Rapid processing method and system for three-dimensional induction logging information

Abstract

The embodiment of the invention relates to the field of petroleum well logging, and discloses a three-dimensional induction well logging information rapid processing method, system and device and a storage medium, and the method comprises the steps that the well logging response and the hole drift angle of a three-dimensional induction instrument are obtained; constructing a combination curve of each component of the logging response; dividing a stratum according to cross component response difference in logging response, and giving a stratum boundary initial value; giving a stratum horizontal resistivity initial value and a stratum vertical resistivity initial value, and establishing an initial inversion stratum model based on the stratum boundary initial value and the hole drift angle; and based on the initial inversion stratum model, taking a combined curve of each component of logging response as a target function, and performing inversion to obtain stratum horizontal resistivity, stratum vertical resistivity, stratum boundary and borehole inclination angle. According to the embodiment of the invention, the three-dimensional induction logging information of the inclined shaft is quickly processed, the logging information processing time is greatly shortened, the working efficiency of a logging instrument is improved, and meanwhile, the well testing cost of the instrument is greatly reduced.

Description

TECHNICAL FIELD

[0001] The embodiment of the present disclosure relates to the technical field of oil well logging, in particular to a method, system and device for fast processing of three-dimensional induction logging data of anisotropic formation in a deviated well and a storage medium. BACKGROUND

[0002] It is estimated that about 30% of oil and gas reserves in the world are stored in sand-mud thin interbedded layers. Such thin interbedded reservoirs can be equivalent to macroscopic uniaxial anisotropic formations (or, referred to as transverse isotropic formations, abbreviated as TI formations). It is of great significance to detect and identify such formations for the development of oil and gas resources. For existing axial induction logging instruments, due to insufficient longitudinal resolution, such thin interbedded oil reservoirs are often mistaken for high water saturation layers and missed in logging. A three-dimensional induction logging instrument is composed of three mutually perpendicular transmitting coils and three parallel receiving coils, which can detect the horizontal and vertical conductivity information of the formation and identify the formation characteristics from a three-dimensional perspective, and has an inherent advantage in the detection of thin reservoirs and complex reservoirs.

[0003] The processing of three-dimensional induction logging data in anisotropic formations in a deviated well is generally no longer a two-dimensional problem of axial symmetry, but a three-dimensional problem. A three-dimensional numerical method can be used to simulate the logging response of a three-dimensional induction instrument in an anisotropic formation in a deviated well containing a borehole. In order to obtain the resistivity distribution of the formation, nonlinear multi-parameter iterative inversion is needed for the logging data. Iterative inversion requires multiple repeated forward simulation calculations, and the current three-dimensional numerical algorithm is slow, occupies a large amount of computer memory, and is still difficult to adapt to the needs of data inversion. Therefore, the existing three-dimensional induction logging data processing generally adopts the method of first correcting the measured data for the borehole, and then performing longitudinal one-dimensional inversion using the data after the borehole correction. The logging response of a three-dimensional induction instrument is much more complex than that of a traditional axial induction instrument, with more components, and the borehole correction model is affected by multiple parameters such as formation and inclination, resulting in large amount of calculation and great difficulty. The longitudinal one-dimensional inversion is usually slow in calculation, and most of the calculation time is spent on the calculation of the Jacobian matrix of the inversion objective function. SUMMARY

[0004] The embodiment of the present disclosure provides a three-dimensional induction logging data fast processing method, system, device and storage medium to solve or alleviate one or more of the above technical problems in the prior art.

[0005] According to one aspect of the present disclosure, a three-dimensional induction logging data fast processing method is provided, comprising:

[0006] obtaining a three-dimensional induction instrument logging response and a well inclination angle;

[0007] constructing a combination curve of each component of the logging response;

[0008] dividing the formation according to the difference of cross-component responses in the logging responses, and giving initial values of the formation boundary;

[0009] giving initial values of the horizontal resistivity and the vertical resistivity of the formation, and establishing an initial inversion formation model based on the initial values of the formation boundary and the inclination angle;

[0010] based on the initial inversion formation model, taking the combined curve of each component of the logging responses as a target function, and performing inversion to obtain the horizontal resistivity, the vertical resistivity, the formation boundary and the inclination angle of the borehole.

[0011] In a possible implementation, the obtaining of the logging responses of the three-dimensional induction instrument includes:

[0012] constructing a formation coordinate system, a borehole coordinate system and an instrument coordinate system;

[0013] establishing a rotation transformation rule of the magnetic field intensity of the formation coordinate system, the borehole coordinate system and the instrument coordinate system:

[0014] the first rule: calculating the magnetic field intensity in the borehole coordinate system according to the magnetic field tensor in the formation coordinate system and the inclination angle of the borehole;

[0015] the second rule: calculating the magnetic field intensity in the instrument coordinate system according to the magnetic field tensor in the borehole coordinate system and the instrument azimuth angle;

[0016] calculating the magnetic field intensity in the formation coordinate system excited by the transmitting coil through numerical simulation;

[0017] transforming the magnetic field intensity in the borehole coordinate system based on the first rule according to the electromagnetic field in the formation coordinate system;

[0018] transforming the magnetic field intensity in the instrument coordinate system based on the second rule according to the magnetic field intensity in the borehole coordinate system;

[0019] calculating the logging responses of the three-dimensional induction instrument according to the magnetic field intensity in the instrument coordinate system and the coil system instrument coefficient.

[0020] In a possible implementation, based on the initial inversion formation model, taking the combined curve of each component of the logging responses as a target function, and performing inversion to obtain the horizontal resistivity, the vertical resistivity, the formation boundary and the inclination angle of the borehole includes:

[0021] based on the initial inversion formation model, taking the combined curve of each component of the logging responses as a target function, and performing full-parameter inversion by using a Gauss-Newton iterative algorithm;

[0022] when the fitting error of one of the components in the logging responses reaches the minimum, the iterative inversion ends, and the horizontal resistivity, the vertical resistivity, the formation boundary and the inclination angle of the borehole are obtained.

