PETROLEUM ANALYTICS AND DATA SCIENCE IN THE MANAGING OIL AND GAS ASSETS
COURSE OVERVIEW & LEARNING OUTCOMES
There is a digital revolution underway in almost all of the human endeavor. In the O&G industry many
wonder what it really is; even though they see its implementation around them. Big data and its analysis are fast becoming an important differentiator in the Upstream oil business. Through big data analytics and data-driven analysis of trends and patterns, industry professionals have opened the fairway of production optimization, reservoir performance prediction and enhanced recovery. Data Analytics presents a great opportunity to leverage big data in reducing costs.
This course presents a realistic and science-based understanding of this technology versus traditional statistics enough to generate interests and promote increased adoption in O&G organizations. It cuts through the jargons and deep science of the subject to focus more on its application
TARGET PARTICIPANTS
Geoscientists,
Engineers: Reservoir, Drilling and Completions,
Production and Operations,
Facilities etc.
EXAMPLE MODULES
Introduction to machine learning terminology and workflows
Introduction to data analytics and workflows
Difference between business analytics and data analytics
Current data management practices, silos, clouds, and lakes
Types of data
Data federation, QA/QC
Use-cases: unsupervised and supervised machine learning algorithms
Data Story Telling - visualization and communications challenges
Predictive Analytics
Overview of Artificial Intelligence (AI) and Machine Learning (ML)
Artificial Neural Networks (Deep Learning)
Fuzzy Set Theory
Evolutionary Computation
Engineering & Non-Engineering Problem Solving using AI&ML
Traditional Statistics vs. Artificial Intelligence and Machine Learning
Petroleum Data Analytics in Conventional O&G Resources
Data-Driven Reservoir Modeling - Top-Down Modeling (TDM)
Case Studies
DURATION
5 Days
LOCATIONS:
Accra,
Kigali,
Dubai,
London,
Houston.