1887

Abstract

Summary

Using thin section, confocal and SEM data to analyze and extract pore network plays a vital role in evaluation of reservoir quality. A complete workflow containing three steps is developed to perform accurate and quantitative pore structure and connectivity analysis. In the first step, both manual and automatic solutions have been applied for pore identification. In the second step, the density-based clustering algorithm is developed to perform pore segmentation based on pixel connectivity. Monolithic pore complexities are recognized without be separated into individual small pores. In the third step, the combination of dilation, median filter and watershed transformation provides an accurate pore and throat detection. 9 parameters, i.e., area, major axis length, minor axis length, eccentricity, equivalent diameter, solidity, perimeter, coordinate number, average throat length are calculated to depict the geometry and connectivity of pore structure.

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/content/papers/10.3997/2214-4609.201901424
2019-06-03
2024-03-28
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