[0023] In a possible implementation, based on the initial inversion stratum model, a combination curve of each component of the logging response is taken as a target function, and inversion is performed to obtain stratum horizontal resistivity, stratum vertical resistivity, stratum boundary and wellbore inclination, including:

[0024] Let the logging response data on a three-dimensional induction instrument be:

[0025] q u (X)=q i (X1,X2,...,X N ),i=1,2,...,M;

[0026] In the formula, M is the number of acquisition points; X is a parameter to be inverted; q i (X) is a nonlinear function of X; N is the number of variables; X=X(σ h ,σ v ,d,α), σ h is horizontal conductivity, σ v is vertical conductivity, d is stratum boundary, and α is wellbore inclination;

[0027] Define the target function as:

[0028]

[0029] In the formula, q i (X t ) is a logging response value;

[0030] Introduce a vector matrix:

[0031]

[0032] Let X (k) be the result of the kth iteration, and according to the Gauss-Newton optimization algorithm, derive the modification amount ΔX (k) of X:

[0033] ΔX (k) =-[J T (X (k) )J(X (k) )] -1 J T (X (k) )f(X (k) );

[0034] In the formula, J(X) is the Jacobian matrix of F(X):

[0035]

[0036] The next iteration point X (k+1) is:

[0037] X (k+1) =X (k) +ΔX (k) ;

[0038] Introduce an N×N dimensional diagonal damping matrix B(β), whose matrix elements are:

[0039]

[0040] The damping matrix B(β) gradually approaches the identity matrix as the number of iterations increases, so the next iteration point is:

[0041] X (k+1) =X (k) +B(β (k) )ΔX (k) ;

[0042] Introducing relative error of logging response during inversion process Relative error with formation parameters To monitor the convergence of the inversion procedure:

[0043]

[0044] In the formula, n is the total number of logging curves; m is the number of measurement points for each logging curve; N is the total number of vertical layers contained in the formation model; d i The location of the i-th layer boundary; α is the wellbore dip angle; R hi R is the horizontal resistivity of the i-th stratum; vi Let q be the vertical resistivity of the i-th stratum; ij This refers to the three-dimensional induction logging response in the instrument coordinate system. The three-dimensional induction logging response in the instrument coordinate system during the k-th iteration; This represents the boundary position of the i-th layer in the k-th iteration; Let be the horizontal resistivity of the i-th layer in the k-th iteration; α is the vertical resistivity of the i-th layer in the k-th iteration; k Let be the wellbore dip angle in the k-th iteration;

[0045] Add constraints that limit formation resistivity during iterative inversion:

[0046] The vertical resistivity of the formation is greater than or equal to the horizontal resistivity of the formation, R v ≥R h ;

[0047] The anisotropy coefficient λ of anisotropic strata is limited to a set value. 2 =R v / R h .

[0048] According to one aspect of the present disclosure, a three-dimensional induction logging data rapid processing system is provided, comprising:

[0049] An acquisition unit is configured to acquire a three-dimensional induction instrument logging response and a hole inclination angle;

[0050] A construction unit is configured to construct a combined curve of each component of the logging response;

[0051] A division unit is configured to divide a formation according to a cross-component response difference in the logging response, and give an initial value of a formation boundary;

[0052] An establishment unit is configured to give an initial value of a formation horizontal resistivity and an initial value of a formation vertical resistivity, and establish an initial inversion formation model based on the initial value of the formation boundary and the hole inclination angle;

[0053] An inversion unit is configured to perform inversion to obtain a formation horizontal resistivity, a formation vertical resistivity, a formation boundary and a hole inclination angle based on the initial inversion formation model and taking the combined curve of each component of the logging response as an objective function.

[0054] In one possible implementation, the acquisition unit comprises:

[0055] A construction module is configured to construct a formation coordinate system, a borehole coordinate system and an instrument coordinate system;

[0056] An establishment module is configured to establish a magnetic field strength rotation transformation rule of the formation coordinate system, the borehole coordinate system and the instrument coordinate system:

[0057] First rule: calculating the magnetic field strength in the borehole coordinate system according to the magnetic field tensor in the formation coordinate system and the hole inclination angle;

[0058] Second rule: calculating the magnetic field strength in the instrument coordinate system according to the magnetic field tensor in the borehole coordinate system and the instrument azimuth angle;

[0059] A first calculation module is configured to calculate the magnetic field strength in the formation coordinate system excited by a transmitting coil through numerical simulation;

[0060] A first transformation module is configured to transform the magnetic field strength in the borehole coordinate system based on the first rule according to the electromagnetic field in the formation coordinate system;

[0061] A second transformation module is configured to transform the magnetic field strength in the instrument coordinate system based on the second rule according to the magnetic field strength in the borehole coordinate system;

[0062] A second calculation module is configured to calculate the three-dimensional induction instrument logging response according to the magnetic field strength in the instrument coordinate system and a coil system-instrument system coefficient.

[0063] In one possible implementation, the inversion unit comprises:

[0064] an inversion module, configured to perform full parameter inversion based on the initial inversion formation model, with a combination curve of each component of the logging response as a target function, and a Gauss-Newton iterative algorithm;

[0065] an acquisition module, configured to obtain the formation horizontal resistivity, the formation vertical resistivity, the formation boundary and the borehole inclination when fitting error of one of the components of the logging response reaches minimum and the iterative inversion ends.

[0066] In a possible implementation, the inversion unit is configured to:

[0067] denote logging response data on a three-dimensional induction instrument as:

[0068] q i (X)=q i (X1,X2,...,X N ),i=1,2,...,M;

[0069] wherein M is the number of acquisition points; X is a parameter to be inverted; q i (X) is a nonlinear function of X; N is the number of variables; X=X(σ h ,σ v ,d,α), σ h is the horizontal conductivity, σ v is the vertical conductivity, d is the formation boundary, and α is the borehole inclination;

[0070] define a target function as:

[0071]

[0072] wherein q i (X t ) is a logging response value;

[0073] introduce a vector matrix:

[0074]

[0075] Let X (k) be the result of the kth iteration, and according to the Gauss-Newton optimization algorithm, derive the modification amount ΔX (k) of X:

[0076] ΔX (k) =-[J T (X (k) )J(X (k) )] -1 J T (X (k) )f(X (k) );

[0077] where J(X) is the Jacobian matrix of F(X):

[0078]

[0079] Next iteration point X (k+1) is:

[0080] X (k+1) = X (k) + ΔX (k) ;

[0081] A N x N diagonal damping matrix B(β) is introduced, the matrix element of B is:

[0082]

[0083] The damping matrix B(β) gradually approaches to the unit matrix with the increase of iteration number, then the next iteration point is:

[0084] X (k+1) = X (k) + B(β (k) )ΔX (k) ;

[0085] The relative error of logging response and the relative error of formation parameters are introduced to monitor the convergence of inversion program:

[0086]

[0087] where n is the total number of logging curves; m is the number of measurement points of each logging curve; N is the total number of vertical layers contained in the formation model; di i is the boundary position of the i-th layer; α is the wellbore inclination; Ri hi is the horizontal resistivity of the i-th layer; Ri vi is the vertical resistivity of the i-th layer; qi ij is the three-dimensional induction logging response in the instrument coordinate system; is the three-dimensional induction logging response in the instrument coordinate system of the k-th iteration; is the boundary position of the i-th layer of the k-th iteration; is the horizontal resistivity of the i-th layer of the k-th iteration; is the vertical resistivity of the i-th layer of the k-th iteration; αk k is the wellbore inclination of the k-th iteration;

[0088] A constraint condition of limiting the formation resistivity is added during iterative inversion:

[0089] The vertical resistivity of the formation is greater than or equal to the horizontal resistivity of the formation, Ri v ≥ Ri h ;

[0090] The anisotropy coefficient λ of the anisotropic stratum is limited within a set value, λ 2 = R v / R h .

