Casing corrosion morphology quantitative identification and grading method based on logging data

Abstract

The invention relates to the technical field of shaft integrity evaluation, in particular to a casing corrosion morphology quantitative identification and grading method based on logging data. The method comprises the following steps: determining various standard parameters of the casing to obtain the inner radius and the outer radius of the casing; performing standardized filtering processing on the casing pipe inner diameter / wall thickness logging matrix, constructing a similar binarization casing pipe inner diameter / wall thickness logging data matrix, and merging the similar binarization casing pipe inner diameter / wall thickness logging data matrix to obtain a casing pipe logging data matrix containing corrosion defect information; extracting the boundary row number of each internal and external corrosion defect sub-matrix, and determining the length, width and depth parameters and the depth range of each internal and external corrosion defect of the casing pipe; and grading the corrosion defects of the casing according to a grading principle. According to the method provided by the invention, by processing and analyzing the casing logging data, the length, width and depth parameters of the internal and external corrosion defects of the casing and the three-dimensional space positions of the corrosion defects are efficiently obtained, quantitative grading is carried out on the corrosion defects according to the geometric parameters of the corrosion defects, and an important basis is provided for casing safety evaluation.

Description

Technical Field

[0001] The invention relates to the technical field of wellbore integrity evaluation, and in particular to a method for quantitatively identifying and grading casing corrosion morphology based on well logging data. Background Art

[0002] During the development of oil and gas fields, corrosion often causes corrosion defects on the inner or outer walls of the casing, causing strength loss or even perforation, leading to casing failure and serious threats to the safe production of oil and gas wells. Blindly replacing the casing or scrapping the wellbore after the casing is corroded will lead to a decrease in development benefits. Therefore, accurate evaluation of the safety of in-service casing is particularly important for guiding the safe and efficient production of oil and gas wells.

[0003] Accurately identifying the morphology of corrosion defects is the key to casing safety evaluation. Currently, casing corrosion defect detection mainly relies on logging technology. However, for a long time, how to use the logging data to quantify the morphology of casing corrosion defects has not been effectively solved. Although the current logging data interpretation results can analyze the degree of corrosion through changes in casing wall thickness, the interpretation method still has the following shortcomings: First, logging cannot give the morphological characteristic parameters such as length, width, and depth of each corrosion defect along the wellbore, and classify them, and cannot guide the analysis of casing corrosion types; second, it is impossible to determine the three-dimensional spatial position of the casing where the casing corrosion defect is located. Due to the different corrosion environments inside and outside the casing, it is impossible to effectively guide the study of the development law of casing corrosion. In general, the current logging interpretation method still cannot accurately quantify the morphology of casing corrosion defects, and cannot effectively guide the accurate assessment of casing safety.

[0004] At present, researchers in related fields have also proposed some methods for identifying the corrosion morphology of oil and gas field pipelines to evaluate the current safety status of the pipeline. Existing corrosion morphology identification methods, for example: a corrosion morphology description and interpretation method based on three-dimensional image analysis (CN108711145B), the method obtains a two-dimensional contour map of the corrosion depth by scanning the corrosion surface over a large area, and obtains a corrosion depth frequency distribution map based on the contours, fits the corrosion depth density using the Gauss model, and then corrects the fitting results using the average corrosion rate, redraws the corrosion depth density distribution map, and again uses the Gauss model to fit the corrosion depth density distribution twice, and interprets the corrosion type and pitting probability based on the secondary fitting results. Although this method can characterize the corrosion depth distribution through statistical analysis, it is unable to obtain information such as the length and width of each corrosion pit, so this method cannot comprehensively and quantitatively identify the corrosion defect morphology.

[0005] Another existing technology: A quantitative detection method for pipeline outer wall corrosion morphology (CN105486240B) uses a grating projector to perform an overall scan of the pipeline outer wall corrosion defects to obtain point cloud data of the entire pipeline outer surface morphology, and then uses professional reverse software to perform three-dimensional restoration of the obtained point cloud data to obtain a three-dimensional solid image of the pipeline, and finally uses software to analyze the three-dimensional image of the pipeline to obtain the degree of corrosion in different areas of the pipeline outer wall. This method can indeed effectively quantitatively characterize the external corrosion morphology of the pipeline, and has the advantage of high precision, but this method requires the use of a grating projector to scan the pipeline, which is currently impossible to achieve under the high temperature and high pressure conditions of oil and gas wells. Therefore, it can only analyze the corrosion morphology of the ground pipeline, and cannot quantitatively characterize the corrosion morphology of the underground casing.

[0006] In general, there is currently no effective method that can accurately characterize the morphology of casing corrosion defects and guide casing safety evaluation. Summary of the invention

[0007] 1. Technical issues to be resolved

[0008] The present invention provides a method for quantitatively identifying and grading casing corrosion morphology based on logging data, so as to overcome the problem that the prior art cannot comprehensively and accurately quantitatively identify the corrosion defect morphology, resulting in the inability to accurately and effectively evaluate the casing safety.

[0009] (II) Technical solution

[0010] To solve the above problems, the present invention provides a method for quantitatively identifying and grading casing corrosion morphology based on logging data, comprising:

[0011] Step S1, determine various standard parameters of the casing and obtain the inner and outer radii of the casing;

[0012] Step S2, standardize the inner diameter filtering process of the casing inner diameter logging matrix to construct a binary casing inner diameter logging data matrix; standardize the wall thickness filtering process of the casing wall thickness logging matrix to construct a binary casing wall thickness logging data matrix; and merge the above casing logging data matrices to obtain a casing logging matrix that can comprehensively reflect the internal and external corrosion of the casing;

[0013] Step S3, extracting casing corrosion defect submatrix information, by scanning the corrosion defect submatrix row by row, extracting the row and column numbers of the boundaries of each inner corrosion submatrix, determining the length, width, and depth parameters of each casing inner corrosion defect, and the depth range of the inner corrosion defect;

[0014] Extract the row and column numbers of the boundaries of each external corrosion submatrix, determine the length, width, depth parameters of each casing external corrosion defect, and the depth range of the external corrosion defect;

[0015] Step S4: Classify the casing corrosion defects according to the extracted casing internal and external corrosion defect information and the classification principle.

[0016] Preferably, it also includes:

[0017] Step S5: Based on the quantitative classification results of casing corrosion defects, the remaining service life of the casing is evaluated, and the subsequent casing safety inspection cycle is adjusted.

