HR-285 Neural Networks and Machine Learning Applications in Petroleum Exploration

Audience

Geoscientists, engineers and technical staff who want to understand statistical and machine learning theory and how to apply these increasingly critical techniques.

Content

- A comprehensive overview of the generation of seismic attributes
- A discussion on how to derive complex relationships between seismic attributes and petrophysical parameters
- An understanding of how to recognize reliable attributes when estimating reservoir parameters
- Basic theory of neural network and machine learning technologies
- Application of neural network technology in well log prediction, petrophysical volume generation and seismic lithology classification
- A combination of theory and practical exercises, which equip the user with the necessary skills to apply the Emerge software module to challenging geoscience tasks

Learning Objectives

Each section will include both numerical exercises and real data examples taken from geoscience. The objective of the course is to get behind all the current “hype” around the subject of machine learning and to understand the fundamentals of neural networks and machine learning. Mathematics will be fully explained.

Duration

2-days

Number of Participants

20-30

Prerequisites

None

Software Used

Course Format

Instructor-led, workflow-based, classroom training

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CGG GeoTraining offers the most comprehensive industry training based on years of practical experience acquired by our personnel.

Our proprietary courses are fully customizable and can be offered at a time and location convenient to you. Please request a course for more information.