[0091] According to one aspect of the present disclosure, there is provided an apparatus comprising:

[0092] a processor and a memory;

[0093] The memory is configured to store a computer program, and the processor is configured to invoke the computer program stored in the memory to execute the three-dimensional induction logging data processing method according to any one of the preceding aspects.

[0094] According to one aspect of the present disclosure, there is provided a computer readable storage medium having stored therein a computer program, which, when executed by a processor, causes the processor to perform the three-dimensional induction logging data processing method according to any one of the preceding aspects.

[0095] The exemplary embodiments of the present disclosure have the following beneficial effects: The exemplary embodiments of the present disclosure construct three-dimensional induction logging response component combination curves that can eliminate the influence of wellbore environment and longitudinal adjacent layer heterogeneity on logging response, use these response component combination curves as an inversion target function, and reduce the three-dimensional induction wellbore correction module which is difficult to calculate and has a large amount of calculation. Meanwhile, the present disclosure derives an analytical calculation formula of a Jacobi matrix according to a forward numerical analytical solution, thereby greatly saving the calculation time of inversion and improving the calculation accuracy. A damping matrix and a constraint condition are introduced in the inversion process to improve the stability of the inversion program.

[0096] In summary, the present disclosure can process three-dimensional induction logging data of deviated wells quickly, greatly shorten the logging data processing time, improve the working efficiency of logging instruments, greatly reduce the cost of instrument testing, make three-dimensional induction logging data better applied to field processing and interpretation and evaluation, and have great significance for the wide promotion of three-dimensional induction instrument field application.

[0097] The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below. Other features and advantages of the application will become apparent from the description that follows. It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application. BRIEF DESCRIPTION OF DRAWINGS

[0098] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate embodiments consistent with the present disclosure and, together with the description, further serve to explain the principles of the disclosure. It is apparent that the drawings described below are only some embodiments of the present disclosure, and other drawings can be obtained by those of ordinary skill in the art without creative effort based on these drawings.

[0099] Figure 1 FIG. 1 is a flow chart of a method for quickly processing three-dimensional induction logging data according to an example embodiment of the present disclosure;

[0100] Figure 2 FIG. 2 is a flow chart of quickly processing logging data of a three-dimensional induction instrument in a deviated well according to an example embodiment of the present disclosure;

[0101] Figure 3 FIG. 3 is a structure diagram of a coil system of a three-dimensional induction logging instrument according to an example embodiment of the present disclosure;

[0102] Figure 4 FIG. 4 is a diagram showing relationships among a formation coordinate system, a borehole coordinate system and an instrument coordinate system according to an example embodiment of the present disclosure;

[0103] Figure 5 FIG. 5 is a diagram of an error curve of iterative inversion according to an example embodiment of the present disclosure;

[0104] Figure 6 FIG. 6 is a diagram of horizontal resistivity and vertical resistivity curves obtained after inversion according to an example embodiment of the present disclosure;

[0105] Figure 7 FIG. 7 is a block diagram of a system for quickly processing three-dimensional induction logging data according to an example embodiment of the present disclosure;

[0106] Figure 8 FIG. 8 is a structure diagram of an apparatus according to an example embodiment of the present disclosure. DETAILED DESCRIPTION

[0107] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations may, however, be implemented in many different forms and should not be construed as limited to the examples set forth herein; rather, these examples are provided so that this disclosure will be thorough and complete, and will fully convey the scope of example implementations to those skilled in the art. The described features, structures, or characteristics can be combined in one or more implementations. In the following description, numerous specific details are provided to give a thorough understanding of example implementations. One skilled in the relevant art will recognize, however, that the implementations can be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures have not been described in detail to avoid obscuring the description of the example implementations.​​​​​​​​​​​​​​​​​​​​​​​​​​​

[0108] Furthermore, the accompanying drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification. The drawings are not necessarily to scale, the same reference numerals in different drawings representing the same or similar elements. For the purposes of the present disclosure, the phrase "at least one of X, Y, and Z" shall mean X or Y or Z or any combination of these. In the attached drawings:

[0109] The flow charts shown in the various figures are examples only and are not necessarily meant to include all of the steps. For example, some steps can be broken down, while others can be combined or partially combined, and the order of the actual implementation can vary depending on the circumstances.

[0110] The terms "first", "second", and the like, herein do not necessarily have an ordinal, sequential, or chronologic implication, but are used to differentiate between two or more objects. It is to be understood that the use of the terms so

[0111] Furthermore, the terms "comprise", "comprising", "include", "including", and the like, are to be construed open-ended, meaning that they include not only the recited elements, but also other elements not recited. It is to be understood that the use of terms such as "first" and "second", among others, are used to differentiate between two or more objects, and are not meant to imply a particular order or chronology.

[0112] Figure 1 is a flow chart of a method for fast processing of 3D induction logging data, according to an example embodiment of the present disclosure, as shown in FIG. 1. The method for fast processing of 3D induction logging data, according to an example embodiment of the present disclosure, comprises: Figure 1

[0113] obtaining the 3D induction logging response and the inclination angle;

[0114] constructing a combination curve of each component of the logging response;

[0115] dividing the formation according to the difference of the cross-component response in the logging response, and giving an initial value of the formation boundary;

[0116] giving an initial value of the horizontal resistivity of the formation and an initial value of the vertical resistivity of the formation, and based on the initial value of the formation boundary and the inclination angle, establishing an initial inversion formation model;

[0117] ​Based on the initial inversion stratum model, a combination curve of each component of the logging response is taken as a target function to perform inversion to obtain stratum horizontal resistivity, stratum vertical resistivity, stratum boundary and wellbore inclination.

[0118] The purpose of the embodiment is to quickly and accurately obtain parameters such as TI stratum conductivity and wellbore inclination, so that 3D induction instrument logging data can be processed and applied on site more quickly.

