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Articles 1 - 3 of 3
Full-Text Articles in Geological Engineering
Dental Cement Thickening Agents For Mudslide Prevention, Kristina Emiliya Babayev, Emily Elizabeth Johnson, Diana Evet Reihaneh
Dental Cement Thickening Agents For Mudslide Prevention, Kristina Emiliya Babayev, Emily Elizabeth Johnson, Diana Evet Reihaneh
Materials Engineering
The purpose of this project is to develop a non-toxic mud thickening agent for the application of decreasing mudslide intensity where performance is measured by flow rate, viscosity, and toxicity tests. We hypothesized that dental cements could be a potential candidate due to their adhesive, hydrophilic, and biocompatible properties. Zinc phosphate, glass ionomer, and polycarboxylate cement were among the dental cements tested. These tests were performed at low and high concentrations of 25 grams and 125 grams, respectively, mixed into soil to produce 3500 gram samples. The dental cements produced noticeable thickening effects in the mud, as the average viscosity …
Development Of A Marine Biodegradable Target Balloon, Blake Samuel Robinson, Arash Sam Akhavi, David Leonardo Albarran-Martinez
Development Of A Marine Biodegradable Target Balloon, Blake Samuel Robinson, Arash Sam Akhavi, David Leonardo Albarran-Martinez
Materials Engineering
The US Navy utilizes PVC target balloons, known as Killer Tomatoes, that are inflated onboard a naval vessel then deployed into the ocean to calibrate a variety of weaponry. The Navy has requested the investigation of biodegradable polymers to replace the PVC in attempts to reduce ocean waste that is generated from the leftover PVC material. After communicating with American Pacific Plastic Fabricators (APPF), the current manufacturer of the Killer Tomatoes, we gained an understanding of the manufacturing process and the material requirements that would allow a new material to be integrated into their current process. Two proprietary, trial polymers …
Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen
Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen
Master's Theses
Current methods of production forecasting such as decline curve analysis (DCA) or numerical simulation require years of historical production data, and their accuracy is limited by the choice of model parameters. Unconventional resources have proven challenging to apply traditional methods of production forecasting because they lack long production histories and have extremely variable model parameters. This research proposes a data-driven alternative to reservoir simulation and production forecasting techniques. We create a proxy-well model for predicting cumulative oil production by selecting statistically significant well completion parameters and reservoir information as independent predictor variables in regression-based models. Then, principal component analysis (PCA) …