Drilling Mud Property Estimation with Uncertainty Modeling
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Solution Overview
Problem
Current methods for monitoring and controlling drilling mud properties are manual, uncertain, and not optimized for real-time conditions, leading to difficulties in maintaining desired fluid properties and inefficiencies in drilling operations.
Innovation Solution
A model-based approach is used to estimate uncertainties in drilling mud properties, optimizing the surface mud sampling interval and adjusting mud mixer operational parameters to maintain consistent mud quality, reducing costs and improving measurement and control performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual testing of drilling mud properties is performed every 15 minutes, then the engineer can monitor fluid characteristics, but the measurement precision and reliability are reduced due to uncertainties from manual analysis, unknown downhole conditions, and time delays
Solution Approach 1:
The patent replaces manual mechanical testing with a model-based estimation system that uses measured values and dynamic models to calculate mud properties. The system substitutes human engineer analysis with automated computational models that process measurements and uncertainties mathematically, eliminating manual analysis errors and time delays while improving measurement precision and reliability simultaneously
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously updates uncertainty estimates based on new measurements and uses this feedback to adjust sampling intervals and control decisions. The uncertainty estimates feed back into the decision-making process, allowing the system to adaptively improve measurement precision and reliability by focusing resources when uncertainties are highest
2Productivity
If measurements are taken at fixed intervals, then the monitoring process is simple, but the productivity is reduced because real-time drilling conditions cannot be optimized
Solution Approach 1:
The patent transforms the static fixed-interval sampling system into a dynamic adaptive sampling system. The sampling interval becomes a dynamic variable that adjusts automatically based on real-time uncertainty estimates and drilling conditions. This allows the system to increase sampling frequency when conditions change rapidly (improving productivity) while maintaining simplicity through automated decision rules (managing complexity)
Solution Approach 2:
The patent changes the parameter of sampling interval from a constant value to a variable that depends on uncertainty levels and drilling conditions. By making the sampling interval a changeable parameter rather than a fixed value, the system can optimize productivity by sampling more frequently when needed while keeping the monitoring framework relatively simple through automated parameter adjustment
3Manufacturing precision
If the sampling interval is reduced to capture real-time conditions, then the productivity and control accuracy improve, but the loss of time and operational costs increase
Solution Approach 1:
The patent applies partial action by performing detailed uncertainty analysis and adaptive sampling only when necessary, rather than continuously at maximum frequency. The system uses uncertainty estimates to determine when full measurement and analysis cycles are needed versus when existing data suffices, reducing time loss while maintaining control accuracy through targeted rather than exhaustive monitoring
Data Source
AI summary
During drilling operations various drilling mud properties may be measured and predicted. Uncertainties in the measured or predicted values may also be calculated. The estimated uncertainties may then be used to optimize mud sampling interval and/or control a mud mixer. A decision making algorithm may be performed to optimize a surface mud sampling interval such that the uncertainties are maintained within a bounded region with minimal number of sampling times.