Training Course

Artificial Intelligence AI and Data Analytics DA For Energy Exploration and Production

12 November
13.30-17.00
Xanadu Resort Hotel
Antalya | Türkiye

*Course Fees: free for EGCE delegate

To Register

Email to : Cansu Arıcan

carican@ankara.edu.tr

! RSVP by: 21th of October 2023

Course Description

This half-day course sampler is based on a pioneering and original new book written by the foremost knowledgeable authorities on the application of datas cience and artificial intelligence techniques in exploration and production in the energy industry, covering the most comprehensive and updated new processes, concepts, and practical applications in the field. The complete course could be given as a 3 to 10 day course with different levels of details and tailor-made to different audiences

Course prerequisite

High level of understanding of the oil and gas industry, General knowledge of digital technologies
Knowledge or prior course in statistics, math, machine learning, smart drilling, and other computationally intensive courses to traditional geosciences and petroleum engineering are desirable.

Who should attend?

Any professional (he/she) works in the energy industry of exploration, production, IT professionals and data scientists.

Course Outline

Chapter 1 Introduction to Modern Intelligent Data Analysis
Chapter 2 Machine Learning and Human Computer Interface
Chapter 3 Artificial Neural Networks
Chapter 4 Fuzzy Logic
Chapter 5 Integration of Conventional and Unconventional Methods
Chapter 6 Natural Language Processing (NLP)
Chapter 7 Data Science and Big Data Analytics
Chapter 8 Applications of Machine Learning in Exploration
Chapter 9 Applications in Oil and Gas Drilling
Chapter 10 Applications in Reservoir Characterization, Field Development
Chapter 11 ML Applications in Production Forecasting
Chapter 12 Applications in Production Optimization, well Completion
Chapter 13 ML Applications in Reservoir Engineering and Simulation
Chapter 14 Machine Learning Applications in Artificial Lift
Chapter 15 ML Applications in Enhanced Oil and Gas Recovery
Chapter 16 Conclusions and Future Direction

About the Course

The course is designed to support new digital strategies/ technologies using artificial intelligence and machine learning developments in exploration, production, optimization of supply chains, carbon sequestration, and other applications.
Participants will learn the essential technical details on many tools used in “smart oil fields”
pattern recognition, neural networks,
fuzzy logic, evolutionary computing,
expert systems, artificial intelligence machine learning,
human-computer interface, natural language processing,
data analytics and next-generation visualization.
Overall understanding of the AI and ML applications for oil and gas from both geoscientists and petroleum/reservoir engineers’ point of view.

About Dr. Fred Aminzadeh, the Instructor

President of FACT Inc.
Co-founder of Energy Transition International
Past president of Society of Exploration Geophysicists
Previously a professor at
-University of Houston (UH), leading its AIM-Deep and
-University of Southern California leading its Center for Interactive Smart Oil field Technologies, leading its Global Energy Network (GEN.USC.edu)Taught 50+ short courses worldwide and three courses at UH and USC
-Data Analytics and Machine Learning for Exploration and Production (UH)
-Intelligent and Collaborative Oilfield Systems Characterization & Management (USC)
-Advanced Oilfield Operations with Remote Visualization and Control (USC)
Over 30 years of experience in the oil and gas industry including 20 years at Unocal (now part of Chevron) and 10 years at dGB(with its OpndTectsoftware)
Worked at Bell Laboratories and consulted for LBNL, LANL, ORNL and NETL# Fellow of IEEE and Honorary member of SEG.
Authored 16 books & 4 patents
PhD / MS (USC), Electrical Engineering with minor in Geophysics