Casing Wear Estimation via Drill String Visual Analysis
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Solution Overview
Problem
Current methods for estimating casing wear in boreholes are costly and inefficient, particularly using wireline logs, which fail to accurately predict casing wear and potential failures, leading to increased risks of borehole collapse and operational inefficiencies.
Innovation Solution
A method and system that analyze surface changes on drilling pipes using visual data, combining physics-based models with machine learning techniques to correlate surface defects with casing wear, allowing for the estimation of casing wear parameters and well integrity by processing visual frames from drilling operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wireline logs are used to estimate casing wear, then casing wear estimation is performed, but the method is costly and inaccurate
Solution Approach 1:
The patent uses digital images as a copy or representation of the actual casing wear condition. Instead of using expensive wireline logs to directly measure casing wear, the system captures visual images of the drill string surface, which serve as a surrogate or copy of the wear information. These images are then processed to extract wear characteristics, providing an accurate but cost-effective alternative to direct measurement methods.
2Reliability
If traditional methods are used to predict casing failure, then failure prediction is attempted, but the methods increase risks of borehole collapse
Solution Approach 1:
The system implements a feedback mechanism by continuously monitoring the drill string surface condition through digital imaging during drilling operations. The processed wear data provides real-time feedback about casing wear progression, allowing operators to take preventive actions before critical wear levels are reached. This proactive feedback loop reduces the risk of borehole collapse by enabling early intervention rather than relying on inaccurate traditional prediction methods.
3Measurement precision
If visual analysis of drill string surface is performed, then surface changes are detected, but processing and analyzing images requires computational resources
Solution Approach 1:
The system extracts only the essential wear-related features from the digital images rather than performing comprehensive analysis of entire images. The image processing focuses on identifying and measuring specific surface characteristics such as wear patterns, roughness changes, and dimensional variations. This selective extraction of relevant information reduces computational energy requirements while maintaining high precision in detecting surface changes related to casing wear.
Data Source
AI summary
The disclosure presents solutions for determining a casing wear parameter. Image collecting or capturing devices can be used to capture visual frames of a section of drilling pipe during a trip out operation. The visual frames can be oriented to how the drilling pipe was oriented within the borehole during a drilling operation. The visual frames can be analyzed for wear, e.g., surface changes, of the drilling pipe. The surface changes can be classified as to the type, depth, volume, length, shape, and other characteristics. The section of drilling pipe can be correlated to a depth range where the drilling pipe was located during drilling operations. The surface changes, with the depth range, can be correlated to an estimated casing wear to generate the casing wear parameter. An analysis of multiple sections of drilling pipe can be used to improve the locating of sections of casing where wear is likely.