CN115773101A - Array induction borehole correction method, device, storage medium and processor - Google Patents

Abstract

The invention discloses an array induction borehole correction method, device, storage medium and processor. The method includes: obtaining the measurement signal obtained by the measurement of each sub-array of the array induction logging tool; determining the borehole environment parameters corresponding to the borehole environment of the target formation, and using the multi-dimensional space interpolation method to obtain the borehole geometric factor library according to the borehole environment parameters Obtain the target wellbore geometry factor of the wellbore environment; establish the tomographic matrix equation based on the radial formation model and measurement signals, and solve the tomographic matrix equation to obtain the radial conductivity distribution of the target formation; according to the radial formation model and the radial The measured value expression is determined by the conductivity distribution, and the borehole correction formula is determined by using the target borehole geometric factor corresponding to the borehole environment; based on the measured value expression and the borehole correction formula, the corrected measured value of the target formation is determined, and the wellbore is completed. eye correction. The invention solves the technical problem of borehole correction error caused by ignoring mud invasion in the existing borehole correction method.

Description

Array induction borehole correction method, device, storage medium and processor

technical field

The invention relates to the technical field of well logging data processing, in particular to an array induction wellbore correction method, device, storage medium and processor.

Background technique

The measurement signals of each sub-array of the array induction logging tool are greatly affected by the borehole environment. If this part of the influence cannot be corrected correctly, the borehole correction residual will be propagated or even amplified during subsequent data processing such as soft focusing. As a result, the reliability of the final measurement curve is reduced.

The existing array induction wellbore correction is often ineffective, and field engineers or processing personnel often need to repeatedly adjust the control parameters of borehole correction for processing in order to obtain a satisfactory final logging curve, but the obtained measurement results are not good. When there is invasion, the invasion response is regarded as the influence of the borehole and is “corrected”. After the borehole is corrected, the curve difference becomes smaller, which reduces the ability of the curve to analyze the invasion radially, and also affects the calculation of the true formation resistivity.

In view of the above problems, the present invention proposes an effective solution.

Contents of the invention

Embodiments of the present invention provide an array induction wellbore correction method, device, storage medium and processor to at least solve the technical problem of wellbore correction errors caused by ignoring mud invasion in existing wellbore correction methods.

According to an aspect of an embodiment of the present invention, a method for calibrating an array induction wellbore is provided, including: acquiring measurement signals measured by each sub-array of an array induction logging tool, wherein the measurement signals at least include: a set of conductivity curves; Determine the wellbore environment parameters corresponding to the wellbore environment of the target formation, and use the multidimensional space interpolation method to obtain the target wellbore geometric factors of the above-mentioned wellbore environment from the wellbore geometric factor library according to the above-mentioned wellbore environment parameters, wherein the above-mentioned wellbore environment Parameters include: borehole cal, mud conductivity σ _m , formation conductivity σ _t and eccentricity ecc, the above-mentioned wellbore geometric factor database is a pre-established wellbore geometric factor database, and the above-mentioned wellbore geometric factor is the above-mentioned wellbore environmental parameters function; based on the radial stratigraphic model and the above-mentioned measurement signals, the tomographic matrix equation is established, and the above-mentioned tomographic matrix equation is solved to obtain the radial conductivity distribution of the above-mentioned target formation, wherein the above-mentioned radial formation model is used to characterize the above-mentioned target The conductivity change of the formation; determine the measurement value expression according to the above-mentioned radial formation model and the above-mentioned radial conductivity distribution, and use the above-mentioned target wellbore geometry factor corresponding to the above-mentioned wellbore environment to determine the wellbore correction formula; based on the above-mentioned measurement value expression and the above-mentioned wellbore correction formula to determine the corrected measured value of the above-mentioned target formation, and complete the wellbore correction.

Optionally, before the multi-dimensional space interpolation method is used to obtain the target wellbore geometric factor of the above-mentioned wellbore environment from the wellbore geometric factor library according to the above-mentioned wellbore environment parameters, the above method also includes: determining the variation range of the above-mentioned well diameter, and Determine the preset number of discrete points of the borehole diameter based on the variation range of the above-mentioned well diameter to form a set of discrete points in the first dimension; determine the variation range of the above-mentioned mud conductivity, and determine the prediction of the mud conductivity based on the variation range of the above-mentioned mud conductivity Set a number of discrete points to form a set of discrete points in the second dimension; determine the variation range of the above-mentioned formation conductivity, and determine the preset number of discrete points of the formation conductivity based on the variation range of the formation conductivity to form the third dimension discrete points set; determine the variation range of the above-mentioned eccentricity, and determine the preset number of discrete points of the eccentricity based on the variation range of the above-mentioned eccentricity, and form a fourth dimension discrete point set; for the above-mentioned first dimension discrete point set, the above-mentioned second dimension The discrete point set, the above-mentioned third-dimensional discrete point set and the above-mentioned fourth-dimensional discrete point set are combined to calculate the wellbore geometric factors of the above-mentioned sub-arrays, and store all the well-bore geometric factors of the above-mentioned sub-arrays according to the preset storage rules , to construct the above-mentioned wellbore geometry factor library.

Optionally, the above-mentioned wellbore environment parameters corresponding to the wellbore environment of the target formation are determined, and the target wellbore geometric factors of the above-mentioned wellbore environment are obtained from the wellbore geometric factor library according to the above-mentioned wellbore environment parameters by using multi-dimensional space interpolation method, including : Determine the value of the wellbore environment parameter corresponding to the above-mentioned wellbore environment of the above-mentioned target formation; according to the value of the above-mentioned wellbore environment parameter, obtain the closest target discrete point from the above-mentioned wellbore geometric factor library; adopt the above-mentioned multi-dimensional space interpolation method Based on the first dimension discrete point set, the second dimension discrete point set, the third dimension discrete point set and the fourth dimension discrete point set, the target wellbore geometry factor is determined.

Optionally, based on the radial formation model and the above-mentioned measurement signals, the tomographic matrix equation is established, and the above-mentioned tomographic matrix equation is solved, and before the radial conductivity distribution of the above-mentioned target formation is obtained, the above-mentioned method also includes: Divide the above-mentioned target strata into multiple layers, wherein the wellbore is the innermost layer, and the formations other than the above-mentioned wellbore are the invasion and flushing zone, the invasion transition zone and the original formation; the above-mentioned wellbore, the above-mentioned invasion and flushing zone, the above-mentioned invasion transition The aforementioned radial stratigraphic model was constructed using the zone and the aforementioned undisturbed strata.

Optionally, based on the radial formation model and the above-mentioned measurement signals, establish a tomographic matrix equation, and solve the above-mentioned tomographic matrix equation to obtain the radial conductivity distribution of the above-mentioned target formation, including: determining the borehole geometry of each of the above-mentioned sub-arrays factor and the radial geometric factors of the above-mentioned sub-arrays; based on the above-mentioned radial stratigraphic model and the above-mentioned measurement signals, the above-mentioned borehole geometric factors and the above-mentioned radial geometric factors, the above-mentioned tomographic matrix equation is established, wherein the above-mentioned tomographic matrix equation The left item is the above-mentioned measurement signal of each of the above-mentioned sub-arrays, the unknown quantity of the above-mentioned tomographic matrix equation is the conductivity difference between radially adjacent layers, and the coefficient array of the above-mentioned tomographic matrix equation is determined by the above-mentioned wellbore of each of the above-mentioned sub-arrays. Geometric factors, the above-mentioned radial geometric factors and constants, the constraints of the above-mentioned tomographic matrix equations are determined according to the above-mentioned wellbore environment parameters; the above-mentioned tomographic matrix equations are solved to obtain the above-mentioned radial conductivity distribution of the above-mentioned target formation.

