COMING SOON: IBM Presentation – Machine Learning Application to Real World Problems in Energy & Mining

Dr. Omolade Saliu will talk about machine learning applied to energy and mining

Date and location TBA.

Machine Learning Application to Real World Problems in Energy & Mining

Abstract: The Advanced Analytics & AI Practice of the IBM Global Business Services (GBS) help clients drive business value through innovative application of Artificial Intelligence to challenging industry problems. Our Calgary based team of Data Scientists specializes in solving these complex business problems for IBM customers in Energy & Mining. In this talk, I will introduce the range of problems we are solving for our customers as part of our Watson for Natural Resources (WNR) Industry. The talk will then focus on two of our most recent use cases: (1) the implementation of a 3D-convolutional neural networks (3D-CNN) solution to predict the level of gold mineralization at any specified location within the boundaries of a gold mine and (2) the application of physics constrained machine learning modeling approach to sub-surface heavy oil production forecasting and steam allocation problem in a Steam Assisted Gravity Drainage (SAGD) operation. I will share our experiences in addressing the unique challenges encountered in this exciting domain of applied machine learning research.

Bio: Omolade is the Lead Data Scientist for Natural Resources at IBM. He leads a team of Data Scientists, providing thought leadership in the translation of business problems to data science and overseeing the design and implementation of innovative machine learning and AI solutions to drive business results for our clients. He is a hands-on leader with broad industry exposure and 20 years of consulting and research experience in implementing and managing predictive modeling, mathematical optimization, and business intelligence solutions across various industries, including over 10 years of primary focus in the Energy and Mining space. Omolade is the author of numerous publications in international journals, conferences, book chapters and six(6) filed US Patents. An NSERC and Alberta iCORE scholar, Omolade obtained his PhD in Computer Science at the University of Calgary in 2007. He was featured in the April 2015 Edition of the Alberta Oil Magazine discussing the application of Machine Learning in Oil & Gas.