Wellsite Sensor Data Quality Assessment for Workflow Selection
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Solution Overview
Problem
In the oil and gas industry, real-time sensor data used for drilling operations is often unreliable due to incorrect or missing inputs, excessive noise, and lack of calibration, which can lead to inaccurate workflow decisions.
Innovation Solution
A method and system that receive measured sensor data, assess its quality across multiple dimensions, predict expected data using models, compare with actual data, determine uncertainty, and select appropriate workflows for implementation based on data quality and comparison results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If real-time sensor data is used for workflow selection during drilling operations, then operational decision-making speed is improved, but data reliability deteriorates due to noise, incorrect inputs, and calibration issues
Solution Approach 1:
The system implements feedback by comparing actual sensor measurements with predicted values from planning models. This comparison provides continuous information about data quality and model accuracy, enabling automatic workflow selection adjustments. The feedback loop includes measuring actual sensor data, comparing it with predicted data, determining uncertainty, and selecting workflows based on this comparison, thereby resolving the contradiction between speed and reliability.
Solution Approach 2:
The system introduces an intermediary layer between raw sensor data and workflow selection decisions. This intermediary involves planning models that predict expected sensor data and uncertainty determination mechanisms. By comparing actual measurements with model predictions through this intermediary layer, the system filters out noise and incorrect inputs while maintaining rapid decision-making capability.
2Measurement precision
If multiple data quality dimensions are assessed to improve measurement accuracy, then data quality evaluation becomes more comprehensive, but system complexity increases
Solution Approach 1:
The system segments data quality assessment into multiple independent dimensions rather than attempting a single comprehensive evaluation. By dividing the assessment into separate quality dimensions, the system can evaluate each aspect independently and combine results, improving overall measurement precision while keeping individual evaluation components manageable and not excessively complex.
3Reliability
If sensor data is continuously monitored and compared with model predictions, then workflow selection accuracy is improved, but computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary action by establishing planning models before drilling operations begin. These pre-developed models contain predicted sensor data and workflow parameters that are prepared in advance. During actual operations, the system only needs to compare real-time measurements against these pre-computed predictions, significantly reducing processing time while maintaining high workflow selection accuracy.
Data Source
AI summary
A method for conducting wellsite activities includes receiving measured sensor data collected by one or more sensors in a wellsite construction rig, determining a data quality of the measured sensor data based on a plurality of data quality dimensions, predicting predicted sensor data using a model, comparing the measured sensor data with the predicted sensor data, determining an uncertainty of the measured sensor data based at least in part on the data quality and the comparison, and selecting one or more workflows for implementation using the one or more sensors, the wellsite construction rig, or both.