Applied Machine Learning and Data Science for Production Engineering
Join us for an immersive workshop tailored for professionals in the oil and gas industry to understand how machine learning can be implemented in production engineering and production monitoring domain Through hands-on exercises, attendees will explore data manipulation, visualization, and analysis techniques essential for optimizing production workflows.
Workshop Objectives
Day 1: Regression Problems in Production Domain Data
In day one the following topics will be covered.
Introduction to python.
Python as a tool for ML.
Introduction to regression problems(prediction)
Types of regression.
Time Series Analysis.
Hands on project on Regression Analysis
Day 2: Classification on Production Data
In day 2 we will be taking a look at the possibilities and features of applying classifications algorithms to oil and gas data.
Introduction to Classification.
Introduction to Decision tree
Introduction to Labeled Data
Hands on Project on Classification
About the Presenter
Mr. Nashat Jumaah Omar - 12+Years of Experience In Oil & Gas Industry
Applied Machine Learning for Upstream and Subsurface Domains
This two-day hands-on workshop is designed for petroleum and subsurface professionals seeking practical skills in machine learning for upstream oil & gas operations. The program teaches participants how to apply machine learning to uncover patterns in production and reservoir data, discover equations from historical relationships, and build predictive models for vital engineering parameters. Real-world datasets from drilling and subsurface domains are used, focusing on automating reports, visualizing data, and interpreting model outputs for improved decision-making.