Field Development Planning Through Integrated Subsurface Simulation
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Solution Overview
Problem
Existing oil and gas exploration methods lack accurate models for subsurface regions, leading to inefficiencies in resource extraction operations such as drilling and production, as they do not effectively integrate computational frameworks for enhanced interpretation and simulation of geologic environments.
Innovation Solution
A system and method that utilizes computational simulators to generate equipment specifications, create a work breakdown structure, and render a graphical user interface for real-time updates and optimization of facility projects, incorporating frameworks like DRILLPLAN, PETREL, and SYMMETRY for improved subsurface modeling and resource extraction planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional interpretation methods are used for subsurface analysis, then the process is simpler and requires fewer computational resources, but the accuracy and reliability of subsurface modeling deteriorates
Solution Approach 1:
The patent combines multiple computational frameworks (seismic interpretation, reservoir modeling, drilling planning) into an integrated system where data and models are shared across modules. This merging allows accurate subsurface modeling through comprehensive data integration while managing complexity through unified architecture rather than separate standalone systems.
Solution Approach 2:
The computational framework is designed to perform multiple functions including seismic data processing, subsurface structure interpretation, reservoir characterization, and drilling plan optimization within a single integrated system. This multi-functionality improves modeling accuracy by using consistent data across all functions while avoiding the complexity of multiple separate systems.
2Reliability
If comprehensive computational frameworks are integrated for enhanced interpretation, then the accuracy of subsurface modeling improves, but the complexity of the system increases
Solution Approach 1:
The integrated computational framework is divided into distinct functional modules including seismic interpretation module, reservoir modeling module, and drilling planning module. Each module handles specific tasks independently, improving reliability through specialized processing while managing overall system complexity through modular architecture that allows independent development and maintenance of each component.
Solution Approach 2:
The system implements feedback loops where simulation results from reservoir modeling are used to refine subsurface interpretations, which in turn improve drilling plan optimization. This iterative feedback process enhances reliability by continuously improving model accuracy based on simulated outcomes while managing complexity through automated feedback mechanisms rather than manual intervention.
3Productivity
If manual methods are used for facility planning and equipment specification, then the process is more controllable and easier to manage, but the productivity and efficiency of field operations deteriorates
Solution Approach 1:
The system performs preliminary automated generation of facility plans and equipment specifications based on subsurface models and drilling plans. This preliminary action provides draft plans that can be reviewed and adjusted manually, improving productivity through automated initial design while maintaining ease of operation by allowing human oversight and modification before final implementation.
Solution Approach 2:
The computational framework automatically generates equipment specifications and facility planning documents by extracting required information from integrated subsurface models and project parameters. This self-service capability improves productivity by eliminating manual compilation processes while maintaining ease of operation through automated consistency checks and standardization built into the generation process.
Data Source
AI summary
A method can include generating equipment specifications for a facility project at a field site by simulating physical phenomena using one or more computational simulators; using the equipment specifications and a computational facility planner system, generating a work breakdown structure for the facility project, where the work breakdown structure represents activities to be performed to deliver a defined scope of the facility project within a defined time; rendering a graphical user interface to a display that includes graphical controls for dependencies of the activities and equipment characterized by the equipment specifications; responsive to input received via one or more of the graphical controls, automatically updating at least durations of the activities; and, based at least in part on the updating, generating an optimal scenario for the facility project.