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Petroleum Engineering Theses and Dissertations

Theses/dissertations from 2023 2023.

Investigation of Cyclic Gaseous Solvent Injection for Enhanced Oil Recovery in Unconventional Formations , Samuel Asante Afari

A Data Driven Approach To Optimize Re-Fracturing Operations In The Williston Basin , Joshua Kroschel

“Blue” Hydrogen & Helium From Flare Gas Of The Bakken Formation Of The Williston Basin, North Dakota: A Novel Process , Martin R. Leipzig

Theses/Dissertations from 2022 2022

The Impact Of Stress Dependent Permeability Alteration On Gas Based EOR In The Bakken Formation , Ailin Assady

Evaluation Of CO2 Enhanced Oil Recovery In Unconventional Reservoirs , Nidhal Badrouchi

Fracture Initiation And Propagation In Shale Formations With Anisotropic Toughness , Nourelhouda Benouadah

The Effect Of Mineral Composition On Elastic Properties Of The Bakken Formation In The Williston Basin, North Dakota , John Albert Harju

Rock Physics Based Velocity-Porosity Correlations Developed For Estimation Of The Elastic Properties Of The Bakken Formations Of The Williston Basin, North Dakota , Lynn D. Helms

Multiple Surface Pipeline Leak Detection Using Real-Time Sensor Data Analysis , Francis Enejo Idachaba

High Resolution Compositional Characterization Of Degraded Crude Oils Using Petroleomics , Miguel Fernando Jimenez Jacome

Investigation Of Transient Multiphase Flow Performance In Undulating Horizontal Unconventional Wells , Youcef Khetib

Impact Of CO2 Storage On The Geomechanical And Geophysical Properties Of Bakken Formation , Ogochukwu Ozotta

Characterization Of Vertical Growth Of Fractures In Layered Formations , Vibhas Jagdish Pandey

Data Driven Approach To Saltwater Disposal (SWD) Well Location Optimization In North Dakota , Kalyanaraman Venugopal

Modeling And Simulations Of Stress Shadow Effect On Multistage Hydraulic Fractures , Agustinus Zandy

Theses/Dissertations from 2021 2021

Numerical Simulations Of Hydraulic Fracturing Through Perforated Wellbores , Omar Akash

Development Of Image Processing Techniques For Core-Scale Characterization And Synthetic 3D-Printed Core Replicas , Ahmed Galal Alqassaby Almetwally

Hole Cleaning And Cuttings Transportation Modelling And Optimization , Foued Badrouchi

Integrative Approach For Improved Oil Recovery In Unconventional Reservoirs , Abdulaziz Ellafi

Investigation Of Factors That Affect Site Selection For Geothermal Energy Extraction In North Dakota , Ogonna Obinwa

Hydraulic Fracture Propagation And Its Geometry Evolvement In Transversely Isotropic Formations , Dezhi Qiu

Theses/Dissertations from 2020 2020

Carbon-Dioxide Pipeline Infrastructure Route Optimization And Network Modeling For Carbon Capture Storage And Utilization , Karthik Balaji

Simulation Of Notch Driven Hydraulic Fracture In Open Hole Completion , Nejma Djabelkhir

Application And Development Of Advanced Atomic-Scale Analysis And Simulations For Complex Systems , Hyeonseok Lee

Molecular Simulation Study Of Enhanced Oil Recovery Methods In Tight Formation , Chuncheng Li

Evaluation Of Gas Hydrate In Gas Pipeline Transportation , Paschal Ogadi Mokwenye

Treatment Of Bakken Produced Water Using Supercritical Water Desalination , Joshua Oloruntimilehin Oluwayomi

Coupled Simulation Of Hydraulic Fracturing, Production, And Refracturing For Unconventional Reservoirs , Xincheng Wan

Enhanced Hydrocarbon Recovery In Tight And Shale Reservoirs Using Surfactants And Supercritical CO2 , Shaojie Zhang

Surfactant-Nanoparticle Augmented Systems For Enhanced Oil Recovery: Formula Development And Evaluation , Xun Zhong

Theses/Dissertations from 2019 2019

Multi-Scale Organic Material Characterization Of The Bakken Source Rock , Arash Abarghani

Impact Of Stress On The Characterization Of The Flow Units In The Complex Three Forks Reservoir, Williston Basin , Aldjia Boualam

