable by the instrument; in the second case, for the edge detection distance defined by the amplitude ratio and the phase difference, the minimum signal threshold is the minimum amplitude ratio and the phase difference value which can be identified by the instrument. The minimum measurement accuracy of the instrument, the minimum amplitude ratio and the phase difference which can be identified by the instrument are constant.

In some alternative implementations, before determining, by the fast calculation method, at least one target edge detection distance corresponding to the at least one set of initial optimization parameters according to the at least one set of initial optimization parameters and the preset first threshold, the method further includes: determining a first sampling point and a preset second sampling point of the edge detection electromagnetic wave logging instrument at the stratum interface, and determining an initial edge detection distance according to the first sampling point and the second sampling point; and determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters by a rapid calculation method according to the at least one set of initial optimization parameters and a preset first threshold, wherein the method comprises the following steps: acquiring a preset first threshold value; determining whether the difference value between the simulation calculation signal of each group of initial optimization parameters and the first threshold value meets a preset third optimization termination condition or not under the initial edge detection distance, and determining the initial edge detection distance as a target edge detection distance if the difference value meets the preset third optimization termination condition; if the preset third optimization termination condition is not met, updating the first sampling point and the second sampling point, determining an updated edge detection distance according to the updated first sampling point and the updated second sampling point, and determining whether the difference value between the simulation calculation signal of each group of initial optimization parameters and the first threshold value meets the preset third optimization condition or not under the updated edge detection distance.

As an example, the selection of sampling points may be referred to fig. 2 and 3. FIG. 2 is a model of the formation and instrument structure: the interface of the two layers of stratum is Z ₁; above the interface is a surrounding rock layer, and below is a reservoir layer. A transmitting coil T and a receiving coil R; the transmit coil and the receive coil may have different tilt angles. And l _TR is the distance between the transmit and receive coils, also referred to as the source distance. The instrument is placed parallel to the formation interface. DTB is the distance of the instrument from the interface. The structural parameters of the instrument are factors affecting the response of the instrument, including coil spacing L, coil size, number of turns of the coil, and angle of inclination of the coil. Determining a first sampling point and a preset second sampling point of the edge detection electromagnetic wave logging instrument at the stratum interface, and determining an initial edge detection distance according to the first sampling point and the second sampling point, wherein the following steps can be referred to:

First, selecting a sampling point of an instrument at a stratum interface, namely DTB=0; secondly, selecting a sampling point of DTB=LL on a detection edge distance L far larger than a preset detection edge distance L before optimization; DTB is the distance of the logging instrument from the formation interface.

The initial sampling points are selected to obtain the edge detection distance of the corresponding instrument structure under the optimized parameters by comparing the magnitude relation between the simulation calculation signals under different boundary distances and the minimum signal threshold on the premise of the stratum model and the corresponding instrument structure model under the optimized parameters.

FIG. 3 is a graph showing calculated values of induced electromotive force at different boundary distances DTB, wherein the induced electromotive force graph can be forward calculated values of DTB within-20 m to 20 m; dtb=0m is the interface of the formation; the instrument moves from left to right along the abscissa, the horizontal line in the figure being the minimum signal threshold of the instrument. The graph is an instrument response curve obtained under the condition of calculating different boundary distances in a large quantity, and an intersection point a of the response curve and a minimum threshold value is the edge detection distance of the instrument under the model. Dtb=ll/2 corresponding to point a in the figure; b is the intermediate point between A and LL. In order to avoid a large number of forward calculations, only a small number of sampling points need to be found to obtain the edge detection distance a. The initial sampling points are dtb=0 and dtb=ll in fig. 3 as the initial two sampling points (i.e. the first sampling point and the second sampling point), and the range of the sampling points must include the edge detection distance a to be calculated.

The edge detection distance a in fig. 3 is determined by the minimum signal threshold and DTB being greater than 0. In fig. 3, DTB is greater than 0 when the instrument is gradually away from the formation boundary, and the induced electromotive force is monotonically decreasing when DTB is greater than 0. When the instrument under the optimized parameters gradually approaches the stratum interface, the analysis condition of the edge detection distance is opposite because the signal is strongly influenced by the stratum, and the received signal is monotonically increased when the DTB is greater than 0. The signal response of fig. 3 is the induced electromotive force, and when the signal response is the amplitude ratio and the phase difference, the trend of the signal response is the same as that of the curve of the induced electromotive force, and the determination of the edge detection distance is similar to that of the induced electromotive force.