[0018] Preferably, step S1 specifically includes:

[0019] The inner radius of the casing r=(Dt×2) / 2, and the outer radius of the casing R=D / 2, wherein D is the standard diameter of the casing of the target well, and t is the standard wall thickness of the casing.

[0020] Preferably, step S2 comprises: based on the logging data, obtaining a two-dimensional matrix of casing inner diameter: converting the logging data into a two-dimensional matrix of m×a except for the depth column, wherein each row of the matrix has the casing inner diameter value corresponding to the depth of each sampling point in the casing axial direction, and the axial interval is d 0 ; Each column of the matrix corresponds to the inner diameter value of each sampling point on the circumference of the casing. The order of each column represents the measurement arm number of the multi-arm caliper. The arm number ranges from 1 to a. The value of a is the number of arms of the multi-arm caliper and the corresponding phase range. That is, the corresponding phase range of each column is (p 1 -1)×360° / a to p 1 ×360° / a, where p 1 =1, 2, ...., the value of a is the number of multi-arm caliper logging arms, and the circumferential sampling interval can be deduced to be d 1 =(2×3.14×r) / a;

[0021] Get the two-dimensional matrix of casing wall thickness: convert the logging data into a two-dimensional matrix of m×b excluding the depth column. Each row of the matrix corresponds to the casing wall thickness value of each sampling point in the axial direction of the casing; each column of the matrix corresponds to the wall thickness value of each sampling point in the circumferential direction of the casing, and the axial interval is d 0 Each column represents the wall thickness logging sector number, the sector number ranges from 1 to b, the value of b is the wall thickness logging sector number, and the corresponding phase range, that is, the corresponding phase range of each column is (p 2 -1)×360° / b to p2×360° / b, where p 2 =1, 2, ...b, and the circumferential sampling interval can be deduced to be d 2 =(2×3.14×r) / b.

[0022] Preferably, step S2 further includes:

[0023] The casing inner diameter matrix is ​​subjected to standardized inner diameter filtering: a filtering threshold is used, which is generally set to 1.02r, and the matrix is ​​filtered. Elements below the threshold are set to 0, indicating no corrosion defects; elements above the threshold are subtracted from the threshold, indicating corrosion defects;

[0024] After filtering, the matrix is ​​transformed into a binary matrix A with only 0 and positive values. The positive value area corresponds to the corrosion defect area, and the maximum positive value corresponds to the maximum corrosion depth. The larger the positive value, the greater the corrosion depth.

[0025] The casing wall thickness matrix is ​​subjected to standardized wall thickness filtering: a filtering threshold is used, generally the threshold is set to 0.875t, and the matrix is ​​filtered. Elements above the threshold are set to 0, indicating no corrosion defects; elements below the threshold are subtracted from the threshold, indicating corrosion defects. After filtering, the matrix is ​​converted into a binary matrix B with only 0 and negative values. The negative value area corresponds to the corrosion defect area, and the minimum negative value corresponds to the maximum corrosion depth;

[0026] Determine internal and external corrosion defects: merge the values ​​of each column in the A matrix with the values ​​of each column in the corresponding phase of the B matrix. If the phase of each column of the B matrix can contain k columns on the corresponding phase of the A matrix (K≥2), then first perform equal value expansion on each column of the B matrix, that is, add k-1 columns to the right of each column of the B matrix, and assign the corresponding values ​​of each column of the original B matrix to the newly added columns on the right to obtain a new matrix B'; when merging matrices A and B', if the corresponding value in the B' matrix is ​​0, the value in the A matrix remains unchanged; if the corresponding value in the B matrix is ​​a negative number, and the corresponding value in the A matrix is ​​0, then the value in the A matrix is ​​assigned to the value in the B' matrix; that is, convert the A matrix into a new matrix A', which contains negative numbers, 0, and positive numbers, where the distribution range of positive values ​​indicates that the corrosion defect is on the inner wall of the casing, and the distribution range of negative values ​​indicates that the defect is on the outer wall of the casing.

[0027] Preferably, step S3 specifically includes:

[0028] The area containing positive or negative values ​​is divided into a submatrix, and each submatrix corresponds to a corrosion defect. The specific method is as follows:

[0029] Step S31: define the number of rows in the casing logging data matrix A' as i 1 、i 2 、....i n , define the number of matrix columns as j 1 、j 2 、....j a , then we get i n Row and J a Matrix steps of columns;

[0030] Step S32: Scan the matrix row by row from left to right. When the first non-zero value is found, for example, a positive value, the row number and column number are i. x 、j y , the value is h y , define the minimum and maximum row number i min =i max =i x , define the minimum and maximum column number j min =j max =j y , define the maximum depth h max =h y ;

[0031] Step S33, then continue to scan to the right, when the adjacent data is still non-zero, the row number and column number are i x 、j y+1 , the value is h y+1 , then the minimum and maximum row numbers i are still defined min =i max =i x , and define the minimum column number as j min =j y , maximum column number j max =j y+1 ; such as h y+1 >h y , then define h max =h y+1 ; Continue scanning to the right until the last non-zero value in this row is found. At this time, the row number and column number are i x 、j y+t , then the minimum and maximum row numbers i are still defined min =i max =i x , and the minimum column number is still defined as j min =j y , maximum column number j max =j y+t ; such as h y to h y+t Medium y+z1 The value of is the largest, then the maximum value is defined as h max =h y+z1 ;

[0032] Step S34: Continue scanning the next row in this way, starting from row and column number i. x+1 The row, j y ~j y+t The column with the first non-zero value on the left side of the column range is scanned once to the left and once to the right from the starting point. For example, scan left to the column number j with the leftmost non-zero value. y-m1 ≤jy , then define the minimum column number j min =j y-m1 , such as scanning the rightmost non-zero column number j to the right y+t+m2 ≥j y+t , then define the maximum column number j max =j y+t+m2 ; Also define the minimum row number i min =i x , the maximum row number i max =i x+1 ; and find the maximum value during the scanning process, define h max =h y+z2 ;

[0033] Step S35, scan row by row in this way to obtain the four boundary row and column numbers of the corrosion defect submatrix, which are the minimum row number i and the minimum row number t. min =i x , the maximum row number i max =i x+k , minimum column number j min =j y-min1 , maximum column number j max =j y+max1 , and the maximum depth h max =h y+zk .