Fracture Detection And Prediction In Unconventional Reservoirs For Finding Sweet Spot , Sofiane Djezzar

Fine Scale Characterization Of Organic Matter Using Analytical Methods: Raman And NMR Spectroscopies , Seyedalireza Khatibi

Innovation Of Petrophysical And Geomechanical Experiment Methodologies: The Application Of 3D Printing Technology , Lingyun Kong

NMR Characterization And Chemical Enhanced Oil Recovery Using Surfactants In Unconventional Reservoirs , Mohamed Mohamed Awad Mohamed

Reservoir Characterization And Simulation Of Enhanced Oil Recovery For Bakken , Runxuan Sun

Evaluation Of CO2 Flooding In Tight Formation , Sai Wang

Theses/Dissertations from 2018 2018

Molecular Dynamics Simulation Of Gas Transport And Adsorption In Ultra-Tight Formations , Yannick Tambe Agbor

Investigating The Impact Of Offset Fracture Hits Using Rate Transient Analysis In The Bakken And Three Forks Formation, Divide County, North Dakota , Cody Lee Brown

The Application Of Nanoindentation Technology With Simulation On The Micromechanical Properties Of Bakken Formation , Hao Fu

Microstructures And Nanomechanical Properties Of The Bakken Shale , Kouqi Liu

A 3D Geomechanical Model Of Blue Buttes Field In Williston Basin, North Dakota , Rehan Ali Mohammed

Digital Rock Reconstruction And Property Calculation Of Fractured Shale Rock Samples , Hongsheng Wang

A Study Of Two-Phase Flow Regime And Pressure Drop In Vertical Pipe , Yanbo Wang

Analysis Of Pressure Distribution Along Pipeline Blockage Based On The Cfd Simulation , Lu Yang

Digital Rock Analysis On Berea Sandstone And An Eor Study On Middle Bakken , Barco N. Yolo

Theses/Dissertations from 2017 2017

A Comprehensive Reservoir Characterization Of The Bakken Formation: Blue Buttes Field, Williston Basin , Alan Alexeyev

Study Of Pore-Dependent Petroleum Fluid Properties In Tight Shale Plays: Bakken Formation , Agustinus Zandy

Theses/Dissertations from 2015 2015

Study About Petrophysical And Geomechanical Properties Of Bakken Formation , Jun He

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Ph.d. dissertations, master theses.

Theses and Dissertations — 2019

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Past Theses and Dissertations

UT PGE graduate students produce influential reports, theses and dissertations that help solve the oil and gas industry’s recovery and environmental challenges. This section features the most recent papers, as well as those in our database going back to 2004.

Newly Released Research

Dissertations, master’s theses, master’s reports.

Eghbali, Ali. Combining Spectroscopy Elemental Well Logs, Inverted Nuclear Logs, and High-Resolution Borehole Images for Improved Mineral and Petrophysical Interpretations . Takahashi, Toma. Development of an Algorithm for Wellbore Stability Calculation with Arbitrary Deviations . Xiao, Yuchen. Application of Spatial Causal Inference in Induced Seismicity Studies .

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Waterflooding Optimization for Improved Reservoir Management