As an example, according to at least one set of initial optimization parameters and a preset first threshold, determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters by a fast calculation method, the following steps may be referred to:

according to the characteristic that a simulation calculation signal of an instrument is monotonically decreased along with the increase of the DTB when the DTB is larger than 0, the calculation of the edge detection distance of the instrument comprises the following steps:

A1. a new sampling point DTB (1) is obtained by taking the intermediate value of the first sampling point DTBdown (1) =0 and the second sampling point DTBup (1) =ll, i.e. DTB (1) =ll/2. DTBdown (1) and DTBup (1) are respectively the lower limit and the upper limit of the 1 st round of sampling points; DTB (1) is a new sampling point of the 1 st round, which is obtained between the upper limit and the lower limit of the sampling point of the 1 st round;

A2, judging whether the simulation calculation signal F ₁ and the minimum signal threshold F ₂ corresponding to the new sampling point DTB (i) meet the ending condition; DTB (i) is the new sampling point of the ith round; the ending condition is that the simulation calculation signal F ₁ corresponding to the sampling point DTB and the minimum signal threshold F ₂ (first threshold) meet |F ₁-F₂ | is less than or equal to delta (namely a third optimization termination condition), and delta is a set threshold (namely a third optimization termination condition) and is a constant; wherein i=1, 2,3 …, represents the ith round;

A3, if the simulation calculation signal F ₁ and the minimum signal threshold F ₂ corresponding to the DTB (i) meet the end condition, finishing the edge detection distance calculation, and outputting the DTB (i) value at the moment, namely the edge detection distance (namely the target edge detection distance) of the instrument under the instrument structure parameter model.

A4, if the simulation calculation signal F ₁ and the minimum signal threshold F ₂ corresponding to the DTB (i) do not meet the end condition, the following judgment is carried out:

If the simulation calculation signal F ₁ of the new sampling point DTB (i) is greater than the minimum signal threshold F ₂, indicating that the actual edge detection distance is greater than DTB (i), updating the lower limit and the upper limit of the i+1st round of sampling points to DTBdown (i+1) =dtb (i) and DTBup (i+1) =dtbup (i), taking the intermediate value of the two as the i+1st round of new sampling point DTB (i+1), and returning to A2 to perform the next round of judgment;

If the simulation calculation signal F ₁ corresponding to the DTB (i) of the new sampling point is smaller than the minimum signal threshold F ₂, which indicates that the actual edge detection distance is smaller than the DTB (i), the lower limit and the upper limit of the i+1st round of sampling points are DTBdown (i+1) =dtbdown (i) and DTBup (i+1) =dtb (i), and the intermediate value of the two is taken as the i+1st round of new sampling points DTB (i+1), and the next round of judgment is performed by returning to A2.

The rapid calculation method of the edge detection distance is adopted, a large number of forward calculations shown in fig. 3 are not needed, and the rapid calculation method can be obtained only by carrying out the analysis and judgment on the initial two sampling points.

In some alternative implementations, determining the simulated computing signals for each set of initial optimization parameters includes: according to the forward computing method, simulation computing signals of each group of initial optimization parameters are respectively determined.

As an example, the simulation calculation signal for determining each set of initial optimization parameters may be determined by a forward calculation method, where the forward calculation method includes one or more of a parallel vector Green function method (i.e., a fast parallel vector Green function method, or called a parallel vector Green function method), a pattern matching method, a finite element method, and a finite difference method, and in order to improve the structural parameter optimization efficiency of the edge-detecting logging instrument, the fast parallel vector Green function method may be used to perform forward calculation:

The parallel Green function method is mainly used for processing the layered anisotropic medium model and solving the electric field and magnetic field intensity of a field with a source point and a field point at any position in any multilayer model. As shown in fig. 4-1, the detailed parameters are as follows: a theta well bevel angle; mu magnetic permeability; σ _h0、σ_h1、σ_h2 … 0, 1, 2 … … horizontal conductivity; σ _v0、σ_v1、σ_v2 …,0, 1, 2 … … vertical conductivity; z ₀、Z₁ … dividing line Z coordinate; x _T、y_T、z_T is the source point coordinates; x, y and z are field point coordinates; h ₁、h₂、h₂ … layers 1, 2 … … thick; m _T、M_R transmit coil, receive coil magnetic moment. The magnetic current source and vector Green function G ^HM in the layered medium can be calculated through the stratum model:

wherein G ^HM＝^SG^HM+^PG^HM;^PG^HM is a background term, which is non-zero only when the field and the source point are not in the same layer, and the calculation can obtain an expression by using Hertz potential generated by a unit magnetic dipole in a uniform medium; ^SG^HM The expression of the scattering term is as follows:

wherein, six Sophine integral expressions are as follows:

Wherein,

K _hl ²＝ω²μπε-iωμσ_hl formula (20)

K _vl ²＝ω²μπε-iωμσ_vl formula (21)

Wherein: x _T、y_T、z_T is the source point coordinates; x, y and z are field point coordinates; r is the distance between the source point and the field point; k _l represents the anisotropy coefficient of the first layer; k _hl、k_vl represents the horizontal and longitudinal wavenumbers of the first layer; wherein A _l、B_l、C_l、D_l、E_l、F_l is the undetermined coefficient of each layer, and is obtained by the continuity condition of an electric field and a magnetic field at the interface of the layers;

The calculation results are obtained under the stratum coordinate systems x, y and z, G ^HM obtained by the stratum coordinate systems x, y and z is converted into instrument coordinate systems x ', y ' and z ', the instrument coordinate systems are shown in fig. 4-2, phi _T、φ_R is the azimuth angles of the transmitting coil and the receiving coil, and theta _T、θ_R is the included angle between the magnetic moment direction and the instrument axial direction.

