CHARACTERIZATION METHOD FOR FINE-GRAINED SEDIMENTARY ROCK LAMINAR TEXTURE
First Claim
1. A characterization method for a fine-grained sedimentary rock laminar texture, wherein, including the following specific steps:
- S1;
image preprocessing;
acquiring a microscopic image of a fine-grained sedimentary rock thin section, and daubing non-laminar feature in the microscopic image of the fine-grained sedimentary rock thin section;
S2;
loading the image, and normalizing the image to a specified size;
S3;
performing mean filtering, dilation operation and binarization processing on the image successively;
S4;
determining whether laminars are developed;
counting bright pixel points in each row of the image;
setting a first threshold according to peaks, i.e., high values of the bright pixel points; and
determining, according to the first threshold, whether laminars are developed in the image;
S5;
determining the number of bright laminars and dark laminars;
setting a second threshold, finding the positions of troughs according to adjacent two peaks;
if an elevation difference between a peak and an adjacent trough is greater than the second threshold, considering that there is a trough; and
acquiring accurate positions of peaks and troughs, i.e., effective peaks and effective troughs, wherein the number of effective peaks is the number of bright laminars and the number of effective troughs is the number of dark laminars;
S6;
determining the continuity of bright laminars and dark laminars;
in the bright laminars or the dark laminars, counting the number of corresponding break points by using the pixel points in each row of the image as a unit;
obtaining a reciprocal of an average number of break points; and
using a size of the reciprocal to characterize a strength of the continuity of bright laminars or the continuity of dark laminars; and
,S7;
according to the statistical result and the calculation result, writing the number of bright laminars, the number of dark laminars, the average width of bright laminars, the average width of dark laminars, the average width of bright and dark laminars, the continuity of bright laminars, the continuity of dark laminar, the continuity of bright and dark laminars, the width variance of bright laminars, the width variance of dark laminars, and the average width variance of bright and dark laminars into Excel.
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Abstract
The present application relates to a characterization method for fine-grained sedimentary rock laminar texture, including S1: image preprocessing; S2: loading the image, and normalizing the image to a specified size; S3: performing mean filtering, dilation operation and binarization processing on the image; S4: determining whether laminars are developed; S5: determining the number of bright laminars and dark laminars; S6: determining the continuity of bright laminars and dark laminars; S7: according to the statistical result and the calculation result, recording the characterized parameters into Excel. The present application can accurately characterize the texture features of fine-grained sedimentary rock laminar. Compared with the prior art, the present application have higher efficiency and satisfies the requirement of symmetrically depicting the growth features of fine-grained sedimentary rock laminar, and a technical support is provided for the exploration and development of shale oil and gas.
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8 Claims
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1. A characterization method for a fine-grained sedimentary rock laminar texture, wherein, including the following specific steps:
-
S1;
image preprocessing;acquiring a microscopic image of a fine-grained sedimentary rock thin section, and daubing non-laminar feature in the microscopic image of the fine-grained sedimentary rock thin section; S2;
loading the image, and normalizing the image to a specified size;S3;
performing mean filtering, dilation operation and binarization processing on the image successively;S4;
determining whether laminars are developed;counting bright pixel points in each row of the image;
setting a first threshold according to peaks, i.e., high values of the bright pixel points; and
determining, according to the first threshold, whether laminars are developed in the image;S5;
determining the number of bright laminars and dark laminars;setting a second threshold, finding the positions of troughs according to adjacent two peaks;
if an elevation difference between a peak and an adjacent trough is greater than the second threshold, considering that there is a trough; and
acquiring accurate positions of peaks and troughs, i.e., effective peaks and effective troughs, wherein the number of effective peaks is the number of bright laminars and the number of effective troughs is the number of dark laminars;S6;
determining the continuity of bright laminars and dark laminars;in the bright laminars or the dark laminars, counting the number of corresponding break points by using the pixel points in each row of the image as a unit;
obtaining a reciprocal of an average number of break points; and
using a size of the reciprocal to characterize a strength of the continuity of bright laminars or the continuity of dark laminars; and
,S7;
according to the statistical result and the calculation result, writing the number of bright laminars, the number of dark laminars, the average width of bright laminars, the average width of dark laminars, the average width of bright and dark laminars, the continuity of bright laminars, the continuity of dark laminar, the continuity of bright and dark laminars, the width variance of bright laminars, the width variance of dark laminars, and the average width variance of bright and dark laminars into Excel. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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Specification