Optionally, based on the above-mentioned measured value expression and the above-mentioned wellbore correction formula, the above-mentioned corrected measured value of the above-mentioned target formation is determined, and the completion of the wellbore correction includes: using the above-mentioned measured value expression and the above-mentioned wellbore correction formula to process the above-mentioned The signal is measured to determine the conductivity of the target formation and the conductivity of the target wellbore mud of the above-mentioned target formation; using the conductivity of the above-mentioned target formation and the conductivity of the target wellbore mud to perform borehole correction on the target measurement value.

According to another aspect of the embodiment of the present invention, there is also provided an array induction borehole correction device, which is characterized in that it includes: an acquisition module, configured to acquire the measurement signals measured by each sub-array of the array induction logging tool, wherein, The above-mentioned measurement signals at least include: a group of conductivity curves; a first determination module, which determines the borehole environment parameters corresponding to the borehole environment of the target formation, and obtains the above-mentioned parameters from the borehole geometric factor library according to the above-mentioned borehole environment parameters by using a multi-dimensional space interpolation method. The target wellbore geometric factors of the wellbore environment, wherein the above-mentioned wellbore environment parameters include: borehole cal, mud conductivity σ _m , formation conductivity σ _t and eccentricity ecc, and the above-mentioned wellbore geometric factor library is a pre-established well Borehole geometric factor database, the above-mentioned wellbore geometric factor is a function of the above-mentioned wellbore environmental parameters; the processing module is used to establish the tomographic matrix equation based on the radial formation model and the above-mentioned measurement signal, and solve the above-mentioned tomographic matrix equation to obtain the above-mentioned The radial conductivity distribution of the target formation, wherein the above-mentioned radial formation model is used to characterize the change in conductivity of the above-mentioned target formation; the second determination module is used to determine the measurement value according to the above-mentioned radial formation model and the above-mentioned radial conductivity distribution expression, and using the above-mentioned target wellbore geometry factor corresponding to the above-mentioned wellbore environment to determine the wellbore correction formula; the correction module is used to determine the corrected above-mentioned target formation based on the above-mentioned measured value expression and the above-mentioned wellbore correction formula Measured values to complete borehole calibration.

According to another aspect of the embodiments of the present invention, a non-volatile storage medium is also provided. The above-mentioned non-volatile storage medium stores a plurality of instructions, and the above-mentioned instructions are suitable for being loaded by a processor and executing any one of the above-mentioned Array induction borehole correction method.

According to another aspect of the embodiments of the present invention, there is also provided a processor, the above-mentioned processor is used to run a program, wherein the above-mentioned program is configured to execute any one of the above-mentioned array induction wellbore calibration methods when running.

According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute any one of the above-mentioned arrays Induction borehole correction method.

In the embodiment of the present invention, the measurement signal obtained by the array induction logging instrument is obtained, wherein the above-mentioned measurement signal at least includes: a resistivity curve group; determining the wellbore environment parameters, and establishing the wellbore geometry factor based on the above-mentioned wellbore environment parameters library, and determine the target wellbore geometric factor of the target formation based on the above-mentioned wellbore geometric factor library; use the radial formation model to process the above-mentioned measurement signal, determine the expression of the measurement value, and use the radial formation model to process the above-mentioned measurement signal and the above-mentioned target well The borehole geometric factor is used to determine the borehole correction formula; based on the above-mentioned measured value expression and the above-mentioned borehole correction formula, the corrected measured value of the above-mentioned target formation is determined, and the borehole correction is completed, achieving the construction of a new self-adaptive borehole environment The purpose of the parameter solution algorithm is to achieve the technical effect of accurately obtaining the true conductivity of the formation, and then solve the technical problem of borehole correction errors caused by the neglect of mud invasion in the existing borehole correction methods.

Description of drawings

The accompanying drawings described here are used to provide a further understanding of the present invention and constitute a part of the application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations to the present invention. In the attached picture:

Fig. 1 is a flowchart of an array induction wellbore correction method according to an embodiment of the present invention;

Fig. 2 is a schematic structural diagram of an optional array induction logging tool probe according to an embodiment of the present invention;

Fig. 3 is a kind of optional typical array induction logging tool logging curve diagram according to the embodiment of the present invention;

Fig. 4 is a schematic diagram of an optional array induction tool logging according to an embodiment of the present invention;

Fig. 5 is a schematic diagram of an optional array induction wellbore geometry factor curve according to an embodiment of the present invention;

Fig. 6 is a schematic diagram of an optional radial two-layer model according to an embodiment of the present invention;

Fig. 7 is a schematic diagram of an optional radial three-layer model according to an embodiment of the present invention;

Fig. 8 is a schematic diagram of apparent conductivity after model correction when σ _m >σ _xo >σ _t according to an embodiment of the present invention;

Fig. 9 is a schematic diagram of apparent conductivity after model correction when σ _t >σ _xo ≥ σ _m according to an embodiment of the present invention;

Fig. 10 is a schematic diagram of apparent conductivity after model correction when σ _t >σ _m >σ _xo according to an embodiment of the present invention;

Fig. 11 is a schematic diagram of apparent conductivity after model correction when σ _m ≥ σ _t > σ _xo according to an embodiment of the present invention;

Fig. 12 is a schematic diagram of an optional intrusion transition path according to an embodiment of the present invention;

Fig. 13 is a schematic diagram of a radial cross-sectional view of electrical conductivity represented by an optional wellbore calibration before/after array induction curves according to an embodiment of the present invention;

Fig. 14 is a schematic structural diagram of a wellbore correction device according to an embodiment of the present invention.

Detailed ways

In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such that the embodiments of the invention described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having", as well as any variations thereof, are intended to cover a non-exclusive inclusion, for example, a process, method, system, product or device comprising a sequence of steps or elements is not necessarily limited to the expressly listed instead, may include other steps or elements not explicitly listed or inherent to the process, method, product or apparatus.

Example 1

According to an embodiment of the present invention, an embodiment of an array induction wellbore calibration method is provided. It should be noted that the steps shown in the flow chart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, Also, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

In the prior art, there are two defects in the array induction borehole calibration method: (1) The establishment of the borehole calibration model is composed of a borehole plus an infinite uniform formation, which is inconsistent with the actual formation and inconsistent with the original intention of the array induction design; (2) ) in adaptive wellbore calibration, the "intrinsic correlation" between the measured values of the array induction sub-array is poor, which is only a qualitative concept, and no quantitative description has been established.

In view of the theoretical defects and application pain points of the existing array induction borehole correction method, the concept of tomography can be applied to introduce multiple step functions to approximate any radial one-dimensional formation, and then approximated by the approximate method (Born) to deduce the internal The mathematical expression of the correlation relationship is applied to the wellbore environmental parameters for adaptive solution. Reconstructing the wellbore correction formula based on the invasion model avoids the phenomenon of “correcting” the invasion effect as the wellbore effect, maintains the curve difference after the wellbore correction, and improves the ability to analyze the invasion in the radial direction of the curve.