[0119] The embodiment provides a fast processing method for 3D induction logging data of anisotropic stratum of a deviated well after detailed investigation and analysis of 3D induction instrument logging response characteristics, as shown in the figure, comprising the following steps: Figure 2

[0120] 1) Logging is performed by using a 3D induction instrument to obtain 3D induction instrument logging response: coil system apparent resistivity curve, and well inclination is measured by using a clinometer;

[0121] 2) A combination curve of nine components of 3D induction logging response is constructed, which can eliminate the influence of wellbore environment and longitudinal adjacent layer heterogeneity on logging response, and the combination curve of the response components is used as an inversion program target function;

[0122] 3) The stratum is divided according to local maximum and minimum values of cross-component response difference (XZ-ZX), and initial stratum boundary is given;

[0123] 4) Initial stratum model for iterative inversion processing is given, including stratum boundary, well inclination and initial values of stratum horizontal resistivity and vertical resistivity;

[0124] 5) A Gauss-Newton iterative algorithm is used for full parameter inversion;

[0125] When fitting error of one component (preferably ZZ component) of the logging response reaches minimum, the iterative inversion ends, and stratum horizontal resistivity, vertical resistivity, stratum boundary and well inclination are obtained.

[0126] Specifically, the 3D induction instrument logging response comprises:

[0127] A stratum coordinate system, a wellbore coordinate system and an instrument coordinate system are constructed;

[0128] A magnetic field strength rotation transformation rule of the stratum coordinate system, the wellbore coordinate system and the instrument coordinate system is established:

[0129] First rule: the magnetic field strength in the wellbore coordinate system is calculated according to the magnetic field tensor in the stratum coordinate system and the wellbore inclination;

[0130] Second rule: the magnetic field strength in the instrument coordinate system is calculated according to the magnetic field tensor in the wellbore coordinate system and the instrument azimuth.​

[0131] The magnetic field intensity in the formation coordinate system excited by the transmitting coil is calculated by numerical simulation;

[0132] The magnetic field intensity in the borehole coordinate system is obtained based on the first rule transformation according to the electromagnetic field in the formation coordinate system;

[0133] The magnetic field intensity in the instrument coordinate system is obtained based on the second rule transformation according to the magnetic field intensity in the borehole coordinate system;

[0134] The three-dimensional induction logging response is calculated according to the magnetic field intensity in the instrument coordinate system and the coil-instrument coefficient.

[0135] Figure 3 A diagram showing the coil system structure of the three-dimensional induction logging instrument is shown. As shown in Figure 3 , the coil system structure of the three-dimensional induction logging instrument is composed of three transmitting coils T x , T y , T z , three receiving coils R x , R y , R z (parallel to the transmitting coils and with a source distance of L1), and three shielding coils B x , B y , B z (parallel to the receiving coils and with a source distance of L2). The shielding coils are introduced to cancel the direct coupling component generated by the transmitting coils in the receiving coils. The so-called direct coupling refers to the induced signal in the receiving coils due to the closing characteristic of the magnetic flux without passing through the formation. The winding direction of the shielding coils is opposite to that of the receiving coils, and the number of turns is different, so that the direct coupling electromotive force generated in the shielding coils and the receiving coils in the air cancels each other out.

[0136] When the transmitting coil system transmits sinusoidal alternating current to the surroundings, nine magnetic field components H ij (i=x, y, z; j=x, y, z) on the receiving coil system can be measured at the same time, where H xy represents the magnetic field intensity generated by the x-direction transmitting and y-direction receiving, and the other components are defined in the same way.

[0137] In order to investigate the three-dimensional induction logging response in the inclined well, three coordinate systems need to be introduced, i.e., the formation coordinate system O-X f Y f Z f , the borehole coordinate system O-X w Y w Z w and the instrument coordinate system O-X t Y t Z t (As shown inFigure 4 The magnetic field strength in the three coordinate systems satisfies the following rotation transformation rule:

[0138]

[0139] wherein:

[0140]

[0141] In the formula (1) and formula (2), α is a borehole inclination angle, defined as the included angle between the Z axis (Z f ) in the stratum coordinate system and the Z axis (Z w ) in the borehole coordinate system; is an instrument azimuth angle, defined as the included angle between the projection of the instrument in the XY plane and the X axis. After compensation, the magnetic field strength measured by the receiving coil system in the instrument coordinate system is which can be expressed by the following formula (3):

[0142]

[0143] In the formula, H ij1 represents the magnetic field generated by the receiving coil, and H ij2 represents the magnetic field generated by the shielding coil. In order to facilitate the comparison between the logging response and the stratum electrical parameter, the induction logging response is usually normalized to a measurement quantity of dimension of electrical conductivity as follows:

[0144]

[0145] wherein, is the imaginary part of the coil system magnetic field, K ij is the coil system instrument coefficient;

[0146]

[0147] First, the electromagnetic field in the stratum coordinate system excited by the three orthogonal transmitting coils is numerically simulated in the stratum coordinate system, the three-dimensional induction logging response in the borehole coordinate system is obtained through the coordinate rotation transformation related to the borehole inclination angle α, and the three-dimensional induction logging response in the instrument coordinate system is obtained through the coordinate rotation transformation related to the instrument azimuth angle φ. The actual logging data is always obtained in the instrument coordinate system, and in the data processing, the measured data is usually selected to obtain the logging response curve in the borehole coordinate system through the inverse transformation of the instrument azimuth angle and then processed.

[0148] Specifically, based on the initial inversion stratum model, the combination curve of each component of the logging response is taken as the objective function, and inversion is performed to obtain the stratum horizontal resistivity, the stratum vertical resistivity, the stratum boundary and the borehole inclination angle, including:

[0149] Based on the initial inversion stratum model, a combination curve of each component of the logging response is taken as a target function, and a Gauss-Newton iterative algorithm is used for full parameter inversion;

[0150] When the fitting error of one of the logging responses reaches the minimum, the iterative inversion ends, and the stratum horizontal resistivity, stratum vertical resistivity, stratum boundary and wellbore inclination are obtained.

[0151] The principle of the method for rapidly processing three-dimensional induction logging data of anisotropic TI stratum of a deviated well is as follows: after the logging response characteristics of the three-dimensional induction instrument are investigated and analyzed in detail, the combination curves of the three-dimensional induction logging response components which can eliminate the influence of the wellbore environment and the longitudinal adjacent layers on the logging response are constructed, and then the combination curves of the response components are used as the target function of the inversion program. For the long source distance probe of the instrument, the logging data thereof are affected by the wellbore environment much less than the short source distance probe of the instrument, and can better reflect the information of the original stratum, so the four response combination curves of the long source distance probe of the instrument are selected for one-dimensional inversion: σ zz ,(2σ zz -σ xx ), (σ zx +σ xz ), (σ zx -σ xz ).

[0152] The inversion model initial value is given: the stratum is divided according to the local maximum and minimum of the cross-component response difference (σ zx -σ xz ), the stratum boundary initial value is given, the well inclination angle is taken as the initial value of the wellbore inclination angle, the horizontal resistivity and the vertical resistivity initial values are given according to the intuitive interpretation result, and then the longitudinal one-dimensional inversion is started.

