Drilling Data Analytics Engine for Time-Synced Rig-State Detection
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Solution Overview
Problem
Existing drilling technologies face challenges in detecting and mitigating drilling dysfunctions such as excessive torque, shocks, bit bounce, and induced vibrations due to non-synchronized timing of sensor data from multiple sources, leading to potential equipment failure and increased operational costs.
Innovation Solution
A Big Drilling Data Analytics Engine that synchronizes and analyzes real-time data from various sensors using a processing graph to detect and mitigate drilling dysfunctions by correcting timing errors and predicting downhole conditions, enabling efficient data-driven drilling performance optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data from multiple sensors are aggregated without time synchronization, then data processing complexity is reduced, but measurement precision and reliability of drilling dysfunction detection deteriorate due to timing errors and variable timing drift
Solution Approach 1:
The patent introduces a reference clock as an intermediary time synchronization source that all sensors use to timestamp their measurements. This mediator resolves the timing coordination problem between multiple sensors without requiring complex inter-sensor communication or synchronization protocols, thereby maintaining measurement precision while avoiding excessive system complexity
Solution Approach 2:
The system performs time synchronization preparation in advance by establishing a common reference clock framework before data collection begins. All sensors are pre-configured to use this reference clock for timestamping, which eliminates timing drift issues during actual data acquisition and simplifies subsequent data processing
2Reliability
If sensor timing is corrected for environmental factors, then reliability of drilling dysfunction detection is improved, but device complexity increases due to additional correction mechanisms
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors timing deviations of sensors and automatically applies corrections based on observed drift patterns. This feedback loop maintains high detection reliability by compensating for environmental timing drift without requiring manual intervention or overly complex correction algorithms
Solution Approach 2:
The system performs self-correction of timing errors by using the reference clock to identify and compensate for drift in individual sensors. Each sensor's timing issues are automatically detected and corrected through comparison with the stable reference clock, eliminating the need for external calibration services or complex manual adjustment mechanisms
3Productivity
If real-time data analysis is performed at high speed, then productivity of drilling operations is improved, but measurement precision may deteriorate due to processing speed compromises
Solution Approach 1:
The patent performs preliminary time synchronization and data preprocessing actions before the main analysis phase. By pre-aligning all sensor data to the reference clock and organizing data structures in advance, the system enables high-speed real-time processing without compromising measurement precision, as the data is already optimized for rapid analysis
Data Source
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AI summary
The invention relates to systems, processes and apparatuses for determining a rig-state of a drilling rig during a wellbore drilling operation and detecting and mitigating drilling dysfunctions. These systems, processes and apparatuses provide a computer with a memory and a processor, a plurality of sensors associated with a wellbore drilling operation for acquiring time series data wherein the data are formatted for sample and bandwidth regularization and time-corrected to provide substantially time-synchronized data, a processing graph of data-stream networked mathematical operators that applies continuous analytics to the data at least as rapidly as the data are acquired to determine dynamic conditions of a plurality of rig conditions associated with the wellbore drilling operation and determining a rig-state from the plurality of rig conditions.