Fig. 1 is a flowchart of an array induction wellbore correction method according to an embodiment of the present invention. As shown in Fig. 1, the method includes the following steps:

Step S102, acquiring the measurement signals measured by each sub-array of the array induction logging tool, wherein the above-mentioned measurement signals at least include: a set of conductivity curves;

Step S104, determine the wellbore environment parameters corresponding to the wellbore environment of the target formation, and use the multi-dimensional space interpolation method to obtain the target wellbore geometric factors of the above-mentioned wellbore environment from the wellbore geometric factor library according to the above-mentioned wellbore environment parameters, wherein, the above-mentioned Wellbore environmental parameters include: borehole cal, mud conductivity σ _m , formation conductivity σ _t and eccentricity ecc. The above-mentioned wellbore geometric factor database is a pre-established wellbore geometric factor database. A function of eye environment parameters;

Step S106, based on the radial formation model and the above-mentioned measurement signals, establish a tomographic matrix equation, and solve the above-mentioned tomographic matrix equation to obtain the radial conductivity distribution of the above-mentioned target formation, wherein the above-mentioned radial formation model is used to characterize the above-mentioned target Changes in the conductivity of the formation;

Step S108, determining the measured value expression according to the above-mentioned radial formation model and the above-mentioned radial conductivity distribution, and using the above-mentioned target wellbore geometry factor corresponding to the above-mentioned wellbore environment to determine a wellbore correction formula;

Step S110, based on the above-mentioned measured value expression and the above-mentioned borehole correction formula, determine the corrected measured value of the above-mentioned target formation, and complete the borehole correction.

In the embodiment of the present invention, the array induction borehole correction method from the above step S102 to step S110 is executed by the array induction borehole correction system, and the measurement signal obtained by the measurement of each sub-array of the array induction logging tool is obtained by using the above system, wherein , the above-mentioned measurement signal at least includes: conductivity curve group; determine the borehole environment parameters corresponding to the borehole environment of the target formation, and use the multi-dimensional space interpolation method to obtain the above-mentioned borehole environment from the borehole geometric factor library according to the above-mentioned borehole environment parameters Target wellbore geometric factors, wherein the above-mentioned wellbore environmental parameters include: borehole cal, mud conductivity σ _m , formation conductivity σ _t and eccentricity ecc, and the above-mentioned wellbore geometric factor database is a pre-established wellbore geometric factor database , the above-mentioned wellbore geometry factor is a function of the above-mentioned wellbore environmental parameters; based on the radial formation model and the above-mentioned measurement signals, the tomographic matrix equation is established, and the above-mentioned tomographic matrix equation is solved to obtain the radial conductivity distribution of the above-mentioned target formation, Wherein, the above-mentioned radial formation model is used to characterize the conductivity change of the above-mentioned target formation; the measurement value expression is determined according to the above-mentioned radial formation model and the above-mentioned radial conductivity distribution, and the above-mentioned target wellbore geometry corresponding to the above-mentioned wellbore environment is adopted factor to determine the borehole correction formula; based on the above-mentioned measured value expression and the above-mentioned borehole correction formula, determine the corrected measured value of the above-mentioned target formation, and complete the borehole correction.

It should be noted that the array induction logging tool includes a plurality of sub-measurement arrays, and its functional feature is to obtain a curve group of multi-radial detection depths used to describe the invasion profile. The obtained curve set may include, but not limited to: a conductivity curve set, a resistivity curve set, and the like. As shown in FIG. 2 , the schematic diagram of the probe structure of the array induction logging tool, the probe consists of multiple (5 or 6 or 7 or more) sub-arrays (for example: A1 to A6 in the figure). Each sub-array consists of a transmitting coil and a set of receiving coils connected in series (at least 2 coils, a main receiving coil and a shielding receiving coil). A transmit coil is shared between the subarrays.

As an optional embodiment, the final measurement signal is obtained by performing a series of signal processing on the raw measurement data of multiple sub-arrays of the array induction logging tool; the above series of signal processing includes: scale processing, temperature effect correction , skin effect correction, borehole correction, software focusing, resolution matching and radial inversion processing, etc.

As an optional embodiment, after acquiring the measurement signals measured by the array induction logging tool, certain preprocessing may be performed on the obtained measurement signals, for example, missing data processing, error data processing, and the like. As shown in Fig. 3, the log curve of a typical array induction logging tool, the original measurement signal of the array induction logging tool undergoes data processing steps such as preprocessing, skin effect correction, borehole correction and software focusing, and various longitudinal Set of resistivity curves with resolution (1ft, 2ft, 4ft or 0.5ft) and multiple radial depths of detection (10in, 20in, 30in, 60in, 90in and/or 120in).

In an optional embodiment, before adopting the multi-dimensional space interpolation method to obtain the target wellbore geometric factor of the above-mentioned wellbore environment from the wellbore geometric factor library according to the above-mentioned wellbore environment parameters, the above-mentioned method further includes: determining the above-mentioned wellbore diameter, and based on the range of variation of the above-mentioned well diameter, determine the preset number of discrete points of the well diameter to form a set of discrete points in the first dimension; determine the range of variation of the above-mentioned mud conductivity, and Determining a preset number of discrete points of mud conductivity to form a set of discrete points in the second dimension; determining the variation range of the above-mentioned formation conductivity, and determining a preset number of discrete points of the formation conductivity based on the above-mentioned variation range of the formation conductivity, Forming a set of discrete points in the third dimension; determining the variation range of the above-mentioned eccentricity, and determining a preset number of discrete points of the eccentricity based on the variation range of the above-mentioned eccentricity, forming a set of discrete points in the fourth dimension; set, the above-mentioned second-dimensional discrete point set, the above-mentioned third-dimensional discrete point set, and the above-mentioned fourth-dimensional discrete point set are combined and calculated to obtain the wellbore geometry factors of the above-mentioned sub-arrays, and store all the above-mentioned sub-arrays according to the preset storage rules. The wellbore geometry factors of the array are constructed into the above-mentioned wellbore geometry factor library.

In the embodiment of the present invention, the value of the borehole geometry factor of a certain sub-array of the array sensing instrument is determined by the values of the above four borehole environment parameters. In order to conveniently obtain geometric factor values of each sub-array of the array induction corresponding to a specific borehole environment, a wellbore geometric factor library can be established in advance.

当仪器居中时，相对偏心为0；当仪器完全贴井壁时，相对偏心为1。It should be noted that, in the schematic diagram of array induction tool logging shown in Fig. 4, σ _t is the formation conductivity (its reciprocal is the formation resistivity R _t ), σ _m is the conductivity of the borehole mud (the reciprocal is the mud resistivity R _m ), cal is the diameter of the well, d _tool is the diameter of the tool, and x is the distance between the tool and the well wall. For convenience, the relative eccentricity ecc of the instrument is introduced:

When the tool is centered, the relative eccentricity is 0; when the tool is completely attached to the well wall, the relative eccentricity is 1.

