Power Loss Signal Propagation for Drilling Dysfunction Detection
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Solution Overview
Problem
Current drilling operations face challenges in detecting and mitigating downhole drilling dysfunctions such as excessive torque, shocks, and vibrations due to non-synchronized sensor timing and environmental factors, which can lead to tool failures and operational inefficiencies.
Innovation Solution
A process and system that measure power-loss of signal propagation along the drill string by acquiring time series data from both mid-string and surface sensors, using model parameters alpha and beta to characterize wellbore geometry and predict real-time dysfunctions, allowing for timely detection and mitigation of drilling issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple sensors with independent clocks are used to monitor drilling operations, then measurement coverage and data completeness are improved, but timing synchronization and data aggregation accuracy deteriorate
Solution Approach 1:
The patent introduces an intermediary synchronization signal that propagates through the drill string to coordinate timing across all sensors. This mediator (synchronization signal) allows multiple sensors to operate independently while maintaining precise temporal alignment, resolving the contradiction between having many sensors and maintaining timing accuracy.
Solution Approach 2:
The system employs feedback mechanisms where timing information from synchronized sensors is continuously monitored and adjusted. The synchronization process uses feedback from the propagated signal to correct timing drift and maintain precise alignment across all sensor measurements throughout the drilling operation.
2Loss of time
If sensor data is collected and processed in real-time to detect dysfunctions quickly, then response time to drilling problems is improved, but computational complexity and data processing requirements worsen
Solution Approach 1:
The patent extracts and isolates specific critical parameters related to drilling dysfunctions from the full sensor data stream. By focusing only on the most relevant features (such as torque anomalies, vibration patterns, or temperature deviations) rather than processing all raw data, the system achieves rapid detection without requiring overly complex processing infrastructure.
Solution Approach 2:
The monitoring system is segmented into distributed sensor units that perform local preprocessing and feature extraction independently. Each sensor node processes its own data locally and transmits only essential information to the central system, reducing overall computational complexity while maintaining real-time detection capability.
3Measurement precision
If mid-string sensors are deployed to improve downhole measurement accuracy, then detection capability is improved, but device complexity and cost worsen
Solution Approach 1:
The mid-string sensor is designed as a multi-functional device that performs multiple measurement tasks simultaneously (torque, vibration, temperature, or other parameters). This universal sensor replaces what would otherwise require multiple separate specialized sensors, reducing overall system complexity while maintaining high measurement accuracy across all monitored parameters.
Data Source
AI summary
The invention relates to a method, system and apparatus for determining real-time drilling operations dysfunctions by measuring the power-loss of signal propagation associated with a drill string in a wellbore. The invention comprises acquiring a first time series from a mid-string drilling sub sensor associated with a drill string in a wellbore and acquiring a second time series from a sensor associated with the drill string wherein the sensor is on or near a drill rig on the surface of the earth. The process further comprises determining the geometry of the wellbore and determining model parameters alpha and beta for characterizing a wellbore using the first time series, the second time series and the geometry of the wellbore by deriving a power loss of signal propagation. The model parameters may then be used for drilling a subsequent well using surface sensor acquired data to detect drilling dysfunctions.