A method for determining perforation parameters based on a perforation image

Abstract

A kind of determination method of perforation parameter based on perforation image, first utilize ultra wide angle downhole camera to obtain downhole perforation image, and mark contour in graph, finally extract calculation, determine the only maximum diameter and minimum diameter of perforation, and determine other parameters along with it, the algorithm principle of the present application is simple, low complexity, high reliability, strong adaptability, can obtain the diameter of irregular perforation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of shale oil and gas horizontal well perforation fracturing evaluation in the oil and gas industry, and particularly relates to a perforation parameter determination method based on a perforation image, which is a quantitative perforation abrasion measurement technology based on a forward-looking ultra-wide-angle oil and gas well visual detection instrument. BACKGROUND

[0002] The horizontal well segmented multi-cluster perforation abrasion monitoring technology uses a downhole visual imaging device to obtain a perforation image, monitors the perforation abrasion degree after fracturing, evaluates the perforation fracturing effect, and has been proved to be an effective shale oil and gas horizontal well segmented multi-cluster perforation fracturing evaluation method.

[0003] Perforation abrasion monitoring has been tested in oil and gas fields such as Xinjiang, Changqing, Daqing, and Southwest of China, and gradually expanded in application. Perforation abrasion monitoring obtains a perforation image through coiled tubing delivery horizontal well visual logging, measures perforation parameters, analyzes and evaluates the fracturing effect through the erosion and abrasion degree of perforation, studies the influence of perforation methods, fracturing parameters, and temporary plugging agents on the fracturing effect, and optimizes fracturing design and technology.

[0004] Shale oil and gas wells usually have long horizontal sections, a large number of perforations, and a large amount of perforation parameter measurement work. Intelligent algorithms are needed to automatically measure the aperture parameters to reduce human influence and improve work efficiency. The current mainstream technology is mainly based on an array ring scanning camera from abroad, which realizes quantitative measurement of perforation parameters. When the array ring scanning camera scans a perforation, the complete image of the perforation is composed of four images, and finally the Vernier function of the related software is used to measure the parameters of the perforation. It is generally believed in the field that the forward-looking ultra-wide-angle camera cannot accurately and quantitatively determine the perforation parameters of the perforation image, because the image obtained by the forward-looking ultra-wide-angle camera is severely distorted, and there is no suitable image calculation correction method. Therefore, there is no method for accurately measuring perforation parameters in the related field in China at present. Therefore, the perforation recorded by the forward-looking ultra-wide-angle camera is only in the form of an image, and the related data of the perforation cannot be obtained, and accurate perforation measurement is an important link in evaluating the fracturing effect.

[0005] The ideal perforation is circular, but due to the long horizontal section of shale oil and gas wells, the large number of perforations, and the various shapes of the actual perforations after fracturing, most of them are irregular circles, and a small part of them are special-shaped holes. The commonly used method for measuring the aperture is the minimum circumscribed circle method to measure the long axis and the maximum inscribed circle method to measure the short axis. This method has a relatively complex algorithm, and the maximum and minimum diameters obtained do not pass through the center of the hole, and cannot be directly marked on the image. SUMMARY

[0006] In order to overcome the defects of the prior art, the present application aims to provide a method for determining perforation parameters based on perforation images, which is based on in-pipe visualization video for eccentricity correction and expansion transformation, uses a super-wide-angle downhole camera to obtain downhole perforation images, marks the contour in the image, and finally extracts and calculates, determines the unique maximum and minimum diameters of the perforation from the perforation image, and determines other parameters accordingly; the algorithm principle of the present application is simple, has low complexity, high reliability, and strong adaptability, and can obtain irregular hole diameters.

[0007] In order to achieve the above-mentioned purpose, the technical scheme of the present application is as follows:

[0008] A method for determining perforation parameters based on perforation images, comprising the following steps:

[0009] (1) Obtaining the maximum and minimum diameters of the perforation

[0010] (1.1) Marking the hole contour

[0011] Use a super-wide-angle downhole camera to obtain downhole perforation images, and mark the hole contour on the image of the hole with one color of the RGB three primary colors;

[0012] (1.2) Hole contour extraction

[0013] Use threshold discrimination method to extract the contour of the hole, and the discrimination formula is:

[0014] R / (R+G+B)>=TH

[0015] Wherein, R, G, B are the numerical values of the BMP image RGB three primary color components of the perforation image, the extracted contour is a set of point (x, y) coordinates on the boundary, and TH is the threshold value;

[0016] (1.3) Obtaining the coordinates (xo, yo) of the centroid O point

[0017]

[0018]

[0019] Wherein, N is the total number of contour line point sets, x i is the horizontal coordinate of each point, and y i is the vertical coordinate of each point;

