Drilling Emissions Framework Real-Time Monitoring
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Solution Overview
Problem
Current drilling operations lack efficient methods to accurately determine and manage emissions in real-time, particularly in complex geologic environments, which can impact operational efficiency and environmental sustainability.
Innovation Solution
A system and method that integrates drilling operations data with contextual information to determine emissions at a rig site, utilizing computational frameworks and sensors to receive and process data, enabling real-time emissions assessment and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If drilling operations are conducted in complex geologic environments, then operational complexity increases, but emissions monitoring accuracy deteriorates
Solution Approach 1:
The emissions monitoring system is segmented into multiple specialized sensors (combustion emissions sensors, hydraulic emissions sensors, atmospheric sensors) that each monitor specific emission sources independently. This segmentation allows the system to maintain high measurement precision for each emission type even in complex geologic environments by focusing measurement capabilities on specific parameters rather than attempting comprehensive monitoring with a single system.
Solution Approach 2:
The patent introduces computational frameworks and data processing intermediaries that bridge the gap between raw sensor data and accurate emissions determinations. These intermediaries process and contextualize data from multiple sensors, applying algorithms that account for complex geologic conditions, thereby maintaining measurement accuracy despite environmental complexity.
2Productivity
If real-time emissions data processing is implemented, then operational efficiency improves, but system complexity increases
Solution Approach 1:
The computational framework is designed with multi-functionality, serving as a universal platform that performs emissions calculations, operational optimization, and real-time data processing across different drilling operations. This universal system reduces overall complexity by consolidating multiple functions into a single integrated framework rather than requiring separate systems for each function.
Solution Approach 2:
The system incorporates self-service capabilities through automated emissions calculations and real-time optimization algorithms that adjust operational parameters without external intervention. This automation reduces the need for complex manual monitoring and control systems, thereby improving operational efficiency while managing system complexity through intelligent self-regulation.
3Measurement precision
If comprehensive drilling operations data is collected, then emissions determination accuracy improves, but data processing requirements increase
Solution Approach 1:
The system extracts and processes only the most critical emissions-related parameters from the comprehensive drilling data, rather than processing all available data. By identifying and focusing on key indicators of emissions (combustion parameters, hydraulic flow rates, atmospheric conditions), the system maintains high emissions determination accuracy while significantly reducing computational energy requirements.
Solution Approach 2:
The patent applies partial action by processing a selected subset of drilling parameters that have the greatest impact on emissions determination. Rather than exhaustively processing all drilling data, the system focuses computational resources on the most influential parameters, achieving sufficient emissions accuracy with reduced energy consumption.
Data Source
AI summary
A method may include receiving drilling operations data with respect to time as acquired during drilling operations at a rig site; receiving contextual information associated with the drilling operations at the rig site; and determining emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information.