[0153] The improved Gauss-Newton iterative algorithm is used in the inversion process, and the algorithm is briefly introduced as follows:

[0154] The logging response data of the three-dimensional induction instrument are denoted as: q i (X) = q i (X1, X2,..., X N ), i = 1, 2,..., M; in the formula, M is the number of acquisition points; X is the parameter to be inverted; q i (X) is the nonlinear function of X; N is the number of variables, for example, for a five-layer model, N is the sum of five horizontal conductivities σ h , five vertical conductivities σ v , four stratum boundaries d and one wellbore inclination angle α, and there are 15 variables in total; X = X(σ h , σ v , d, α), σ h is the horizontal conductivity, σv vertical conductivity, d is the boundary of the formation, a is the hole angle;

[0155] Define the objective function:

[0156]

[0157] where q i (X t ) is the logging response value, X t is the parameter value to be inverted, for the convenience of writing, vector matrix can be introduced:

[0158]

[0159]

[0160] Solving the minimum value problem of the objective function F(X) is usually called nonlinear least square problem. Let X (k) be the result of the kth iteration, according to the Gauss-Newton optimization algorithm, the modification amount ΔX (k) of X is derived as follows:

[0161] ΔX (k) = -[J T (X (k) )J(X (k) )] -1 J T (X (k) )f(X (k) ); (9)

[0162] where J(X) is the Jacobi matrix of F(X):

[0163]

[0164] The next iteration point X (k+1) is:

[0165] X (k+1) = X (k) + ΔX (k) ; (11)

[0166] Since ΔX (k) is obtained by retaining only the first order term in the Taylor expansion of f i (X), only when X (k) is sufficiently close to the minimum point of the objective function can the iteration converge, which is sometimes difficult to guarantee, therefore the stability of the Gauss-Newton solution is poor, and the inversion iteration may fail, in order to overcome this shortcoming, we introduce the following form of N×N diagonal damping matrix B(β), the matrix element of B is:

[0167]

[0168] The damping matrix B(β) gradually approaches the unit matrix with the increase of the iteration number, and the next iteration point is:

[0169] X (k+1) = X (k) +B(β (k) )ΔX (k) ; (13)

[0170] Wherein, the parameter β takes the value example is 0.5~1.

[0171] For the inversion of three-dimensional induction logging data of one-dimensional layered TI formation without borehole and mud invasion, the embodiment deduces the analytical calculation formula of Jacobi matrix according to the forward numerical analytical solution, thereby greatly saving the calculation time of inversion.

[0172] The relative error of logging response and the relative error of formation parameters are introduced in the inversion process to monitor the convergence of the inversion program, and the two parameters are defined as follows:

[0173]

[0174] In the formula, n is the total number of logging curves; m is the number of measurement points of each logging curve; N is the total number of longitudinal layers contained in the formation model; di is the boundary position of the i-th layer; α is the borehole inclination; Ri is the horizontal resistivity of the i-th layer; Ri is the vertical resistivity of the i-th layer; q is the three-dimensional induction logging response in the instrument coordinate system; qk is the three-dimensional induction logging response in the instrument coordinate system of the k-th iteration; di k is the boundary position of the i-th layer of the k-th iteration; Ri k is the horizontal resistivity of the i-th layer of the k-th iteration; Ri k is the vertical resistivity of the i-th layer of the k-th iteration; α k is the borehole inclination of the k-th iteration. i hi vi ij k

[0175] The constraint condition of limiting the formation resistivity is added in the iterative inversion:

[0176] Considering the physical mechanism that thin sand-shale interbedding is equivalent to macroscopic anisotropic formation, the vertical resistivity of the formation is greater than or equal to the horizontal resistivity of the formation in the iterative inversion process… v ≥ R h ;

[0177] ​​​​​​​​​Anisotropy coefficient λ of anisotropic formation 2 = R v / R h Generally limited to 20, mainly because the three-dimensional induction logging instrument has low detection sensitivity to the vertical resistivity, it is difficult to accurately invert the vertical resistivity of the anisotropy coefficient greater than 20.

[0178] Above, the embodiment constructs the combination curve of the three-dimensional induction logging response component which can eliminate the influence of the wellbore environment and the longitudinal adjacent layer and other heterogeneities on the logging response, uses the response component combination curve as the inversion target function, reduces the three-dimensional induction wellbore correction module which is difficult and has large calculation amount. At the same time, the embodiment deduces the analytical calculation formula of the Jacobi matrix according to the forward numerical analytical solution, thereby greatly saving the calculation time of the inversion and improving the calculation accuracy. The damping matrix and the constraint condition are introduced in the inversion process to improve the stability of the inversion program. In summary, the embodiment can quickly process the three-dimensional induction logging data of the deviated well, greatly shortens the logging data processing time, improves the working efficiency of the logging instrument, and greatly reduces the cost of the instrument on the well test. The three-dimensional induction instrument logging data can be better applied to the field processing and interpretation and evaluation, and has great significance for the wide popularization of the field application of the three-dimensional induction instrument.

[0179] Since the method of the embodiment can accurately obtain the numerical values of the horizontal conductivity and the vertical conductivity of the formation in the anisotropic TI formation of the deviated well with high precision, the processing method can accurately determine the thin sand-shale interbedded layer and avoid missing this thin interbedded oil reservoir in logging by mistakenly considering it as a high water saturation layer, which has important significance in logging.

[0180] The present disclosure will be described in further detail below in conjunction with the accompanying drawings and embodiments, but the present disclosure is not limited to the following embodiments.

[0181] The following will take the anisotropic TI formation model of the deviated well as an example to illustrate and verify the method of quickly processing the anisotropic formation of the deviated well by using the three-dimensional induction logging data. In a typical anisotropic thin interbedded formation model, the wellbore inclination α = 60°, the wellbore radius is 0.10795 m (4.25 in), the mud resistivity R m = 0.5 Ω.m. The three-dimensional induction instrument has a transmission frequency f = 25 kHz, and the preferred instrument long source coil system: the main receiving coil source distance L1 = 63 in, the shielding coil source distance L2 = 49.5 in, wherein 1 in = 2.54 cm. The anisotropic TI formation model parameters of the deviated well are shown in Table 1:

[0182] Table 1

[0183]

[0184] Given the initial value of inversion, the borehole inclination α0=55°, the horizontal conductivity R h0 =1..5R h , the vertical conductivity R v0 =1.5R v , considering the actual measurement, the simulation logging response plus 3% random noise as the measured signal to carry out the inversion.

