Short Course

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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

ICE SC 6 | Data Science and Deep Learning in Exploration and Production

London, England - ExCeL Exhibition Centre

One Western Gateway, Royal Victoria Dock

London, Aberdeen City E16 1XL

United Kingdom

+44 (0)20 7069 5000

Website Map

Instructor

Short course block

Important Notes Regarding Short Courses

Short courses are limited in size and are reserved on a first-come, first-served basis and must be accompanied by a full payment.
If you do not plan on attending the conference, a US $30 enrollment fee will be added to the short course fee. This fee may be applied toward registration if you decide to attend the conference at a later date.
A wait list is automatically created if a short course sells out. AAPG will notify you if space becomes available.
Before purchasing non-refundable airline tickets, confirm that the course will take place, as courses may be cancelled if undersubscribed.
Please register well before the deadline of 5 August 2024. Short course cancellations due to low enrollment will be considered at this time. No refunds will be allowed on short courses after 5 August 2024
We will continue to take registrations for short courses not cancelled until they are either sold out or closed.
Courses will be held in the Oman Convention and Exhibition Centre unless otherwise indicated. Participants will be advised via email of the specific location approximately two weeks prior to the course.

Cancellation Policy

Cancellations can be made by contacting ICE Registration on or before 5 August via email at [email protected]
Cancellations received on or before 5 August will receive a refund LESS a US $75 processing fee.
Refunds will not be issued after 5 August or for “no shows.”
You may substitute one participant for another.