Reservoir management uses the geological and petroleum engineering knowledge to predict and maximize the future production of the oil and gas reservoirs. Finding an optimal production strategy has always been a key task in reservoir management. The main aim is to determine the most cost-effective strategy to develop a new field or to optimize the production from an existing field using improved oil recovery methods. Through the use of a suite of technologies, including remote sensors and reservoir simulation, reservoir management can improve the well placement as well as well controls (production/injection rates) and increase the total amount of hydrocarbons that is ultimately recovered from a field. Most optimized strategies are model-based and are effective if the model predicts the future reservoir behavior correctly. The updated reservoir models are used to determine the best field development and production plan in the future. Traditionally, this task was done manually by a large number of trials and errors. During the last few years, a number of optimization strategies were developed to assist this decision making process, e.g. well placement optimization or rate optimization in a given well configuration. The optimization problem requires the maximization of net present value, or recovery factor, by manipulation of some parameters in the reservoir system, e.g. well location, liquid production/injection rates or valve settings in an on/off mode. These parameters are usually subject to some limitations (also known as constraints) due to operational conditions, surface process facilities etc. These constraints pose substantial complication while solving the optimization problem. Although production optimization can be applied to any kind of recovery method in the reservoir, most of the works focus on optimizing the reservoir performance under waterflooding. The most important reason is that waterflooding is the most widely applied improve recovery method among the secondary and tertiary recovery methods in the oil reservoirs. The injected water may reach from the injectors to the producers without touching a large region of the reservoir, thus resulting to a low recovery factor. Intelligent or smart wells are equipped with downhole valves to control the fluid flow from the reservoir to the well and sensors to monitor the downhole pressure and saturation changes. This technology has the capability to significantly improve the recovery from the reservoir. Determination of the optimal rates, or valve settings, is the main challenge in the intelligent fields. The main focus of this thesis was finding an efficient workflow to determine the optimal production/injection strategy for a reservoir waterflooding project in a given well configuration. A comparative closed loop reservoir management exercise was performed in connection with the SPE Applied Technology Workshop in Brugge June 2008. The model used in this exercise was a synthetic reservoir with typical geological features of North Sea fields and considerably larger than those used in most previous studies. The Brugge model was used to explore a cost-effective workflow for waterflooding of an intelligent oil field. The effect of a proper formulation on the waterflooding optimization problem was investigated and two different formulations were presented. In the first formulation, the production/injection rates of producer/injector completions were selected as the optimization variables to maximize NPV value of the Brugge field. In the original Brugge optimization problem, the parameters were asked to be updated on monthly basis (20,160 variables). In this thesis, these variables were optimized monthly and every 6 months (3,360 variables), depending on the memory requirements of the chosen optimization algorithms. For the steepest descent and conjugate gradient methods, the variables were updated on monthly basis. For the interior point and active set methods the variables were optimized every 6 months. The optimization constraints were maximum production/injection rates and minimum/maximum production/injection bottomhole pressures in each well. The adjoint approach in combination with a multiscale estimation technique was proposed to solve the rate formulation. The main advantages of the multiscale optimization were acceleration of the optimization process and increasing the chance of finding a better optimal solution. Gradient based algorithms were used to utilize the adjoint gradients for finding an optimal solution. Different gradient based optimization methods, interior point and active set algorithms were evaluated for the adjoint optimization solution. Among the gradient based optimization algorithms, the active-set method outperformed all other methods used in this thesis. The multiscale optimization approach improved the computational efficiency of the optimization algorithms for initial optimization iterations. Combination of the multiscale optimization with interior-point algorithm accelerated the optimization process and improved the quality of the obtained optimal point by this method. In the second formulation, the shut-in water-cuts were proposed as the optimization variables to maximize NPV. The optimal injection strategy was chosen to be the unity voidage replacement ratio, to maintain the reservoir pressure. The decision was to close the completions producing too much water by optimizing the maximum water-cut level. This formulation efficiently reduced the number of variables to 54 parameters, which was the number of initially open completions in the production wells, and avoided optimizing on the high dimensional rate optimization problem. The optimization constraints were changed to simple upper and lower bounds on water-cuts and the production/injection rate & pressure constraints were handled by the reservoir simulator. A guide rate approach was presented to distribute the production rates between the producers to penalize the production from the completions with higher water-cut values. Due to the existence of the noise in the finite difference gradients, several derivative free optimization algorithms were used to optimize the shut-in water-cuts: pattern search Hooke-Jeeves, reflection simplex Nelder-Mead, a generalized pattern search method and a line search derivative free method. Here, the line search derivative free method was developed based on an existing line search derivative free algorithm in combination with Hooke-Jeeves method. The fractional ranking method was utilized to rank the performance of these algorithms based on the convergence rate of the methods and the quality of the objective function in the optimal point. Among these methods, the developed line search derivative free was the most efficient and the highest NPV value was achieved by both Hooke-Jeeves and line search derivative free methods. Overall, the line search derivative free method performed better than the other derivative free methods used in here. Comparing two above mentioned formulations, high optimal NPV values were achieved, on the history matched model used in this thesis: 4.52 B$ & 4.54 B$ for the adjoint and guide rate approaches respectively. Based on the reactive case in Peters et al. (2010), the obtained NPV on the same history matched model was 3.94 B$. The NPV were improved approximately 15%, assuming the reactive control as the base case. Also, the average reservoir pressure was compared for the optimal solutions from these two approaches. In the guide rate approach, the main aim was reservoir pressure maintenance all through the life of the reservoir to maintain the performance of the waterflooding project. The adjoint solution suggested repressurization of the reservoir in the beginning and cutting the field injection rate in the end of the optimization horizon, which is not advisable in practice. In terms of availability of computing resources, the memory requirement for the guide rate approach is trivial and for the adjoint optimization it is dependent on the size of the optimization problem (number of variables) and the choice of the mathematical algorithm. It is simple and easy to implement the guide rate approach for every single reservoir simulator, while the implementation of the adjoint approach is a major programming effort and requires a proper knowledge of the reservoir simulator.