By means of coordinate transformation:

g' ^HM＝R_θ ^TG^HMR_θ formula (23)

Wherein:

The method comprises the following steps:

The magnetic moment of the transmitting coil has three components in an instrument coordinate system, and the induced electromotive force generated by the three components of the magnetic moment in the receiving coil is calculated respectively.

The transmit coil magnetic moment is:

M _T＝I_TN_TA_T formula (26)

Wherein: i _T is the transmitting coil current; n _T is the number of turns of the transmitting coil; a _T is the section area of the transmitting coil;

projection of M _T in three components:

M_Tx'＝M_T×sinθ_T×cosφ_T

M_Ty'＝M_T×sinθ_T×sinφ_T

M _Tz'＝M_T×cosθ_T formula (27)

For M _Tx':

for M _Ty':

For M _Tz':

the total magnetic field generated by three components of magnetic moment at the receiving coil:

H_Rx'＝H_x'Mx'sinθ_Rcosφ_R+H_y'Mx'sinθ_Rsinφ_R+H_z'Mx'cosθ_R Formula (31)

H_Ry'＝H_x'My'sinθ_Rcosφ_R+H_y'My'sinθ_Rsinφ_R+H_z'My'cosθ_R Formula (32)

H_Rz'＝H_x'Mz'sinθ_Rcosφ_R+H_y'Mz'sinθ_Rsinφ_R+H_z'Mz'cosθ_R Formula (33)

V _x'＝-iωμH_Rx'N_RA_R formula (34)

V _y'＝-iωμH_Ry'N_RA_R formula (35)

V _z'＝-iωμH_Rz'N_RA_R formula (36)

Wherein: ω is angular frequency, ω=2pi f, f is emission frequency; n _R is the number of turns of the receiving coil; a _R is the sectional area of the receiving coil;

The three components of the magnetic moment of the transmitting coil under the instrument coordinate system are respectively generated at the receiving coil to obtain the induced electromotive force. Combining the angle theta _R between the magnetic moment direction of the receiving coil and the axial direction of the instrument, the azimuth angle phi _R and the formula (31) to the formula (36), V _x'x'、V_x'y'、V_x'z' can be obtained when theta _R＝90°;φ_R = 0 degrees; v _y'x'、V_y'y'、V_y'z' is obtained when θ _R＝90°;φ_R =90°; v _z'x'、V_z'y'、V_z'z' is obtained when θ _R＝0°;φ_R =0°; the following 9 azimuth induced electromotive forces can be obtained in combination:

Wherein: v _x'y' represents the induced electromotive force emitted in the y 'direction and received in the x' direction by the source point, and others are similar;

When the edge detection distance of the instrument is defined by the voltage geological signal, the simulation calculation signal F ₁ is one of V _x'x'、V_x'y'、V_x'z' mainly aiming at the situation of the orthogonal receiving coil; v _x'x'、V_x'y'、V_x'z' represents different instrument coil combinations, respectively; v _x'x' is the x 'orthogonal transmit-along x' orthogonal receive coil combination; v _x'y' is the y 'orthogonal transmit-along x' orthogonal receive coil combination; v _x'z' is the axial transmit-along x' orthogonal receive coil combination;

when the distance between the edges of the instrument is defined by the amplitude ratio and phase difference signals, the simulation calculation signal F ₁ is the amplitude ratio signal mainly aiming at the situation of the inclined receiving coil Or phase difference signal

Im is the imaginary part of the signal and Re is the real part of the signal; phi ₁、φ₂ represents the two azimuth angles of the receiving coil, typically taken at 0 deg. and 180 deg., respectively.

The problem of integration of the Bessel function can be solved by a parallel vector Green function method, and a fast Hank transformation filter method can be adopted for the problem, so that the solving precision is high and the solving speed is high. The vector Green function algorithm greatly improves the efficiency of optimizing the structural parameters of the logging instrument. When the optimization target is the edge detection distance of the instrument, the instrument model only needs to select a calculation model containing one stratum interface.

