Applying a semi-quantitative risk assessment on petroleum production unit

Area of Science:

• Petroleum Engineering
• Industrial Safety
• Control Systems

Background:

• Industrial safety is paramount in the petroleum sector.
• Semi-quantitative risk assessment methods like Layers of Protection Analysis (LOPA) are crucial for facility maintenance.
• Existing methods like Hazard and Operability studies (HAZOP) and Fault Tree Analysis (FTA) have limitations in quantifying risk.

Purpose of the Study:

• To introduce a novel fuzzy logic system for mitigating crude oil shipping pump failures.
• To evaluate and select the most effective fuzzy membership functions for this application.
• To compare the proposed fuzzy logic system with the LOPA model for risk reduction.

Main Methods:

• A novel fuzzy logic system was developed to address pump failures.
• Various fuzzy membership function models were analyzed and compared.
• The fuzzy logic system's performance was evaluated against the Layers of Protection Analysis (LOPA) model.

Main Results:

• The fuzzy logic system effectively addresses crude oil shipping pump failures.
• The proposed model demonstrates advantages over the LOPA model in risk reduction.
• A simple and reliable control strategy was achieved using the fuzzy logic system.

Conclusions:

• The novel fuzzy logic system provides an effective and reliable method for controlling crude oil shipping pump failures.
• This approach offers significant advantages in reducing risk compared to traditional LOPA.
• The study highlights the potential of fuzzy logic systems in enhancing industrial safety within the petroleum industry.