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Waterflood injection on the Shell Bonga field offshore Nigeria is accomplished via a network of subsea flowlines and 15 subsea injection wells. Maximizing water injection volume is an important economic objective for Bonga. Water injection is used for maintaining the reservoir pressure and thereby maximize oil production. The water injection flowrate to each well is limited by the fracture pressure of the overlying shale layer. Fracture of overlying shale could significantly reduce oil recovery from the damaged reservoir. Hence, it is important to accurately control the reservoir injection pressure such that volume of injected water is maximized without excessive risk of damaging the overlying shales. Since there are no downhole pressure gauges in the injection wells, the downhole injection pressure must be estimated from other measured variables. For this, we developed a novel technology, WRIPS (Waterflood Reservoir Injection Pressure System). The WRIPS algorithm is used to: ■Estim...

2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA)

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Mpge link tree, reservoir engineering & reservoir simulation.

Learn about faculty at the Mewbourne School of Petroleum and Geological Engineering researching in the area of Reservoir Engineering & Reservoir Simulation

Mashhad Fahes

Associate Professor

E-mail:     [email protected] Office:    SEC 1338

Research Interests:

View Bio | Download CV (PDF)

Rouzbeh Ghanbar Moghanloo

Director of Natural Gas Engineering & Management Prgm ONEOK Chair in Natural Gas Engineering and Management

E-mail:     [email protected]

Office:    SEC 1176

Research interests: Enhanced Oil Recovery, Production, Flow Assurance & Emission Reduction,  Unconventional Resources

Deepak Devegowda

Professor & Mewbourne Chair in Petroleum Engineering #1

E-mail:     [email protected] Office:    SEC 1322

Research interests: Reservoir characterization & uncertainty assessment, Geostatistics, Unconventional oil & gas reservoir engineering

E-mail:     [email protected] Office:    SEC 1362

Research interests: Physics of multiphase flow in permeable media, Enhanced hydrocarbon recovery, Reservoir characterization, Geothermal recovery

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Master’s Thesis Reservoir Management

A thesis is an integral part of a master study program. it is the documentation of a student’s “mastery” by practical or theoretical research results in the field of his/her elective course..

DGE defines “mastery” as the ability to successfully apply the concepts, methods, and skills taught in the different modules of its International Study Program in Petroleum Engineering, in order to solve a well-posed problem of relevance to industry and/or academia.

The following information applies to students who started the MSc program at Montanuniversität Leoben. For detailed information regarding thesis procedure, thesis defense and further requirement at Mines consult the Colorado School of Mines website.

Master’s Thesis Advanced Well Construction and Operation Technology

The following information applies to students who started the MSc program at Montanuniversität Leoben. For detailed information regarding thesis procedure, thesis defense and further requirement at Gubkin consult the Gubkin University website.

Master’s Thesis Global Energy Transportation and Storage

DPE defines “mastery” as the ability to successfully apply the concepts, methods, and skills taught in the different modules of its International Study Program in Petroleum Engineering, in order to solve a well-posed problem of relevance to industry and/or academia.

The following information applies to students who started the MSc program at Montanuniversität Leoben. For detailed information regarding thesis procedure, thesis defense and further requirement at Ufa consult the Ufa University website.

