Machine Learning and Data Management in the Oil and Gas industry

Introduction

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

Objectives

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

Training Methodology

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.

Organisational Impact

Data is now main element of sustainability and improvement. When the companies properly acquire, analyze, manage, store and secure their data they gain incredible competitive advantage, however it is not enough only to collect and store the data as the data itself does not guarantee success, the important element is to discover meaning within the data, correlation and causational paths which will help organizations improve their operations and planning by limiting and mitigating the risks of uncertainty.

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

• Optimal principles of data management
• Creation of data centric organization and adequate management of company data
• Machine learning techniques and algorithms
• Implementation of machine learning in anomaly detection
• Principal Component Analysis and other techniques used

Personal Impact

The delegates will learn from the experiences of real projects, get the insight into the success stories, problems and even failures to be able to avoid mistakes, identify adequate use cases and implement proper methods and algorithms.

The delegates will acquire:

• Full knowledge of data management, analysis and interpretation
• Anomaly detection and risks mitigation measures related to data quality and data security
• Use of available software and applications
• Insight into the ways of removing data silos within the organization
• Knowledge of modern Machine Learning algorithms and techniques used