The edge detection distance is judged according to the magnitude relation between the simulation calculation signal and the minimum signal threshold value under different boundary distances. The invention takes the trend of the simulation calculation signal under different boundary distances as the premise, sets a small number of sampling points on two sides of the predicted edge detection distance, and uses a rapid calculation method to judge the size relation between the sampling point simulation calculation signal and the minimum signal threshold (namely F1) to reduce the range. And obtaining the edge detection distance and constructing a general objective function based on the condition that the sampling points (such as the first sampling point and the second sampling point) simulate calculation signals and the minimum signal threshold meet the ending condition. And continuously iterating through the algorithm until the optimization termination condition is met, and obtaining the optimal instrument structural parameters. According to the method provided by the invention, the edge detection distance of the instrument can be obtained only by a small number of sampling points, the problem that a large number of simulation calculation signals under different boundary distances are calculated each time is avoided, the number of forward calculation times is obviously reduced, and the instrument optimization efficiency is improved.

Step 103, for each set of initial optimization parameters, constructing at least one corresponding objective function according to the corresponding target edge detection distance, constructing an overall objective function according to the at least one objective function, and determining at least one overall objective function corresponding to the at least one set of initial optimization parameters.

In some alternative implementations, constructing the overall objective function from the at least one objective function includes: the method comprises the steps of constructing an overall objective function according to a first objective function representing the capability of the edge-detecting electromagnetic wave logging instrument to distinguish stratum boundaries, a second objective function representing the resolution of the edge-detecting electromagnetic wave logging instrument, a range of maximum distance between a preset transmitting coil and a receiving coil, a frequency range of the preset transmitting coil, an inclination angle range of the preset receiving coil, a turn number range of the preset transmitting coil, a turn number range of the preset receiving coil and a range of minimum signals receivable by the preset edge-detecting electromagnetic wave logging instrument.

As an example, the construction of the overall objective function, the following may be referred to:

The calculation formula of the overall objective function f is: Wherein f _i is an expression of a different objective function; w _i is the weight corresponding to different objective functions, and w _i is more than 0 and less than or equal to 1. The objective functions f _i correspond to:

First objective function f ₁: the capability of the edge detection electromagnetic wave logging instrument for distinguishing stratum boundaries is measured, and the calculation formula is as follows Wherein L _C is the edge detection distance (namely the target edge detection distance) achieved in the optimization process of the structural parameters of the actual instrument; l is the edge detection distance which can be achieved by a preset instrument;

second objective function f ₂: the resolution of the instrument is mainly realized by considering the first objective function edge detection distance and also has sensitive resolution capability on the thin layer, and the calculation formula is that Wherein lambda _C is the thickness of the thin layer which can be identified in the optimization process of the structural parameters of the practical instrument, and the calculation formula is thatWherein F _C is a simulation calculation signal corresponding to L _C; delta is a set value, which is a constant; lambda is the minimum layer thickness identifiable by a preset instrument;

on the basis of the first optimization target and the second optimization target, the maximum distance between the coils, the frequency of the transmitting coil, the inclination angle of the receiving coil, the number of turns of the transmitting coil, the number of turns of the receiving coil and the minimum signal receivable by the instrument are controlled to be within a preset range.

104, Evaluating at least one group of initial optimization parameters through at least one corresponding overall objective function respectively, judging whether an evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and redetermining the target edge detection distance of the at least one group of updated optimization parameters; if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in at least one group of initial optimization parameters according to the evaluation result.

As an example, if one set of the initial optimization parameters meets the requirement and the other sets of the initial optimization parameters do not meet the requirement as the evaluation result, the parameters in the initial optimization parameters which do not meet the requirement are disturbed, the parameters in the initial optimization parameters which meet the requirement are unchanged, and finally the initial optimization parameters are rearranged to obtain at least one updated optimization parameter.

As an example, at least one set of initial optimization parameters may be substituted into at least one corresponding overall objective function respectively to obtain at least one value, an evaluation threshold is preset, at least one value is compared with the evaluation threshold respectively, and whether the instrument structure parameters corresponding to the at least one set of initial optimization parameters are optimized (i.e. an optimization result of the at least one set of initial optimization parameters is obtained) is determined.

As an example, the fitness function in the genetic algorithm is an evaluation criterion for evaluating whether a set of initial optimization parameters (or a set of updated optimization parameters) are better or not, i.e. a fitness value is obtained by the fitness function, and a child with a larger fitness value or a set of initial optimization parameters are retained to the next generation. The final target optimization parameters may also be determined according to the above-described ideas.

As an example, for judging whether the evaluation result satisfies the preset optimization termination condition, that is, for the evaluation result of at least one set of initial optimization parameters, it is judged whether the preset optimization termination condition is satisfied.

In some optional implementations, the preset optimization termination conditions include a preset first optimization termination condition and a preset second optimization termination condition, the first optimization termination condition includes judging whether the current optimization times reach a preset maximum optimization times, if so, determining a target optimization parameter according to the current evaluation result; the second optimization termination condition is to judge whether the difference value between the current evaluation result and the preset times of evaluation results meets a preset second threshold value, and if so, determining a target optimization parameter according to the current evaluation result; and judging whether the evaluation result meets a preset optimization termination condition, comprising: judging whether the evaluation result meets a preset first optimization termination condition or a preset second optimization termination condition.