[0034] Step S36: When scanning the corrosion defect morphology according to this method, if the non-zero value of the corrosion defect submatrix is ​​positive, it indicates internal corrosion. At this time, the corrosion defect depth h is the maximum value h. max As the target; when the non-zero value of the corrosion defect submatrix is ​​negative, it indicates external corrosion. At this time, the corrosion defect depth h is used to find the minimum value h min For the goal, the method is the same;

[0035] Step S37, determine the length, width and depth parameters of the corrosion defect: the axial length L of the corrosion defect is the difference of the maximum number of small rows in the range of the positive or negative submatrix plus 1, multiplied by the axial sampling interval, that is, L = (i max -i min +1)×d 0 The width of the corrosion defect W is the difference of the maximum number of small columns in the submatrix containing positive or negative numbers plus 1 multiplied by the circumferential sampling interval, that is: W = (j max -j min +1)×d 1 ; Internal corrosion depth h in That is, the maximum value h in the positive submatrix max , external corrosion depth h out is the minimum value h in the negative submatrix min ;

[0036] At the same time, record the minimum and maximum row numbers of the corrosion defect submatrix. The depth range is dep 1 ~dep 2 , that is, the depth range of the corrosion defect is dep 1 ~dep 2 ;

[0037] Repeat the above steps and analyze each corrosion defect one by one to determine the length, width, depth and depth of each corrosion defect in the wellbore.

[0038] Preferably, in step S4, the casing corrosion defects are classified according to the classification principle, and the internal corrosion defects corresponding to the positive submatrix specifically include:

[0039] When the corrosion depth |h in |≤0.1t, when the aspect ratio of the corrosion defect L / w≥1, it is a level III axial internal corrosion defect, and when L / w<1, it is a level III circumferential internal corrosion defect;

[0040] When the corrosion depth is 0.1t<|h in |≤0.3t, when the aspect ratio of the corrosion defect L / w≥1, it is a level II axial internal corrosion defect, and when L / w<1, it is a level II circumferential internal corrosion defect;

[0041] When the corrosion depth |h in |>0.3t, when the aspect ratio of the corrosion defect L / w≥1, it is a level I axial internal corrosion defect, and when L / w<1, it is a level I circumferential internal corrosion defect;

[0042] Similarly, the external corrosion defects corresponding to the negative value submatrix are classified, and the casing corrosion defects are statistically analyzed to determine the number of corrosion defects at each level, the type of corrosion defects, and the depth of the corrosion defects.

[0043] Preferably, for the corrosion defects in the casing, the development law of the corrosion in the casing is further analyzed according to the corrosion rate in the casing, and the corresponding remaining life evaluation is performed; the remaining life of the casing N = (t s-in -t c ) / f in ; Where: t s-in is the minimum remaining wall thickness at the internal corrosion site, mm; t c is the critical wall thickness, mm; f in is the corrosion rate inside the casing, mm / a;

[0044] For the corrosion defects outside the casing, the development law of the external corrosion of the casing is further analyzed according to the external corrosion rate of the casing, and the corresponding remaining life evaluation is carried out; the remaining life of the casing N = (t s-out -t c ) / f out , where: t s-outis the minimum remaining wall thickness at the external corrosion site, mm; t c is the critical wall thickness, mm; f out is the casing external corrosion rate, mm / a;

[0045] The minimum remaining life evaluated under the condition of internal and external corrosion of the casing is taken as the remaining life of the casing;

[0046] At the same time, if the casing has grade III corrosion defects, the subsequent casing safety assessment cycle will remain unchanged, and will still be assessed once every N years; if the casing has grade II corrosion defects, the subsequent casing safety assessment cycle will be shortened to 2 / 3 of the original assessment cycle, and will be assessed once every N×2 / 3 years; if the casing has grade I corrosion defects, the subsequent casing safety assessment cycle will be shortened to 1 / 3 of the original assessment cycle, and will be assessed once every N×1 / 3 years.

[0047] (III) Beneficial effects

[0048] The present invention provides a method for quantitatively identifying and grading casing corrosion morphology based on logging data. By processing and analyzing the casing logging data, key parameters such as the length, width, and depth of the casing corrosion defects, as well as the three-dimensional spatial position of the corrosion defects, are efficiently obtained, and the corrosion defects are quantitatively graded according to their geometric parameters, which can provide an important basis for casing safety evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 The present invention is a flowchart of a method for quantitatively identifying and grading casing corrosion morphology based on well logging data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] like Figure 1 As shown, the present invention provides a method for quantitatively identifying and grading casing corrosion morphology based on well logging data, including:

[0052] A method for quantitatively identifying and grading casing corrosion morphology based on well logging data, characterized by comprising:

[0053] Step S1, determine various standard parameters of the casing and obtain the inner and outer radii of the casing;

[0054] Step S2, standardize the inner diameter filtering process of the casing inner diameter logging matrix to construct a binary casing inner diameter logging data matrix; standardize the wall thickness filtering process of the casing wall thickness logging matrix to construct a binary casing wall thickness logging data matrix; and merge the above casing logging data matrices to obtain a casing logging matrix that can comprehensively reflect the internal and external corrosion of the casing;

[0055] Step S3, extracting casing corrosion defect submatrix information, by scanning the corrosion defect submatrix row by row, extracting the row and column numbers of the boundaries of each inner corrosion submatrix, determining the length, width, and depth parameters of each casing inner corrosion defect, and the depth range of the inner corrosion defect;

[0056] Extract the row and column numbers of the boundaries of each external corrosion submatrix, determine the length, width, and depth parameters of each casing internal corrosion defect, and the depth range of the external corrosion defect;

[0057] Step S4: Classify the casing corrosion defects according to the extracted casing internal and external corrosion defect information and the classification principle.

[0058] In this embodiment, the method further includes: step S5, evaluating the remaining service life of the casing based on the quantitative classification result of the casing corrosion defects, and adjusting the subsequent casing safety inspection cycle.

[0059] Wherein, step S1 specifically includes:

[0060] The inner radius of the casing r=(Dt×2) / 2, and the outer radius of the casing R=D / 2, wherein D is the standard diameter of the casing of the target well, and t is the standard wall thickness of the casing.

[0061] Step S2 specifically includes: based on the logging data, obtaining a two-dimensional matrix of casing inner diameters, using a multi-arm caliper logging instrument to detect the target well, and using the interpretation software to convert the logging data into a two-dimensional matrix of m×a excluding the depth column, where each row of the matrix corresponds to the casing inner diameter value of each sampling point in the axial direction of the casing, and the axial interval is d 0 ; Each column of the matrix corresponds to the inner diameter value of each sampling point on the circumference of the casing. The order of each column represents the measurement arm number of the multi-arm caliper. The arm number ranges from 1 to a. The value of a is the number of arms of the multi-arm caliper and the corresponding phase range. That is, the corresponding phase range of each column is (p 1 -1)×360° / a to p 1 ×360° / a, where p 1 =1, 2, ....a, and the circumferential sampling interval can be deduced to be d 1 =(2×3.14×r) / a.

