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Strategies For Process Systems Mapping And Control Based On Operability Analysis, Victor Manuel Cunha Alves Jan 2024

Strategies For Process Systems Mapping And Control Based On Operability Analysis, Victor Manuel Cunha Alves

Graduate Theses, Dissertations, and Problem Reports

This dissertation aims to develop strategies for process systems engineering (PSE) mapping using models, emerging tools and algorithms motivated by process operability analysis research. Such strategies will be employed to ensure simultaneous design and control of large-scale industrial systems. The emerging tools and techniques in this research include supervised machine learning-based (ML-based) operability mapping, automatic differentiation (AD) for implicit mapping, and the development of a systematic mapping approach for control structure selection using operability analysis. Thus far, the developed operability algorithms either recur to nonlinear programming (NLP) solutions which are computationally expensive or to linearizing the underlying modeling task at …


Modeling, Control, And Fault Detection Of Energy Systems Under Limited High-Confidence Data Scenarios, Selorme K. Agbleze Jan 2024

Modeling, Control, And Fault Detection Of Energy Systems Under Limited High-Confidence Data Scenarios, Selorme K. Agbleze

Graduate Theses, Dissertations, and Problem Reports

Abstract

Modeling, Control, and Fault Detection of Energy Systems under Limited High-Confidence Data Scenarios

Selorme K. Agbleze

Utilizing process measurements for fault detection is an established approach for processes with adequate datasets. For systems with limited high-confidence data representing fault cases and some amount of low-confidence data, few quantitative hybrid techniques exist for performing fault detection. In real systems, it is time-consuming, expensive, and sometimes not productive to generate enough high-confidence data with fault characteristics of a specific process. The problem of limited high-confidence data scenarios may also arise due to process novelty, the need for new operating conditions, or …


Characterization And Evaluation Of Various Biochar Types As Green Adsorbents For Rare Earth Element Recovery From Aqueous Solutions, Oluwaseun Victor Famobuwa Jan 2024

Characterization And Evaluation Of Various Biochar Types As Green Adsorbents For Rare Earth Element Recovery From Aqueous Solutions, Oluwaseun Victor Famobuwa

Graduate Theses, Dissertations, and Problem Reports

Rare earth elements (REEs) are members of the lanthanide family (atomic number 57 – 71). They are significantly important to the global economy due to their applications in renewable energy, defense, and medical industries. REEs are primarily derived from bastnaesite and monazite but may also be present in xenotime, cerite, alanite, and many other types of mineralization in lesser amounts. Due to the increasing demand for REEs and their criticality in the supply chain, the need to explore secondary sources of REEs has gained tremendous importance.

Secondary sources of REEs include but are not limited to acid mine drainage (AMD), …


Microwave-Assisted Ammonia Synthesis Over Cs-Ru/Ceo2 Catalyst, Alazar Kesete Araia Jan 2023

Microwave-Assisted Ammonia Synthesis Over Cs-Ru/Ceo2 Catalyst, Alazar Kesete Araia

Graduate Theses, Dissertations, and Problem Reports

Ammonia synthesis is one of the greatest innovations of the 20th century with extensive applications from fertilizers to intermediates for nitrogen-containing chemicals and pharmaceuticals. Annually, more than 242 million tons of ammonia is produced globally, supporting approximately 27% of the world’s population. One of the fast-growing applications for ammonia is as H2 energy carrier due to its high energy storage capacity, considered to be a decarbonized energy source. The low volumetric energy density and incompressibility makes Hydrogen a non-preferable energy carrier; an alternative carrier becomes a requirement. Ammonia possesses unique property as an energy-dense carrier to store and …


An Artificial Neural Network Approach To Predicting Formation Stress In Multi-Stage Fractured Marcellus Shale Horizontal Wells Based On Drilling Operations Data, Moudhi Alawadh Jan 2023

An Artificial Neural Network Approach To Predicting Formation Stress In Multi-Stage Fractured Marcellus Shale Horizontal Wells Based On Drilling Operations Data, Moudhi Alawadh

Graduate Theses, Dissertations, and Problem Reports

The distribution of the anisotropic minimum horizontal stress, both in horizontal and vertical directions, is necessary for effective hydraulic fracture treatment design in Marcellus Shale horizontal wells. Typically, the minimum horizontal stress can be estimated sonic logs. However, sonic log data is not commonly available for the horizontal Marcellus shale wells due to the complexity and cost. The objective of this research is to predict the anisotropic minimum horizontal stress by utilizing drilling parameters including depth, weight-on-bit (WOB), revolution per minute (RPM), standpipe pressure, torque, pump flow rate, and the rate of penetration (ROP). More specifically, artificial neural network (ANN) …


Modeling And Simulation Of A Process That Converts Ethane To Ethylene And Ethylene To Low Density Polyethylene, Ernest Bosire Mokaya Jan 2023