As an example, the first optimization termination condition may be to set a fixed optimization frequency N, and when the optimization frequency does not reach the maximum optimization frequency N, and the optimization target of the edge detection electromagnetic wave logging instrument has been reached, the optimization is ended, and the instrument structure corresponding to the optimization parameter with the minimum overall objective function and reaching the optimization target is taken as the final optimization result; when the optimization times reach the maximum times N of optimization, and the optimization target of the edge detection electromagnetic wave logging instrument is not reached yet, the optimization is finished, and an instrument structure corresponding to the optimization parameter with the minimum overall objective function is taken as a final optimization result (namely a target optimization parameter);

As an example, the second optimization termination condition may be whether or not the result G _i of the i-th optimization and the result G _i+j of the next m-th optimization both satisfy |g _i-G_i+j |+.gamma, where j∈ [1, m ] by the overall objective function; gamma is a set threshold. If yes, the optimization is finished, and the optimal far detection logging instrument structure (namely the target optimization parameters) is output.

As an example, the first optimization termination condition may be that a fixed number of optimization times N is set, and if the number of optimization times reaches the maximum number of optimization times N, an instrument structure corresponding to an optimization parameter with the smallest overall objective function is taken as a final optimization result (i.e., a target optimization parameter). If the optimization times do not reach the maximum optimization times N, judging whether the optimization times are met or not through a second optimization termination condition, if yes, finishing optimization, outputting an optimal remote detection logging instrument structure (namely a target optimization parameter), and if not, continuing optimization until the second optimization termination condition is met. Or the second optimization termination condition is not met all the time and the maximum optimization times are reached, at the moment, the first optimization termination condition is met, and the instrument structure corresponding to the optimization parameter with the minimum overall objective function is taken as the final optimization result (namely the objective optimization parameter).

In some alternative implementations, perturbing at least one set of initial optimization parameters according to a preset rule includes: and randomly perturbing and/or perturbing the at least one set of initial optimization parameters according to a preset rule.

As an example, the perturbations may include both random perturbations and directional perturbations: the random disturbance can be based on the steps (i.e. preset rules) of selection, crossing, variation and the like in intelligent optimization algorithms such as genetic algorithm, differential evolution algorithm and the like, and the random disturbance is carried out on an initial edge detection instrument structure parameter model (i.e. at least one group of initial optimization parameters) in respective value ranges, and a last generation of better individual, namely an instrument structure model with good edge detection performance, is reserved when each disturbance occurs; the directional disturbance can comprise optimization algorithms such as Newton iterative algorithm, gradient descent method and conjugate gradient method, and the like, and the optimization direction is guided by solving a derivative construction Jacobian matrix or a Hessian matrix of an objective function to generate a better instrument structure model (namely target optimization parameters).

In summary, by calculating the edge detection distance of the instrument in the optimization of the instrument structural parameters, the intersection point of the simulation signals at different boundary distances and the minimum threshold identifiable by the instrument does not need to be calculated in a large amount. And firstly, selecting a representative small amount of initial sampling points, then obtaining a simulation calculation signal of a new sampling point through a rapid calculation method, judging the size relation between the simulation calculation signal of the sampling point and a minimum threshold value, and obtaining the target edge detection distance according to the condition that the simulation calculation signal of the sampling point and the minimum signal threshold value meet the ending condition. And then, constructing a general objective function, so that the problem that a large number of simulation calculation signals under different boundary distances are calculated each time is avoided, the number of forward calculation times is obviously reduced, and the instrument optimization efficiency is improved.

According to the method for acquiring structural parameters of the edge detection electromagnetic wave logging instrument disclosed by some embodiments of the invention, at least one set of initial optimization parameters of the edge detection electromagnetic wave logging instrument are acquired, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil; according to at least one set of initial optimization parameters and a preset first threshold value, determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters by a rapid calculation method, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by an edge detection electromagnetic wave logging instrument under the corresponding set of initial optimization parameters; for each set of initial optimization parameters, constructing at least one corresponding objective function according to the corresponding target edge detection distance, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters; evaluating at least one group of initial optimization parameters through at least one corresponding overall objective function respectively, judging whether an evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and redetermining the target edge detection distance of the at least one group of updated optimization parameters; if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in at least one group of initial optimization parameters according to the evaluation result. It can be seen that the number of forward calculation times in the optimization process can be greatly reduced on the premise of ensuring calculation accuracy by constructing the overall objective function, and the instrument optimization efficiency is greatly improved. And constructing at least one corresponding objective function according to the corresponding target edge detection distance, so that the appropriate objective function is quickly constructed, and the optimization efficiency is improved.

Referring to fig. 5, fig. 5 is a schematic structural diagram of some embodiments of an apparatus for obtaining structural parameters of an edge-detecting electromagnetic logging instrument according to the present invention, and as an implementation of the method shown in the foregoing drawings, some embodiments of an apparatus for obtaining structural parameters of an edge-detecting electromagnetic logging instrument are provided, where the embodiments of the apparatus correspond to the embodiments of the method shown in fig. 1, and the apparatus may be applied to various electronic devices.

