The module on "Overview of Oil and Gas Industry" provides students with a comprehensive understanding of the fundamentals and key components of the oil and gas industry. It begins with an exploration of the origin and formation of crude oil, enabling students to grasp the geological processes that lead to its existence. It further discusses elaborately the accumulation and types of reservoirs, gaining insights into the various geological formations that contain oil and gas. The module provides an overview of the life cycle of oil and gas fields, covering exploration methods used to identify potential reserves. It also explores the equipment used in upstream oil and gas production, including drilling rigs, gathering stations and surface production/separation facilities. Furthermore, it introduces crude oil treating systems and natural gas processing, understanding the processes involved in refining and purifying these resources. The module concludes with an exploration of onshore and offshore hydrocarbon storage facilities, highlighting their importance in the oil and gas industry.

The module on "AI & ML Applications in the Oil and Gas Industry" explores the transformative role of artificial intelligence and machine learning in revolutionizing the operations and decision-making processes within the industry. The module begins with a comprehensive review of the impacts of ML in the oil and gas industry, highlighting the key advancements and benefits brought about by these technologies. It further delves into specific applications, starting with seismic data processing techniques, focusing on salt body delineation. It also explores the geomodelling process and its integration with AI and ML algorithms for accurate reservoir characterization. Reservoir engineering will be a key focus, with emphasis on ML techniques for reservoir rock classification and optimal production engineering. It gives insights into the application of AI in the upstream sector of the industry, exploring its use in exploration, drilling and production optimization. Advances in AI technology specific to the oil and gas industry is covered, including the integration of machine learning with sensor data, predictive maintenance and anomaly detection. It gives a fundamental understanding of data handling in the industry and the state-of-the-art approaches to handle big data in the oil and gas domain.