Modeling And Simulation Of A Process That Converts Ethane To Ethylene And Ethylene To Low Density Polyethylene, Ernest Bosire Mokaya

Graduate Theses, Dissertations, and Problem Reports

Ethylene is a critical feedstock and a major building block in the petrochemical industry that is used in synthesizing important products like polyethylene, ethanol, ethylene oxide, ethylene dichloride and ethylbenzene. With increasing demand of plastics, production of ethylene and subsequently polyethylene has increased globally. This thesis conducts the modeling and simulation of an integrated process that utilizes ethane as the primary feedstock to produce ethylene and the subsequent polymerization of ethylene to low-density polyethylene (LDPE). The process combines two different processes into one integrated process: (1) conversion of ethane to ethylene and (2) conversion of ethylene to LDPE. First, a …


Machine Learning Assisted Framework For Advanced Subsurface Fracture Mapping And Well Interference Quantification, Mohammad Faiq Adenan Jan 2023

Machine Learning Assisted Framework For Advanced Subsurface Fracture Mapping And Well Interference Quantification, Mohammad Faiq Adenan

Graduate Theses, Dissertations, and Problem Reports

The oil and gas industry has historically spent significant amount of capital to acquire large volumes of analog and digital data often left unused due to lack of digital awareness. It has instead relied on individual expertise and numerical modelling for reservoir development, characterization, and simulation, which is extremely time consuming and expensive and inevitably invites significant human bias and error into the equation. One of the major questions that has significant impact in unconventional reservoir development (e.g., completion design, production, and well spacing optimization), CO2 sequestration in geological formations (e.g., well and reservoir integrity), and engineered geothermal systems (e.g., …


Nonlinear Dynamic Analysis And Control Of Chemical Processes Using Dynamic Operability, San Quan Dinh Jan 2023

Nonlinear Dynamic Analysis And Control Of Chemical Processes Using Dynamic Operability, San Quan Dinh

Graduate Theses, Dissertations, and Problem Reports

Nonlinear dynamic analysis serves an increasingly important role in process systems engineering research. Understanding the nonlinear dynamics from the mathematical model of a process helps to find the boundaries of all achievable process conditions and identify the system instabilities. The information on such boundaries is beneficial for optimizing the design and formulating a control structure. However, a systematic approach to analyzing nonlinear dynamics of chemical processes considering such boundaries in a quantifiable and adaptable way is yet to exist in the literature. The primary aim of this work is to formulate theoretical concepts for dynamic operability, as well as develop …


Dynamic Modeling, Data Reconciliation, Parameter Estimation, And Health Monitoring Of A Supercritical Power Plant, Katherine Grace Hedrick Jan 2023

Dynamic Modeling, Data Reconciliation, Parameter Estimation, And Health Monitoring Of A Supercritical Power Plant, Katherine Grace Hedrick

Graduate Theses, Dissertations, and Problem Reports

With the introduction of a larger portion of renewable sources of power coming onto the U.S. power grid in recent decades, the operational strategy of coal-fired power plants has changed significantly to focus more on flexibility in response to the changing energy market. This has naturally led to different operational challenges. Many of these challenges are focused on the boilers within these plants, as they are producing more emissions and experiencing increased damage during load-following, which in turn leads to increased costs from penalties for not achieving emission standards or maintenance costs as boilers accumulate damage from the cycling behavior. …


Modular Supply Network Optimization Of Renewable Ammonia And Methanol Co-Production, Benjamin Akoh Jan 2023

Modular Supply Network Optimization Of Renewable Ammonia And Methanol Co-Production, Benjamin Akoh

Graduate Theses, Dissertations, and Problem Reports

To reduce the use of fossil fuels and other carbonaceous fuels, renewable energy sources such as solar, wind, geothermal energy have been suggested to be promising alternative energy that guarantee sustainable and clean environment. However, the availability of renewable energy has been limited due to its dependence on weather and geographical location. This challenge is intended to be solved by the utilization of the renewable energy in the production of chemical energy carriers. Hydrogen has been proposed as a potential renewable energy carrier, however, its chemical instability and high liquefaction energy makes researchers seek for other alternative energy carriers. Ammonia …


Ambient Ammonia Synthesis Via Microwave-Catalytic Materials And Plasma Chemistry, Siobhan Brown Jan 2023

Ambient Ammonia Synthesis Via Microwave-Catalytic Materials And Plasma Chemistry, Siobhan Brown

Graduate Theses, Dissertations, and Problem Reports

Ammonia is critical to supporting human life on earth because of its use as fertilizer. The Haber-Bosch process to produce ammonia has been practiced for over 100 years. This process operates at high pressure and temperature to overcome the thermodynamic and kinetic limitations of the ammonia synthesis reaction thus researchers have tried to overcome it for decades. At present this process represents 1% of global energy usage and 2.5% of global CO2 emissions. The proposed chemical looping ammonia synthesis approach seeks to reduce the environmental impact of this critical process and to elucidate microwave-catalytic principles.