In the embodiment of the present invention, according to the principle of induction logging, the influence of the array induction wellbore is controlled by four environmental parameters, namely: borehole cal, mud conductivity σ _m (or its reciprocal, mud resistivity R _m ), instrument Eccentricity ecc in the borehole, and formation conductivity σ _t (or its inverse, formation resistivity R _t ). The above four environmental parameters are determined as the above-mentioned wellbore environmental parameters.

As an optional embodiment, determine the change range of the above four wellbore environmental parameter values, determine the number of discrete points based on the change range, and form four discrete point sets, combine the discrete point sets, and then combine all combinations Perform calculations to obtain the borehole geometric factors of each sub-array, store the borehole geometric factors of all sub-arrays corresponding to all combinations in a certain way, and construct the above-mentioned borehole geometric factor library. For example, set a discrete point at intervals of 0.5 inches from 4 inches to 32 inches, and obtain 57 discrete points in total; set a discrete point at intervals of 0.05 from 0 to 0.95, and obtain 20 discrete points in total; Select 25 discrete points for conductivity from 0.0001S/m to 1000S/m; select 20 discrete points for formation conductivity from 0.0001S/m to 100S/m; there are 57x20x25x20 discrete points in the above four dimensions Discrete points, for an array sensing tool with 7 sub-arrays, there are 57x20x25x20x7 borehole geometry factor values in the borehole geometry factor library.

Optionally, for the convenience and quickness of borehole calibration, the borehole geometric factors will be calculated in advance according to the probe coil system structure of the array induction tool and other relevant structural parameters: in the four borehole environmental parameters (ecc, cal, σ _m , σ _t ), the geometric factors of each sub-array are calculated and stored for all discrete combination points to form a wellbore geometric factor library. The schematic diagram of array induction wellbore geometry factor curve shown in Fig. 5 corresponds to Rt=100Ohmm, Rm=0.1Ohmm, and eccentricity Ecc is equal to 0.0, 0.5, 0.75, 0.85, 0.90 and 0.95 respectively. It can be concluded from the figure that: (1) the borehole geometry factors of the three shorter sub-arrays are more sensitive to borehole environmental parameters and are relatively reliable; (2) relative to the conductivity variables (σ _m , σ _t ), the borehole Geometry factors are more sensitive to geometry variables (ecc, cal).

It should be noted that in wells with high contrast between mud and formation conductivity (such as mud/formation conductivity ratio greater than 100), most of the subarray (subarray A1, subarray A2, subarray A3) readings of shallow detection come from the well Eye. In the case of large boreholes and high formation resistivity, the borehole geometric factor may reach more than 0.6, and the measurement signal is almost entirely contributed by the borehole. The measurement error of the total reading may be greater than the formation signal, and over-correction or under-correction may easily occur at this time . Therefore, the influence of the borehole environment must be eliminated as much as possible before the synthetic focus processing.

In an optional embodiment, the above-mentioned wellbore environment parameters corresponding to the wellbore environment of the target formation are determined, and the target of the above-mentioned wellbore environment is obtained from the wellbore geometric factor library according to the above-mentioned wellbore environment parameters by using a multi-dimensional space interpolation method. The borehole geometric factor includes: determining the value of the borehole environment parameter corresponding to the above borehole environment of the above target formation; obtaining the closest target discrete point from the above borehole geometry factor library according to the value of the above borehole environment parameter; The above-mentioned target borehole geometry factor is determined based on the above-mentioned first-dimension discrete point set, above-mentioned second-dimension discrete point set, above-mentioned third-dimension discrete point set, and above-mentioned fourth-dimension discrete point set by using the above-mentioned multi-dimensional space interpolation method.

As an optional embodiment, determine the values of the four borehole environmental parameters corresponding to the target formation; and obtain the target closest to the values of the four borehole environmental parameters corresponding to the target formation from the above-mentioned borehole geometric factor library For discrete points, the target wellbore geometric factor of the above-mentioned target formation is determined from the above-mentioned wellbore geometric factor library based on the above-mentioned four borehole environmental parameters by using a spatial interpolation method.

In an optional embodiment, based on the radial formation model and the above-mentioned measurement signals, the tomographic matrix equation is established, and the above-mentioned tomographic matrix equation is solved, and before the radial conductivity distribution of the above-mentioned target formation is obtained, the above-mentioned method further includes : The above-mentioned target formation is divided into multiple layers in the radial direction, wherein the wellbore is the innermost layer, and the formations except the above-mentioned wellbore are the invasion and flushing zone, the invasion transition zone and the original formation; the above-mentioned wellbore, the above-mentioned invasion and flushing The aforementioned radial stratigraphic model was constructed using the aforementioned intrusive transition zone and the aforementioned undisturbed strata.

In an optional embodiment, based on the radial formation model and the above-mentioned measurement signals, a tomographic matrix equation is established, and the above-mentioned tomographic matrix equation is solved to obtain the radial conductivity distribution of the above-mentioned target formation, including: determining the above-mentioned The borehole geometric factors of the sub-arrays and the radial geometric factors of the above-mentioned sub-arrays; based on the above-mentioned radial formation model and the above-mentioned measurement signals, the above-mentioned borehole geometric factors and the above-mentioned radial geometric factors, the above-mentioned tomographic matrix equation is established, wherein, The left side item of above-mentioned tomographic matrix equation is the above-mentioned measurement signal of above-mentioned each sub-array, and the unknown quantity of above-mentioned tomographic matrix equation is the conductivity difference between radially adjacent layers, and the coefficient matrix of above-mentioned tomographic matrix equation is formed by above-mentioned each The above-mentioned wellbore geometric factors, the above-mentioned radial geometric factors and constants of the sub-array are composed, and the constraint conditions of the above-mentioned tomographic matrix equation are determined according to the above-mentioned wellbore environmental parameters; the above-mentioned tomographic matrix equation is solved to obtain the above-mentioned radial conductance of the above-mentioned target formation rate distribution.

In the embodiment of the present invention, the original measurement data of the array sensing satisfy a certain relationship, and whether a sub-array response is significantly abnormal can be judged according to the trend formed among fuzzy sub-arrays. The tendency of formation among subarrays is controlled by two factors: the radial variation of formation conductivity and the radial geometry factor of the subarrays. After skin correction, it can be considered that each subarray measurement satisfies the Born approximation. Under the Born approximation, when the invasion depth is D, the response of the i-th subarray can be expressed by the following formula: σ _a (i, D) = σ _t + Δσ(D)*GF(i, D); where, Δσ (D) is a step function, the step amplitude is σ _xo -σ _t , and the step position is D; GF(i, D) is the radial integral geometric factor when the i-th subarray has a radial depth of D. When the radial change of formation conductivity is not a single step, the concept of radial tomography can be used to approximate it with the schematic diagram of multiple radial steps as shown in Fig. 7 . The step function Δσ _l (r _l ) represents the lth step, the step amplitude is Δσ _l =σ _l -σ _l-1 , and the step position is r _l . After introducing the step function, the conductivity σ of the formation can be expressed as:

σ＝σ ₀ +Δσ ₁ (r ₁ )+Δσ ₂ (r ₂ )+…+Δσ _K (r _K )

Optionally, the measured value of the i-th subarray using the Born approximation can be expressed as follows:

σ _a (i)=σ ₀ +Δσ ₁ *GF(i,r ₁ )+...+Δσ _i *GF(i,r _i )+...+Δσ _k *GF(i,r _k )

Optionally, the array induction sub-array measurement value of the radial multi-level formation is described in matrix form, and the intrinsic quantitative correlation general formula describing the array induction sub-array measurement value is obtained:

Wherein, M is the number of sub-arrays; K is the number of analysis layers; the tomographic coefficient G _ij corresponds to the radial integral geometric factor, and G _i0 =1.