[0185] The change of inversion iteration error with iteration number n is shown in Figure 5 , Figure 5 The horizontal coordinate is n, and the vertical coordinate is Error(%). In the figure, S is defined as the relative error of logging response fitting (%) according to formula (14); Sp is defined as the relative error of formation parameter fitting (%) according to formula (15); S Rh is defined as the relative error of horizontal resistivity fitting (%) according to formula (15); SRV is defined as the relative error of vertical resistivity fitting (%) according to formula (15); Sh is defined as the relative error of longitudinal boundary fitting (%) according to formula (15). S alpha- is defined as the relative error of borehole inclination fitting (%) according to formula (15). It can be seen from Figure 5 that the stability and convergence speed of inversion iteration are very good. Even considering the noise, the relative error of logging response and the relative error of formation parameter quickly reach convergence within 10 steps. The results of formation horizontal resistivity and vertical resistivity obtained after iterative inversion are shown in Figure 6 , Figure 6 The horizontal coordinate is TVD (m), and the vertical coordinate is R f (Ω.m). The specific numerical results of the obtained formation boundary, borehole inclination, formation horizontal resistivity and vertical resistivity are shown in Table 2.

[0186] Table 2

[0187]

[0188] From Figure 6 and Table 2, it can be seen that the accuracy of the borehole inclination obtained when the inversion iteration converges is very high, the formation horizontal resistivity R h and the vertical resistivity R v The results of formation resistivity obtained in anisotropic formation are also in good agreement with the real horizontal resistivity and vertical resistivity curves, which shows that this fast processing method is feasible and satisfactory results are obtained.

[0189] In summary, according to the method of the present application, the three-dimensional induction logging response component combination curve which can eliminate the influence of the wellbore environment and the longitudinal adjacent layer heterogeneity on the logging response is constructed as the inversion objective function, and the three-dimensional induction wellbore correction module which is difficult to calculate and has a large amount of calculation is reduced. The present application can quickly process the three-dimensional induction logging data of the anisotropic formation of the deviated well, greatly shortens the logging data processing time, and improves the working efficiency of the logging instrument. The three-dimensional induction instrument logging data can be better applied to the field processing and interpretation and evaluation, and has great significance for the wide popularization of the field application of the three-dimensional induction instrument.

[0190] Since the method of the present application can obtain the values of the horizontal conductivity and the vertical conductivity of the formation in the anisotropic TI formation deviated well with high precision, the present processing method can accurately determine the thin sand-shale interbedded layer and avoid missing this thin interbedded oil reservoir due to the mistake of considering it as a high water saturation layer in logging, which has important significance in logging.

[0191] Figure 7 A block diagram of a three-dimensional induction logging data quick processing system of the present exemplary embodiment is shown in FIG. 1. Figure 7 As shown in FIG. 1, the exemplary embodiment of the present disclosure provides a three-dimensional induction logging data quick processing system, which comprises:

[0192] An acquisition unit 10 is configured to acquire the three-dimensional induction instrument logging response and the well inclination angle. The acquisition unit 10 comprises a three-dimensional induction instrument and a deviation instrument. The three-dimensional induction instrument logging response is acquired by the three-dimensional induction instrument, and the well inclination angle is acquired by the deviation instrument.

[0193] A construction unit 20 is configured to construct the combination curve of each component of the logging response.

[0194] A division unit 30 is configured to divide the formation according to the difference of the cross component response in the logging response, and give the initial value of the formation boundary.

[0195] An establishment unit 40 is configured to give the initial value of the formation horizontal resistivity and the initial value of the formation vertical resistivity, and establish an initial inversion formation model based on the initial value of the formation boundary and the well inclination angle.

[0196] An inversion unit 50 is configured to perform inversion to obtain the formation horizontal resistivity, the formation vertical resistivity, the formation boundary and the wellbore inclination angle based on the initial inversion formation model and taking the combination curve of each component of the logging response as the objective function.

[0197] Specifically, the acquisition unit comprises:

[0198] A construction module is configured to construct the formation coordinate system, the wellbore coordinate system and the instrument coordinate system.

[0199] The establishing module is configured to establish a magnetic field strength rotation transformation rule of a formation coordinate system, a borehole coordinate system and an instrument coordinate system:

[0200] The first rule is to calculate the magnetic field strength in the borehole coordinate system according to the magnetic field tensor in the formation coordinate system and the borehole inclination angle;

[0201] The second rule is to calculate the magnetic field strength in the instrument coordinate system according to the magnetic field tensor in the borehole coordinate system and the instrument azimuth angle;

[0202] The first calculation module is configured to calculate the magnetic field strength in the formation coordinate system excited by the transmitting coil through numerical simulation;

[0203] The first transformation module is configured to transform the magnetic field strength in the borehole coordinate system based on the first rule according to the electromagnetic field in the formation coordinate system;

[0204] The second transformation module is configured to transform the magnetic field strength in the instrument coordinate system based on the second rule according to the magnetic field strength in the borehole coordinate system;

[0205] The second calculation module is configured to calculate the three-dimensional induction instrument logging response according to the magnetic field strength in the instrument coordinate system and the coil-instrument coefficient.

[0206] Specifically, the inversion unit comprises:

[0207] The inversion module is configured to perform full-parameter inversion on the initial inversion formation model by taking the combined curve of each component of the logging response as the objective function and using the Gauss-Newton iteration algorithm;

[0208] The acquisition module is configured to obtain the formation horizontal resistivity, the formation vertical resistivity, the formation boundary and the borehole inclination angle when the fitting error of one of the logging responses reaches the minimum and the iterative inversion ends.

[0209] Specifically, the inversion unit is configured to:

[0210] Let the logging response data on the three-dimensional induction instrument be:

[0211] q i (X)=q i (X1,X2,...,X N ),i=1,2,...,M;

[0212] In the formula, M is the number of acquisition points; X is the parameter to be inverted; q i (X) is a nonlinear function of X; N is the number of variables; X=X(σ h ,σ v ,d,α), σ h is the horizontal conductivity, σ v is the vertical conductivity, d is the formation boundary, and α is the borehole inclination angle;

[0213] Define the objective function:

[0214]

[0215] where q i (X t ) is the log response value;

[0216] Introduce the vector matrix:

[0217]

[0218] Let X (k) be the result of the kth iteration, the modification of X ΔX (k) is derived according to the Gauss-Newton optimization algorithm:

[0219] ΔX (k) = -[J T (X (k) )J(X (k) )] -1 J T (X (k) )f(X (k) );

[0220] where J(X) is the Jacobian matrix of F(X):

[0221]

[0222] The next iteration point X (k+1) is:

[0223] X (k+1) = X (k) + ΔX (k) ;

[0224] Introduce an N x N dimensional diagonal damping matrix B(β), the matrix element of B is:

[0225]

