About this Virtual Instructor Led Training (VILT)
Are you someone in Exploration & Production interested in using Python or vendor-specific Machine Learning (ML) and Deep Learning (DL) software to be a key member of your company’s digitalization project?
By the end of this Virtual Instructor-Led Training (VILT) course, participants can immediately see the value by applying ML and DL on their E&P datasets. This three-half-day VILT course will then get you going with sound background understanding, illustrated by real case studies.
This VILT course will equip participants with an understanding of:
- Fundamental concepts of Machine Learning and Deep Learning in O&G
- Machine Learning workflow and how to implement the steps effectively
- The role of performance metrics and how to identify their essential methods
- Upstream case studies with data and Python Notebooks for your practical application of ML/DL
This VILT course is designed for engineers, geologists, petrophysicists, geophysicists, and geoscientists – specifically, those involved with reservoir and production optimization in operating and service companies. The course is designed for those who want to apply reservoir description and data-driven modeling techniques for reservoir management. It is also for managers and supervisors who wish to update their skills to the technology’s current level. Oil & Gas professionals interested in understanding how to apply machine learning methods in their upstream projects and traditional workflows and who have some experience using Python in Jupyter Notebooks will find this VILT course beneficial.
- Engineers & data scientists in Oil & Gas companies: operators & services
- Technical professionals involved in upstream subsurface analysis & interpretation
This VILT will be delivered online in 3 half-day sessions comprising 4 hours per day, with two breaks of 10 minutes per day.
Course Duration: 3 half-day sessions, 4 hours per session (12 hours in total).
Day 1 opens the critical conversation of applying data-driven analytical models in three upstream areas. What are the standard soft-computing modeling practices in seismic data analysis, production optimization, and subsurface reservoir characterization? Day 1 also sheds light on data-driven approaches and helps participants decide when and how to get the most out of a digital transformation in O&G exploration.
Day 2 gets into the details and builds on the topics introduced on Day 1. Participants will go through an anonymized case study in each of the three areas: seismic analysis, production optimization, and subsurface reservoir characterization.
Day 3 will draw upon some advanced geophysical and petrophysical data-driven methodologies from the book ‘Enhance Oil & Gas Exploration with Data-driven Geophysical and Petrophysical Models,’ co-authored by your expert course leader. Participants will have the opportunity to run through some seismic images, reservoir characterization, seismic attributes analysis, and cover-well logs analysis to automate tops’ location and identify rock facies and fluid content.
To further optimise your learning experience from our courses, we also offer individualized “One to One” coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.
Request for further information about post training coaching support and fees applicable for this.
Learn what past participants have said about EnergyEdge training courses
I have known Mr. Keith Holdaway for many years. He is one of the best Domain Experts with solid understanding of AI and Machine Learning. I strongly recommend taking short courses that he teaches
Shahab D. Mohaghegh, Ph.D., CEO Intelligent Solutions Inc and Professor, Petroleum & Natural Gas Engineering, West Virginia University
This is a time of great change in the oil and gas industry, and even before embracing real time systems, we were struggling to extract meaningful insights from a large accumulation of data that was right under our noses. Based on his years of global experience, Keith has developed a deep technical understanding of these issues, and in his book, Harness Oil and Gas Big Data with Analytics, he combines this understanding with his unique talent for communicating complex issues in a straightforward manner