Drilling Rig Control System Knowledge Graph for Diagnostics
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Solution Overview
Problem
Current drilling rig control systems face challenges in efficiently managing and diagnosing complex interactions between various components, leading to suboptimal performance and increased maintenance costs due to the lack of comprehensive data communication and resource utilization analysis.
Innovation Solution
A method and system that generates a knowledge graph using machine learning algorithms to represent data communication and resource utilization between components of a drilling rig control system, enabling effective management, diagnostics, and maintenance by providing a unified commissioning and diagnostic framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional drilling rig control systems are used without comprehensive data communication analysis, then system complexity is reduced and ease of operation is maintained, but management efficiency and diagnostic capability deteriorate
Solution Approach 1:
The patent introduces a knowledge graph as an intermediary data structure that mediates between the complex control system components and the management/diagnostic processes. The knowledge graph captures data communication relationships and resource utilization metrics, enabling efficient querying and analysis without requiring direct complex interactions between all system components.
Solution Approach 2:
The patent replaces traditional manual analysis and mechanical diagnostic procedures with automated machine learning algorithms that process the knowledge graph. This substitution enables intelligent agents to perform commissioning, diagnostics, and maintenance tasks automatically, significantly improving productivity while managing system complexity through software-based solutions.
2Reliability
If comprehensive data communication and resource utilization analysis is implemented, then diagnostic capability and system reliability are improved, but device complexity and implementation difficulty increase
Solution Approach 1:
The patent performs preliminary action by capturing and storing data communication relationships and resource utilization metrics in the knowledge graph during system operation. This pre-processing of data enables rapid diagnostic queries and reliability assessments without requiring complex real-time analysis, as the foundational data structure is already in place.
Solution Approach 2:
The patent creates a virtual copy of the control system's data communication architecture in the form of a knowledge graph. This graphical representation copies the essential relationships and metrics, allowing analysts to study and diagnose system behavior without directly interacting with the complex physical system, thereby improving reliability while managing complexity.
3Loss of time
If manual analysis methods are used for component interactions, then system complexity is lower and ease of operation is maintained, but loss of time for diagnostics and maintenance increases
Solution Approach 1:
The patent implements self-service by enabling the system to automatically perform diagnostic and maintenance tasks through intelligent agents that query the knowledge graph and execute corrective actions. The system serves itself by identifying issues, analyzing root causes, and implementing solutions without requiring extensive manual intervention, thereby reducing diagnostic time while increasing automation.
Solution Approach 2:
The patent establishes feedback loops where the knowledge graph continuously receives updated data from control system components, and diagnostic algorithms continuously analyze this data to identify issues. This ongoing feedback mechanism enables real-time monitoring and rapid response to system anomalies, significantly reducing diagnostic time compared to manual periodic checks.
4Ease of operation
If standardized framework for commissioning and diagnostics is implemented, then ease of operation and maintenance efficiency are improved, but device complexity and framework development effort increase
Solution Approach 1:
The patent creates a universal knowledge graph framework that can be applied across different drilling rig control systems and configurations. The knowledge graph uses standardized data structures and relationships that can represent various components and interactions, enabling a single framework to handle multiple commissioning and diagnostic scenarios, thereby improving ease of operation while managing framework complexity through reusability.
Data Source
AI summary
A method for commissioning a drilling rig. The method includes detecting a first plurality of components of a drilling rig control system to control a drilling operation, obtaining a knowledge graph comprising a plurality of nodes corresponding to the first plurality of components, and a plurality of links connecting the plurality of nodes, wherein each of the plurality of links represents at least a target measure of data communication and resource utilization of each pair of components of the first plurality of components, and performing, by a drilling rig commissioning system and based on the knowledge graph, a management task of the drilling rig control system.