Procedure at Montanuniversität Leoben Reservoir Management

• According to your topic, get in touch with the contact person from the Chair of Drilling & Completion Engineering.
• A supervisor from the scientific staff, involved in the respective field of study, will be assigned to you. He or she will advise and guide you on your selected topic.
• Write the thesis proposal and submit it for approval.
• The standard time frame for the Master’s Thesis is at least five months. Usually, a 60-80 pages long thesis - without appendices and supplemental material- is expected.
• You will defend your MSc thesis at both universities. 
• Montanuniversität Leoben: There are four dates available per year (usually during October, December, March, and June) to defend the MSc thesis. You can consult the specific dates on Joint MSc PE Calendar or ask Ms. Patrizia Gäbler.
• Colorado School of Mines: Consult available dates on the Colorado School of Mines website.

Defense and Examination at Montanuniversität Leoben

The thesis defense will take place at least one week before the Master’s Examination date.

• The presentation of the thesis will take 20 minutes, and 10-20 minutes will be for questions from the scientific staff. You can introduce yourself for 2-3 minutes. In the end, you will receive the final grade for your MSc thesis.

The Master’s examination will be structured as follows:

• Short presentation (5 minutes max.) of your MSc thesis.
• Oral examination in two of the following areas:
• Data Acquisition & Analysis
• Solid & Fluid Mechanics
• Economics & Management
• Drilling & Completion

Requirements at Montanuniversität Leoben

To be able to select a date for the MSc thesis defense and Master’s Examination at Montanuniversität Leoben, you must fulfill the following requirements:

• Have all courses (lectures, labs, etc.) from the MSc program completed.
• The thesis must be finished at least one month before the exam date.
• Have the thesis registered on MUOnline at the Theses menu point. The abstract must be uploaded in English and German. Keywords, supervisors, co-supervisors must be appropriately listed.
• The abstract is required in both English and German because submission and acceptance on MUOnline can only be done if the abstract in German has been uploaded.
• Once your MSc thesis has been approved, it is required to be printed and bounded. You will be informed how many copies are needed.

Contact person

Ass.Prof. Dipl.-Ing. Dr.mont. Michael Prohaska-Marchried Drilling and Completion Engineering

Procedure at Montanuniversität Leoben Advanced Well Construction and Operation Technology

• Gubkin University: Consult available dates on Gubkin University website.

Procedure at Montanuniversität Leoben Global Energy Transportation and Storage

• Ufa University: Consult available dates on Ufa University website.

AUTOMATED ADAPTIVE HYPERPARAMETER TUNING FOR ENGINEERING DESIGN OPTIMIZATION WITH NEURAL NETWORK MODELS

Neural networks (NNs) effectively address the challenges of engineering design optimization by using data-driven models, thus reducing computational demands. However, their effectiveness depends heavily on hyperparameter optimization (HPO), which is a global optimization problem. While traditional HPO methods, such as manual, grid, and random search, are simple, they often fail to navigate the vast hyperparameter (HP) space efficiently. This work examines the effectiveness of integrating Bayesian optimization (BO) with multi-armed bandit (MAB) optimization for HPO in NNs. The thesis initially addresses HPO in one-shot sampling, where NNs are trained using datasets of varying sample sizes. It compares the performance of NNs optimized through traditional HPO techniques and a combination of BO and MAB optimization on the analytical Branin function and aerodynamic shape optimization (ASO) of an airfoil in transonic flow. Findings from the optimization of the Branin function indicate that the combined BO and MAB optimization approach leads to simpler NNs and reduces the sample size by approximately 10 to 20 compared to traditional HPO methods, all within half the time. This efficiency improvement is even more pronounced in ASO, where the BO and MAB optimization use about 100 fewer samples than the traditional methods to achieve the optimized airfoil design. The thesis then expands on adaptive HPOs within the framework of efficient global optimization (EGO) using a NN-based prediction and uncertainty (EGONN) algorithm. It employs the BO and MAB optimization for tuning HPs during sequential sampling, either every iteration (HPO-1itr) or every five iterations (HPO-5itr). These strategies are evaluated against the EGO as a benchmark method. Through experimentation with the analytical three-dimensional Hartmann function and ASO, assessing both comprehensive and selective tunable HP sets, the thesis contrasts adaptive HPO approaches with a static HPO method (HPO-static), which uses the initial HP settings throughout. Initially, a comprehensive set of the HPs is optimized and evaluated, followed by an examination of selectively chosen HPs. For the optimization of the three-dimensional Hartmann function, the adaptive HPO strategies surpass HPO-static in performance in both cases, achieving optimal convergence and sample efficiency comparable to EGO. In ASO, applying the adaptive HPO strategies reduces the baseline airfoil's drag coefficient to 123 drag counts (d.c.) for HPO-1itr and 120 d.c. for HPO-5itr when tuning the full set of the HPs. For a selected subset of the HPs, 123 d.c. and 121 d.c. are achieved by HPO-1itr and HPO-5itr, respectively, which are comparable to the minimum achieved by EGO. While the HPO-static method reduces the drag coefficient to 127 d.c. by tuning a subset of the HPs, which is a 15 d.c. reduction from its full set case, it falls short of the minimum of adaptive HPO strategies. Focusing on a subset of the HPs reduces time costs and enhances the convergence rate without sacrificing optimization efficiency. The time reduction is more significant with higher HPO frequencies as HPO-1itr cuts time by 66%, HPO-5itr by 38%, and HPO-static by 2%. However, HPO-5itr still requires 31% of the time needed by HPO-1itr for the full HP tuning and 56% for the subset HP tuning.

