Shahab D Mohaghegh
West Virginia University, USA Intelligent Solutions, Inc., USA
Title: Fact-based modeling; analysis, predictive modeling and optimization of hydraulic fracturing in shale and other unconventional reservoirs
Biography
Biography: Shahab D Mohaghegh
Abstract
Advanced Data-Driven Analytics provide much needed insight into hydraulic fracturing practices in Shale. Unlike traditional modeling, Advanced Data-Driven Analytics incorporate “Hard Data” rather than “Soft Data”. Using this technology, synthetic geo-mechanical well logs can be generated, impact of reservoir quality can be meaningfully assessed and contribution of completion and hydraulic fracturing practices to production from shale can be modeled and optimized. Advanced Data-Driven Analytics are the result of more than two decades of focused research and development to address upstream E&P related problems with unique and innovative implementation of artificial intelligence, machine learning and data mining. Data-Driven predictive models are trained, calibrated and validated using “Hard Data”. They are used to design frac jobs by optimizing design parameters such as: Distance between laterals and between stages, number of clusters per stage, amount of water (clean and slurry) and proppant to be injected as well as injection rate and pressure. Application of this technology is demonstrated using case studies in multiple Shale assets (Marcellus, Eagle Ford and Niobrara)