Engineering Commons^™

Quantitative Analysis Of Rate Transient Analysis In Unconventional Shale Gas Reserviors, Gabriel Quintero

Graduate Theses, Dissertations, and Problem Reports

Rate Transient Analysis is a quick reservoir modeling solution that has been used throughout the oil and gas industry over its continuous development and has provided breakthroughs for modeling conventional plays for decades. As the Marcellus Shale play continues to be a massive producer of Natural Gas in the world, operators look to find economical yet fairly accurate solutions to develop accurate reservoir models of their wells given the complex nature of unconventional reservoirs. Due to extremely low permeability and heterogeneity along with its complex fracture networks, it becomes an extremely difficult problem to model and predict the fluid flow …

Thermochemical Water-Splitting Using Novel High-Entropy Perovskite Oxides, Hector Alexis De Santiago Hernandez

Graduate Theses, Dissertations, and Problem Reports

In this project, we designed, synthesized, and tested the transformative (La_0.8Sr_0.2)(Mn_[1-x]/3Fe_[1-x]/3Co_xAl_[1-x]/3)O₃ (0 ≤ x ≤ 1.0) high-entropy perovskite oxides (HEPOs) as redox active oxygen carriers for thermochemical hydrogen production with improved stability, kinetics, and H₂ yield. The developed HEPOs form an R3c (hexagonal) phase and were successfully synthesized using both the Pechini and solid-state reactions with the latter synthesis being the primary source for testing. These innovative perovskites demonstrated an improved kinetics with oxygen surface exchange coefficient, k, greater than 7.5 x 10^-4 cm/s, …

Reinforcement Learning For Process Control: Applications To Energy Systems, Elijah Ballard Hedrick

Graduate Theses, Dissertations, and Problem Reports

Reinforcement learning (RL) is a machine learning method that has recently seen significant research activity owing to its successes in the areas of robotics and gameplaying (Silver et al., 2017). However, significant challenges exist in the extension of these control methods to process control problems, where state and input signals are nearly always continuous and more stringent performance guarantees are required. The goal of this work is to explore ways that modern RL algorithms can be adapted to handle process control problems; avenues for this work include using RL with existing controllers such as model predictive control (MPC) and adapting …

Advanced Process Modeling And Optimization Of Amine-Based Carbon Capture Process, Paul Jide Terhemba Akula

Graduate Theses, Dissertations, and Problem Reports

With the rise of carbondioxide (CO2) concentration in the atmosphere to more than 400 parts per million (ppm), research efforts have been focused on achieving net-zero carbon emission technologies. Post-combustion CO2 capture (PCC) is a key strategy in reducing CO2 emissions. Amine-based CO2 capture is the baseline technology for retrofitting existing power stations. However, the integration of amine-based PCC technology with power plants to reduce greenhouse gas emissions incurs a high energy penalty, decreasing a powerplant’s efficiency by about 23 percentage points. Understanding the capture plant dynamics plays an important role in its technical and economic performance. Rigorous models are …

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 …

Combinatorial Approaches For Effective Design, Synthesis, And Optimization Of Enzyme-Based Conjugates, Jordan Scott Chapman

Graduate Theses, Dissertations, and Problem Reports

The specificity and efficiency with which enzymes catalyze selective chemical reactions far exceeds the performance of traditional heterogeneous catalysts that are predominant in industrial applications such as conversion of commodity chemicals to value-added products, fuel cells, and petroleum refinement. Moreover, biocatalysts exhibit exceptionally high product turnover at ambient conditions with little health and environmental burden. These advantageous qualities have led to the prolific use of enzyme catalysis in pharmaceutical, detergents, and food preservation industries wherein their use has greatly reduced waste generation, Unfortunately, the full slate of benefits that enzymes can impart to a broader range of chemical processes is …

Predictions Of Produced Water Quality And Recycled Water Optimization For Spatially-Distributed Wells In Point Pleasant Formation, Armel Quentin Mbakop

Graduate Theses, Dissertations, and Problem Reports

The treatment of produced water as a fracturing fluid is becoming an increasingly important aspect of water management surrounding the booming of the unconventional oil and gas industry. Two main problems facing the oil and gas industry are the availability of water for well drilling and completion and disposal of the produced water. Unconventional well drilling and completion in the Utica shale requires large amounts of water. The wastewater that results after production—containing high levels of organic and inorganic matter— is usually disposed of through deep well injection. A new approach reuses this produced water as part of subsequent fracturing …

Calcite Depression In Bastnaesite-Calcite Flotation System Using Organic Acids, Emmy Muhoza