Degree Type

• Master of Science in Aeronautics and Astronautics
• Aeronautics and Astronautics

Campus location

• West Lafayette

Advisor/Supervisor/Committee Chair

Additional committee member 2, additional committee member 3, usage metrics.

• Aerospace engineering not elsewhere classified

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Master of science in electrical engineering.

Welcome to the Department of Electrical and Computer Engineering at San Diego State University! We are committed to shaping a great future for each one of our students. If you are interested in applying to our program, please follow this link . 

MSEE Program Overview

The Department of Electrical and Computer Engineering offers graduate study leading to a Master of Science degree in Electrical Engineering (MSEE). The areas of study are Communication Systems, Digital Signal Processing, Electromagnetic Systems, VLSI Systems, Computer Networks, Energy Systems and Control, and Embedded Systems.

The MSEE program comprises of several coursework and a culminating experience which can either be a thesis (Plan A) or a project (Plan B). Each student must complete 30 units either by selecting Plan A (Thesis) or Plan B (Project). This is referred to as the student’s Program of Study or POS. Each of our courses are worth three units – therefore you are looking at completing ten courses for a MSEE degree. Eighteen of the thirty units should be 600 and 700-numbered courses. The remaining twelve units can be from 500, 600 or 700-level courses offered by the department. No more than two courses can be taken from other departments in the College of Engineering or from the College of Sciences to satisfy these requirements, with the prior approval of the Graduate Advisor. Students are required to pick an area of specialization and then choose relevant courses that help the student to gain mastery in that area (referred to as “Depth area courses”) and a few other courses that pertain to peripheral skills that can make the student well-rounded (referred to as “Breadth area courses”). The department allows the student to tailor their individual course selection (or POS) to align with their interest and their career goals, often in consultation with their Thesis/Project advisor and/or the Graduate Advisor. A minimum average GPA of 3.0 is required to successfully complete the degree.

IMPORTANT NOTE: International Students requiring an I-20 immigration document from SDSU must be enrolled in a minimum of 6 units of in-person course instruction on campus, per semester. International students may not take more than 3 units of fully online course instruction, per semester.

Thesis and Project Plans

There are two plans of studies: Plan-A (Thesis) and Plan-B (Project).

Plan A: Thesis Option

Students opting for Plan A must complete 21 units of course work (7 courses), 6 units of EE 797 "Research" (typically as two 3-unit EE 797 “Research”, taken in two different semesters) and 3 units of EE 799A "Thesis" under supervision of a full-time ECE faculty. The remaining twenty-one units can be taken from the course guidelines document , all subject to the approval of the Thesis Advisor and Graduate Advisor.

Credit for EE 799A will be given only after completing the thesis. Credit cannot be given for EE 798 for students in Plan A. An oral defense of the thesis is required in front of a committee of three faculty members one of whom will be your Thesis Advisor, another from your department and the third member from any department other than your own. In addition, a completed thesis report in a required format needs to be submitted to the university. Once your thesis has been published, credit will be given for EE 799A. Please visit the Thesis/Project Procedures site for instructions on how and when to file your thesis and graduation paperwork. Please note, that the University requires you to complete several formalities as you approach your graduation – please stay abreast with the procedures and monitor your progress on your digital webportal.