This research aims to …


The Effect Of Different Fracturing Fluids On The Productivity Of Multi-Staged Fractured Marcellus Shale Horizontal Wells, Vida Gyaubea Matey-Korley Jan 2023

The Effect Of Different Fracturing Fluids On The Productivity Of Multi-Staged Fractured Marcellus Shale Horizontal Wells, Vida Gyaubea Matey-Korley

Graduate Theses, Dissertations, and Problem Reports

While hydraulic fracturing has undeniably improved the production from oil and gas reservoirs, this technology is not without limitations. The primary hurdles lie in the areas of proppant transport, fluid rheology, and stress management. Despite the extensive research conducted in this domain, there remains a considerable amount of work to be done for comprehensive solutions that account for the complex interactions among fracturing fluid, proppant distribution, and geomechanical conditions. Achieving this will then make room for a holistic and efficient hydraulic fracturing strategy.

This study addresses the above-mentioned problem by examining the impact of fluid type on proppant transport and …


Synthesis Of Quasi-Freestanding Graphene Films Using Radical Species Formed In Cold Plasmas, Michael A. Mathews Jr. Jan 2023

Synthesis Of Quasi-Freestanding Graphene Films Using Radical Species Formed In Cold Plasmas, Michael A. Mathews Jr.

Graduate Theses, Dissertations, and Problem Reports

For over a decade, the Stinespring laboratory has investigated scalable, plasma assisted synthesis (PAS) methods for the growth of graphene films on silicon carbide (SiC). These typically utilized CF4-based inductively coupled plasma (ICP) with reactive ion etching (RIE) to selectively etch silicon from the SiC lattice. This yielded a halogenated carbon-rich surface layer which was then annealed to produce the graphene layers. The thickness of the films was controlled by the plasma parameters, and overall, the process was readily scalable to the diameter of the SiC wafer.

The PAS process reproducibly yielded two- to three-layer thick graphene films …


Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani Jan 2023

Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani

Graduate Theses, Dissertations, and Problem Reports

The increasing significance of renewable energy sources is thrusting the load cycling of fossil-fueled power plants (FFPP), designed to operate under nominal-load conditions. Integration of energy storage systems (ESS) with the FFPPs such as hydrogen energy storage (HES) and mechanical energy storage facility such as compressed air energy storage (CAES) shows the potential to minimize the levelized cost of electricity during high demand scenarios and also minimize the negative impacts of off-design FFPP operation. The deployment of energy storage facilities at the FFPP level have considerable potential advantages as they can be exploited within the existing equipment items and facilities …


State Estimation, Covariance Estimation, And Economic Optimization Of Semi-Batch Bioprocesses, Ronald Hunter Alexander Jan 2023

State Estimation, Covariance Estimation, And Economic Optimization Of Semi-Batch Bioprocesses, Ronald Hunter Alexander

Graduate Theses, Dissertations, and Problem Reports

One of the most critical aspects of any chemical process engineer is the ability to gather, analyze, and trust incoming process data as it is often required in control and process monitoring applications. In real processes, online data can be unreliable due to factors such as poor tuning, calibration drift, or mechanical drift. Outside of these sources of noise, it may not be economically viable to directly measure all process states of interest (e.g., component concentrations). While process models can help validate incoming process data, models are often subject to plant-model mismatches, unmodeled disturbances, or lack enough detail to track …


Leveraging Artificial Intelligence And Geomechanical Data For Accurate Shear Stress Prediction In Co2 Sequestration Within Saline Aquifers (Smart Proxy Modeling), Munirah Alawadh Jan 2023

Leveraging Artificial Intelligence And Geomechanical Data For Accurate Shear Stress Prediction In Co2 Sequestration Within Saline Aquifers (Smart Proxy Modeling), Munirah Alawadh

Graduate Theses, Dissertations, and Problem Reports

This research builds upon the success of a previous project that used a Smart Proxy Model (SPM) to predict pressure and saturation in Carbon Capture and Storage (CCS) operations into saline aquifers. The Smart Proxy Model is a data-driven machine learning model that can replicate the output of a sophisticated numerical simulation model for each time step in a short amount of time, using Artificial Intelligence (AI) and large volumes of subsurface data. This study aims to develop the Smart Proxy Model further by incorporating geomechanical datadriven techniques to predict shear stress by using a neural network, specifically through supervised …


Evaluating Electrification Of Fossil Fuel-Fired Boilers For Decarbonization Using Discrete Event Simulation, Nahian Ismail Chowdhury Jan 2023

Evaluating Electrification Of Fossil Fuel-Fired Boilers For Decarbonization Using Discrete Event Simulation, Nahian Ismail Chowdhury