[0226] The damping matrix B(β) gradually approaches the unit matrix with the increase of the iteration number, then the next iteration point is:

[0227] X (k+1) = X (k) + B(β (k) )ΔX (k) ;

[0228] Introduce the relative error of the log response and the relative error of the formation parameters to monitor the convergence of the inversion program:

[0229]

[0230] In the formula, n is the total number of logging curves; m is the number of measurement points for each logging curve; N is the total number of vertical layers contained in the formation model; d i The location of the i-th layer boundary; α is the wellbore dip angle; R hi R is the horizontal resistivity of the i-th stratum; vi Let q be the vertical resistivity of the i-th stratum; ij This refers to the three-dimensional induction logging response in the instrument coordinate system. The three-dimensional induction logging response in the instrument coordinate system during the k-th iteration; This represents the boundary position of the i-th layer in the k-th iteration; Let be the horizontal resistivity of the i-th layer in the k-th iteration; α is the vertical resistivity of the i-th layer in the k-th iteration; k Let the wellbore dip angle be the value of the k-th iteration.

[0231] Add constraints that limit formation resistivity during iterative inversion:

[0232] The vertical resistivity of the formation is greater than or equal to the horizontal resistivity of the formation, R v ≥R h ;

[0233] The anisotropy coefficient λ of anisotropic strata is limited to a set value. 2 =R v / R h .

[0234] Figure 8 This is a schematic diagram of the structure of a device according to an exemplary embodiment of this invention. Figure 8 As shown, corresponding to the above-described rapid processing method for three-dimensional induction logging data, this disclosure also provides a device. Since the embodiment of this device is similar to the above-described method embodiment, the description is relatively simple; relevant details can be found in the description of the above-described method embodiment section. The device described below is merely illustrative. The device may include: a processor 1, a memory 2, a communication bus (i.e., the aforementioned device bus), and a lookup engine. The processor 1 and memory 2 communicate with each other via the communication bus and communicate with external systems via a communication interface. The processor 1 can call logical instructions in the memory 2 to execute the rapid processing method for three-dimensional induction logging data.

[0235] In addition, the logic instructions in the memory 2 described above can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present disclosure essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present disclosure. The aforementioned storage medium includes: a storage chip, a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0236] In another aspect, the embodiments of the present disclosure also provide a processor readable storage medium, and the processor readable storage medium stores a computer program 3. When the computer program 3 is executed by the processor 1, the three-dimensional induction logging data fast processing method provided by the above-mentioned embodiments is implemented.

[0237] The processor readable storage medium can be any available medium or data storage device that the processor 1 can access, including but not limited to a magnetic storage (such as a floppy disk, a hard disk, a magnetic tape, a magneto-optical disk (MO), etc.), an optical storage (such as a CD, a DVD, a BD, a HVD, etc.), and a semiconductor storage (such as a ROM, an EPROM, an EEPROM, a non-volatile memory (NAND FLASH), a solid state disk (SSD)), etc.

[0238] The above is only the preferred embodiment of the present disclosure, and the protection scope of the present disclosure is not limited to the above-mentioned embodiments. Any technical solution that belongs to the technical solutions of the present disclosure should be considered as the protection scope of the present disclosure. It should be noted that for ordinary skilled in the art, some improvements and refinements without departing from the principles of the present disclosure should be considered as the protection scope of the present disclosure.

Claims

1. A method for fast processing of three-dimensional induction logging data, characterized in that, The method comprises the following steps: obtaining the logging response of a three-dimensional induction instrument and the inclination angle of a well; constructing a combined curve of each component of the logging response; dividing a formation according to the difference between the responses of cross components in the logging response, and giving an initial value of the formation boundary; giving an initial value of the horizontal resistivity of the formation and an initial value of the vertical resistivity of the formation, and establishing an initial inversion formation model based on the initial value of the formation boundary and the inclination angle of the well; based on the initial inversion formation model, taking the combined curve of each component of the logging response as an objective function, and performing inversion to obtain the horizontal resistivity of the formation, the vertical resistivity of the formation, the formation boundary and the inclination angle of the wellbore.

2. The method of claim 1, wherein, The method for obtaining the logging response of a three-dimensional induction instrument comprises the following steps: constructing a formation coordinate system, a wellbore coordinate system and an instrument coordinate system; establishing a rotation transformation rule of magnetic field intensity of the formation coordinate system, the wellbore coordinate system and the instrument coordinate system; a first rule: calculating the magnetic field intensity in the wellbore coordinate system according to the magnetic field tensor in the formation coordinate system and the inclination angle of the wellbore; a second rule: calculating the magnetic field intensity in the instrument coordinate system according to the magnetic field tensor in the wellbore coordinate system and the instrument azimuth angle; calculating the magnetic field intensity in the formation coordinate system excited by a transmitting coil through numerical simulation; transforming the magnetic field intensity in the formation coordinate system to the magnetic field intensity in the wellbore coordinate system based on the first rule according to the electromagnetic field in the formation coordinate system; transforming the magnetic field intensity in the wellbore coordinate system to the magnetic field intensity in the instrument coordinate system based on the second rule according to the magnetic field intensity in the wellbore coordinate system; calculating the logging response of the three-dimensional induction instrument according to the magnetic field intensity in the instrument coordinate system and the instrument coefficient of the coil system.

3. The method of claim 1, wherein, The method for obtaining the horizontal resistivity of the formation, the vertical resistivity of the formation, the formation boundary and the inclination angle of the wellbore based on the initial inversion formation model and taking the combined curve of each component of the logging response as an objective function comprises the following steps: based on the initial inversion formation model, taking the combined curve of each component of the logging response as an objective function, and performing full-parameter inversion by using a Gauss-Newton iterative algorithm; when the fitting error of one of the components in the logging response reaches a minimum, the iterative inversion is ended, and the horizontal resistivity of the formation, the vertical resistivity of the formation, the formation boundary and the inclination angle of the wellbore are obtained.