[0062] Obtain casing wall thickness two-dimensional matrix: Use electromagnetic wall thickness logging instrument to detect the target well, and use interpretation software to convert the logging data into a two-dimensional matrix of m×b, excluding the depth column. Each row of the matrix corresponds to the casing wall thickness value of each sampling point in the axial direction of the casing, and the axial interval is also d. 0 ; Each column of the matrix corresponds to the wall thickness value of each sampling point on the casing circumference, and each column represents the wall thickness logging sector number in sequence. The sector number ranges from 1 to b, and the value of b is the wall thickness logging sector number and the corresponding phase range, that is, the corresponding phase range of each column is (p 2 -1)×360° / b to p 2 ×360° / b, where p 2 =1, 2, ...b, and it can be deduced that the circumferential sampling interval is d 2 =(2×3.14×r) / b.

[0063] The casing inner diameter matrix is ​​subjected to standardized inner diameter filtering: a filtering threshold is set to 1.02r, and the matrix is ​​filtered. Elements below the threshold are set to 0, indicating no corrosion defects; elements above the threshold are subtracted from the threshold, indicating corrosion defects;

[0064] After filtering, the matrix is ​​transformed into a binary matrix A with only 0 and positive values. The positive value area corresponds to the corrosion defect area, and the maximum positive value corresponds to the maximum corrosion depth. The larger the positive value, the greater the corrosion depth.

[0065] The casing wall thickness matrix is ​​subjected to standardized wall thickness filtering: through a filtering threshold, the threshold is set to 0.875t, the matrix is ​​filtered, and the elements above the threshold are set to 0, indicating no corrosion defects; the elements below the threshold are subtracted from the threshold, indicating corrosion defects. After filtering, the matrix is ​​converted into a binary matrix B with only 0 and negative values. The negative value area corresponds to the corrosion defect area, and the minimum negative value corresponds to the maximum corrosion depth.

[0066] Determine internal and external corrosion defects: combine the values ​​of each column in the A matrix with the values ​​of each column in the corresponding phase of the B matrix. If the phase of each column in the B matrix can contain k columns on the corresponding phase of the A matrix (K≥2), then first perform equal value expansion on each column of the B matrix, that is, add k-1 columns to the right of each column of the B matrix, and assign the corresponding values ​​of each column of the original B matrix to the newly added columns on the right to obtain a new matrix B';

[0067] When merging matrices A and B', if the corresponding value in the B' matrix is ​​0, the value in the A matrix remains unchanged. If the corresponding value in the B matrix is ​​a negative number and the corresponding value in the A matrix is ​​0, the value in the A matrix is ​​assigned to the value in the B' matrix; that is, the A matrix is ​​converted into a new matrix A', and the matrix A' contains negative numbers, 0, and positive numbers, where the distribution range of positive values ​​indicates that the corrosion defect is on the inner wall of the casing, and the distribution range of negative values ​​indicates that the defect is on the outer wall of the casing.

[0068] Wherein, step S3 specifically includes:

[0069] The area containing positive or negative values ​​is divided into a submatrix, and each submatrix corresponds to a corrosion defect. The specific method is as follows:

[0070] Step S31: define the number of rows in the casing logging data matrix A' as i 1 、i 2 、....i n , define the number of matrix columns as j 1 、j 2 、....j a , then we get i n Row and J a Matrix steps of columns;

[0071] Step S32: Scan the matrix row by row from left to right. When the first non-zero value is found, taking a positive value as an example, the row number and column number are i. x 、j y , the value is h y , define the minimum and maximum row number i min =i max =i x , define the minimum and maximum column number j min =j max =j y , define the maximum depth h max =h y ;

[0072] Step S33, then continue to scan to the right, when the adjacent data is still non-zero, the row number and column number are i x 、j y+1 , the value is h y+1 , then the minimum and maximum row numbers i are still defined min =i max =i x , and define the minimum column number as j min =j y , maximum column number j max =j y+1 ; such as h y+1 >h y , then define h max =hy+1 . Continue scanning to the right until the last non-zero value in this row is found. At this time, the row number and column number are i x 、j y+t , then the minimum and maximum row numbers i are still defined min =i max =i x , and the minimum column number is still defined as j min =j y , maximum column number j max =j y+t ; such as h y to h y+t Medium y+z1 The value of is the largest, then the maximum value is defined as h max =h y+z1 ;

[0073] Step S34: Continue scanning the next row line by line in this way, starting from row and column number i. x+1 The row, j y ~j y+t The column with the first non-zero value on the left side of the column range is scanned once to the left and once to the right from the starting point. For example, scan left to the column number j with the leftmost non-zero value. y-m1 ≤j y , then define the minimum column number j min =j y-m1 , such as scanning the rightmost non-zero column number j to the right y+t+m2 ≥j y+t , then define the maximum column number j max =j y+t+m2 . At the same time, define the minimum row number i min =i x , the maximum row number i max =i x+1 . And find the maximum value during the scanning process, define h max =h y+z2 ;

[0074] Step S35, and so on, scan and obtain the four boundary row and column numbers of the corrosion defect, which are the minimum row number i and the minimum row number t. min =i x , the maximum row number i max =i x+k , minimum column number j min =j y-min1 , maximum column number j max =j y+max1 , and the maximum depth h max =h y+zk .

[0075] Step S36: When scanning the corrosion defect according to this method, if the non-zero value of the corrosion defect submatrix is ​​positive, it indicates internal corrosion. At this time, the corrosion defect depth h is the maximum value h. max As the target; when the non-zero value of the corrosion defect submatrix is ​​negative, it indicates external corrosion. At this time, the corrosion defect depth h is used to find the minimum value h min For the goal, the method is the same;

[0076] Step S37, determine the length, width and depth parameters of the corrosion defect: the axial length L of the corrosion defect is the difference of the maximum number of small rows in the range of the positive or negative submatrix plus 1, multiplied by the axial sampling interval, that is, L = (i max -i min +1)×d 0 The width of the corrosion defect W is the difference of the maximum number of small columns in the range of the positive or negative submatrix plus 1 multiplied by the circumferential sampling interval, that is: W = (j max -j min +1)×d 1 ; Internal corrosion depth h in That is, the maximum value h in the positive submatrix max , external corrosion depth h out is the minimum value h in the negative submatrix min ;

[0077] At the same time, record the minimum and maximum row numbers of the corrosion defect submatrix. The depth range is dep 1 ~dep 2 , that is, the range of the corrosion defect is dep 1 ~dep 2 ;

[0078] Repeat the above steps and analyze each corrosion defect one by one to determine the length, width, depth and depth of each corrosion defect in the wellbore.