Graduate Theses, Dissertations, and Problem Reports

Decarbonizing fossil fuel usage is crucial in mitigating the impacts of climate change. CO2, which comprises the major portion of greenhouse gas, is emitted from burning fossil fuels. One of the significant sources of fossil fuel user is industrial process heating, and most of the heating in industrial processes is achieved through boilers. Electrification is a promising solution for decarbonizing these boilers, as it enables renewable energy sources to generate electricity, which can then be used to power the electric boilers. The electrification of boilers can reduce greenhouse gas emissions, improve air quality, and increase energy efficiency. However, it requires …


Combustion Characteristics Of Methane, Ethane, Propane, And Butane Blends Under Conditions Relevant Of A Dual-Fuel Diesel And Natural Gas Engine, Christopher Joseph Ulishney Jan 2023

Combustion Characteristics Of Methane, Ethane, Propane, And Butane Blends Under Conditions Relevant Of A Dual-Fuel Diesel And Natural Gas Engine, Christopher Joseph Ulishney

Graduate Theses, Dissertations, and Problem Reports

As natural gas production infrastructure is already in place in most of the world and will continue expanding for the foreseeable future, natural gas is an alternative to traditional liquid petroleum fuels in heavy-duty engines. Dedicated natural gas or dual-fuel diesel-natural gas heavy-duty engines are alternatives to diesel-only power generation equipment. One challenge is the large variation in the natural gas composition available for such applications, which is known to significantly affect engine’s combustion characteristics and the emissions composition. As the literature on dual-fuel combustion under low load engine operating conditions that use more realistic natural gas mixtures (i.e., mixtures …


Comparative Analysis Of Artificial Intelligence And Numerical Reservoir Simulation In Marcellus Shale Wells, Arya Maher Sattari Jan 2023

Comparative Analysis Of Artificial Intelligence And Numerical Reservoir Simulation In Marcellus Shale Wells, Arya Maher Sattari

Graduate Theses, Dissertations, and Problem Reports

This dissertation addresses the limitations of conventional numerical reservoir simulation techniques in the context of unconventional shale plays and proposes the use of data-driven artificial intelligence (AI) models as a promising alternative. Traditional methods, while providing valuable insights, often rely on simplifying assumptions and are constrained by time, resources, and data quality. The research leverages AI models to handle the complexities of shale behavior more effectively, facilitating accurate predictions and optimizations with less resource expenditure.

Two specific methodologies are investigated for this purpose: traditional numerical reservoir simulations using Computer Modelling Group's GEM reservoir simulation software, and an AI-based Shale Analytics …


Optimal Design And Operation Of Integrated Hydrogen Generation And Utilization Plants, Ijiwole Solomon Ijiyinka Jan 2023

Optimal Design And Operation Of Integrated Hydrogen Generation And Utilization Plants, Ijiwole Solomon Ijiyinka

Graduate Theses, Dissertations, and Problem Reports

There are considerable efforts worldwide for reducing the use of fossil fuel for energy production. While renewable energy sources are being increasingly used, fossil fuel still contribute about 80% of the energy used worldwide. As a result, the level of CO2 is still increasing fast in the atmosphere currently exceeding about 410 parts per million (ppm). For reducing CO2 build up in the atmosphere, various approaches are being investigated. For the electric power generation sector, two key approaches are post-combustion CO2 capture and use of hydrogen as a fuel for power generation. These two solutions can also …


Quantitative Analysis Of Rate Transient Analysis In Unconventional Shale Gas Reserviors, Gabriel Quintero Jan 2022

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 …


Machine Learning Based Real-Time Quantification Of Production From Individual Clusters In Shale Wells, Ayodeji Luke Aboaba Jan 2022

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 …


Application Of Artificial Intelligence For Co2 Storage In Saline Aquifer (Smart Proxy For Snap-Shot In Time), Marwan Mohammed Alnuaimi Jan 2022

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 …


Combinatorial Approaches For Effective Design, Synthesis, And Optimization Of Enzyme-Based Conjugates, Jordan Scott Chapman Jan 2022

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 Jan 2022

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 Jan 2022

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 …


A Workflow For Unconventional Reservoirs Optimization Using Supervised Machine Learning In Conjunction With Orthorhombic Elasticity Modeling, Aymen Ab Ali Alhemdi Jan 2022

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 …


Microwave-Assisted Carbon Nanotube Growth From Methane On Surface Catalyst Exsolving Perovskite Oxide, Angela M. Deibel Jan 2022

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 COx-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 …


Advanced Process Modeling And Optimization Of Amine-Based Carbon Capture Process, Paul Jide Terhemba Akula Jan 2022

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 …


Hydrocarbon Pay Zone Prediction Using Ai Neural Network Modeling., Darren D. Guedon Jan 2022

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 …