4. The method of claim 1, wherein, The method for obtaining the horizontal resistivity of the formation, the vertical resistivity of the formation, the formation boundary and the inclination angle of the wellbore based on the initial inversion formation model and taking the combined curve of each component of the logging response as an objective function comprises the following steps: denote the logging response data on the three-dimensional induction instrument as: q i (X) = q i (X1, X2,..., X N ), i = 1, 2,..., M; where M is the number of acquisition points; X is the parameter to be inverted; q i (X) is a nonlinear function of X; N is the number of variables; X = X(σ h ,σ v ,d,α), σ h is the horizontal conductivity, σ v is the vertical conductivity, d is the boundary of the formation, and α is the wellbore inclination; define an objective function as: where q i (X t ) is the log response value; introduce a vector matrix as: Let X (k) As a result of the kth iteration, the modification of X, ΔX, is derived from the Gauss-Newton optimization algorithm (k) : ΔX (k) = -[J T (X (k) )J(X (k) )] -1 J T (X (k) )f(X (k) ); wherein J(X) is the Jacobian matrix of F(X): Next iteration point X (k+1) is: X (k+1) = X (k) + ΔX (k) ; introduce an N×N diagonal damping matrix B(β), and the matrix element of B is: the damping matrix B(β) gradually approaches a unit matrix with the increase of the number of iterations, and the next iteration point is: X (k+1) = X (k) + B(β (k) )ΔX (k) ; introducing relative errors in the well logging responses during inversion relative errors in the formation parameters to monitor the convergence of the inversion procedure: where n is the total number of well logging curves; m is the number of measurement points of each well logging curve; N is the total number of vertical layers contained in the formation model; d i is the boundary position of the i-th layer; a is the borehole inclination angle; R hi is the horizontal resistivity of the i-th layer formation; R vi is the vertical resistivity of the i-th layer formation; q ij is the three-dimensional induction logging response in the instrument coordinate system; is the three-dimensional induction logging response in the instrument coordinate system of the k-th iteration; is the boundary position of the i-th layer of the k-th iteration; is the horizontal resistivity of the i-th layer formation of the k-th iteration; is the vertical resistivity of the i-th layer formation of the k-th iteration; a k is the borehole inclination angle of the k-th iteration; add a constraint condition of limiting the resistivity of the formation during the iterative inversion: R v ≥R h ; The anisotropy coefficient λ of the anisotropic layer is limited within a set value, λ 2 = R v / R h .

5. A system for rapid processing of three-dimensional induction logging data, characterized by The method comprises the following steps: a obtaining unit, configured to obtain the logging response of a three-dimensional induction instrument and the inclination angle of a well; a constructing unit, configured to construct a combined curve of each component of the logging response; a dividing unit, configured to divide a formation according to the difference between the responses of cross components in the logging response, and give an initial value of the formation boundary; an establishing unit, configured to give an initial value of the horizontal resistivity of the formation and an initial value of the vertical resistivity of the formation, and establish an initial inversion formation model based on the initial value of the formation boundary and the inclination angle of the well. The inversion unit is configured to perform inversion to obtain formation horizontal resistivity, formation vertical resistivity, formation boundary and wellbore inclination based on the initial inversion formation model and taking a combination curve of each component of the logging response as an objective function.

6. The system for rapid processing of three-dimensional induction logging data of claim 5, wherein, The acquisition unit comprises: The construction module is configured to construct a formation coordinate system, a wellbore coordinate system and an instrument coordinate system; The establishment module is configured to establish a magnetic field strength rotation transformation rule of the formation coordinate system, the wellbore coordinate system and the instrument coordinate system: The first rule: calculating the magnetic field strength in the wellbore coordinate system according to the magnetic field tensor in the formation coordinate system and the wellbore inclination; The second rule: calculating the magnetic field strength in the instrument coordinate system according to the magnetic field tensor in the wellbore coordinate system and the instrument azimuth angle; The first calculation module is configured to calculate the magnetic field strength in the formation coordinate system excited by the transmitting coil through numerical simulation; The first transformation module is configured to transform the magnetic field strength in the wellbore coordinate system based on the first rule according to the electromagnetic field in the formation coordinate system; The second transformation module is configured to transform the magnetic field strength in the instrument coordinate system based on the second rule according to the magnetic field strength in the wellbore coordinate system; The second calculation module is configured to calculate the three-dimensional induction instrument logging response according to the magnetic field strength in the instrument coordinate system and the coil system-instrument coefficient.

7. The system for rapid processing of three-dimensional induction logging data of claim 5, wherein, The inversion unit comprises: The inversion module is configured to perform full-parameter inversion by using a Gauss-Newton iterative algorithm based on the initial inversion formation model and taking a combination curve of each component of the logging response as an objective function; The acquisition module is configured to obtain formation horizontal resistivity, formation vertical resistivity, formation boundary and wellbore inclination when fitting error of one of the logging responses reaches a minimum and iterative inversion ends.

8. The system for rapid processing of three-dimensional induction logging data of claim 5, wherein, The inversion unit is configured to: Let the logging response data on the three-dimensional induction instrument be: q i (X) = q i (X1, X2,..., X N ), i = 1, 2,..., M; where M is the number of acquisition points; X is the parameter to be inverted; q i (X) is a nonlinear function of X; N is the number of variables; X = X(σ h ,σ v ,d,α), σ h is the horizontal conductivity, σ v is the vertical conductivity, d is the formation boundary, and α is the borehole inclination; Define an objective function: where q i (X t ) is the log response value; Introduce a vector matrix: Let X (k) As a result of the kth iteration, the modification of X, ΔX, is derived from the Gauss-Newton optimization algorithm (k) : ΔX (k) = -[J T (X (k) )J(X (k) )] -1 J T (X (k) )f(X (k) ) In the formula, J(X) is a Jacobian matrix of F(X): Next iteration point X (k+1) is: X (k+1) = X (k) + ΔX (k) ; Introduce an N×N diagonal damping matrix B(β), and the matrix element of B is: The damping matrix B(β) gradually approaches a unit matrix with the increase of the number of iterations, and the next iteration point is: X (k+1) = X (k) + B(β (k) )ΔX (k) ; introducing relative errors in the well logging responses during inversion relative errors in the formation parameters to monitor the convergence of the inversion procedure: where n is the total number of well logging curves; m is the number of measurement points of each well logging curve; N is the total number of vertical layers contained in the formation model; d i is the boundary position of the i-th layer; a is the borehole inclination angle; R hi is the horizontal resistivity of the i-th layer formation; R vi is the vertical resistivity of the i-th layer formation; q ij is the three-dimensional induction logging response in the instrument coordinate system; is the three-dimensional induction logging response in the instrument coordinate system of the k-th iteration; is the boundary position of the i-th layer of the k-th iteration; is the horizontal resistivity of the i-th layer formation of the k-th iteration; is the vertical resistivity of the i-th layer formation of the k-th iteration; a k is the borehole inclination angle of the k-th iteration; Add a constraint condition of limiting formation resistivity during iterative inversion: R v ≥R h ; The anisotropy coefficient λ of the anisotropic layer is limited within a set value, λ 2 = R v / R h .

9. An apparatus, comprising: Comprise: A processor and a memory; The memory is configured to store a computer program, and the processor is configured to call the computer program stored in the memory to execute the three-dimensional induction logging data fast processing method in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and when the computer program is executed by the processor, the processor can execute the three-dimensional induction logging data fast processing method in any one of claims 1 to 4.

Images