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Læring av uønskede hendelser på tvers av vedlikeholdsentreprenører
(Masteroppgave/UIS-TN-IØRP/2011;, Master thesis, 2011)Utgangspunktet for denne masteroppgaven er en rapport fra SINTEF presentert på Petroleumstilsynets(Ptil) konferanse “Læring av uønskede hendelser hos vedlikeholdsentreprenører” i november 2010. Rapporten antydet at læringen ... -
Læring etter granskninger av uønskede hendelser i Odfjell Drilling
(Masteroppgave/UIS-TN-IØRP/2011;, Master thesis, 2011)Denne oppgaven tar utgangspunkt i hvordan organisatorisk læring forekommer hos en borekontraktør etter granskning av uønskede hendelser. Problemstillingene er rettet mot læring, og stiller spørsmål med hvordan granskningens ... -
Læring etter hendelser: Hvordan forbedre erfaringsoverføring etter granskninger av uønskede hendelser? Learning from incidents: How to improve experience transfer after investigations of unwanted events?
(Master thesis, 2023)Denne masteroppgaven handler om erfaringsoverføring og læring etter uønskede hendelser i den norske petroleumsvirksomheten. Bakgrunnen for oppgaven er tidligere forskning som viser at organisasjoner i den norske ... -
Læring fra uønskede hendelser med ny teknologi på ferjer i Norled
(Masteroppgave/UIS-TN-IØRP/2015;, Master thesis, 2015-06-15)Som et av Norges ledende ferjeselskap frakter Norled årlig rundt 15 millioner passasjerer og 7,5 millioner personbilenheter. Selskapet satser på å være innovative og bruke nye løsninger, men har også hatt enkelte uhell med ... -
Lærings System og Smart Tekst Editor for å forbedre Lærer - Student Samarbeid
(Bachelor thesis, 2021)Web Utvikling, TypeScript, JavaScript, HTML, CSS, MySQL, Database, Vue.js, Node.js -
Lærings System og Smart Tekst Editor for å forbedre Lærer - Student Samarbeid
(Bachelor thesis, 2021)Web Utvikling, TypeScript, JavaScript, HTML, CSS, MySQL, Database, Vue.js, Node.js -
Læringspotensialet til granskingsrapporter fra Norge og USAs nasjonale granskingskommisjoner
(Master thesis, 2021)Accident investigations are an important tool for learning from accidents, by giving insight into what went wrong, and how to prevent similar accidents from happening in the future. However, there is a lack of standard ... -
Læringsprosesser hos Statens Vegvesen
(Masteroppgave/UIS-TN-ISØP/2020;, Master thesis, 2020-07-15)Denne oppgaven tar for seg forholdet mellom to av de mest sentrale aktørene i håndteringen av trafikksikkerhet i Norge: Statens Havarikommisjon for Transport og Statens vegvesen. Formålet med oppgaven er å avdekke hvordan ... -
Lønnsom foredling av sjømat i Norge
(Research report, 2014)Automatisering og robotisering av produksjonsprosesser forventes å få en sentral plass i samfunnet. I en utredning fra Stiftelsen for Strategisk Forsking i Sverige, forventes det at i løpet av en periode på 20 år, vil hele ... -
Lønnsomheten ved implementering av Økt Oljeutvinning - Økonomisk Potensial for Smart Vann i Sandstein
(Master thesis, 2021)Smart Vann er en fremvoksende økt oljeutvinning (EOR) teknologi, som har vist lovende resultater i laboratoriet. Ved å uvinne en ytterligere 26% OOIP har denne EOR-metoden et stort potensial for implementering i felt, ved ... -
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 ...