Machine Learning is not new to the industry, but few oil and gas players fully leverage its power in their workflows. Millions of dollars are at stake for Operators and financial service firms as they assess development and capital allocation scenarios.
Our teams of data science experts have spent over 6 years perfecting our technology built on patent-pending machine learning algorithms. Customers are enabled to increase operational efficiency and generate higher-quality forecasts in minutes. However, don't take our word for it!
In this open discussion, Michael Mast of Primexx will present a case study on his experience leveraging Novi's Machine Learning technology to optimize development and execute strategic planning.
Michael and Novi's Ted Cross will dive into:
Michael Mast has over 10 years of experience in Permian unconventional completions across various operational and technical roles. Michael joined Primexx in the fall of 2018 as the team’s Completion Engineer- focusing on completion optimization through diagnostics and data analytics. Michael’s role has since grown to address the company’s growing need for an improved spacing model.
As the Subsurface Engineering Manager, Michael leverages a multi-disciplinary workflow to inform well-spacing and completion design. Michael initially developed a proprietary spatio-temporal predictive model to forecast well production based on reservoir quality, spacing, and completion size. In late 2020, Michael incorporated Novi’s expertise to further develop and augment Primexx’s modeling capabilities.
Prior to Primexx, Michael worked for Halliburton Energy Services in various engineering roles, ultimately serving as a Technical Advisor on the Midland Technology Team.
Michael graduated from Rose-Hulman Institute of Technology in 2010 with a Bachelor’s degree in Chemical Engineering.
Ted Cross is Director of Product Management at Novi, where he guides product development efforts to bridge between the challenges operators face and solutions that advanced analytics and machine learning can provide. Ted has presented Novi's technology in a number of conferences and workshops sponsored by AAPG, SEG, and SPE. His work has been featured in JPT and selected three times as "Best of URTeC”.
Prior to joining Novi, Ted worked as a geologist for ConocoPhillips in a range of roles including Williston Basin development, Lower 48 exploration, global new ventures, and deepwater Gulf of Mexico exploration. He has applied advanced analytics across the asset life cycle and served as an instructor in Conoco's Citizen Data Scientists course.
He received a Master's in Geology from the University of Arizona, where he received an NSF Graduate Research Fellowship. His thesis focused on the structure and tectonic evolution of the Lesser Himalaya of central Nepal. Ted attended the University of Texas at Austin for undergraduate work, graduating with a B.S. in Earth Sciences and a B.A. in Plan II Honors.