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Machine Learning and Data Management in the Oil and Gas industry

Boosting Efficiency and Accuracy with AI-Driven Analytics and Automation

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Course Schedule

27-31 Oct 2025

Dubai

$5,950

27-31 Oct 2025

Online

$3,950

Course Overview

This training course on Machine Learning and Data Management in the Oil and Gas Industry focuses on the fact that energy and technological worlds are witnessing drastic changes that are influenced by intertwined causes of growth: energy demand, transition of energy systems, technological evolution and revolution.

As the oil and gas industry is evolving and changing the necessity of bringing together leadership power, domain expertise, knowledge, and many data silos that still exist within the organizations. This training course focuses on fundamental understanding of the petroleum industry and machine learning, as well as the data management, helping the organizations within the industry to achieve success by using the data they possess and reduce the risk and uncertainty which is omnipresent in oil and gas industry.

This Machine Learning and Data Management in the Oil and Gas Industry training course will highlight:

Importance of Data analysis and removal of obstacles for unified data flow
Data cleaning practices and techniques
Interpretation of data, as well as machine learning techniques within the oil and gas industry
CDMP® Data Management Fundamentals examination
Components of an enterprise data / information management framework
Main application areas of machine learning and data management in oil and gas industry

What are the Goals?

This training course focuses on presenting the delegates with the opportunity to learn the essentials of data governance, data collection and management, data security, data analysis, Machine Learning algorithms and their implementation within oil and gas industry.

By the end of this Machine Learning and Data Management in the Oil and Gas Industry training course, participants will learn to:

Learn to identify the impact of data quality and data management on success of oil and gas enterprise
Acquire the knowledge about data management framework across the enterprises
Identify the machine learning algorithms applied within the oil and gas industry
Learn how to gather, transform and use the spatial, seismic, production and other data
Identify the relations between the master data management process optimization

Who is this Training Course for?

The training course has been designed for professionals whose jobs involve the data gathering, data analysis, decision making.

This training course is suitable to a wide range of professionals but will greatly benefit:

Petroleum Data Analysts
CEOs, CIOs, COOs
Systems Analysts
Programmers
Data Analysts
Database Administrators
Project Leaders
Software Engineers

How will this Training Course be Presented?

The training course uses a number of proved adult learning techniques, theoretical presentations with practical work of the delegates on how to properly use the data in their enterprise, how to prepare and implement the retention schedule and how to define the data architecture applicable for their enterprise. The course also teaches the delegates how to use available software as well as combine it with R, Python and other available software to achieve improvement in exploration, production, operation as well as other areas where the data and machine learning combination can help organization achieve improvements and optimization.

Course Outline

Day 1

Data sources
Data rules for well identification and classification
PPDM data model
Geospatial data storage, analysis and use
Machine learning in geospatial data

Day 2

Machine learning algorithms
Python programming
R programming
Use of existing software and its combination with Python and R
Tensorflow

Day 3

Forecasting
Anomaly detection
Process control
Optimization
Maintenance
HSE
Other areas

Day 4

Data from SCADA
Data from sensors
Data from ECM
Data visualization
Data Analytics techniques for immediate insights

Day 5

Digital core
Digital oilfield
Machine learning in predictive maintenance
Use of soft sensors
Example cases and way forward

Accreditation

GLOMACS is registered with NASBA as a sponsor of Continuing Professional Education (CPE) on the National Registry of CPE Sponsors. NASBA have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.learningmarket.org.

All Training Seminars delivered by GLOMACS by default are eligible for CPE Credit.

Would you like to take this course as a team?

Frequently Asked Questions

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Our courses are open to professionals at all career levels — from beginners seeking to understand AI fundamentals to senior executives aiming to integrate AI into organizational strategy. Each course clearly outlines the ideal participant profile to help you choose the best fit for your goals.

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