Statistical method for reservoir fractures and machine readable storage medium

Abstract

The invention provides a statistical method for reservoir fractures and a machine readable storage medium, and belongs to the technical field of oil and gas exploration. The statistical method for reservoir fractures comprises the following steps: acquiring a sample image; extracting an effective crack from the sample image; drawing a maximum circle with the opening degree of the effective crack as the diameter at preset intervals in the sample image; and determining crack information of the sample according to the maximum circle. Through the technical scheme, automatic identification of effective cracks of the sample and automatic statistics of crack information of the sample can be realized, and the method has the advantages of high statistical speed and high accuracy.

Description

technical field [0001] The invention relates to the technical field of oil and gas exploration, in particular to a statistical method for reservoir fractures and a machine-readable storage medium. Background technique [0002] With the development of unconventional oil and gas exploration, the law of fluid flow in low-permeability reservoirs has gradually become a research hotspot. The geometric characteristics of micro-fractures in low-permeability reservoirs are one of the key factors restricting fluid flow. Previous studies have shown that the opening of micro-fractures in low-permeability reservoirs is generally at the nanometer-micron level, and the length can reach centimeters. At the same time, it has high resolution (nano-micron level). [0003] The inventors of the present application have found that it is difficult to simultaneously collect the nanometer-centimeter-scale field of view for the collection of samples by the existing methods. In addition, when the fi...

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Problems solved by technology

[0003] The inventors of the present application have found that it is difficult to simultaneously collect the nanometer-centimeter-scale field of view for the collection of samples by the existing methods. In addition, when the field of view is large enough while having high resolution, the scanned sample The plan view of the image will be very large, and it will take a lot of manpower and time to find cracks and calculate the geometric characteristics of micro-cracks with the naked eye, and there will be a large subjective error in the quantitative method of counting the geometric features of micro-cracks manually

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