ICE SC 6 | Data Science and Deep Learning in Exploration and Production
American Association of Petroleum Geologists (AAPG)
Sunday, 15 October 2017, 8:00 a.m.–5:00 p.m. | London, England
Objectives
Learning Outcomes
Participants will understand the basics of statistics, and machine learning. R, the open source statistical software will be introduced during the course, so participants will be able to practice after the course, and build their own tools. Deep learning libraries will also be mentioned, and practical example will be demonstrated.
Research topics on deep learning will be discussed to provide a broad knowledge of the current state of development of these techniques. Participants will get a good understanding of the different approaches, technologies and use cases of various deep learning methods.
Course Content
Course Overview
Data Science and Deep Learning in Exploration and Production is an introduction to statistical methods, and neural networks applicable for oil and gas industry scientists. During this course, participants will learn fundamentals of multi-variate analysis, and statistical validation of results. Predictive methods, such as regressions and neural networks will be presented, explained and applied to geophysical data.
Course Outline
A bit of history: development of statistics and machine learning
- History in all domains
- Focus on geosciences
- Overview of Descriptive statistics
- Introduction to Data mining
- Correlation and regression
- Probabilities
- Confidence Intervals
- Significance Tests
- Multivariate analysis
- Principal Component analysis and Discriminant analysis
- Factor analysis
- Analysis of Variance
From Machine Learning to Deep Learning
- What is machine learning?
- What are Artificial Neural Networks?
- Introduction to Deep Neural Networks
- A look at Convolutional Neural Networks for image detection
- Review of recent applications and trends in research
- Discussion on applications in G&G
- From facies analysis to inverting properties
- How can Deep networks model reservoirs and improve over time?
- The impact of deep learning on time series analysis
Fees
Professionals: US $495 + 20% VAT
Students: US $295 + 20% VAT
Includes: Course notes and refreshments
Limit: 20 Professionals and 5 Students
CEU: 0.8 PDH: 8
Venue
London, England - ExCeL Exhibition Centre
One Western Gateway, Royal Victoria Dock
London,
Aberdeen City
E16 1XL
United Kingdom
+44 (0)20 7069 5000