[0079] Among them, in step S4, the casing corrosion defects are classified according to the classification principle, and the internal corrosion defects corresponding to the positive submatrix specifically include:

[0080] When the corrosion depth |h in |≤0.1t, when the aspect ratio of the corrosion defect L / w≥1, it is a level III axial internal corrosion defect, and when L / w<1, it is a level III circumferential internal corrosion defect;

[0081] When the corrosion depth is 0.1t<|h in |≤0.3t, when the aspect ratio of the corrosion defect L / w≥1, it is a level II axial internal corrosion defect, and when L / w<1, it is a level II circumferential internal corrosion defect;

[0082] When the corrosion depth |h in|>0.3t, when the aspect ratio of the corrosion defect L / w≥1, it is a level I axial internal corrosion defect, and when L / w<1, it is a level I circumferential internal corrosion defect.

[0083] Similarly, the external corrosion defects corresponding to the negative value submatrix are classified, and the casing corrosion defects are statistically analyzed to determine the number of corrosion defects at each level, the type of corrosion defects, and the depth of the corrosion defects.

[0084] According to the corrosion defects in the casing, the development law of the corrosion in the casing is further analyzed according to the corrosion rate in the casing, and the corresponding remaining life evaluation is carried out; the remaining life of the casing N = (t s-in -t c ) / f in ; Where: t s-in is the minimum remaining wall thickness at the internal corrosion site, mm; t c is the critical wall thickness, mm; f in is the corrosion rate inside the casing, mm / a.

[0085] For the corrosion defects outside the casing, the development law of the external corrosion of the casing is further analyzed according to the external corrosion rate of the casing, and the corresponding remaining life evaluation is carried out; the remaining life of the casing N = (t s-out -t c ) / f out , where: t s-out is the minimum remaining wall thickness at the external corrosion site, mm; t c is the critical wall thickness, mm; f out is the casing external corrosion rate, mm / a.

[0086] The minimum remaining life evaluated under the condition of internal and external corrosion of the casing is taken as the remaining life of the casing;

[0087] At the same time, if the casing has grade III corrosion defects, the subsequent casing safety assessment cycle will remain unchanged, and will still be assessed once every N years; if the casing has grade II corrosion defects, the subsequent casing safety assessment cycle will be shortened to 2 / 3 of the original assessment cycle, and will be assessed once every N×2 / 3 years; if the casing has grade I corrosion defects, the subsequent casing safety assessment cycle will be shortened to 1 / 3 of the original assessment cycle, and will be assessed once every N×1 / 3 years.

[0088] The specific application of the casing corrosion morphology quantitative identification and classification method based on logging data is described in detail below:

[0089] (1) Determine the inner and outer radius and wall thickness of the target well casing. In this example, the commonly used casing outer diameter D = 139.7 mm and wall thickness t = 7.72 mm are used as an example. The inner radius of the casing r = (Dt × 2) / 2 = 62.13 mm and the outer radius of the casing R = D / 2 = 69.85 mm.

[0090] (2) Obtaining a two-dimensional matrix of casing inner diameter: In this example, 24-arm caliper logging is performed, with an axial sampling interval of d 0 =25mm, and the measurement depth range is 804.025~804.400m. As an example, the logging data is exported into a two-dimensional matrix of 16×24 except the depth column through the logging interpretation software, as shown in Table 2. Each row of the matrix corresponds to the inner diameter value of the casing at the depth of each sampling point in the casing axial direction; each column of the matrix corresponds to the inner diameter value of each sampling point in the casing circumferential direction. The order of each column represents the measurement arm number of the multi-arm caliper instrument, which ranges from 1 to 24, and the corresponding phase range. The corresponding phase range of each column is 360° / 24=15°, that is, the phase range of each column is 0~15°, 15°~30°....345°~360°, and it can be deduced that the circumferential sampling interval is d 1 =(2×3.14×r) / a=16.26mm.

[0091] Table 2 Two-dimensional matrix of casing inner diameter

[0092]

[0093] (3) Obtaining a two-dimensional matrix of casing wall thickness: In this case, 12-sector electromagnetic thickness logging is performed, with an axial sampling interval of d 0 =25mm, and the measurement depth range is 804.025~804.400m. For example, the logging data is converted into a two-dimensional matrix of 16×12 except the depth column through the logging interpretation software, as shown in Table 3. Each row of the matrix is ​​the casing wall thickness value corresponding to the depth of each sampling point in the axial direction of the casing wall thickness; each column of the matrix is ​​the wall thickness value corresponding to each sampling point in the circumferential direction of the casing. The order of each column represents the wall thickness logging sector number, which ranges from 1 to 12, and the corresponding phase range. The phase range of each column is 360° / 12=30°, that is, the phase range of each column is 0~30°, 30°~60°....330°~360°, and it can be deduced that the circumferential sampling interval is d 2 =(2×3.14×r) / b=32.52mm.

[0094] Table 3 Casing wall thickness two-dimensional matrix

[0095]

[0096] (4) The casing inner diameter matrix is ​​subjected to standardized inner diameter filtering: the matrix is ​​filtered using a filtering threshold of 1.02r = 1.02 × 62.13 = 63.37. Elements below the threshold are set to 0; elements above the threshold are subtracted by 63.37. After filtering, the matrix is ​​converted into a binary matrix A containing only 0 and positive values, as shown in Table 4.

[0097] Table 4 Two-dimensional matrix A of casing inner diameter after filtering

[0098]

[0099]

[0100] (5) Standardized filtering of the casing wall thickness matrix: The matrix is ​​filtered using a filtering threshold of 0.875t = 0.875 × 7.72 = 6.76. Elements above the threshold are set to 0, and elements below the threshold are subtracted by 6.76. After filtering, the matrix is ​​converted into a binary matrix B containing only 0 and negative values, as shown in Table 5.

