Drill String Image Inspection for Real-Time Failure Detection
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Solution Overview
Problem
Conventional drill rig inspection methods, such as in-person visual inspection and non-destructive testing, are time-consuming, prone to human error, and ineffective in monitoring the integrity of drill string components in real-time, leading to delays and increased costs during drilling operations.
Innovation Solution
An image-based monitoring system utilizing an image sensor and an on-site edge gateway that captures real-time images of drill string components, analyzes them for integrity and failure conditions, and automatically triggers corrective actions, such as ordering replacement parts or manufacturing new components, through edge/fog computing and machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional in-person visual inspection and non-destructive testing are used to monitor drill string components, then inspection accuracy can be maintained, but inspection time increases and real-time monitoring is lost
Solution Approach 1:
The patent replaces manual visual inspection and conventional non-destructive testing with an automated optical inspection system using high-definition cameras and machine learning algorithms. The system captures images of drill string components and uses AI models to automatically detect defects, eliminating the need for human inspectors while maintaining high detection accuracy and enabling real-time monitoring during drilling operations.
Solution Approach 2:
The inspection system performs self-assessment by automatically analyzing component images and generating inspection reports without human intervention. The machine learning models continuously learn from new data to improve detection accuracy autonomously, and the system can automatically trigger maintenance alerts when defects are detected, enabling the system to serve itself in the inspection process.
2Productivity
If manual inspection methods are used for drill string components, then equipment complexity remains low, but productivity decreases due to time-consuming inspections
Solution Approach 1:
The optical inspection system is designed to inspect multiple types of drill string components (drill pipes, drill bits, tool joints, casings) using the same hardware platform and machine learning models. The system can detect various defect types (cracks, corrosion, wear, deformations) across different components, making it a universal inspection solution that improves productivity without proportionally increasing complexity.
Solution Approach 2:
The patent introduces an edge computing gateway as an intermediary between the image capture sensors and the central processing system. This edge gateway performs preliminary image processing and defect detection locally, reducing the data transmission burden and enabling faster real-time inspection. The intermediary layer manages system complexity by handling computational tasks distributed across multiple levels.
3Reliability
If real-time monitoring of drill string components is implemented, then unplanned downtime is reduced, but system complexity and initial costs increase
Solution Approach 1:
The system performs preliminary defect detection by continuously monitoring drill string components during drilling operations. By detecting defects early before they lead to component failure, the system enables proactive maintenance scheduling and prevents unplanned downtime. The machine learning models are trained on historical defect data to recognize early signs of component degradation, allowing intervention before critical failures occur.
Solution Approach 2:
The inspection system implements continuous feedback by monitoring component conditions in real-time and automatically generating alerts when defects are detected. The system provides feedback to operators and maintenance teams, enabling them to take corrective actions promptly. The machine learning models continuously learn from new inspection data, improving their detection accuracy over time through feedback loops.
Data Source
AI summary
A monitoring system includes an image sensor positioned about a rig, the image sensor directed at a drill string component positioned on the rig, and an onsite gateway communicably coupled to the image sensor and disposed proximate to the rig. The onsite gateway includes one or more processors, and a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors. The programming instructions instruct the one or more processors to receive an image stream of the drill string component from the image sensor, identify an operating parameter of the drill string component, generate an operating condition of the drill string component, determine that the generated operating condition meets a failure threshold of the drill string component, and send an instruction to drive a controllable device.