As shown in fig. 5, the apparatus for acquiring structural parameters of the edge-detecting electromagnetic wave logging instrument in some embodiments includes a first processing module 501, a second processing module 502, a third processing module 503, and a fourth processing module 504: a first processing module 501, configured to obtain at least one set of initial optimization parameters of the edge-detecting electromagnetic wave logging instrument, where each set of initial optimization parameters includes a transmit coil inclination angle, a receive coil inclination angle, a distance between the transmit coil and the receive coil, and a transmit frequency of the transmit coil; the second processing module 502 is configured to determine, according to at least one set of initial optimization parameters and a preset first threshold, at least one target edge detection distance corresponding to the at least one set of initial optimization parameters by using a fast calculation method, where the target edge detection distance represents a distance of a farthest stratum boundary that can be detected by the edge detection electromagnetic wave logging instrument under the corresponding set of initial optimization parameters; a third processing module 503, configured to construct, for each set of initial optimization parameters, at least one corresponding objective function according to the corresponding target edge detection distance, construct, according to the at least one objective function, an overall objective function, and determine at least one overall objective function corresponding to the at least one set of initial optimization parameters; a fourth processing module 504, configured to evaluate at least one set of initial optimization parameters through at least one corresponding overall objective function, determine whether the evaluation result meets a preset optimization termination condition, and if the evaluation result does not meet the preset optimization termination condition, perturb the at least one set of initial optimization parameters according to a preset rule, generate at least one set of updated optimization parameters, and redetermine a target edge detection distance of the at least one set of updated optimization parameters; if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in at least one group of initial optimization parameters according to the evaluation result.

In an alternative implementation manner of some embodiments, the preset optimization termination conditions include a preset first optimization termination condition and a preset second optimization termination condition, the first optimization termination condition includes judging whether the current optimization times reach a preset maximum optimization times, if so, determining a target optimization parameter according to the current evaluation result; the second optimization termination condition is to judge whether the difference value between the current evaluation result and the preset times of evaluation results meets a preset second threshold value, and if so, determining a target optimization parameter according to the current evaluation result; and the fourth processing module 504 is further configured to: judging whether the evaluation result meets a preset first optimization termination condition or a preset second optimization termination condition.

In an alternative implementation of some embodiments, the third processing module 503 is further configured to: the method comprises the steps of constructing an overall objective function according to a first objective function representing the capability of the edge-detecting electromagnetic wave logging instrument to distinguish stratum boundaries, a second objective function representing the resolution of the edge-detecting electromagnetic wave logging instrument, a range of maximum distance between a preset transmitting coil and a receiving coil, a frequency range of the preset transmitting coil, an inclination angle range of the preset receiving coil, a turn number range of the preset transmitting coil, a turn number range of the preset receiving coil and a range of minimum signals receivable by the preset edge-detecting electromagnetic wave logging instrument.

In an alternative implementation of some embodiments, the apparatus further includes a fifth processing module configured to: determining a first sampling point and a preset second sampling point of the edge detection electromagnetic wave logging instrument at the stratum interface, and determining an initial edge detection distance according to the first sampling point and the second sampling point; the second processing module is further configured to: acquiring a preset first threshold value; determining whether the difference value between the simulation calculation signal of each group of initial optimization parameters and the first threshold value meets a preset third optimization termination condition or not under the initial edge detection distance, and determining the initial edge detection distance as a target edge detection distance if the difference value meets the preset third optimization termination condition; if the preset third optimization termination condition is not met, updating the first sampling point and the second sampling point, determining an updated edge detection distance according to the updated first sampling point and the updated second sampling point, and determining whether the difference value between the simulation calculation signal of each group of initial optimization parameters and the first threshold value meets the preset third optimization condition or not under the updated edge detection distance.

In an alternative implementation of some embodiments, the fifth processing module is further configured to: according to the forward computing method, simulation computing signals of each group of initial optimization parameters are respectively determined.

In an alternative implementation of some embodiments, the fourth processing module is further configured to: and randomly perturbing and/or perturbing the at least one set of initial optimization parameters according to a preset rule.

In alternative implementations of some embodiments, it is understood that the modules recited in the apparatus correspond to the steps in the method described with reference to fig. 1. Thus, the operations, features and advantages described above for the method are equally applicable to the apparatus and the modules, units contained therein, and are not described here again.