[0101] Table 5 Two-dimensional matrix B of casing wall thickness after filtering

[0102]

[0103] (6) Determine internal and external corrosion defects: Merge the values ​​of each column in the A matrix with the values ​​of each column in the corresponding phase of the B matrix. If each column of the B matrix can contain two columns corresponding to the phase of the A matrix, then first perform equal value expansion on each column of the B matrix, that is, add one column to the right of each column of the B matrix, and assign the corresponding values ​​of each column of the original B matrix to the newly added columns on the right to obtain a new matrix B', as shown in Table 6. When merging matrices A and B', if the corresponding phase value in the B' matrix is ​​0, the value in the A matrix remains unchanged. If the corresponding phase value in the B matrix is ​​negative and the corresponding value in the A matrix is ​​0, the value in the A matrix is ​​assigned to the value in the B' matrix. Convert the A matrix into a new casing corrosion defect composite matrix A', which contains negative values, 0, and positive values. The positive value distribution range indicates that the corrosion defect is on the inner wall of the casing, and the negative value distribution range indicates that the defect is on the outer wall of the casing, as shown in Table 7.

[0104] Table 6B Matrix is ​​expanded to get matrix B'

[0105]

[0106] Table 7 Casing corrosion defect composite matrix A'

[0107]

[0108] (7) Extracting the corrosion defect submatrix: Divide each region containing positive or negative values ​​into a submatrix. Each submatrix corresponds to a corrosion defect. Scan row by row to obtain the row and column numbers of the corrosion defect boundary. In this example, the positive value matrix of the corrosion in the casing is scanned as an example.

[0109] ① Definition of row number of casing logging data matrix A'i 1 、i 2 、....i 16 , define the number of matrix columns as j 1 、j 2 、....j 24, then a matrix with 16 rows and 24 columns is obtained, as shown in Table 8.

[0110] Table 8 Definition of row and column numbers of casing corrosion defect composite matrix A'

[0111]

[0112] ② Scan the matrix row by row from left to right. When the first non-zero value is found, the row number i x 3, column number j y is 4, value h y is 0.1, defining the minimum and maximum row numbers i min =i max =3, define the minimum and maximum column numbers j min =j max =4, defines the maximum depth h max =0.1.

[0113] ③ Then continue scanning to the right. When the adjacent data is still non-zero, the row number i x 3, column number j y+1 is 5, value h y+1 is 0.2, the minimum and maximum row numbers i are still defined min =i max =3, and define the minimum column number as j min =4, maximum column number j max =5; due to h y+1 >h y , then define h max =h y+1 = 0.2. Continue scanning rightward until the last non-zero value in this row is found. Since this example has reached the rightmost non-zero value, the scan of this row ends. At this time, the row number i x 3, column number j y+1 If it is 5, the minimum and maximum row numbers i are still defined. min =i max =3, and the minimum column number is still defined as j min =4, maximum column number j max =5, define the maximum value as h max =0.2.

[0114] ④Continue scanning the next row in this way, with the row and column number of the starting point being i x+1 The row, i.e. row 4, j y ~j y+1 The column where the first non-zero value on the left side of the column range is located, that is, the column where the first non-zero value on the left side of the range of columns 4 to 5 is located, the 4th column; so the starting row number of the scan is 4 and the column number is 4.

[0115] The scanning direction is to scan leftward once and rightward once from the starting point, and the leftmost column number that has a non-zero value is 3. Since column number 3 ≤ column number 4, the minimum column number j is defined. min =3, scan rightwards, the column number of the rightmost non-zero value is 5, since column number 5 ≥ column number 5, the maximum column number j is defined max = 5. At the same time, define the minimum row number i min =i x =3, maximum row number i max =i x+1 =4. And find the maximum value during the scanning process, define h max =0.6.

[0116] ⑤ Similarly, the four boundary row and column numbers of the corrosion defect are obtained by scanning, which are the minimum row number i and min =i x =3, maximum row number i max =i x+k =15, minimum column number j min =j y-min1 =2, maximum column number j max =j y+max1 =6, and the maximum depth value h max =3.4.

[0117] ⑥ When scanning according to this method, if a non-zero value is found to be positive, it indicates internal corrosion. At this time, the corrosion defect depth h is the maximum value h. max As the target; when the scanned value is negative, it indicates external corrosion. At this time, the h value of the corrosion defect is to find the minimum value h min The goal is the same, the method is the same.

[0118] (8) Determine the length, width, and depth parameters of the corrosion defect: The axial length L of the corrosion defect is the difference between the maximum number of small rows in the range of the positive or negative submatrix plus 1, multiplied by the axial sampling interval, that is, L = (i max -i min +1)×d 0 =(15-3+1)×25=325mm; the width of the corrosion defect W is the difference of the maximum number of small columns in the range of the positive or negative submatrix plus 1 multiplied by the circumferential sampling interval, that is: W=(j max -j min +1)×d 1 =(6-2+1)×16.26=81.3mm; the internal corrosion depth is the maximum value h in the positive submatrix max = 3.4. At the same time, the minimum and maximum line number depths are recorded in the range of 804.075 to 804.375, and the corrosion defect is in the range of 804.075 to 804.375.

[0119] (9) Repeat the method of steps 7 to 8 to analyze each corrosion defect one by one to determine the length, width, depth, and depth of each corrosion defect;

[0120] In this example, there are two corrosion defects. The inner corrosion defect corresponds to the submatrix C1 with a range of 3 to 15 rows, 2 to 6 columns, and a depth range of 804.075 to 804.375. The outer corrosion defect corresponds to the matrix C2 with a range of 7 to 11 rows, 15 to 22 columns, and a depth range of 804.175 to 804.275, see Tables 9 and 10.

[0121] Table 9 Internal corrosion defect sub-matrix C1

[0122]

[0123] Table 10 External corrosion defect submatrix C2

[0124]

[0125] (10) Classification of corrosion defects: Corrosion defect C1 element is positive, which is internal corrosion, |h in |=3.4≥0.3t, the aspect ratio of the corrosion defect L / w=3.99≥1, which is a level I axial internal corrosion defect. The C2 element of the corrosion defect is a negative value, which is external corrosion, 0.2t<|h out |=2.3≤0.3t, the aspect ratio of the corrosion defect L / w=0.96<1, which is a level II circumferential external corrosion defect. The casing has 1 level I axial internal corrosion defect and 1 level II circumferential external corrosion defect.

[0126] (11) The development law of casing corrosion is analyzed based on the casing corrosion rate, and corresponding safety assessment is carried out. in =0.1mm / a as an example, the minimum remaining wall thickness of the casing at the corrosion defect is t s-in =6.2-3.4=2.8mm, according to the critical wall thickness t c =2mm analysis, the remaining life of the casing N = (t s-in -t c ) / f=(2.8-2.0) / 0.1=8 years.

