Wellbore Operation Planning for Early Carbon Footprint Optimization
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Solution Overview
Problem
Wellbore operations face challenges in determining and mitigating their carbon footprint due to the complexity of data analysis and variability in equipment and services used, often resulting in high environmental impact that is difficult to assess in a timely manner.
Innovation Solution
A computing device and system that estimates sustainability impacts by allowing users to input parameters and constraints related to wellbore operations, utilizing machine-learning models and non-linear optimization algorithms to recommend equipment and energy source usage, thereby minimizing environmental impact and cost, and providing real-time adjustments to meet sustainability targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional carbon footprint determination methods are used, then comprehensive data analysis can be performed, but the determination time is delayed beyond when adjustments can be made
Solution Approach 1:
The system performs preliminary carbon footprint determination during the planning and design phases of wellbore operations, before operations begin. By calculating projected carbon footprints using equipment specifications and operational parameters in advance, the system enables adjustments to be made beforehand, preventing high carbon footprints rather than identifying them after the fact.
2Measurement precision
If detailed equipment and service data are collected for accurate carbon footprint calculation, then sustainability metrics improve, but system complexity increases
Solution Approach 1:
The system segments carbon footprint determination into distinct phases: planning phase calculations using equipment specifications, real-time monitoring during operations, and post-operation analysis. Each phase handles specific data requirements independently, reducing overall system complexity while maintaining comprehensive measurement accuracy.
Solution Approach 2:
The system introduces an intermediary computational layer that processes equipment specifications, operational parameters, and real-time data through standardized algorithms. This intermediary layer translates diverse input data into unified sustainability metrics, simplifying the complexity of collecting and analyzing detailed equipment and service data.
3Adaptability or versatility
If multiple equipment and service options are evaluated for carbon footprint impact, then sustainability optimization improves, but analysis difficulty increases
Solution Approach 1:
The system implements feedback mechanisms that provide immediate carbon footprint assessments for different equipment and service options during the planning phase. By comparing projected carbon footprints of alternative equipment selections and operational approaches, the system guides decision-makers toward lower-carbon options without requiring complex manual analysis of multiple scenarios.
Data Source
AI summary
A system can receive, at a user interface, at least one constraint and a range for at least one parameter for a wellbore operation. The system can generate, by at least one algorithm, a recommendation of a value for the at least one parameter within the range for the at least one parameter. The recommendation can be based on a sustainability metric and the at least one constraint for the wellbore operation. The system can output, at the user interface, the recommendation of the value for the at least one parameter and an indication of additional outcomes for the sustainability metric using other values within the range for the at least one parameter.