Graduate Theses, Dissertations, and Problem Reports

Bastnaesite is the primary source of light REEs, namely cerium (Ce), lanthanum (La), praseodymium (Pr), neodymium (Nd), to name a few. Bastnaesite is typically concentrated using the froth flotation beneficiation method. Flotation of bastnaesite suffers from high reagent consumption due to the similar surface characteristics of bastnaesite and associated gangue minerals, including calcite. Additionally, complex stages of high-temperature conditioning are often required to suppress the detrimental impact of dissolved calcium ions on the flotation of bastnaesite. This research seeks to investigate the capabilities of organic acids in the bastnaesite-calcite flotation systems to selectively depress calcite minerals and effectively chelate calcium …

Microwave-Assisted Carbon Nanotube Growth From Methane On Surface Catalyst Exsolving Perovskite Oxide, Angela M. Deibel

Graduate Theses, Dissertations, and Problem Reports

The novel method of using a perovskite exsolution catalyst, strontium titanium nickel oxide (STNO), proved capable of simultaneously producing carbon nanotubes (CNTs) and CO_x-free hydrogen during methane decomposition under microwave irradiation. An optimization of common perovskite materials was conducted for microwave-responsiveness with the results reported in this study. Out of the materials screened, strontium titanium nickel oxide (STNO) was the best candidate to achieve an acceptable methane conversion rate as well as a decent responsiveness to microwave. STNO was further optimized through Ni content, reduction dwell time, and reduction temperature to produce the best methane conversion and CNT …

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 …

Ethane Dehydrogenation For Light Olefins Production Over Stable Catalyst, Xiaoyan Wang

Graduate Theses, Dissertations, and Problem Reports

Accompanied by the development of modern industry, the demand for light olefins (e.g., ethylene, propylene, butene, butadiene) increases year by year. Light olefins are important intermediates in producing polymers (Polyethylene, Polypropylene, etc.) and rubber (Styrene Butadiene Rubber, Polybutadiene rubber, etc.). The primary process for the production of light olefins is steam cracking of petroleum liquids (naphtha and distillate fuel oil). It is an energy-intensive process, requiring high temperature (750-850℃) and pressure (1.0-4.5 MPa). Meanwhile, due to undesired side reactions, this process has lowered the efficiency of light olefins production and suffers from severe coking issues. Furthermore, as petroleum liquids become …

Application Of Artificial Intelligence For Co2 Storage In Saline Aquifer (Smart Proxy For Snap-Shot In Time), Marwan Mohammed Alnuaimi

Graduate Theses, Dissertations, and Problem Reports

In recent years, artificial intelligence (AI) and machine learning (ML) technology have grown in popularity. Smart Proxy Models (SPM) are AI/ML based data-driven models which have proven to be quite crucial in petroleum engineering domain with abundant data, or operations in which large surface/ subsurface volume of data is generated. Climate change mitigation is one application of such technology to simulate and monitor CO2 injection into underground formations.

The goal of the SPM developed in this study is to replicate the results (in terms of pressure and saturation outputs) of the numerical reservoir simulation model (CMG) for CO2 injection into …

Design And Control Of Intensified Membrane Reactor Systems Through Module-Based Design Approach, Brent Bishop

Graduate Theses, Dissertations, and Problem Reports

As interest in the modularization and intensification of chemical processes continues to grow, more research must be directed towards the modeling and analysis of intensified process units. Intensified process units such as membrane reactors pose unique challenges pertaining to design and operation that have not been fully addressed in the reported literature. This work aims to address the design and control challenges caused by the integration of phenomena and the loss of degrees of freedom (DOF) that occur in the intensification of modular membrane reactor units.

First, a novel first-principles approach for modeling membrane reactors is developed using the AVEVA …

A Workflow For Unconventional Reservoirs Optimization Using Supervised Machine Learning In Conjunction With Orthorhombic Elasticity Modeling, Aymen Ab Ali Alhemdi

Graduate Theses, Dissertations, and Problem Reports

Due to the anisotropy and heterogeneous nature of unconventional reservoirs like shale, a comprehensive parametric study to optimize hydraulic fracture treatment for such reservoirs is a tough challenge, especially when natural fractures are present. Most of the current frac simulators do not consider the anisotropy of rock elasticity in the shales. Besides, using the fracture simulation linked with reservoir simulation for the parametric study to understand the impact of multiple different design parameters on fracture propagation and production is time expensive and low efficient. The study proposes a workflow including a new orthorhombic (OB) rock algorithm to interpret geomechanical properties …