Nonparametric Risk Model for Drilling Tool Failure Estimation
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Solution Overview
Problem
Traditional reliability-driven risk assessment methods in the drilling industry are inadequate as they fail to accurately estimate tool failure probability due to their reliance on time-based statistics, neglecting the impact of various stresses such as vibration and temperature on tool health.
Innovation Solution
A nonparametric risk assessment method that creates a risk model from tool data and maintenance data to estimate failure probability by mapping stress levels and operational times, allowing for real-time risk analysis and informed decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional time-based reliability assessment methods are used, then the assessment process is simple and easy to implement, but the accuracy of failure probability estimation is insufficient because stress factors are not considered
Solution Approach 1:
The patent transforms the risk assessment from using only time-based parameters to incorporating multiple stress parameters (vibration, temperature, pressure) that directly affect tool health. This parameter expansion enables accurate estimation of failure probability by considering the actual physical stresses experienced during drilling operations.
Solution Approach 2:
The patent introduces a nonparametric risk model as an intermediary between raw stress data and failure probability estimation. This model processes complex stress sequences and operational data to produce accurate risk assessments without requiring complex parametric assumptions, thereby balancing accuracy with computational feasibility.
2Reliability
If stress-based risk assessment is implemented, then the reliability estimation accuracy is improved, but the data processing and model creation complexity increases
Solution Approach 1:
The patent performs preliminary processing of stress data by creating compressed representations of stress sequences during normal operations. This pre-processing enables rapid risk assessment when needed, as the complex stress patterns have already been organized and stored in an efficient format, reducing processing time during critical evaluation periods.
Solution Approach 2:
The patent creates simplified copies or representations of complex stress sequences that capture the essential characteristics needed for risk assessment. These compressed stress representations allow for rapid comparison and evaluation without requiring processing of the complete raw data sets, thereby reducing computational time while maintaining assessment accuracy.
Data Source
AI summary
A method for creating a risk estimate for a tool includes creating a plurality of source patterns from tool data and maintenance data related to a plurality of tools. The method also includes creating a risk model from the plurality of source patterns, the risk model including a plurality of example stressors each having an associated risk value. The method also includes creating at least one stress pattern from tool data related to the tool and comparing the at least one stress pattern to the risk model to create a risk estimate for the tool.