Intelligent Data Warehouse for Reservoir Simulation

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Solution Overview

Problem

Reservoir simulations face challenges in data management, including retention, access, and organization across the lifetime of an energy asset, due to the complexity of handling vast and diverse data sets from various sources, which hinders efficient reuse and historical data maintenance.

Innovation Solution

An intelligent data management system leveraging heterogeneous database technologies and cloud technology to organize and store data from reservoir simulations, using a machine learning component to learn and guide simulation runs and model building workflows, and create a predictive model for configuration and data management.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If vast and diverse data sets from various sources are handled in reservoir simulations, then the simulation accuracy and completeness are improved, but the data management complexity and difficulty increase

Engineering Contradiction:

Improvesimulation accuracyVSAvoiddata management complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the vast and diverse data sets into distinct categories (well data, field data, seismic data, geologic data, fluid data) and organizes them using a hierarchical data warehouse structure. This segmentation allows each data type to be managed independently while maintaining overall simulation accuracy, thereby reducing data management complexity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a data warehouse as an intermediary layer between various data sources and simulation models. This intermediary structure standardizes data formats, manages data relationships, and facilitates efficient data access, thereby handling diverse data sets without proportionally increasing management complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If historical data and measurements are maintained over the asset lifetime, then the simulation quality and decision-making are improved, but the data storage and retrieval complexity increase

Engineering Contradiction:

Improvesimulation qualityVSAvoiddata storage and retrieval complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements preliminary organization of historical data into a structured data warehouse with predefined schemas and relationships before simulations are run. Data is categorized, standardized, and indexed in advance, enabling efficient retrieval during simulations without increasing operational complexity when data needs to be accessed over the asset lifetime.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If data is organized and stored for efficient access across changing compute platforms, then the scalability is improved, but the data management system complexity increases

Engineering Contradiction:

ImprovescalabilityVSAvoiddata management system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent creates a universal data warehouse structure that can interface with multiple compute platforms and simulation tools through standardized protocols and formats. This multi-functional design allows the same data organization system to serve different platforms (analytics tools, visualization software, simulation models) without requiring platform-specific management complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If compute-intensive and data-intensive modeling is performed, then the simulation accuracy is improved, but the data processing time and resource requirements increase

Engineering Contradiction:

Improvesimulation accuracyVSAvoiddata processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent performs preliminary data processing, cleaning, and organization into standardized formats before simulations are executed. By pre-processing data into the required formats and structures, the actual simulation computing time is reduced while maintaining the accuracy required for compute-intensive modeling.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements a continuous data management system where data is organized, validated, and made available in real-time as simulations are run. This continuous availability of processed data eliminates repeated data preparation steps, reducing overall processing time while maintaining simulation accuracy across multiple runs over the asset lifetime.

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS11797577B2Smart data warehouse for cloud-based reservoir simulation

Publication Date: 2023.10.24 LANDMARK GRAPHICS CORP

AI summary

An intelligent data management system leverages heterogeneous database technologies and cloud technology to manage data for reservoir simulations across the lifetime of a corresponding energy asset(s) and facilitates access of that data by various consumers despite changing compute platforms and adoption of open source paradigms. The intelligent data management system identifies the various data units that constitute a reservoir simulation output for storage and organization. The intelligent data management system organizes the constituent data units across a file system and object database based on correspondence with different simulation run attributes: project, study, and model. The intelligent data management system also learns to specify or guide configuration of simulation runs.