Correlating Metadata and Asset-Logic Models
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Solution Overview
Problem
Current systems fail to provide uninterrupted interoperability among various data sets, applications, and stakeholders in oil and gas production assets due to lack of a framework for handling transformations and definitions between different system components, leading to incomplete data replication and limited workflow support.
Innovation Solution
A method and system for correlating only approved manipulations of meta-data model representations and asset-logic model representations within a system model, involving manipulation, recording, and transformation of these models on a computer system to ensure data integrity and interoperability across stakeholders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data replication is implemented where each stakeholder develops or receives its own version of the logical network and data model, then each stakeholder can access required data, but data integrity and consistency across stakeholders cannot be effectively controlled
Solution Approach 1:
The patent introduces a central correlation system that acts as an intermediary between multiple stakeholders and the data model. This correlation system maintains a unified version of the logical network and data model, mediating all access and transformation requests to ensure data integrity while allowing each stakeholder to access their required data through controlled transformations.
Solution Approach 2:
The patent creates a universal data model representation that serves all stakeholders simultaneously. Instead of creating separate versions for each stakeholder, a single authoritative data model is maintained that can be transformed and presented to multiple stakeholders according to their specific requirements, ensuring consistency across all accesses.
2Adaptability or versatility
If point to point integration is used to achieve interoperability, then specific workflows can be supported, but the system is limited to supporting only single workflows and cannot handle multiple workflows effectively
Solution Approach 1:
The patent implements a universal correlation system that can handle multiple workflows simultaneously through a single integrated architecture. The system provides multi-functional capabilities to support various workflows without requiring separate point-to-point integrations for each workflow, thereby reducing integration complexity while maintaining versatility.
Solution Approach 2:
The patent segments the integration architecture into modular components including the correlation system, transformation engine, and stakeholder interfaces. This segmentation allows the system to handle multiple workflows independently through standardized interfaces while maintaining overall system coherence and reducing complexity.
3Ease of operation
If each stakeholder can independently decide whether to accept and communicate changes to the data model, then stakeholders have autonomy, but changes to the data model representations cannot be effectively controlled in a systematic and system-wide way
Solution Approach 1:
The patent implements a feedback mechanism where the correlation system monitors and tracks all changes to the data model across stakeholders. When a stakeholder proposes or accepts changes, the system provides feedback to ensure systematic control, validate consistency, and communicate approved changes to all relevant stakeholders, maintaining both autonomy and control.
Solution Approach 2:
The patent requires that change proposals be submitted and approved through the correlation system before implementation. This preliminary action ensures that all changes are evaluated, approved, and recorded systematically before being applied to the data model, preventing uncontrolled modifications while maintaining stakeholder involvement.
Data Source
AI summary
Systems and methods for correlating meta-data model representations and asset-logic model representations in a system model. The system model may be deployed in conjunction with a production allocation application, whereby data pertaining to allocation changes to a production system might be more readily identified for different purposes such as, for example, technical and/or fiscal allocation.