e-Courses Catalog

Machine Learning Essentials (without certification)

Machine Learning Essentials (with certification)

The course is ideal for geoscientists, engineers, and data analysts at all experience levels. Concepts are supported with ample illustrations and case studies, complemented by mathematical rigor benefiting the subject. Aspects of supervised learning, unsupervised learning, classification, and reclassification are introduced to illustrate how these methods apply to seismic data. For this version of the class, assessments are given at intervals throughout the course to gauge comprehension. Upon completion with a passing total score, a certificate is issue, certified by Geophysical Insights. Read more

Instructor: Dr. Tom Smith, President and CEO, Geophysical Insights
Total classroom time: 12 hours
Cost: $425 Free

Machine Learning Essentials (with certification)

Machine Learning Essentials (without certification)

The course is ideal for geoscientists, engineers, and data analysts at all experience levels. Concepts are supported with ample illustrations and case studies, complemented by mathematical rigor benefiting the subject. Aspects of supervised learning, unsupervised learning, classification, and reclassification are introduced to illustrate how these methods apply to seismic data. For this version of the class, no assessments or certification is included. Read more

Instructor: Dr. Tom Smith, President and CEO, Geophysical Insights
Total classroom time: 12 hours
Cost: $395 Free

Seismic Attributes for the Environment of Deposition

Seismic Attributes for the Environment of Deposition (without certification)

The evaluation of seismic attributes is a powerful tool in the interpretation of different geologic environments of deposition. Seismic attributes, specifically geometric and spectral decomposition attributes, provide a framework for interpreting geologic features that define depositional environments. This video course identifies the appropriate seismic attributes for various geologic settings and describes how these attributes are applied. Lecture and demonstrations cover the use of attributes in interpretation workflows and manipulate attribute parameters to highlight geologic features. The last video segment of the course describes how sets of attributes are analyzed and classified using multi-attribute, Machine Learning processes to extract more information from the seismic response. Read more

Instructors: Dr. Kurt Marfurt, The University of Oklahoma | Dr. ChingWen Chen, Geophysical Insights | Rocky Roden, Geophysical Insights
Total classroom time: 5 hours
Cost: $95 Free

Energy Absorption and Traveling Waves

Energy Absorption and Traveling Waves (without certification)

Waves of elastic energy travel through the Earth with the same physical principles as other waves travel through different mediums. This video focuses on the physics of traveling waves and why energy absorption is important to an understanding of seismic data. Starting with a liner second-order vibrating system as a mathematical model, the 50-minute short course presents the classes of waves and their associated measurements. The basics of energy loss in traveling waves are described, as well as the relationship between vibration and energy loss. A simplified model of the seismic geophone is used to described attenuation and damping ratio. Read more

Instructor: Dr. Tom Smith, President and CEO, Geophysical Insights
Total classroom time: 1 hours
Cost: $49 Free

Introduction to Machine Learning for Interpreters

Introduction to Machine Learning for Interpreters (COMING SOON)

Every day our lives are intertwined with applications, services, orders, products, research, and objects that are incorporated, produced, or effected in some way by Artificial Intelligence and Machine Learning. Buzz words like Deep Learning, Big Data, Supervised and Unsupervised Learning are employed routinely to describe Machine Learning, but how do these applications relate to geoscience interpretation and finding oil and gas. More importantly, do these Machine Learning methods produce better results than conventional interpretation approaches? This course will initially wade through the vernacular of Machine Learning and Data Science as it relates to the geoscientist. An overview of how these methods are being employed, as well as, interpretation case studies of different machine learning applications will be presented. An overview of how high performance computing and the utilization of Cloud Services related to Machine Learning will be described. Machine Learning is a disruptive technology that holds great promise and this course will be presented from an interpreter’s perspective, not a data scientist. This course will provide an understanding of how Machine Learning for interpretation is being utilized today and provide insights on future directions and trends.

Instructor: Rocky Roden, Sr. Consulting Geophysicist, Geophysical Insights
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Machine Learning for Incomplete Geoscientists

Machine Learning for Incomplete Geoscientists (COMING SOON)

This course covers big-picture machine learning buzz words with both humor and unassailable frankness. The goal of the course is for every geoscientist to gain confidence in these important concepts and how they add to our well-established practices, particularly seismic interpretation. Presentation topics include a machine learning historical perspective, what makes it different, a fish factory, Shazam, comparison of supervised and unsupervised machine learning methods with examples, tuning thickness, deep learning, hard/soft attribute spaces, seismic wavelets and multi-attribute samples, and several interpretation examples. On conclusion, you may not know how to run machine learning algorithms, but you should be able to appreciate their value and some of their limitations.

Instructor: Dr. Tom Smith, President and CEO, Geophysical Insights
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