[0127] According to the external corrosion rate of casing, the development law of external corrosion of casing is further analyzed, and corresponding safety assessment is carried out. out =0.15mm / a as an example, the minimum remaining wall thickness of the casing is t s-out =6.2-2.3=3.9mm, according to the critical wall thickness t c =2mm analysis, the remaining life of the casing is N = (t s-out -t c) / f=(3.9-2.0) / 0.15=12.7 years.

[0128] Based on the quantitative identification results of casing corrosion morphology, the remaining life of the casing is finally assessed to be 8 years.

[0129] (12) Based on the quantitative identification results of casing corrosion defects, the casing contains level I corrosion defects, so the subsequent casing safety assessment period is shortened to 1 / 3 of the original assessment period. According to the original safety assessment period N = 10 years, after the quantitative identification of the casing corrosion morphology this time, the safety assessment period is adjusted to N×1 / 3=10×1 / 3=3 years.

[0130] The above implementation modes are only used to illustrate the present invention, but not to limit the present invention. Ordinary technicians in the relevant technical field can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, all equivalent technical solutions also belong to the scope of the present invention. The patent protection scope of the present invention should be defined by the claims.

Claims

1. A method for quantitative identification and classification of casing corrosion morphology based on logging data, characterized in that: include: Step S1, determine various standard parameters of the casing and obtain the inner and outer radii of the casing; Step S2, standardize the inner diameter filtering process of the casing inner diameter logging matrix to construct a binary casing inner diameter logging data matrix; standardize the wall thickness filtering process of the casing wall thickness logging matrix to construct a binary casing wall thickness logging data matrix; and merge the above casing logging data matrices to obtain a casing logging matrix that can comprehensively reflect the internal and external corrosion of the casing; Step S3, extracting casing corrosion defect submatrix information, by scanning the corrosion defect submatrix row by row, extracting the row and column numbers of the boundaries of each inner corrosion submatrix, determining the length, width, and depth parameters of each casing inner corrosion defect, and the depth range of the inner corrosion defect; Extract the row and column numbers of the boundaries of each external corrosion submatrix, determine the length, width, depth parameters of each casing external corrosion defect, and the depth range of the external corrosion defect; Step S4: Classify the casing corrosion defects according to the extracted casing internal and external corrosion defect information and the classification principle.

2. The method for quantitative identification and classification of casing corrosion morphology based on logging data according to claim 1, characterized in that: Also includes: Step S5: Based on the quantitative classification results of casing corrosion defects, the remaining service life of the casing is evaluated, and the subsequent casing safety inspection cycle is adjusted.

3. The method for quantitative identification and classification of casing corrosion morphology based on well logging data according to claim 1, characterized in that: Step S1 specifically includes: The inner radius of the casing r=(Dt×2) / 2, and the outer radius of the casing R=D / 2, wherein D is the standard diameter of the casing of the target well, and t is the standard wall thickness of the casing.

4. The method for quantitative identification and classification of casing corrosion morphology based on well logging data according to claim 1, characterized in that: The step S2 comprises: based on the logging data, obtaining a two-dimensional matrix of the inner diameter of the casing: converting the logging data into a two-dimensional matrix of m×a except for the depth column, wherein each row of the matrix is ​​the inner diameter value of the casing corresponding to the depth of each sampling point in the axial direction of the casing, and the axial interval is d0; each column of the matrix corresponds to the inner diameter value of each sampling point in the circumferential direction of the casing, and each column sequentially represents the measurement arm number of the multi-arm caliper, the arm number ranges from 1 to a, the value of a is the number of arms of the multi-arm caliper, and the corresponding phase range, that is, each column corresponds to a phase range of (p1-1)×360° / a to p1×360° / a, wherein p1=1, 2, ....a, and it can be deduced that the circumferential sampling interval is d1=(2×3.14×r) / a; Get the two-dimensional matrix of casing wall thickness: convert the logging data into a two-dimensional matrix of m×b excluding the depth column. Each row of the matrix is ​​the casing wall thickness value corresponding to the depth of each sampling point in the casing axial direction, and the axial interval is also d0; each column of the matrix corresponds to the wall thickness value of each sampling point in the casing circumferential direction, and each column represents the wall thickness logging sector number in sequence, the sector number ranges from 1 to b, the value of b is the wall thickness logging sector number, and the corresponding phase range, that is, each column corresponds to the phase range of (p2-1)×360° / b to p2×360° / b, where p2=1, 2, ...b, and it can be deduced that the circumferential sampling interval is d2=(2×3.14×r) / b.

5. The method for quantitative identification and classification of casing corrosion morphology based on well logging data according to claim 1, characterized in that: Step S2 also includes: The casing inner diameter matrix is ​​subjected to standardized inner diameter filtering: a filtering threshold is generally set to 1.02r, and the matrix is ​​filtered. Elements below the threshold are set to 0, indicating no corrosion defects; elements above the threshold are subtracted from the threshold, indicating corrosion defects; after filtering, the matrix is ​​converted into a binary matrix A with only 0 and positive values, the positive value area corresponds to the corrosion defect area, the maximum positive value corresponds to the maximum corrosion depth, and the larger the positive value, the greater the corrosion depth; The casing wall thickness matrix is ​​subjected to standardized wall thickness filtering: a filtering threshold is used, which is generally set to 0.875t, and the matrix is ​​filtered. Elements above the threshold are set to 0, indicating no corrosion defects; elements below the threshold are subtracted from the threshold, indicating corrosion defects; after filtering, the matrix is ​​converted into a binary matrix B with only 0 and negative values, the negative value area corresponds to the corrosion defect area, and the minimum negative value corresponds to the maximum corrosion depth; Determine internal and external corrosion defects: merge the values ​​of each column in the A matrix with the values ​​of each column in the corresponding phase of the B matrix. If the phase of each column of the B matrix can contain k columns on the corresponding phase of the A matrix (K≥2), then first perform equal value expansion on each column of the B matrix, that is, add k-1 columns to the right of each column of the B matrix, and assign the corresponding values ​​of each column of the original B matrix to the newly added columns on the right to obtain a new matrix B'; when merging matrices A and B', if the corresponding value in the B' matrix is ​​0, the value in the A matrix remains unchanged; if the corresponding value in the B matrix is ​​a negative number, and the corresponding value in the A matrix is ​​0, then the value in the A matrix is ​​assigned to the value in the B' matrix; that is, convert the A matrix into a new matrix A', which contains negative numbers, 0, and positive numbers, where the distribution range of positive values ​​indicates that the corrosion defect is on the inner wall of the casing, and the distribution range of negative values ​​indicates that the defect is on the outer wall of the casing.