[0020] (1.4) Calculating the maximum and minimum diameters of the perforation

[0021] Select a point A (x1, y1) on the contour boundary, calculate the slope of the centroid O point

[0022]

[0023] Scan the boundary, find a point B (x2, y2) with the same slope and k connected to the centroid O, and the B point and the A point are not on the same side of the centroid O, calculate the Euclidean distance between AB

[0024]

[0025] Make A point scan around the boundary, find all d AB The maximum and minimum values of Max(d AB ), the long axis length is Min(d AB );

[0026] (2), calculate the perforation area

[0027] The area is the number of points surrounded by the boundary, obtain the contour curve of the closed region and the coordinates of the curve, and automatically sum each pixel point in the region;

[0028] (3), calculate the average diameter of the perforation

[0029] The area surrounded by the boundary is S, and the average diameter is:

[0030]

[0031] (4), calculate the perforation circumference

[0032] The circumference is calculated by the Euclidean distance sum between two adjacent points on the boundary:

[0033]

[0034] Wherein,

[0035] (5), calculate the perforation roundness

[0036] The roundness is calculated by the following formula:

[0037]

[0038] (6), calculate the perforation azimuth

[0039] The centroid coordinates are (xo, yo), and the image width is w

[0040] Then the azimuth is:

[0041] Alpha=x o / w*360.

[0042] The beneficial effects of the present application are:

[0043] (1), the maximum diameter and the minimum diameter of the perforation are determined by using the calibrated perforation image, and then each parameter is obtained, the calculation principle is simple, the complexity is low, the reliability is high, and it is applicable to irregular hole diameters. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 The ultra-wide-angle visual logging instrument for obtaining the perforation image.

[0045] Figure 2 The coiled tubing logging downhole tool string combination for horizontal wells.

[0046] Figure 3 The obtained perforation original image.

[0047] Figure 4 The image is transformed to obtain a 360 panorama image around the well.

[0048] Figure 5 The 360° expanded image around the well.

[0049] Figure 6 The image of marking the hole contour.

[0050] Figure 7 The centroid and all diameters passing through the centroid are obtained.

[0051] Figure 8 The image of marking the maximum diameter, the minimum diameter and the measurement parameters.

[0052] Figure 9 The measurement and annotation image of a perforation cluster of a shale oil well.

[0053] Figure 10 The measurement and statistical data of a perforation cluster of a shale oil well. DETAILED DESCRIPTION

[0054] The present application will be described in detail below in combination with the drawings.

[0055] A perforation parameter determination method based on a perforation image, the content is as follows:

[0056] (1), the maximum and minimum diameters of the perforation are obtained

[0057] The downhole camera is used to obtain the downhole perforation image, for example Figure 1 The ultra-wide-angle visual logging instrument for obtaining the perforation image, when obtaining the image, the flexible nipple and the centralizing device should be used to center the camera in the wellbore, Figure 2 The downhole visual tool string for obtaining the downhole safety valve video image (patent application number CN201710708245.3), the obtained original image is as follows Figure 3, process the original image by filtering, denoising, camera calibration and other image processing techniques such as Figure 4 a 360 panorama image around the wellbore, such as Figure 5 a 360° expanded image around the wellbore.

[0058] (1.1) labeling the hole contour

[0059] Label the hole contour on the image of the hole with color, select one of the RGB three primary colors,

[0060] In particular, a red line can be selected to label the contour of the hole, such as Figure 6 .

[0061] (1.2) hole contour extraction

[0062] Use threshold discrimination method to extract the contour of the hole, the discrimination formula is:

[0063] R / (R+G+B)>=TH

[0064] Where R, G, B are the numerical values of the BMP image RGB three primary colors components of the perforation image, the extracted contour is the set of point (x, y) coordinates on the boundary, and TH is the threshold value.

[0065] (1.3) find the centroid O point coordinates (xo, yo)

[0066]

[0067]

[0068] N is the total number of contour line point sets, x i is the horizontal coordinate of each point, y i is the vertical coordinate of each point, Figure 7 is the centroid and all diameters passing through the centroid.

[0069] (1.4) calculate the maximum and minimum diameter of the perforation

[0070] Select a point A (x1, y1) on the contour boundary, calculate the slope with the centroid O point:

[0071]

[0072] Scan the boundary to find a point B (x2, y2) with the same slope k as the centroid O and B point and A point are not on the same side of the centroid O point, calculate the Euclidean distance between A and B:

[0073]

[0074] Make A point scan around the boundary, find the maximum and minimum value of all d AB , such asFigure 8 The image of the maximum diameter, minimum diameter and measurement parameters are marked, the long axis length is Max(d AB ), and the short axis length is Min(d AB ).

