Browsing Universitetet i Stavanger by Title
Now showing items 10616-10635 of 18559
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Machine and Deep Learning for Lithofacies Classification from Well Logs in the North Sea.
(Master thesis, 2021)Lithology identification by using well log data is an initial and fundamental step within petroleum geosciences; same that provides essential information about the subsurface and plays a crucial role in reservoir ... -
Machine learning algorithms vs. thresholding to segment ischemic regions in patients with acute ischemic stroke
(Peer reviewed; Journal article, 2021-07)Objective: Computed tomography (CT) scan is a fast and widely used modality for early assessment in patients with symptoms of a cerebral ischemic stroke. CT perfusion (CTP) is often added to the protocol and is used by ... -
Machine Learning Approach for Risk-Based Inspection Screening Assessment
(Peer reviewed; Journal article, 2019-05)Risk-based inspection (RBI) screening assessment is used to identify equipment that makes a significant contribution to the system's total risk of failure (RoF), so that the RBI detailed assessment can focus on analyzing ... -
Machine Learning Based Approach to Predict Fuel Consumption on Mobile Offshore Drilling Units
(Masteroppgave/UIS-TN-IMBM/2019;, Master thesis, 2019-06-15)The use of machine learning models for optimization and improved decision-making has a great potential in the drilling industry. This thesis demonstrates a model for predicting fuel consumption on the Mobile Offshore ... -
Machine learning based decline curve analysis for short-term oil production forecast
(Peer reviewed; Journal article, 2021-05)Traditional decline curve analyses (DCAs), both deterministic and probabilistic, use specific models to fit production data for production forecasting. Various decline curve models have been applied for unconventional ... -
Machine Learning Based Load Forecasting
(Master thesis, 2022)Population is increasing rapidly and all the demands like electricity are also increasing. The government in England installed smart meters in order to analyze and follow better the energy consumption. Machine learning ... -
Machine learning based seismic classification for facies prediction
(Master thesis, 2023)This thesis explores the performance of machine learning (ML) methods for predicting facies from seismic attributes for 2D and 3D datasets. It focuses on building, training, and testing four supervised methods: Logistic ... -
Machine learning based shale volume prediction from the Norwegian North Sea
(Master thesis, 2021)Petroleum geosciences, like other fields, has entered the era of new advanced technologies to handle problems related to complex massive data sets and decision making. The growing quantity of subsurface datasets has created ... -
Machine Learning Based System Health Check Analyzer For Energy Components
(Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)In any system health check is an important measure, which provides details on how the system is performing and whether there is a need for an intervention manual or automated to correct any anomaly. There are several ... -
Machine learning for pay zone identification in the Smørbukk field using well logs and XRF data
(Master thesis, 2022)As geosciences enter the age of big data, a faster and more sophisticated tool is needed to automate manual interpretation workflows, limiting industry professionals' ability to harness all available well-log data to reduce ... -
Machine Learning for Tagging of Educational Content
(Master thesis, 2022)Online education has become a popular education form in recent years, with its use increasing massively during the COVID-19 pandemic. Neddy is a start-up company created at the start of the COVID-19 pandemic with the aim ... -
Machine learning for underground gas storage with cushion CO2 using data from reservoir simulation
(Peer reviewed; Journal article, 2023)Underground natural gas storage (UNGS) is a means to store energy temporarily for later recovery and use. In such storage operations, carbon dioxide (CO2) can be injected as cushion gas to improve the operating efficiency ... -
Machine learning in reservoir permeability prediction and modelling of fluid flow in porous media
(Peer reviewed; Journal article, 2019)Reliable data on the properties of the porous medium are necessary for the correct description of the process of displacing hydrocarbons from the reservoirs and forecasting reservoir performance. The true permeability of ... -
Machine learning methods for assessing value-of-information
(Master thesis, 2022)One of the most useful features of decision analysis is its ability to distinguish between constructive and wasteful information gathering. Value-of-information (VOI) and sequential information gathering (Value-of-Flexibility, ... -
Machine Learning methods to detect improper and irrelevant citations
(Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)The focus of this study is on the relation between papers and their citations using Machine Learning algorithms to detect improper and irrelevant citations. The model takes the paper’s citations and classifies them into ... -
Machine Learning techniques for Prediction of Rock Properties from Reservoir Well Logs
(Master thesis, 2021)Estimation of reservoir parameters is important in reservoir evaluation and estimation of petroleum volume. Reservoir parameters such as oil saturation, water saturation and porosity are derived from petrophysical logs or ... -
Machine learning techniques for the detection of shockable rhythms in automated external defibrillators
(Journal article; Peer reviewed, 2016-07)Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrillators (AED). AED algorithms for ... -
Machine learning to detect corporate greenwashing
(Master thesis, 2023)This master thesis focuses on developing an automatic approach to detect corporate greenwashing. To achieve this, data must be collected, and green claims found from this data must be fact checked. The first step is to ... -
Machine learning, unsupervised learning and stain normalization in digital nephropathology
(Master thesis, 2023)Chronic kidney disease is a serious health challenge and still, the field of study lacks awareness and funding. Improving the efficiency of diagnosing chronic disease is important. Machine learning can be used for various ... -
Machine Learning-Based Analysis of Test Results
(Master thesis, 2023)A comprehensive understanding of the overall performance of the tests is critical in software testing to make necessary adjustments to the test schedule or conduct targeted investigations. In ABB Bryne, the software testing ...