Fig. 6 illustrates a physical schematic diagram of an electronic device, as shown in fig. 6, which may include: processor 610, communication interface (Communications Interface) 620, memory 630, and communication bus 640, wherein processor 610, communication interface 620, memory 630 communicate with each other via communication bus 640. The processor 610 may invoke logic instructions in the memory 630 to perform a method of acquiring structural parameters of a selvedge electromagnetic wave logging instrument, the method comprising: acquiring at least one set of initial optimization parameters of the edge-detecting electromagnetic wave logging instrument, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil; according to at least one set of initial optimization parameters and a preset first threshold value, determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters by a rapid calculation method, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by an edge detection electromagnetic wave logging instrument under the corresponding set of initial optimization parameters; for each set of initial optimization parameters, constructing at least one corresponding objective function according to the corresponding target edge detection distance, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters; evaluating at least one group of initial optimization parameters through at least one corresponding overall objective function respectively, judging whether an evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and redetermining the target edge detection distance of the at least one group of updated optimization parameters; if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in at least one group of initial optimization parameters according to the evaluation result.

Further, the logic instructions in the memory 630 may be implemented in the form of software functional units and stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or a part of the technical solution in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the above-described method of the various embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, are capable of performing the method of obtaining structural parameters of an edge-detecting electromagnetic wave logging instrument provided by the methods described above, the method comprising: acquiring at least one set of initial optimization parameters of the edge-detecting electromagnetic wave logging instrument, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil; according to at least one set of initial optimization parameters and a preset first threshold value, determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters by a rapid calculation method, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by an edge detection electromagnetic wave logging instrument under the corresponding set of initial optimization parameters; for each set of initial optimization parameters, constructing at least one corresponding objective function according to the corresponding target edge detection distance, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters; evaluating at least one group of initial optimization parameters through at least one corresponding overall objective function respectively, judging whether an evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and redetermining the target edge detection distance of the at least one group of updated optimization parameters; if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in at least one group of initial optimization parameters according to the evaluation result.

In yet another aspect, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the methods of obtaining structural parameters of a side-by-side electromagnetic wave logging instrument provided above, the method comprising: acquiring at least one set of initial optimization parameters of the edge-detecting electromagnetic wave logging instrument, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil; according to at least one set of initial optimization parameters and a preset first threshold value, determining at least one target edge detection distance corresponding to the at least one set of initial optimization parameters by a rapid calculation method, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by an edge detection electromagnetic wave logging instrument under the corresponding set of initial optimization parameters; for each set of initial optimization parameters, constructing at least one corresponding objective function according to the corresponding target edge detection distance, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters; evaluating at least one group of initial optimization parameters through at least one corresponding overall objective function respectively, judging whether an evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and redetermining the target edge detection distance of the at least one group of updated optimization parameters; if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in at least one group of initial optimization parameters according to the evaluation result.

The apparatus embodiments described above are merely illustrative, wherein the elements described above as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the respective embodiments or some parts of the methods described above for the embodiments.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method of obtaining structural parameters of a side-finding electromagnetic wave logging instrument, comprising:

acquiring at least one set of initial optimization parameters of the edge-detecting electromagnetic wave logging instrument, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil;

Determining at least one target edge detection distance corresponding to the at least one initial optimization parameter by a rapid calculation method according to the at least one initial optimization parameter and a preset first threshold, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by an edge detection electromagnetic wave logging instrument under the corresponding initial optimization parameter;

for each set of initial optimization parameters, constructing at least one corresponding objective function according to the corresponding target edge detection distance, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters;

Evaluating at least one group of initial optimization parameters through the corresponding at least one overall objective function respectively, judging whether an evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and re-determining the target edge detection distance of the at least one group of updated optimization parameters; if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in the at least one group of initial optimization parameters according to the evaluation result;

The preset optimization termination conditions comprise preset first optimization termination conditions and preset second optimization termination conditions, the first optimization termination conditions comprise judging whether the current optimization times reach preset maximum optimization times, and if so, determining target optimization parameters according to the current evaluation results; the second optimization termination condition is to judge whether the difference value between the current evaluation result and the evaluation result of the preset times meets a preset second threshold value, and if so, determining a target optimization parameter according to the current evaluation result; and

The judging whether the evaluation result meets the preset optimization termination condition comprises the following steps:

judging whether the evaluation result meets a preset first optimization termination condition or a preset second optimization termination condition;

said constructing a global objective function from said at least one objective function, comprising:

The overall objective function is constructed from a first objective function representing the ability of the edge-penetrating electromagnetic wave logging instrument to resolve a formation boundary, a second objective function representing the resolution of the edge-penetrating electromagnetic wave logging instrument, a range of maximum distances between a preset transmitting coil and a receiving coil, a frequency range of the preset transmitting coil, an inclination angle range of the preset receiving coil, a turn number range of the preset transmitting coil, a turn number range of the preset receiving coil, and a range of minimum signals receivable by the preset edge-penetrating electromagnetic wave logging instrument.