As an optional embodiment, after skin correction, the measured value of each sub-array of the array induction has good linearity characteristics, and the measured value of the sub-array is equal to the contribution sum of each area in the surrounding space of the instrument, which can be expressed as: σ _a = ∫∫∫g _j σ _j dv _j . where g _j is called the differential geometry factor of the space volume unit dv _j . The differential geometry factors satisfy the normalization condition, that is, ∫∫∫g _j dv _j =1. Differential geometry factors are functions of spatial coordinates. In the cylindrical coordinate system, the independent variables of the geometric factors are z, r,

Optionally, the radial integral geometry factor GF(i, D) corresponding to any radial depth D can be obtained from N pre-selected radial depth D _j points (j=1, . . . , N) The geometric factor GF(i, D _j ) is interpolated to approximate the calculation, namely:

Optionally, substituting the above formula into the measured value expression of the i-th subarray obtained after Born approximation, we can get:

j＝1,…,N；G(i,j)＝GF(i,D_j)；将上式写成矩阵形式，得：Among them, record a _M+1 = σ ₀ ;

j=1,...,N; G(i,j)=GF(i,D _j ); write the above formula in matrix form, get:

It should be noted that [a ₁ a ₂ ... a _M a _M+1 ] ^T is a trend relationship vector, which describes the relationship trend between the measured values of each sub-array. In the sense of Born approximation, this formula can approximate the subarray measurement value of any radial one-dimensional formation. Wherein, the left term of above-mentioned tomographic matrix equation is the above-mentioned measurement signal of above-mentioned each sub-array, and the unknown quantity of above-mentioned tomographic matrix equation is the electric conductivity difference between radially adjacent layers, and the coefficient matrix of above-mentioned tomographic matrix equation is given by Each sub-array is composed of borehole geometric factors, radial geometric factors and constants, and the constraint conditions of the above-mentioned tomographic matrix equations are determined according to the above-mentioned borehole environment parameters.

z方向从-∞到+∞的圆柱体，则：

引入径向积分几何因子G_r，表达高度为无穷(z方向从-∞到+∞)、外半径为r柱体对测量信号贡献的权重，则：

可见，

与井眼影响相同，井眼几何因子G_bh由四个井眼环境参数(ecc，cal，σ_m，σ_t)决定。引入几何因子之后，某些特殊情况下的测井响应就有了显式表达。例如：不考虑侵入、有井条件下的无穷大均匀地层模型中，第i个子阵列测得的视电导率可表示为：Optionally, in order to analyze the borehole effect of the array induction measurement, a borehole geometry factor G _bh may be introduced to express the weight of the borehole medium contribution to the measurement signal. Think of the wellbore as having a radius of

A cylinder from -∞ to +∞ in the z direction, then:

Introduce the radial integral geometric factor G _r to express the weight of the contribution of the cylinder with an infinite height (from -∞ to +∞ in the z direction) and an outer radius of r to the measurement signal, then:

visible,

Same as the wellbore effect, the wellbore geometry factor G _bh is determined by four wellbore environment parameters (ecc, cal, σ _m , σ _t ). After introducing the geometric factor, the logging response in some special cases has an explicit expression. For example, in an infinite uniform formation model without considering invasion and wells, the apparent conductivity measured by the ith sub-array can be expressed as:

σ _a (i) = σ _m G _bh (i) + σ _t [1−G _bh (i)].

As an optional embodiment, the existing array induction borehole correction methods are all based on the schematic diagram of the radial two-layer model shown in Figure 6, "borehole + infinite formation", which can be called (radial) two-story model. At this time, according to the geometric factor theory, the basic logging response relationship of each sub-array is:

σ _a (i) = σ _m G _bh (i) + σ _t [1-G _bh (i)]

Among them, i represents the subarray number, from 1 to M, the larger the i is, the greater the detection depth of the subarray; G _bh (i) is the borehole geometry factor of the i subarray; σ _a (i) is the i The apparent conductivity of the sub-array; _σt is the conductivity of the undisturbed formation.

Optionally, under the two-layer model, the wellbore correction is to "replace" the wellbore fluid with a formation with conductivity _σt , and the corresponding wellbore correction formula is:

_σbhc (i)= _σa (i)-( _σm - _σt ) _Gbh (i).

Among them, σ _bhc (i) is the corrected measured value of the wellbore of subarray i.

Optionally, the array induction logging tool describes the invasion profile by measuring resistivity curves at multiple detection depths (10in-, 20in-, 30in-, 60in-, 90in- or 120in-) in the radial direction from shallow to deep, namely The radial change of resistivity or conductivity, and then accurately obtain the true resistivity Rt of the formation. Its stratigraphic model is an invasion model, which is simplified as a (radial) three-layer model, as shown in Figure 7, where D _xo is the diameter of the intrusion zone. According to the geometric factor theory, the measured value of the sub-array can be expressed as:

σ _a (i) = σ _m G _bh (i) + σ _xo [G _xo (i) - G _bh (i)] + σ _t [1 - G _xo (i)].

Among them, σ _xo is the formation conductivity of the invasion zone; G _xo (i) is the radial integral geometry factor of the invasion zone of sub-array i, which is a function of the radius of the invasion zone. By “replacing” the wellbore fluid with the formation in the invasion zone with the conductivity σ _xo , the wellbore correction is realized. At this time, the corresponding wellbore correction formula is:

_σbhc (i)= _σa (i)-( _σm - _σxo ) _Gbh (i).

Optionally, when invasion does not exist, σ _xo =σ _t , the three-layer model can be transformed into a two-layer model, and the wellbore correction formula will also be transformed accordingly.

As an optional embodiment, when there is drag reduction intrusion, σ _m >σ _xo >σ _t . Due to the existence of wellbore and invasion, the relationship of the original measurement data is: σ _a (1)>…>σ _a (i)>…>σ _a (M), as shown in Fig. 8, σ _m >σ _xo >σ Schematic diagram of apparent conductivity after model correction at time _t . In the figure, the result of borehole correction based on the formula of the three-layer model (considering invasion) is an ideal result. When using the formula based on the two-layer model (without considering invasion) for borehole correction processing, since σ _t is lower than σ _xo , (σ _m -σ _t )>(σ _m -σ _xo ), overcorrection occurs. This amount of overcorrection gradually decreases as the number of subarrays increases. This results in reduced variance between the subarray curves, resulting in less intrusive variance in the final curve.

