Method and system for guaranteeing safety of offshore oil well control equipment
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Solution Overview
Problem
Traditional maintenance methods for offshore oil well control equipment fail to monitor the real-time status and make timely decisions during the drilling process, making it difficult to assess the equipment's availability and life state effectively.
Innovation Solution
A method and system that identify the state of the main structure, hydraulic control unit, and electronic control unit of offshore oil well control equipment using signal processing and Bayesian networks, predicting potential faults, and making real-time decisions based on these assessments to ensure safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If regular maintenance is performed by hoisting equipment to the drilling platform for testing, then the equipment can be tested and parameters analyzed, but real-time monitoring capability is lost and timely decision-making during drilling operations becomes difficult
Solution Approach 1:
The system performs preliminary state identification and fault prediction by continuously monitoring equipment parameters and storing historical data. Bayesian networks are pre-established to model component relationships, enabling the system to predict potential failures before they occur, thus preparing maintenance decisions in advance rather than waiting for regular maintenance intervals
Solution Approach 2:
The system implements real-time feedback through continuous monitoring of equipment states and fault probabilities. The Bayesian network dynamically updates component failure probabilities based on current sensor data and historical patterns, providing ongoing feedback that enables timely drilling decisions while maintaining accurate equipment state assessment
2Reliability
If traditional regular maintenance methods are used, then equipment safety is maintained to a certain extent, but real-time status monitoring and availability assessment are insufficient
Solution Approach 1:
The system ensures continuous monitoring of equipment status through uninterrupted data collection from sensors during drilling operations. This continuous action provides ongoing reliability assessment and real-time status information, eliminating the information gaps inherent in periodic maintenance approaches while maintaining equipment safety
Solution Approach 2:
The Bayesian network acts as an intermediary that processes raw sensor data and historical information to generate meaningful reliability assessments and fault predictions. This intermediary layer transforms continuous data streams into actionable reliability information, providing both real-time status monitoring and safety assurance simultaneously
Data Source
AI summary
The present disclosure belongs to the field of marine engineering, and in particular relates to a method and system for guaranteeing the safety of offshore oil well control equipment. The method comprises: identifying the state of a main structure of the offshore oil well control equipment, identifying the state of a hydraulic control unit of offshore oil well control equipment, identifying the state of an electronic control unit of offshore oil well control equipment, predicting the state of the offshore oil well control equipment and making a real-time decision based on existing information; and the system for guaranteeing the safety of the offshore oil well control equipment comprises a state identification subsystem of a main structure, a state identification subsystem of the hydraulic control unit, a state identification subsystem of the electronic control unit and a state prediction and real-time decision subsystem.