Well Intervention Scenario Simulation for Faster Reservoir Assessment
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Solution Overview
Problem
Existing methods for characterizing and optimizing subsurface reservoirs in oil and gas exploration lack accuracy and efficiency, particularly in simulating fluid flow and production scenarios, leading to suboptimal drilling and resource extraction operations.
Innovation Solution
A system and method utilizing a simulator to generate and assess scenarios for well actions, incorporating frameworks like PIPESIM and DELFI for enhanced reservoir modeling and simulation, enabling automated scenario generation and analysis to optimize well performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual methods are used for reservoir characterization and scenario analysis, then human expertise and judgment can be applied, but the process is time-consuming and less efficient
Solution Approach 1:
The system pre-generates multiple possible well scenarios and simulations in advance before actual decision-making is needed. By preparing scenario databases beforehand with various well intervention options, the system enables rapid assessment and comparison when real-time decisions are required, significantly reducing analysis time while maintaining comprehensive evaluation
Solution Approach 2:
The system creates virtual copies of well scenarios through digital simulation models. Instead of performing physical trials or extensive manual analysis, the system generates digital replicas of well behavior under different conditions, allowing rapid comparison of multiple scenarios without the time cost of physical experimentation or detailed manual calculations
2Measurement precision
If comprehensive simulation scenarios are generated for well optimization, then decision accuracy improves, but the complexity of the system increases
Solution Approach 1:
The simulation system is divided into modular components: scenario generation modules, simulation execution modules, result assessment modules, and decision support modules. Each module handles specific aspects of the analysis independently, allowing the system to manage complex simulations through organized, manageable segments that can be executed and validated separately
Solution Approach 2:
The system introduces an automated scenario generation and management intermediary layer between the simulation tools and the decision-makers. This intermediary automatically generates, executes, and compares multiple simulation scenarios, filtering and organizing results to present only the most relevant options to users, thereby managing complexity while maintaining comprehensive analysis
3Productivity
If automated scenario generation is implemented, then productivity and consistency improve, but the initial setup and implementation complexity increases
Solution Approach 1:
The system utilizes adjustable parameters and configurable settings that allow the automated scenario generation to be adapted to different well types, reservoir conditions, and operational constraints. By changing parameters rather than redesigning the entire system, the automation can be implemented across various scenarios with minimal reconfiguration, reducing implementation complexity while maintaining high productivity
Data Source
AI summary
A method can include receiving inputs for a well; generating scenarios for the well using the inputs; instructing a simulator to simulate generated scenarios; receiving simulation results for at least some of the generated scenarios; and assessing the received simulation results for implementation of one or more well actions for the well.