Engineering Commons^™

Machine Learning Based Real-Time Quantification Of Production From Individual Clusters In Shale Wells, Ayodeji Luke Aboaba

Graduate Theses, Dissertations, and Problem Reports

Over the last two decades, there has been advances in downhole monitoring in oil and gas wells with the use of Fiber-Optic sensing technology such as the Distributed Temperature Sensing (DTS). Unlike a conventional production log that provides only snapshots of the well performance, DTS provides continuous temperature measurements along the entire wellbore.

Whether by fluid extraction or injection, oil and gas production changes reservoir conditions, and continuous monitoring of downhole conditions is highly desirable. This research study presents a tool for real-time quantification of production from individual perforation clusters in a multi-stage shale well using Artificial Intelligence and Machine …

Hydrocarbon Pay Zone Prediction Using Ai Neural Network Modeling., Darren D. Guedon

Graduate Theses, Dissertations, and Problem Reports

This paper captures the ability of AI neural network technology to analyze petrophysical datasets for pattern recognition and accurate prediction of the pay zone of a vertical well from the Santa Fe field in Kansas.

During this project, data from 10 completed wells in the Santa Fe field were gathered, resulting in a dataset with 25,580 records, ten predictors (logs data), and a single binary output (Yes or No) to identify the availability of Hydrocarbon over a half feet depth segment in the well. Several models composed of different predictors combinations were also tested to determine how impactful some logs …

Modeling Nonlinear Dynamic Systems Using Bss-Anova Gaussian Process, Kyle Matthew Hayes

Graduate Theses, Dissertations, and Problem Reports

Nonlinear dynamic systems are some of the most common variety of systems encountered in the sciences, but are the potentially more onerous to model through system identification than static systems due to their added complexity, sensitivity to initial conditions, and the potential application of new dynamic and nonlinear behavior through any time dependent forcing functions. The BSS-ANOVA Gaussian Process is a Machine Learning method for dynamic system ID that possesses several attributes that make it a natural candidate for this variety of problem. BSS-ANOVA is fully Bayesian, works best for continuous tabular datasets, and fast training and inference times and …

Efficacy Of Reported Issue Times As A Means For Effort Estimation, Paul Phillip Maclean

Graduate Theses, Dissertations, and Problem Reports

Software effort is a measure of manpower dedicated to developing and maintaining and software. Effort estimation can help project managers monitor their software, teams, and timelines. Conversely, improper effort estimation can result in budget overruns, delays, lost contracts, and accumulated Technical Debt (TD). Issue Tracking Systems (ITS) have become mainstream project management tools, with over 65,000 companies using Jira alone. ITS are an untapped resource for issue resolution effort research. Related work investigates issue effort for specific issue types, usually Bugs or similar. They model their developer-documented issue resolution times using features from the issues themselves. This thesis explores a …

Combustion Feature Characterization Using Computer Vision Diagnostics Within Rotating Detonation Combustors, Kristyn B. Johnson May

Graduate Theses, Dissertations, and Problem Reports

In recent years, the possibilities of higher thermodynamic efficiency and power output have led to increasing interest in the field of pressure gain combustion (PGC). Currently, a majority of PGC research is concerned with rotating detonation engines (RDEs), devices which may theoretically achieve pressure gain across the combustor. Within the RDE, detonation waves propagate continuously around a cylindrical annulus, consuming fresh fuel mixtures supplied from the base of the RDE annulus. Through constant-volume heat addition, pressure gain combustion devices theoretically achieve lower entropy generation compared to Brayton cycle combustors. RDEs are being studied for future implementation in gas turbines, where …