Earth-Boring Tool Node Failure Prediction From Communication Metadata
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Solution Overview
Problem
Current methods for predicting failures in electronic components of earth-boring tools are inefficient, often requiring unnecessary extraction of the bottom hole assembly from the wellbore, leading to significant time and financial losses, as they rely heavily on length of service and signal accuracy rather than proactive failure prediction.
Innovation Solution
A method involving monitoring communication between nodes in the earth-boring tool, generating metadata on communication quality, and using historical data to create models for predicting failures, allowing for proactive replacement of components before they fail.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electronic devices are replaced based on length of service and signal accuracy, then failures may be avoided, but unnecessary extractions of the BHA are required, resulting in loss of productive work time
Solution Approach 1:
The system performs preliminary actions by continuously monitoring communication metadata and generating failure predictions before actual failures occur. The health estimation system analyzes communication quality trends and predicts potential failures, allowing operators to plan replacements during scheduled extractions rather than performing emergency extractions, thus reducing loss of productive work time while maintaining reliability
Solution Approach 2:
The system implements feedback by continuously monitoring communication metadata from electronic devices and using this information to update failure predictions. The health estimation system processes ongoing communication quality data, compares it against historical patterns, and provides real-time failure risk assessments, enabling dynamic adjustment of replacement timing to optimize both reliability and productivity
2Reliability
If electronic devices are replaced before failure based on current methods, then failures may be avoided, but unnecessary extractions are performed, leading to significant financial losses
Solution Approach 1:
The system performs preliminary failure prediction by analyzing communication metadata trends before actual failures occur. By predicting which devices are likely to fail and when, the system enables targeted replacements only for high-risk devices during scheduled extractions, avoiding unnecessary replacements of healthy devices and reducing the financial cost of extractions and equipment replacement
Solution Approach 2:
The system changes the parameter basis for replacement decisions from static criteria (length of service, signal accuracy thresholds) to dynamic failure probability predictions based on communication metadata analysis. This parameter transformation allows for more precise replacement timing, reducing unnecessary extractions and associated financial losses while maintaining reliability
3Device complexity
If current methods are used to determine replacement timing, then simplicity is maintained, but accuracy of failure prediction is insufficient, leading to unnecessary extractions
Solution Approach 1:
The system uses feedback from continuous monitoring of communication metadata to improve failure prediction accuracy. The health estimation system processes feedback loops where communication quality data is continuously collected, analyzed against historical patterns, and used to update failure predictions, achieving high measurement precision through sophisticated data analysis while maintaining relatively simple implementation architecture
Data Source
AI summary
A method or system for predicting failures in an earth-boring tool. Communication between one or more nodes in the earth-boring tool may be monitored. Metadata from the communication may be stored in a storage device. The metadata may be compared to historical communication metadata. The metadata may be fed into models built from historic metadata. Predictions from the models may be aggregated in to a recommendation. A failure prediction for each of the one or more nodes may be generated from the comparison.