Energy Institute of the Americas
The Energy Institute of the Americas (EIA) was chartered in May 1995 by the University of Oklahoma and Simon Bolivar University in Caracas, Venezuela, to address issues raised by the growing economic interdependency of the Americas.
It achieves its mission through educating and training professionals in skills and knowledge needed for energy development and related environmental issues; conducting multi-national interdisciplinary research by promoting collaboration between professors and researchers in the Hemisphere; resolving technical problems through application of research results; assisting Oklahoma oil and gas independent and service companies that want to do business in Latin America; providing a hemispheric database and clearinghouse for information and expertise; and forming a hemispheric network of academic, industrial and government organizations.
The EIA has positioned itself as a source for training, research capabilities and business opportunities in the Western Hemisphere. Yoana Walschap, who has been associated with the institute since its inception, replaced Ambassador Corr as the executive director in 2002 and continues today to enhance the program.
In the last 17 years, EIA has coordinated over 90 short-courses for the oil and gas industry in different countries in Latina America and Europe. The EIA has an ample network of contacts in the Western Hemisphere ranging from universities, research centers, private and public sector. Starting in 2018 the EIA is developing short courses at OU and in the United States for industry professionals to enhance the education opportunities to the most valuable resource of all, its human resource. The strength of the oil business lies in the professionals who have the adequate educational capacity and knowledge of new technologies.
This course will present an overview of some common machine learning techniques deployed in shale reservoir characterization. Emphasis will be on the use of neural networks in Bakken and Wolfcamp shale formations using Python and Tensorflow. It is designed for petroleum engineers and geoscientists will learn about the latest applications of machine learning and neural networks in reservoir characterization. Attendees will learn to write machine learning codes using Python and Tensorflow.
California Machine Learning