As an optional embodiment, when there is increased drag invasion, σ _xo <σ _t , if the wellbore correction is performed with the formula based on the two-layer model (without considering invasion), the result varies with σ _m , σ _t and The relationship between σ _xo changes, and the following three situations appear: The first one: σ _t >σ _xo ≥σ _m . At this time, (σ _m -σ _xo ) is negative, and (σ _m -σ _t ) is also negative, and |σ _m -σ _t |>|σ _m -σ _xo |, so overcorrection also occurs, resulting in the final The intrusion difference of the curves is small, as shown in Figure 9, when σ _t >σ _xo ≥σ _m , the schematic diagram of the apparent conductivity after model correction. The second type: σ _t >σ _m >σ _xo . At this time (σ _m -σ _xo ) is positive, but since (σ _m -σ _t ) is negative, the borehole correction direction is in the opposite direction, so that the invasion difference of the final curve is relatively small, as shown in Fig. 10 σ _t > Schematic diagram of apparent conductivity after model correction when σ _m >σ _xo . The third type: σ _m ≥σ _t >σ _xo , at this time (σ _m -σ _t ) and (σ _m -σ _xo ) are both positive or zero, because (σ _m -σ _xo )>(σ _m -σ _t ), so the wellbore correction is not enough, so the invasion difference of the final curve is too small, as shown in Fig. 11, when σ _m ≥ _{σ t} > σ _xo , the schematic diagram of apparent conductivity after model correction.

可以理解为：除井眼以外的所有地层“产生”的电导率“推演”到井眼；这个所有地层“产生”的电导率也就是井眼校正后的结果。如果地层符合二层模型，则该井眼校正后的结果等于σ_t；但如果存在侵入，即三层模型时，则该式校正后的结果为：

It should be noted that when the well correction formula based on the two-layer model is used, the invasion difference of the correction result curve is always small. In addition, the commonly used wellbore correction formula:

It can be understood as: the conductivity "produced" of all formations except the wellbore is "deduced" to the wellbore; the conductivity "produced" of all formations is the result of the correction of the wellbore. If the formation conforms to the two-layer model, the corrected result of the wellbore is equal to _σt ; but if there is invasion, that is, the three-layer model, the corrected result of this formula is:

In an optional embodiment, determining the corrected measured value of the above-mentioned target formation based on the above-mentioned measured value expression and the above-mentioned borehole correction formula, and completing the borehole correction include: using the above-mentioned measured value expression and the above-mentioned The borehole correction formula processes the above-mentioned measurement signals to determine the target formation conductivity and the target wellbore mud conductivity of the above-mentioned target formation; the target measurement value is corrected by using the above-mentioned target formation conductivity and the above-mentioned target wellbore mud conductivity.

In the embodiment of the present invention, based on the radial invasion model, the expression of the measured value of the sub-array and the wellbore correction formula are derived; starting from the multi-level formation model, the born approximation is applied to deduce the expression describing the measured value of the array induction sub-array The general formula of the internal quantitative correlation; according to the internal correlation between the measured values of the array induction sub-array, the parameters required for borehole calibration are solved; finally, the borehole calibration is performed using the borehole calibration formula based on the radial invasion model.

As an optional embodiment, during the solution process, the only parameters that need to be determined according to the experiment in the program are the weights when calculating the fitting residuals. It is necessary to pay attention to the first 4 subarrays with shallow detection, so their corresponding Select 1.0 for the weight, and gradually reduce the other sub-arrays. There are four optional borehole correction modes set in the program, and their functions are listed in the table below:

Table 1

Borehole Correction Mode Functional description conventional Given σ_m, Cal and Ecc, adaptively solve σ_xo and σ_t Adaptive Seeking Mud Known Cal and Ecc, adaptively solve σ_m, σ_xo and σ_t Self-adaptive calculation of well diameter Knowing σ_m and Ecc, adaptively solve Cal, σ_xo and σ_t Adaptive solution to eccentricity Knowing σ_m and Cal, adaptively solve Ecc, σ_xo and σ_t

As an optional embodiment, by applying the above-mentioned self-adaptive solution program, the curve difference can reliably describe the invasion profile, and thus the true formation resistivity Rt can be obtained more accurately.

It should also be noted that the radial three-layer model has made great progress compared with the two-layer model due to the inclusion of the invasion zone, but there is still a gap between it and the actual radial change of formation conductivity. The schematic diagram of the invasion transition path is shown in Fig. 12. The dotted line in the figure shows the radial section of the formation that is closer to the actual formation, which only represents four possible paths from the flushing zone of the wellbore to the transition zone of the undisturbed formation. The actual path There are infinite possibilities.

Using the above method, based on the inline relationship between the measurement curves of the array induction sub-array, applying the concept of tomography, introducing multiple step functions, approaching any radial one-dimensional formation, and deducing the inline relationship according to the geometric factor theory Mathematical expression and applied to adaptive borehole correction. Based on the invasion model, a new wellbore correction formula is determined. Apply the inline relationship between the array induction sub-array measurement curves and the new wellbore correction formula to correctly solve the parameters required for wellbore correction, avoiding the invasion effect as the wellbore effect "corrected", after the wellbore correction The curve difference does not get smaller, maintaining the ability of the curve to analyze intrusion radially.

Through the above steps, a new adaptive wellbore environmental parameter solution algorithm can be constructed by using the inline relationship between the array induction sub-array measurement curves, and the accuracy of the adaptive solution results is greatly improved; based on the invasion model, the target wellbore Correction formula; avoiding the influence of invasion as wellbore effect "corrected", the curve difference will not become smaller after the wellbore is corrected, and the ability to analyze the invasion in the radial direction of the curve is maintained. Figure 13 shows the schematic diagram of the conductivity radial section represented by the array induction curve before and after borehole correction. There is a large difference in the rate, as shown in (a); at this time, the measured value of each sub-array induced by the array is the response of the model in (a). After the wellbore is corrected, it is equivalent to "replacing the wellbore medium with a conductivity of _σm with a medium with a conductivity of _σxo ". At this time, the measured value of each sub-array induced by the array is the response of the (b) model. It solves the technical problems that the existing array induction wellbore correction method has a model inconsistent with the actual formation, and the intrinsic correlation between the measured values of the array induction sub-arrays is low.

Example 2

According to an embodiment of the present invention, an embodiment of a device for implementing the above array induction borehole correction method is also provided. FIG. 14 is a schematic structural diagram of a borehole correction device according to an embodiment of the present invention. As shown in FIG. 14, the above The wellbore correction device includes: an acquisition module 140, a first determination module 142, a processing module 144, a second determination module 146 and a correction module 148, wherein:

The obtaining module 140 is used to obtain the measurement signals measured by each sub-array of the array induction logging tool, wherein the above-mentioned measurement signals at least include: a conductivity curve group;

The first determination module 142 is used to determine the wellbore environment parameters corresponding to the wellbore environment of the target formation, and obtain the target wellbore geometry of the above-mentioned wellbore environment from the wellbore geometric factor library according to the above-mentioned wellbore environment parameters by using multi-dimensional space interpolation method Factors, wherein the above-mentioned wellbore environmental parameters include: borehole cal, mud conductivity σ _m , formation conductivity _σt and eccentricity ecc, the above-mentioned wellbore geometric factor database is a pre-established wellbore geometric factor database, the above-mentioned wellbore The geometry factor is a function of the above-mentioned borehole environmental parameters;

The processing module 144 is configured to establish a tomographic matrix equation based on the radial formation model and the above-mentioned measurement signals, and solve the above-mentioned tomographic matrix equation to obtain the radial conductivity distribution of the above-mentioned target formation, wherein the above-mentioned radial formation model is used for Characterize the change in conductivity of the target formation above;

The second determination module 146 is configured to determine a measurement value expression according to the above-mentioned radial formation model and the above-mentioned radial conductivity distribution, and determine a borehole correction formula by using the above-mentioned target borehole geometry factor corresponding to the above-mentioned borehole environment;

The correction module 148 is configured to determine the corrected measured value of the above-mentioned target formation based on the above-mentioned measured value expression and the above-mentioned borehole correction formula, and complete borehole correction.

