Other Engineering Commons^™

Using Ai And Machine Learning To Indicate Shale Anisotropy And Assist In Completions Design, Cole E. Palmer

Graduate Theses, Dissertations, and Problem Reports

Operating companies in the unconventional Marcellus shale play have all faced a similar and problematic issue, while attempting to produce natural gas over the last decade. Companies have quickly realized that not every perforation along their horizontal wells are producing gas. In fact, producing perforations are only ranging from 15%-70% of the total perforations along the horizontal wellbore [1]. This unexplained issue results in millions of dollars in lost revenue per well, in addition to the sunk cost of paying for completions that are not actually yielding any produced gas.

What is causing these perforations to have no produced gas? …

Smart Proxy Modeling Of Sacroc Co2-Eor, Gholami Vida, Mohaghegh D. Shahab, Maysami Mohammad

Faculty & Staff Scholarship

Large CO2-enhanced oil recovery (EOR) projects usually contain an abundance of geological and good performance data. While this volume of data leads to robust models, it often results in difficult to manage, slow-running numerical flow models. To dramatically reduce the numerical run-times associated with the traditional simulation techniques, this work investigated the feasibility of using artificial intelligence and machine learning technologies to develop a smart proxy model of the Scurry Area Canyon Reef Operators Committee (SACROC) oilfield, located in the Permian Basin, TX, USA. Smart proxy models can be used to facilitate injection-production optimization for CO2-EOR projects. The use of …