Mud Motor Stall Detection Using Differential Pressure Peaks
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Solution Overview
Problem
Existing mud motor stall detection systems fail to accurately identify stalls, leading to potential damage to downhole equipment and inefficiencies in drilling operations due to high false positive rates, which erode trust in the detection system.
Innovation Solution
A method using differential pressure data analysis to identify mud motor stalls by examining features such as peak amplitudes, time durations, and relative comparisons with preceding peaks, combined with threshold checks to classify peaks as indicative of a stall.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing mud motor stall detection systems are used, then detection capability is provided, but false positive rate is high leading to inaccurate identification
Solution Approach 1:
The detection system segments the stall detection process into multiple independent analysis components: differential pressure peak identification, amplitude comparison with preceding peaks, time duration analysis, and shape characterization. Each component evaluates a specific feature independently, and only when multiple features collectively indicate a stall pattern is a false positive generated, significantly improving detection accuracy while reducing false alarms.
2Measurement precision
If simple detection methods are used, then device complexity is low, but detection accuracy is insufficient
Solution Approach 1:
The patent replaces complex mechanical sensing systems with a computational approach that uses standard differential pressure sensors combined with sophisticated signal processing algorithms. The system substitutes mechanical complexity with information processing complexity, analyzing features such as peak amplitude ratios, time durations, and pressure curve shapes through computer-executed methods to achieve high detection accuracy without requiring complex hardware modifications.
3Measurement precision
If multiple features are analyzed for each peak, then detection accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary identification of differential pressure peaks and their key features (amplitude, time duration, shape characteristics) as drilling operations progress. By pre-processing and storing these peak features in real-time, the system prepares detection data in advance, enabling rapid stall determination when needed without requiring extensive post-processing analysis, thus reducing overall processing time while maintaining high detection accuracy.
Data Source
AI summary
Detecting a mud motor stall, using one or more computer processors, includes: receiving differential pressure data indicative of differential pressure measured over time during drilling of a wellbore; identifying, within the differential pressure data, one or more differential pressure peaks; for at least a first peak of the one or more differential pressure peaks, identifying one or more features of the first peak; and determining, based on each of the one or more features, that the first peak is indicative of a mud motor stall. Identifying the one of more features may include identifying at least a first feature including: determining an amplitude of the first peak; determining an amplitude of at least a second peak of the one or more differential pressure peaks; and comparing the amplitude of the first peak to the amplitude of the second peak.