It should be noted here that the acquisition module 140, the first determination module 142, the processing module 144, the second determination module 146 and the correction module 148 correspond to steps S102 to S110 in Embodiment 1. The implementation examples and application scenarios are the same, but are not limited to the content disclosed in Embodiment 1 above. It should be noted that, as a part of the device, the above modules can run in the computer terminal.

It should be noted that, for optional or preferred implementation manners of this embodiment, reference may be made to relevant descriptions in Embodiment 1, and details are not repeated here.

The above-mentioned wellbore correction device may also include a processor and a memory, and the above-mentioned acquisition module 140, first determination module 142, processing module 144, second determination module 146, correction module 148, etc. are all stored in the memory as program units, and are processed by The processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

The processor includes a kernel, and the kernel fetches corresponding program units from the memory, and one or more kernels can be provided. Memory may include non-permanent memory in computer-readable media, random access memory (RAM) and/or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM), memory includes at least one memory chip.

According to an embodiment of the present application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the above-mentioned non-volatile storage medium includes a stored program, wherein, when the above-mentioned program is running, the device where the above-mentioned non-volatile storage medium is located is controlled to perform any one of the above-mentioned array induction wellbore correction methods .

Optionally, in this embodiment, the above-mentioned non-volatile storage medium may be located in any computer terminal in the computer terminal group in the computer network, or in any mobile terminal in the mobile terminal group, and the above-mentioned non-volatile storage medium Nonvolatile storage media include stored programs.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: Acquire the measurement signals measured by each sub-array of the array induction logging tool, wherein the above-mentioned measurement signals at least include: a conductivity curve group; determine For the wellbore environment parameters corresponding to the wellbore environment of the target formation, the target wellbore geometric factors of the above-mentioned wellbore environment are obtained from the wellbore geometric factor library according to the above-mentioned wellbore environment parameters by using the multi-dimensional space interpolation method, wherein the above-mentioned wellbore environment parameters Including: borehole cal, mud conductivity σ _m , formation conductivity σ _t and eccentricity ecc, the above-mentioned wellbore geometric factor database is a pre-established wellbore geometric factor database, and the above-mentioned wellbore geometric factor is the above-mentioned wellbore environmental parameters function; based on the radial stratigraphic model and the above-mentioned measurement signals, the tomographic matrix equation is established, and the above-mentioned tomographic matrix equation is solved to obtain the radial conductivity distribution of the above-mentioned target formation, wherein the above-mentioned radial formation model is used to characterize the above-mentioned target formation Conductivity change; determine the measured value expression according to the above-mentioned radial formation model and the above-mentioned radial conductivity distribution, and use the above-mentioned target wellbore geometry factor corresponding to the above-mentioned wellbore environment to determine the wellbore correction formula; based on the above-mentioned measured value expression Formula and the above-mentioned wellbore correction formula, determine the corrected measured value of the above-mentioned target formation, and complete the borehole correction.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: determine the first variation range of the above-mentioned well diameter, and determine a first preset number of discrete points based on the above-mentioned first variation range to form the second One-dimensional discrete point set; determine the second variation range of the above-mentioned mud conductivity, and determine a second preset number of discrete points based on the above-mentioned second variation range to form a second-dimensional discrete point set; determine the third range of the above-mentioned formation conductivity change range, and determine the third preset number of discrete points based on the above-mentioned third change range to form a third-dimensional discrete point set; determine the fourth change range of the above-mentioned eccentricity, and determine the fourth preset based on the above-mentioned fourth change range The number of discrete points forms the fourth dimension discrete point set; the above-mentioned first dimension discrete point set, the above-mentioned second dimension discrete point set, the above-mentioned third dimension discrete point set and the above-mentioned fourth dimension discrete point set are combined and calculated to obtain The wellbore geometric factors of the above-mentioned sub-arrays are stored according to the preset storage rules to construct the above-mentioned well-bore geometric factor library.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: determine the value of the wellbore environment parameter corresponding to the above-mentioned wellbore environment of the above-mentioned target formation; according to the value of the above-mentioned wellbore environment parameter, from the above-mentioned Obtain the closest target discrete point from the wellbore geometric factor library; adopt the above-mentioned multi-dimensional space interpolation method based on the above-mentioned first-dimensional discrete point set, the above-mentioned second-dimensional discrete point set, the above-mentioned third-dimensional discrete point set and the above-mentioned fourth-dimensional discrete point set Set of points, determine the above-mentioned target wellbore geometry factors.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: divide the above-mentioned target formation into multiple layers in the direction of the horizontal radius, wherein the wellbore is the innermost layer, and the wellbore other than the above-mentioned The stratum is an invasion flushing zone, an invasion transition zone and an undisturbed formation; the above-mentioned radial stratigraphic model is constructed by using the above-mentioned borehole, the above-mentioned invasion flushing zone, the above-mentioned invasion transition zone and the above-mentioned undisturbed formation.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: determine the borehole geometric factors of the above-mentioned sub-arrays and the radial geometric factors of the above-mentioned sub-arrays; based on the above-mentioned radial formation model and the above-mentioned The measurement signal, the above-mentioned borehole geometric factor and the above-mentioned radial geometric factor are used to establish the above-mentioned tomographic matrix equation, wherein the left term of the above-mentioned tomographic matrix equation is the above-mentioned measurement signal of each sub-array, and the unknown quantity of the above-mentioned tomographic matrix equation is is the conductivity difference between radially adjacent layers, the coefficient matrix of the above-mentioned tomographic matrix equation is composed of the above-mentioned wellbore geometric factors, the above-mentioned radial geometric factors and constants of the above-mentioned sub-arrays, and the constraints of the above-mentioned tomographic matrix equation Determine according to the above-mentioned borehole environment parameters; solve the above-mentioned tomographic matrix equation to obtain the above-mentioned radial conductivity distribution of the above-mentioned target formation.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: use the above-mentioned measured value expression and the above-mentioned wellbore correction formula to process the above-mentioned measurement signal, determine the target formation conductivity of the above-mentioned target formation and the target well The electrical conductivity of the borehole mud; the above-mentioned target formation electrical conductivity and the above-mentioned target wellbore mud electrical conductivity are used to perform borehole correction on the target measured value.

According to an embodiment of the present application, an embodiment of a processor is also provided. Optionally, in this embodiment, the above-mentioned processor is configured to run a program, wherein, when the above-mentioned program is running, any one of the above-mentioned array induction wellbore correction methods is executed.

According to an embodiment of the present application, an embodiment of an electronic device is also provided, including a memory and a processor, the memory stores a computer program, and the processor is configured to run the computer program to perform any of the above array sensing Wellbore correction method.

According to an embodiment of the present application, an embodiment of a computer program product is also provided, which, when executed on a data processing device, is suitable for executing a program initialized with the steps of any one of the above-mentioned array induction wellbore calibration methods.

The serial numbers of the above embodiments of the present invention are for description only, and do not represent the advantages and disadvantages of the embodiments.

