Graph Framework for Trillion Cell Reservoir Simulation Data Integration
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Solution Overview
Problem
Conventional systems for handling and analyzing large data sets from reservoir and basin simulations require multiple applications for information visualization, 3D visualization, and analytics, which are inefficient and lack integrated data management.
Innovation Solution
A graph framework with database methods is implemented to analyze and query large data sets, representing reservoir simulation results as a graph that integrates relational and non-relational data, allowing for 3D data integration and unified analytics and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional systems use multiple applications for information visualization, 3D visualization, and analytics, then each application can specialize in its function, but the system complexity increases and data integration becomes inefficient
Solution Approach 1:
The patent combines information visualization, 3D visualization, and analytics into a single integrated application that uses a unified graph data structure. This merging eliminates the need for multiple separate applications while maintaining all functional capabilities, thereby reducing system complexity and improving data integration efficiency.
Solution Approach 2:
The graph data structure serves multiple functions simultaneously: it stores relational and non-relational data, enables 3D spatial relationships, supports analytics queries, and provides visualization capabilities. This multi-functionality allows a single system to replace multiple specialized applications.
2Reliability
If conventional systems use relational database storage, then data integrity is maintained, but the system cannot efficiently handle non-relational data and 3D spatial relationships
Solution Approach 1:
The patent creates a composite data structure that combines the strengths of relational databases (integrity through schema validation) with the flexibility of non-relational databases (handling of diverse data types and 3D spatial relationships). The graph structure maintains relational integrity while accommodating non-relational data formats and spatial information.
Solution Approach 2:
The patent adds a spatial dimension to traditional relational data by incorporating 3D coordinates and spatial relationships into the graph structure. This allows the system to handle both traditional tabular data and spatial data within the same framework, enabling 3D visualization and spatial analytics.
3Productivity
If the system integrates all data types in a unified structure, then data integration efficiency improves, but the query and analysis complexity increases
Solution Approach 1:
The patent segments the unified graph data structure into distinct components: vertices representing entities, edges representing relationships, and attributes storing data. This segmentation allows for efficient data integration while enabling targeted queries that focus on specific aspects of the data, thereby reducing query complexity despite the unified structure.
Data Source
AI summary
Systems and methods include a computer-implemented method for generating and using a graph/document structure to store reservoir simulation results. A graph is generated that represents reservoir simulation results of a reservoir simulation performed on a reservoir using a reservoir simulation model. The graph represents a full set of relational data and non-relational data included in the reservoir simulation results. The graph stores graph information and relational data in a graph/document structure. Objects of the reservoir, elements of the reservoir simulation results, and inputs of the reservoir simulation model are represented as vertices in the graph. Relationships between vertices are represented as edges in the graph. An edge is defined by a pair of vertices in the graph.