Tool Service Life Sensor Wireless Connectivity
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Solution Overview
Problem
Existing systems for monitoring the service life of wellbore intervention tools lack autonomous prediction capabilities and wireless connectivity, relying on human evaluation of data records and not accounting for remote tool locations.
Innovation Solution
The Tool Service Life Sensor (TSLS) uses a set of static algorithms and an application-specific parametric sensor array to measure physical properties, calculate the expected life of wellbore intervention tools, and provide wireless connectivity for remote monitoring, integrating sensors, power means, and control means to predict tool life based on failure mechanisms, workload, and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If human evaluation of data records is used to assess tool life, then flexibility in analysis is maintained, but automation and real-time prediction capability are lost
Solution Approach 1:
The monitoring system performs self-service by autonomously calculating tool life predictions using integrated algorithms that process sensor data without requiring human intervention. The system serves itself by automatically evaluating wear indicators, predicting remaining life, and generating maintenance alerts, thereby resolving the contradiction between automation and complexity through self-contained operational capability.
Solution Approach 2:
The system performs preliminary action by continuously monitoring and accumulating wear data throughout tool operation, preparing predictions in advance before actual tool failure occurs. This allows the system to proactively assess tool condition and predict remaining life, transitioning from reactive human evaluation to proactive automated prediction.
2Adaptability or versatility
If cable connection is used for data transmission, then reliable communication is ensured, but remote tool locations become inaccessible
Solution Approach 1:
The system replaces the mechanical cable connection with wireless communication technology, eliminating the physical constraint that limits accessibility to remote locations. This substitution maintains communication functionality while enabling data transmission from tools located in remote or hard-to-reach areas, thereby resolving the contradiction between adaptability and reliability.
3Measurement precision
If comprehensive sensor arrays are deployed to measure all physical properties, then measurement precision improves, but device complexity and power consumption increase
Solution Approach 1:
The system applies local quality by selecting and deploying specific sensor types tailored to detect particular wear mechanisms relevant to the tool's operating conditions. Rather than uniformly deploying comprehensive sensor arrays everywhere, the system customizes sensor placement and selection to match local wear patterns, improving measurement precision while managing complexity through targeted monitoring.
4Reliability
If continuous monitoring is performed to predict tool life accurately, then prediction accuracy improves, but energy consumption increases
Solution Approach 1:
The system implements periodic action by conducting continuous monitoring at strategically determined intervals rather than constant uninterrupted measurement. This allows the system to maintain reliable life prediction accuracy by capturing critical wear data at key moments while reducing overall energy consumption by allowing brief measurement intervals between monitoring cycles.
Data Source
AI summary
Apparatus for calculating service life expectancy of wellbore intervention tools comprising one or more sensors, power means, control means and wireless connectivity means. Also a method of the measuring and calculating the service life expectancy of wellbore intervention tools using this apparatus.