In the above-mentioned embodiments of the present invention, the descriptions of each embodiment have their own emphases, and for parts not described in detail in a certain embodiment, reference may be made to relevant descriptions of other embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed technical content can be realized in other ways. Wherein, the device embodiments described above are only illustrative. For example, the division of the units may be a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or may be Integrate into another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of units or modules may be in electrical or other forms.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

If the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes. .

The above is only a preferred embodiment of the present invention, it should be pointed out that, for those of ordinary skill in the art, without departing from the principle of the present invention, some improvements and modifications can also be made, and these improvements and modifications can also be made. It should be regarded as the protection scope of the present invention.

Claims (10)

1. An array induction borehole correction method, characterized in that, comprising: Acquiring measurement signals obtained from the measurement of each sub-array of the array induction logging tool, wherein the measurement signals at least include: a set of conductivity curves; Determine the wellbore environment parameters corresponding to the wellbore environment of the target formation, and obtain the target wellbore geometry factors of the wellbore environment from the wellbore geometry factor library according to the wellbore environment parameters by using multi-dimensional space interpolation method, wherein, the Borehole environmental parameters include: borehole cal, mud conductivity σ _m , formation conductivity σ _t and eccentricity ecc. The borehole geometric factor database is a pre-established borehole geometric factor database, and the borehole geometric factor is a function of said wellbore environmental parameters; Based on the radial formation model and the measurement signal, a tomographic matrix equation is established, and the tomographic matrix equation is solved to obtain the radial conductivity distribution of the target formation, wherein the radial formation model is used to characterize the Describe the conductivity change of the target formation; determining a measurement value expression according to the radial formation model and the radial conductivity distribution, and using the target borehole geometry factor corresponding to the borehole environment to determine a borehole correction formula; Based on the measured value expression and the borehole correction formula, the corrected measured value of the target formation is determined to complete the borehole correction. 2. The method according to claim 1, wherein, before adopting the multidimensional space interpolation method to obtain the target borehole geometry factor of the borehole environment from the borehole geometry factor library according to the borehole environment parameter, the The method also includes: determining the variation range of the well diameter, and determining a preset number of discrete points of the well diameter based on the variation range of the well diameter, to form a set of discrete points in the first dimension; determining the variation range of the mud conductivity, and determining a preset number of discrete points of the mud conductivity based on the variation range of the mud conductivity to form a set of discrete points in the second dimension; determining the variation range of the formation conductivity, and determining a preset number of discrete points of the formation conductivity based on the variation range of the formation conductivity to form a third dimension discrete point set; determining the variation range of the eccentricity, and determining a preset number of discrete points of the eccentricity based on the variation range of the eccentricity to form a fourth dimension discrete point set; combining the set of discrete points in the first dimension, the set of discrete points in the second dimension, the set of discrete points in the third dimension and the set of discrete points in the fourth dimension to calculate the borehole geometry of each sub-array factor, store all the borehole geometry factors of the sub-arrays according to the preset storage rules, and construct the borehole geometry factor library. 3. The method according to claim 2, wherein the determination of the borehole environment parameters corresponding to the borehole environment of the target formation adopts a multidimensional space interpolation method from the borehole geometric factor library according to the borehole environment parameters Obtain the target wellbore geometry factors of the wellbore environment, including: determining the value of the wellbore environment parameter corresponding to the wellbore environment of the target formation; Acquiring the closest target discrete point from the wellbore geometric factor library according to the value of the wellbore environment parameter; Using the multi-dimensional space interpolation method to determine the target wellbore based on the first dimension discrete point set, the second dimension discrete point set, the third dimension discrete point set and the fourth dimension discrete point set geometry factor. 4. The method according to claim 1, characterized in that, based on the radial formation model and the measurement signal, a tomographic matrix equation is established, and the tomographic matrix equation is solved to obtain the radial conductance of the target formation Before the rate distribution, the method also includes: The target formation is divided into multiple layers in the radial direction, wherein the wellbore is the innermost layer, and the formations other than the wellbore are the invasion flushing zone, the invasion transition zone and the original formation; The radial stratigraphic model is constructed using the borehole, the invaded flush zone, the invaded transition zone, and the undisturbed formation. 5. The method according to claim 1, characterized in that, based on the radial formation model and the measurement signal, a tomographic matrix equation is established, and the tomographic matrix equation is solved to obtain the radial conductance of the target formation rate distribution, including: determining a borehole geometry factor for each of the subarrays and a radial geometry factor for each of the subarrays; Based on the radial formation model and the measurement signal, the borehole geometric factor and the radial geometric factor, the tomographic matrix equation is established, wherein the left term of the tomographic matrix equation is the each The measurement signal of the sub-array, the unknown quantity of the tomographic matrix equation is the conductivity difference between radially adjacent layers, and the coefficient array of the tomographic matrix equation is determined by the wellbore of each sub-array Geometric factors, the radial geometric factors and constants, the constraints of the tomographic matrix equation are determined according to the wellbore environmental parameters; solving the tomographic matrix equation to obtain the radial conductivity distribution of the target formation. 6. The method according to any one of claims 1 to 5, wherein the corrected measured value of the target formation is determined based on the measured value expression and the borehole correction formula, Complete borehole corrections, including: processing the measured signal by using the measured value expression and the borehole correction formula to determine the target formation conductivity and the target wellbore mud conductivity of the target formation; Borehole correction is performed on target measured values using the target formation conductivity and the target wellbore mud conductivity. 7. An array induction borehole correction device, characterized in that it comprises: An acquisition module, configured to acquire measurement signals measured by each sub-array of the array induction logging tool, wherein the measurement signals at least include: a set of conductivity curves; The first determination module determines the wellbore environment parameters corresponding to the wellbore environment of the target formation, and obtains the target wellbore geometric factors of the wellbore environment from the wellbore geometric factor library according to the wellbore environmental parameters by using multidimensional space interpolation method , wherein the borehole environmental parameters include: borehole cal, mud conductivity σ _m , formation conductivity σ _t and eccentricity ecc, the borehole geometry factor library is a pre-established borehole geometry factor database, the the borehole geometry factor is a function of said borehole environmental parameters; A processing module, configured to establish a tomographic matrix equation based on the radial formation model and the measurement signal, and solve the tomographic matrix equation to obtain the radial conductivity distribution of the target formation, wherein the radial formation a model for characterizing conductivity variations of the formation of interest; The second determination module is configured to determine a measurement value expression according to the radial formation model and the radial conductivity distribution, and determine a wellbore correction formula by using the target wellbore geometry factor corresponding to the wellbore environment ; A correction module, configured to determine the corrected measured value of the target formation based on the measured value expression and the borehole correction formula, and complete borehole correction. 8. A non-volatile storage medium, characterized in that the non-volatile storage medium stores a plurality of instructions and a wellbore geometry factor database, and the instructions are suitable for being loaded by a processor and executing claims 1 to 1. The array induction borehole correction method described in any one of 6. 9. A processor, characterized in that the processor is used to run a program, wherein the program is set to execute the array induction wellbore calibration method according to any one of claims 1 to 6 when running. 10. An electronic device comprising a memory and a processor, wherein a computer program and a wellbore geometry factor database are stored in the memory, and the processor is configured to run the computer program to perform claims 1 to 10. The array induction borehole correction method described in any one of 6.

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