Publications | Indonesian Petroleum Association

Data-Driven Early Detection Model for Slugging in Offshore Gas Production Using Machine Learning: Case Study of NB Field

Year: 2025 Authors: Edyawan, W., Setiawan, D. Reference: IPA25-E-400

Keywords: Early detection, Machine Learning, Offshore gas production, Operational management, Predictive modeling, Random Forest, Reserve management, Slugging, data-driven approach, production optimization,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 49th Ann. Conv., 2025

Slugging presents significant operational challenges in offshore gas production, mainly when fluids from multiple wells are transported from an offsho...

A Machine Learning Approach for Early Fault Detection and Failure Prediction in Gas Turbines with Case Study: Avon 200 Combustor Crack and SOLAR Taurus 60-T7802 Thrust Balance Damage

Year: 2025 Authors: Fernanda, E., Arief, E., P., Afianto, D., Dadan, S. Reference: IPA25-F-395

Keywords: Anomaly detection, Condition-Based Monitoring, Failure Prediction, Gas Turbines, LSTM Auto Encoder, Machine Learning, Predictive modeling, Reliability, deep learning, preventive maintenance,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 49th Ann. Conv., 2025

The critical in our oil and gas company as a failure can led to significant production and financial losses are gas turbines. Based on our operational...

Development of A Predictive Wireless Sensor Network for Real-Time Hazardous Gas Monitoring in Confined Spaces in The Oil and Gas Industry

Year: 2025 Authors: Dewandaru, P., Siddiq, N., A., Baihaqi, M., I., Ritonga, F., J., A., Putra, A., S., S. Reference: IPA25-SE-249

Keywords: ESP32, Early Warning System, Gas Monitoring, Gas hazards, Oil and gas industry, Predictive modeling, Risk Management, Wireless Sensor Network (WSN), XGBoost, safety,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 49th Ann. Conv., 2025

Safety in the oil and gas industry is a critical concern, particularly in confined spaces where hazardous gases such as methane (CH₄) and hydrogen sul...

Result for 3 item(s)

Data-Driven Early Detection Model for Slugging in Offshore Gas Production Using Machine Learning: Case Study of NB Field

A Machine Learning Approach for Early Fault Detection and Failure Prediction in Gas Turbines with Case Study: Avon 200 Combustor Crack and SOLAR Taurus 60-T7802 Thrust Balance Damage

Development of A Predictive Wireless Sensor Network for Real-Time Hazardous Gas Monitoring in Confined Spaces in The Oil and Gas Industry