6. The method for quantitative identification and classification of casing corrosion morphology based on logging data according to claim 1, characterized in that: Step S3 specifically includes: The area containing positive or negative values ​​is divided into a submatrix, and each submatrix corresponds to a corrosion defect. The specific method is as follows: Step S31, define the number of rows of the casing logging data matrix A' as i1, i2, ....i n , define the number of matrix columns as j1, j2, ....j a , then we get i n Row and J a Matrix steps of columns; Step S32: Scan the matrix row by row from left to right. When the first non-zero value is found, taking a positive value as an example, the row number and column number are i. x 、j y , the value is h y , define the minimum and maximum row number i min =i max =i x , define the minimum and maximum column number j min =j max =j y , define the maximum depth h max =h y ; Step S33, then continue to scan to the right, when the adjacent data is still non-zero, the row number and column number are i x 、j y+1 , the value is h y+1 , then the minimum and maximum row numbers i are still defined min =i max =i x , and define the minimum column number as j min =j y , maximum column number j max =j y+1 ; such as h y+1 >h y , then define h max =h y+1 ; Continue scanning to the right until the last non-zero value in this row is found. At this time, the row number and column number are i x 、j y+t , then the minimum and maximum row numbers i are still defined min =i max =i x , and the minimum column number is still defined as j min =j y , maximum column number j max =j y+t ; such as h y to h y+t Medium y+z1 The value of is the largest, then the maximum value is defined as h max =h y+z1 ; Step S34: Continue scanning the next row in this way, starting from row and column number i. x+1 The row, j y ~j y+t The column with the first non-zero value on the left side of the column range is scanned once to the left and once to the right from the starting point. For example, scan left to the column number j with the leftmost non-zero value. y-m1 ≤j y , then define the minimum column number j min =j y-m1 , such as scanning the rightmost non-zero column number j to the right y+t+m2 ≥j y+t , then define the maximum column number j max =j y+t+m2 ; Also define the minimum row number i min =i x , the maximum row number i max =i x+1 ; and find the maximum value during the scanning process, define h max =h y+z2 ; Step S35, scan row by row in this way to obtain the four boundary row and column numbers of the corrosion defect submatrix, which are the minimum row number i and the minimum row number t. min =i x , the maximum row number i max =i x+k , minimum column number j min =j y-min1 , maximum column number j max =j y+max1 , and the maximum depth h max =h y+zk ; Step S36: When scanning the corrosion defect morphology according to this method, if the non-zero value of the corrosion defect submatrix is ​​positive, it indicates internal corrosion. At this time, the corrosion defect depth h is the maximum value h. max As the target; when the non-zero value of the corrosion defect submatrix is ​​negative, it indicates external corrosion. At this time, the corrosion defect depth h is used to find the minimum value h min For the goal, the method is the same; Step S37, determine the length, width and depth parameters of the corrosion defect: the axial length L of the corrosion defect is the difference of the maximum number of small rows in the range of the positive or negative submatrix plus 1, multiplied by the axial sampling interval, that is, L = (i max -i min +1)×d0; the width of the corrosion defect W is the difference of the maximum number of small columns in the range of the positive or negative submatrix plus 1, multiplied by the circumferential sampling interval, that is: W=(j max -j min +1)×d1; internal corrosion depth h in That is, the maximum value h in the positive submatrix max , external corrosion depth h out is the minimum value h in the negative submatrix min ; At the same time, the depth range of the minimum and maximum row numbers of the corrosion defect submatrix is ​​recorded as dep1 to dep2, that is, the depth range of the corrosion defect is dep1 to dep2; Repeat the above steps and analyze each corrosion defect one by one to determine the length, width, depth and depth of each corrosion defect in the wellbore.

7. The method for quantitative identification and classification of casing corrosion morphology based on well logging data according to claim 1, characterized in that: In step S4, the casing corrosion defects are classified according to the classification principle, and the internal corrosion defects corresponding to the positive submatrix specifically include: When the corrosion depth |h in |≤0.1t, when the aspect ratio of the corrosion defect L / w≥1, it is a level III axial internal corrosion defect, and when L / w<1, it is a level III circumferential internal corrosion defect; When the corrosion depth is 0.1t<|h in |≤0.3t, when the aspect ratio of the corrosion defect L / w≥1, it is a level II axial internal corrosion defect, and when L / w<1, it is a level II circumferential internal corrosion defect; When the corrosion depth |h in |>0.3t, when the aspect ratio of the corrosion defect L / w≥1, it is a level I axial internal corrosion defect, and when L / w<1, it is a level I circumferential internal corrosion defect; Similarly, the external corrosion defects corresponding to the negative value submatrix are classified, and the casing corrosion defects are statistically analyzed to determine the number of corrosion defects at each level, the type of corrosion defects, and the depth of the corrosion defects.

8. The method for quantitative identification and classification of casing corrosion morphology based on well logging data according to claim 1, characterized in that: According to the corrosion defects in the casing, the development law of the corrosion in the casing is further analyzed according to the corrosion rate in the casing, and the corresponding remaining life evaluation is carried out; the remaining life of the casing N = (t s-in -t c ) / f in ; Where: t s-in is the minimum remaining wall thickness at the internal corrosion site, mm; t c is the critical wall thickness, mm; f in is the corrosion rate inside the casing, mm / a; For the corrosion defects outside the casing, the development law of the external corrosion of the casing is further analyzed according to the external corrosion rate of the casing, and the corresponding remaining life evaluation is carried out; the remaining life of the casing N = (t s-out -t c ) / f out , where: t s-out is the minimum remaining wall thickness at the external corrosion site, mm; t c is the critical wall thickness, mm; f out is the casing external corrosion rate, mm / a; The minimum remaining life evaluated under the condition of internal and external corrosion of the casing is taken as the remaining life of the casing; At the same time, if the casing has grade III corrosion defects, the subsequent casing safety assessment cycle will remain unchanged, and will still be assessed once every N years; if the casing has grade II corrosion defects, the subsequent casing safety assessment cycle will be shortened to 2 / 3 of the original assessment cycle, and will be assessed once every N×2 / 3 years; if the casing has grade I corrosion defects, the subsequent casing safety assessment cycle will be shortened to 1 / 3 of the original assessment cycle, and will be assessed once every N×1 / 3 years.

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