[0075] (2), calculating the perforation area

[0076] The area is the number of points surrounded by the boundary. The contour curve of the closed region and the coordinates of the curve are obtained, and each pixel point in the region is automatically summed.

[0077] (3), calculating the average diameter of the perforation

[0078] The area surrounded by the boundary is S, and the average diameter is:

[0079]

[0080] (4), calculating the perforation circumference

[0081] The circumference is calculated by the Euclidean distance sum between two adjacent points on the boundary:

[0082]

[0083] Wherein,

[0084] (5), calculating the perforation roundness

[0085] The roundness is calculated by the following formula:

[0086]

[0087] (6), calculating the perforation azimuth

[0088] The centroid coordinates are (x0, y0), and the image width is w

[0089] Then the azimuth is:

[0090] alpha=x o / w*360

[0091] Analyzing the perforation parameters:

[0092] Using downhole television can clearly see the situation in the wellbore, and observe the perforation oil, gas, sand and other conditions. After obtaining the parameters of a cluster or several clusters of perforations by using the above method, the perforation conditions can be better explained by data, and the well personnel can timely observe the oil and gas production in the downhole, and the well production is further guaranteed. For example Figure 9The measured and marked image of a perforation cluster of a shale oil well can clearly observe that the perforation is in a spiral shape in the wellbore; the data calculated by the algorithm can analyze the perforation cluster in more detail, and further obtain various parameters of the perforation cluster such as Figure 10 .

[0093] Fracturing effect evaluation is a key technical bottleneck restricting the development of shale oil development technology in China at present, and the visual evaluation technology for evaluating the fracturing effect of shale oil horizontal wells based on perforation abrasion measurement is monopolized by foreign countries, the present application provides a new engineering measurement method for the quantitative analysis of perforation of the ultra-wide-angle visual logging instrument independently developed by China, so that the instrument has engineering practicability, and lays a solid foundation for breaking the technical monopoly of foreign countries by domestic equipment. The present application has been applied to the perforation measurement and fracturing evaluation of shale oil horizontal wells after fracturing, and more than 1800 perforations of two wells have been measured, good application effect has been achieved, and the perforation quantitative analysis technology of the ultra-wide-angle visual logging instrument has the conditions for scale application.

Claims

1. A method for determining perforation parameters based on perforation images, characterized in that, Includes the following steps: (1) Determine the maximum and minimum diameters of the perforation. (1.1) Mark the hole outline Images of downhole perforations are acquired using an ultra-wide-angle downhole camera, and the outlines of the perforations are marked on the images with colors, using one of the three primary colors of RGB. (1.2) Hole contour extraction The contour of the hole is extracted using a threshold discrimination method. The discrimination formula is as follows: R / (R+G+B)>=TH Where R, G, and B are the values ​​of the RGB three primary color components of the BMP image of the perforation image, respectively, the extracted contour is the set of (x,y) coordinates of points on the boundary, and TH is the threshold. (1.3) Find the coordinates (xo, yo) of the centroid O. Where N is the total number of points forming the contour line set, x i For each point, the x-coordinate, y i The ordinate of each point; (1.4) Calculate the maximum and minimum diameters of the perforation. Choose any point A(x1,y1) on the contour boundary and calculate the slope with respect to the centroid O: Scan the boundary and find a point B(x2,y2) connected to the centroid O with the same slope as k, where point B and point A are not on the same side of the centroid O. Calculate the Euclidean distance between A and B: Find all d such that point A scans the boundary once. AB The maximum and minimum values, with the major axis length being Max(d) AB The minor axis length is Min(d). AB ).

2. The method for determining perforation parameters based on perforation images according to claim 1, characterized in that, The method for determining the area of ​​the perforation hole is as follows: The area is the number of points enclosed by the boundary. The contour curve of the closed region and the coordinates of the curve are obtained, and the summation of each pixel in the region is automatically performed.

3. The method for determining perforation parameters based on perforation images according to claim 2, characterized in that, The method for determining the average diameter of a perforation hole is as follows: Let the area of ​​the region enclosed by the boundary be S, then the average diameter is...

4. The method for determining perforation parameters based on perforation images according to claim 2, characterized in that, The perimeter of a perforation hole is determined by summing the Euclidean distances between any two adjacent points on the boundary. in 5. The method for determining perforation parameters based on perforation images according to claim 4, characterized in that, The method for determining the roundness of the perforation is as follows: Calculate the roundness using the following formula:

6. The method for determining perforation parameters based on perforation images according to claim 1, characterized in that, The method for determining the azimuth angle of the perforation is as follows: Given the centroid coordinates (xo, yo) and the image width w, then the azimuth angle... alpha=x o / w*360。

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