This course gives a holistic understanding of the industry's core principles, while uncovering the transformative potential of AI&ML technologies in revolutionizing operations and decision-making processes within the oil and gas industry. It explains how ML techniques enhance seismic data processing, geomodelling and reservoir engineering, enabling accurate reservoir characterization and optimal production engineering. It also explores the vast potential of AI in the upstream sector, revolutionizing exploration, drilling and production optimization. It keeps the learners updated on the latest advances in AI technology and big data handling, empowering them to drive innovation and efficiency in the industry.
Course Objectives
Online
2 units
IITM Pravartak Technologies Foundation
Technology Innovation Hub (TIH) of IIT Madras
and
L&T EduTech
Rs. 1750/- Inclusive of Tax
Students pursuing Diploma / UG / PG Programs in Chemical/ Petroleum/ Oil and Gas Engineering.
Basic Chemical/ Petroleum/ Oil and Gas Engineering
5
Dr Jagannathan Krishnan
Subject Matter Expert, Chemical Engineering, L&T EduTech
A Professionally motivated Chemical Engineer obtained both M.Tech and Ph.D from Indian Institute of Technology Madras. He has over 25 years of teaching and research experience in Chemical Engineering, serving institutions like IIT Madras, VIT University, SSN Institutions in India and Universiti Teknologi Mara (UiTM) Malaysia.
Origin and formation of crude oil; types of reservoir; oil and gas field life cycle; oil and gas exploration methods; Equipment in Upstream Oil and Gas Production; oil and gas drilling process; gathering stations; Surface Production/Separation Facility; crude oil treating systems; natural gas processing; Onshore and Offshore Hydrocarbon Storage Facilities.
Impacts of ML in O&G Industry; Seismic Data Processing Techniques; Geomodelling Process; ML in Reservoir Engineering; Optimal Production Engineering in O&G Industry; AI in upstream sector of O&G Industry; Advances in AI Technology for O&G Industry; Fundamentals of Data handling in O&G Industry; SOA of big data for O&G Industry.