Course Details

Your Growth, Our Mission

Machine learning & Data Management in Oil and Gas Industry
Course Description
• Machine learning (ML) focuses on the use and development of computer systems that learn from data and past experiences while identifying patterns to make predictions with minimal human intervention. • The Oil and Gas sector recognizes the profound shifts occurring in the energy and technological realms, shaped by interconnected drivers of growth: escalating energy demand, the transformation of energy systems, and ongoing technological evolution and revolution. • As the Oil and Gas industry undergoes transformation, there is a heightened need to amalgamate leadership prowess, domain expertise, and knowledge, addressing the persisting data silos within organizations. This course is designed to provide a foundational understanding of the petroleum industry and machine learning, along with comprehensive data management. Its primary aim is to empower organizations within the industry to leverage their data effectively, mitigating the omnipresent risk and uncertainty prevalent in the oil and gas sector, and fostering a path to success.

This training course is suitable to a wide range of professionals but will greatly benefit:
• Petroleum Data Analysts
• Petroleum Engineers
• Systems Analysts
• Programmers
• Data Analysts
• Database Administrators
• Project Leaders
• Managers
• Software Engineers

Course outline
Day 1
• What is artificial intelligence?
• Applications of artificial intelligence in oil and gas industry.
• Case studies and examples of the application of Artificial Intelligence in Oil and gas Industry.
Day 2
• Introduction to Machine Learning
• History of machine learning in oil and gas industry
• Machine Learning Algorithms.
• Artificial neural network (ANN).
• Data Management from the DCS to the Historian
Day 3
• Project Management for a Machine Learning Project
• Big Data in Oil and Gas Industry
• Detecting Electric Submersible Pump Failures
 
Day 4
• Predictive and Diagnostic Maintenance for Rod Pumps
• Forecasting Slugging in Gas Lift Wells
• Machine Learning application to optimize production in heavy oil reservoirs.
 
Day 5
• Rate of Penetration Prediction in Drilling Operation in Oil and Gas Wells by K-Nearest Neighbors and Multilayer Perceptron Algorithms.
• Prediction of fold-of-increase in productivity index post limited entry fracturing using artificial neural network

 

BTS attendance certificate will be issued to all attendees completing minimum of 80% of the total course duration.

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Course Rounds

5 Days
Code Date Venue Fees Action
DE254-01
2026-04-06
Istanbul
USD 5950
Register
DE254-02
2026-07-05
Dubai
USD 5550
Register
DE254-03
2026-09-20
Marrakesh
USD 5450
Register
DE254-04
2026-12-27
Dubai
USD 5450
Register

Prices don't include VAT

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Your Growth, Our Mission

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