Plan B: Project Option

Students opting for Plan B or the Project option are required to pick an area of specialization and complete a minimum of 18 units of “Depth Area Courses” and 3 units of EE 798 as the project. Courses can be chosen from the following course guidelines document . Students are allowed to enroll in the project course (EE 798) after the completion of 21 units but must do so in the semester immediately after completing 27 units. EE 797 cannot be used for students in Plan B.

An oral defense of the project is required in front of a committee of two faculty members one of whom will be your Project Advisor and another faculty member from your department. In addition, a project report in a required format needs to be submitted to the department. Once your project has been defended, credit will be given for 798. Please visit the Thesis/Project Procedures site for instructions on how and when to file your project and graduation paperwork. Please note, that the University requires you to complete several formalities as you approach your graduation – please stay abreast with the procedures and monitor your progress on your digital webportal.

Program of Study (POS) Plan

Each student should prepare a Program of Study (POS). The POS allows you to plan your graduate coursework ahead of time and gives you clarity on your road ahead. Therefore, it is in your best interest to prepare the POS as soon as possible but no later than the end of your second semester. You will also find the relevant POS forms under the Thesis/Project Procedures tab on our website. Be sure to stay on top-of-your-game throughout your graduate program.

Tracking Your Progress

The College of Graduate Studies offers an electronic resource for you to track your progress towards graduation. This resource is called the Degree Evaluation (or Degree Audit Report). The report can be found in your my.SDSU account under the 'Degree Evaluation' tile. When you click on the Degree Evaluation, your coursework and other degree requirements will be converted into a customized report. The Degree Evaluation is your official guide for tracking your progress towards your graduation. We recommend keeping a close eye on your degree progress through this tool. Please reach out to the College of Graduate Studies at [email protected] if you see any discrepancies in your academic record. For help with my.SDSU, click on my.SDSU Student Guides and Resources .

We Are Here to Help

We are committed to making your graduate student experience with us as smooth, productive and enjoyable as possible. For academic advising please contact the Graduate Advisor – Dr. Santosh Nagaraj at [email protected] . We highly encourage you to refer to the Graduate Handbook which should answer most of the commonly asked questions. The handbook also explains several rules and regulations that you should abide by, during your graduate studies.

Degree Learning Outcomes

The MSEE degree has been designed to achieve the following outcomes in its graduates. Corresponding methods of assessing the outcomes have also been specified.

Note: The forms on this page are in Portable Document Format (PDF) and require Adobe Acrobat Reader 5.0 or higher to view and print. Download Adobe Acrobat Reader free from the Adobe Web site.

Welcome to Electrical and Computer Engineering

Researchers at UC Davis and Oak Ridge National Laboratory Develop New Tool for Neuron Experiments 

• by College of Engineering Communications
• June 04, 2024

A collaboration between Adam Moulé , the Joe and Essie Smith Endowed Chair of Chemical Engineering at the University of California, Davis, former UC Davis Ph.D. student Daniel Vong, and Luke Daemen, a researcher at Oak Ridge National Laboratory, or ORNL, has resulted in rotating sample holder that enables new types of neuron experiments.   

The sample holder tumbles powdered photochemical materials within a neutron beamline. The rotating holder exposes more of the material to light for increased photoactivation and better photochemistry data capture. Conventional sample holders were unable to rotate, or tumble, powdered samples, which meant light could only reach and activate molecules on the sample’s surface, reducing the amount and quality of data that could be captured.   

The new sample holder has already enabled the first neutron scattering observations of an optically excited photon splitting into two particles  —  a process that could lead to increased solar energy conversion efficiency in photovoltaic devices, such as solar cells or solar panels, and industrial processes.   

Vong, the first author of the paper for this research , was a researcher in Moulé’s Renewable Energy Electronics Lab while pursuing his doctorate in materials science and engineering at UC Davis. He spent a year at ORNL collaborating with Daemon on developing the new sample environment based on Moulé’s ideas.   

Vong is now at Intel in Portland, Oregon, and Moulé and his lab group continue to collaborate with Daemon. They plan to do more experiments this year.   

“The collaboration was a win-win, demonstrating how the university and ORNL scientists can work together successfully,” said Moulé. “It was a great opportunity for one of our researchers to intern at ORNL, learning from an expert instrument scientist and having access to the resources needed to build such an innovative sample holder.”   

Read about the collaborative research at ORNL

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