Dr. Tom Smith presenting on Machine Learning at the 3D Seismic Symposium on March 6th in Denver
What is the "holy grail" of Machine Learning in seismic interpretation? by Dr. Tom Smith, GSH Luncheon 2018
Using Attributes to Interpret the Environment of Deposition - A Video Course. Taught by Kurt Marfurt, Rocky Roden, and ChingWen Chen
Dr. Kurt Marfurt and Dr. Tom Smith featured in the July edition of AOGR on Machine Learning and Multi-Attribute Analysis
Rocky Roden and Ching Wen Chen in May edition of First Break - Interpretation of DHI Characteristics using Machine Learning
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Generation and Application of Seismic Attributes in Paradise

Date: November 30 - December 1, 2017
Location: Houston, TX
Time: 8:00 am - 4:30 pm
Instructor(s): Blaine Taylor
Cost: $1,500

As the name indicates, this course exercises the Attribute Generator in Paradise to generate, understand, and apply the various classes of attributes available in the comprehensive Paradise attribute library.  Those interested in taking this course should have taken the Paradise Essentials course, logged extensive experience with Paradise, and/or viewed the set of online Paradise training videos.

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Course outline: Day 1

Basic Attribute Review

  • Instantaneous Attribute (19)  Description, Interpretation Usage, Calculation equations, Generation and preliminary viewing of single attributes.

  • Geometric Attribute (55) Description, Interpretation Usage, Calculation equations, Generation and preliminary viewing of single attributes.

  • Spectral Decomposition Attribute (27) Description, Interpretation Usage, Calculation equations, Generation and preliminary viewing of single attributes.

  • By the end of the Day 1 the above attributes have either been generated or will be completed overnight, and ready at the beginning of the second day for multi-attribute analysis.

Course Outline: Day 2

The second day will instruct in simultaneous analysis of multiple attributes using Neural Network,  Machine Learning technology with the aim of identifying geologic patterns in the Great Southern Basin 3D dataset from New Zealand.  Consequently, the student must be familiar with how to use Paradise as a prerequisite to this course.

The capstone of the second day is selecting the optimum combination (set) of attributes for specific geological features.

Quantity:
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