Title: Introduction to Machine Learning for Geophysical Applications
Instructor: J.C. (Jaap) Mondt, Breakaway
Disciplines: Data Science - Machine Learning
Level: Foundation
CPD points: 10
Format:
This extensive and interactive course consists of videos, presentations, (reading) assignments and quizzes and 4-days live webinars with the instructor (PETRONAS In-house Course, 16-19 Aug). During the PETRONAS In-house Course, the instructor will be available for questions. You will then have time to study independently, review the course material and complete the assignments.
You will have access to the course material for a total period of 2 weeks from the start of the course (16 - 27 August 2021). Please ensure to complete all the requirements for the achievement of this course by this date.
Duration: 14 hours
Note this is an estimate of the time required to go through the course, including watching/reading lectures, attending webinars and completing quizzes.
Short Description
The aim of the course is to introduce how Machine Learning (ML) is used in predicting fluids and lithology. It will give an understanding of the “workflows” used in ML. The used algorithms can be studied separately using references. Power-point presentations and videos will introduce various aspects of ML, but the emphasis is on computer-based exercises using open-source software.
Topics Covered: The lectures and exercises deal with pre-conditioning the datasets (balancing the input classes, standardization & normalization of data) and applying several methods to classify the data: Bayes, Logistic, Multilayer Perceptron, Support Vector, Nearest Neighbour, AdaBoost, Trees. Non-linear Regression is used to predict porosity.
Learning Methods and Tools
At the end of the course participants will have a clear idea how Machine learning, being part of Artificial Intelligence will impact the future of Geosciences. This will be evident from the examples of Machine Learning discussed and applied to the case of predicting lithology and pore fluids.
Intended Audience
All those interested in understanding the impact Machine Learning will have on the Geosciences and then as an example the impact on lithology and pore-fluid prediction. Hence, geologists, geophysicists and engineers, involved in exploration and development of hydrocarbon or mineral resources
Pre-requisites
A basic understanding of Geophysics and Statistics. A Pre-requirement quiz can be taken by participants to check whether their knowledge of Geophysics and Statistics is sufficient to follow the course.
By enrolling in this course, you agree to Terms and Conditions for Registration within EAGE.