2. The method for obtaining structural parameters of an edge-penetrating electromagnetic wave logging instrument according to claim 1, wherein before determining at least one target edge-penetrating distance corresponding to the at least one set of initial optimization parameters by a fast calculation method according to the at least one set of initial optimization parameters and a preset first threshold, the method further comprises:

determining a first sampling point and a preset second sampling point of the edge detection electromagnetic wave logging instrument at a stratum interface, and determining an initial edge detection distance according to the first sampling point and the second sampling point; and

The determining, by a fast calculation method, at least one target edge detection distance corresponding to the at least one set of initial optimization parameters according to the at least one set of initial optimization parameters and a preset first threshold value includes:

Acquiring a preset first threshold value;

Determining whether the difference value between the simulation calculation signal of each group of initial optimization parameters and the first threshold value meets a preset third optimization termination condition or not under the initial edge detection distance, and determining the initial edge detection distance as a target edge detection distance if the difference value meets the preset third optimization termination condition;

if the preset third optimization termination condition is not met, updating the first sampling point and the second sampling point, determining an updated edge detection distance according to the updated first sampling point and the updated second sampling point, and determining whether the difference value between the simulation calculation signal of each group of initial optimization parameters and the first threshold value meets the preset third optimization condition or not under the updated edge detection distance.

3. The method of obtaining structural parameters of a side-finding electromagnetic wave logging instrument of claim 2, wherein determining simulated computing signals for each set of initial optimization parameters comprises:

According to the forward computing method, simulation computing signals of each group of initial optimization parameters are respectively determined.

4. The method for obtaining structural parameters of a side-finding electromagnetic wave logging instrument according to claim 1, wherein the perturbing the at least one set of initial optimization parameters according to a preset rule comprises:

And carrying out random disturbance and/or directional disturbance on the at least one group of initial optimization parameters according to a preset rule.

5. A device for obtaining structural parameters of an edge-detecting electromagnetic wave logging instrument, comprising:

the first processing module is used for acquiring at least one set of initial optimization parameters of the edge detection electromagnetic wave logging instrument, wherein each set of initial optimization parameters comprises an inclination angle of a transmitting coil, an inclination angle of a receiving coil, a distance between the transmitting coil and the receiving coil and a transmitting frequency of the transmitting coil;

the second processing module is used for determining at least one target edge detection distance corresponding to the at least one initial optimization parameter through a rapid calculation method according to the at least one initial optimization parameter and a preset first threshold value, wherein the target edge detection distance represents the distance of the farthest stratum boundary which can be detected by the edge detection electromagnetic wave logging instrument under the corresponding initial optimization parameter;

The third processing module is used for constructing at least one corresponding objective function according to the corresponding target edge detection distance for each set of initial optimization parameters, constructing a general objective function according to the at least one objective function, and determining at least one general objective function corresponding to the at least one set of initial optimization parameters;

The fourth processing module is used for evaluating at least one group of initial optimization parameters through the corresponding at least one overall objective function respectively, judging whether the evaluation result meets a preset optimization termination condition, if the evaluation result does not meet the preset optimization termination condition, perturbing the at least one group of initial optimization parameters according to a preset rule, generating at least one group of updated optimization parameters, and redetermining the objective edge detection distance of the at least one group of updated optimization parameters; if the evaluation result meets the preset optimization termination condition, determining a target optimization parameter in the at least one group of initial optimization parameters according to the evaluation result;

the preset optimization termination conditions comprise preset first optimization termination conditions and preset second optimization termination conditions, the first optimization termination conditions comprise judging whether the current optimization times reach preset maximum optimization times, and if the current optimization times reach the preset maximum optimization times, determining target optimization parameters according to the current evaluation results; the second optimization termination condition is to judge whether the difference value between the current evaluation result and the preset times of evaluation results meets a preset second threshold value, and if so, determining a target optimization parameter according to the current evaluation result; and the fourth processing module is further for: judging whether the evaluation result meets a preset first optimization termination condition or a preset second optimization termination condition;

the third processing module is further configured to: the method comprises the steps of constructing an overall objective function according to a first objective function representing the capability of the edge-detecting electromagnetic wave logging instrument to distinguish stratum boundaries, a second objective function representing the resolution of the edge-detecting electromagnetic wave logging instrument, a range of maximum distance between a preset transmitting coil and a receiving coil, a frequency range of the preset transmitting coil, an inclination angle range of the preset receiving coil, a turn number range of the preset transmitting coil, a turn number range of the preset receiving coil and a range of minimum signals receivable by the preset edge-detecting electromagnetic wave logging instrument.

6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor performs the steps of the method of obtaining structural parameters of an edge-penetrating electromagnetic wave logging instrument as claimed in any one of claims 1 to 4 when the program is executed.

7. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the method of acquiring structural parameters of a sonde electromagnetic logging instrument of any one of claims 1 to 4.

8. A computer program product having stored thereon executable instructions which, when executed by a processor, cause the processor to carry out the steps of a method of obtaining structural parameters of a side-finding electromagnetic wave logging instrument as claimed in any one of claims 1 to 4.