Flexible Framework Integrating External Visualization Algorithms
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Solution Overview
Problem
Current petroleum reservoir visualization software lacks a flexible framework to integrate external algorithms without modifying them, limiting the ability to select the best visualization method for specific data domains.
Innovation Solution
A method and system for integrating external visualization algorithms into a flexible framework by selecting a valid API, executing the algorithm, translating results to geometry primitives, applying attributes and surface normal vectors, and creating a new visualization display, allowing external algorithms to be used as-is.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If visualization software uses a fixed framework with internal algorithms only, then the software structure remains simple and stable, but the adaptability to different data domains and visualization methods is limited
Solution Approach 1:
The system is divided into distinct modules: an external algorithm interface module that accepts third-party algorithms, a data translation module that converts between different data formats, and a core visualization framework. This segmentation allows external algorithms to be integrated without complicating the entire system, as each module handles specific tasks independently.
Solution Approach 2:
A data translation layer acts as an intermediary between external visualization algorithms and the core software framework. This mediator converts external algorithm outputs into the internal data structures required by the visualization system, enabling algorithm integration without direct modification of either the external algorithms or the core framework.
2Adaptability or versatility
If external visualization algorithms are integrated by modifying them to fit the software framework, then the algorithms can be used within the system, but the algorithms lose their original functionality and require substantial revision
Solution Approach 1:
The data translation layer serves as an intermediary that preserves the integrity of external algorithms by preventing direct modification. It translates between external algorithm data formats and internal framework requirements, allowing algorithms to be used as-is while maintaining their original functionality and reliability.
Solution Approach 2:
The external algorithm interface is designed with universal data structures and standardized communication protocols that can accommodate multiple different visualization algorithms from various sources. This universality allows diverse algorithms to be integrated without requiring algorithm-specific modifications to the framework or the algorithms themselves.
3Adaptability or versatility
If the software provides a flexible framework for external algorithms, then various visualization methods can be used, but the device complexity and integration difficulty increase
Solution Approach 1:
The system uses configurable parameters and standardized data structure definitions that can be adjusted to match different external algorithms. By changing data format parameters rather than restructuring the entire framework, the system maintains ease of integration while supporting diverse visualization methods.
Solution Approach 2:
Instead of requiring complex custom integration for each external algorithm, the system creates simplified copy interface definitions that replicate the essential data exchange requirements. This copying approach reduces integration complexity by providing template-based interfaces that can be quickly adapted to different algorithms without deep customization.
Data Source
AI summary
Systems and methods for integrating external algorithms into a flexible framework for imaging visualization data without altering the external algorithm to fit the flexible framework.