Browsing Studentoppgaver (TN-IER) by Author "Hong, Aojie"
Now showing items 1-9 of 9
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A Decision Analysis Framework for Offshore Green Ammonia Project Investments
Valberg, Vegard (Master thesis, 2021)Ammonia has great importance to our daily lives – it is used in household cleaning products and to make agricultural fertilizers. Recently it has attracted attention from the energy sector, since it can be used as a ... -
Bayesian interactive decision support for multi-attribute problems with even swaps
Sandbakk, Trym Seim (Master thesis, 2022)Even swaps (ES) is a multi-criteria decision-making method introduced by Hammond et al. (1998) that makes it easier for decision makers (DMs) to make trade-offs between the decision criteria. The ES method can be further ... -
Decision-Driven Data Analytics for Well Placement Optimization in Field Development Scenario - Powered by Machine Learning
Kor, Peyman (Masteroppgave/UIS-TN-IER/2019;, Master thesis, 2019-06-15)Application of Data Analytics and Machine Learning (ML) in petroleum reservoir management have received a lot of attention in recent years, mainly due to the availability of sheer computational resources and recorded big ... -
Forecast of investment in renewable energy with consideration of dependency of investment in renewable energy and oil and gas prices
Waqar, Muhammad (Master thesis, 2021)Renewables are taking up the role of increasing importance in the energy industry, especially with the recent wave of the drop in prices of oil and gas. Therefore, oil and gas companies are gradually positioning themselves ... -
Impact of risk attitude on optimal IOR initiation time: A case study solved in a sequential decision-making framework powered by machine learning-based non-linear regression
Yanez Sanchez, Marianne Soledad (Master thesis, 2023)The least-squares Monte Carlo algorithm (LSM) is an efficient approximate dynamic programming algorithm for solving sequential decision-making problems, leveraging regression. Previous studies have showcased the LSM workflow ... -
Probabilistic decline curve analysis with multiple models
Bin Alim, Maaz (Master thesis, 2022)Numerical models have been established to help understand the longevity of projects when exploring and drilling for hydrocarbons. They aid in understanding and optimizing decisions on the long-term feasibility of a project ... -
Probabilistic Machine Learning for Production Optimization Under Uncertainty
Mirmohammadhosseini, Seyedehmina (Master thesis, 2023)This thesis investigates the application of Bayesian Optimization (BO) in the optimization of the Expected Net Present Value (ENPV) for oil field development. The objective is to maximize the ENPV while reducing the ... -
Reinforcement Learning for Automated Power Grid Operation: Can a machine be trained to operate a power grid?
Bueno, Rebecca Santana (Master thesis, 2021)The increasingly high demand and amount of renewable energy sources in the power grid have added more complexity to power grid operations. The electrical power system must ensure that the generated power and the consumed ... -
Utilizing machine learning algorithms in the ensemble-based optimization (EnOpt) method for enhancing gradient estimation
Raji, Nidaa (Master thesis, 2022)High or even prohibitive computational cost is one of the key limitations of robust optimization using the Ensemble-based Optimization (EnOpt) approach, especially when a computationally demanding forward model is involved ...