Pore and Fracture Identification via 2D Core Scan Analysis
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Solution Overview
Problem
Existing methods fail to accurately and efficiently distinguish between pores and fractures in reservoir rock, limiting the ability to quantify their characteristics and assess oil and gas storage capacity and migration mechanisms.
Innovation Solution
A method and system that utilize a 2D scan image of a core, involving scanning, filtering, segmentation, and a pore-fracture identification function to differentiate between pores and fractures based on centroid coordinates and preset characterization values, allowing for accurate identification and distribution data acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods are used to analyze core images, then the analysis process is simple, but the accuracy of pore and fracture identification is insufficient
Solution Approach 1:
The patent divides the image processing into distinct segments: initial image acquisition, filtering processing, segmentation processing, and pore-fracture identification. Each segment handles specific tasks with dedicated algorithms, improving overall identification accuracy while maintaining manageable system complexity through modular processing steps.
Solution Approach 2:
The patent transforms geometric parameters of void spaces (area, perimeter, centroid coordinates) into a pore-fracture identification function that quantifies shape characteristics. By changing from simple visual inspection to parameter-based mathematical evaluation, the system achieves higher identification accuracy through objective metric comparison.
2Productivity
If manual pore and fracture identification methods are used, then the equipment required is simple, but the efficiency and quantitative analysis capability are limited
Solution Approach 1:
The patent replaces manual mechanical inspection with automated computer-based image processing. The system uses algorithms to automatically detect, segment, and identify pores and fractures, substituting human visual analysis with machine-based automated recognition, thereby significantly improving analysis efficiency and enabling quantitative measurements.
Solution Approach 2:
The system performs self-service through automated image processing where the computer algorithm independently completes the entire workflow from image acquisition to pore-fracture identification without requiring continuous manual intervention. The automated identification function calculates geometric parameters and classifies features autonomously, enhancing productivity while managing system complexity through algorithmic self-sufficiency.
Data Source
AI summary
A method for identifying a pore and a fracture based on a two-dimensional (2D) scan image of a core includes: scanning a core to acquire an initial 2D image of the core; filtering the initial 2D image of the core to acquire a first 2D image of the core; segmenting the first 2D image of the core to acquire a second 2D image of the core; extracting center coordinates of all pixel points in each void space to acquire a centroid of the void space, and establishing a pore-fracture identification function of the void space; identifying the void space as a fracture if a value of the pore-fracture identification function is greater than a preset characterization value; and identifying the void space as a pore if the value of the pore-fracture identification function is not greater than the preset characterization value.