Browsing NTNU Open by Author "Eidsvik, Jo"
Now showing items 1-20 of 70
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A Bayesian Inversion Approach to Filtering and Decision Making with Applications to Reservoir Characterization
Rezaie, Javad (Doctoral Theses at NTNU, 1503-8181; 2013:275, Doctoral thesis, 2013)The main objectives of this thesis are the estimation/filtering and decision making problems with a Bayesian inversion point of view, and in geophysical systems. In addition, determining the information content in the ... -
A blockyness Constraint for seismic AVA Inversion
Jensås, Ingrid Østgård (Master thesis, 2008)The aim of seismic inversion is to determine the distribution of elastic parameters from recorded seismic reflection data. If a combination of elastic parameters is known, they indicate a certain fluid or lithology. Elastic ... -
A heavy tailed statistical model applied in anti-collision calculations for petroleum wells
Gjerde, Tony (Master thesis, 2008)Anti-collision calculations are done during the planning of a new petroleum well. These calculations are required in order to control the risk of having a well-collision, which is an unwanted event at any cost. The risk ... -
A Novel Profit Scoring Method for Classifying Credit Card Applications
Skarestad, Helge (Master thesis, 2017)This thesis presents a new scoring method for credit card applications. The method balances the risk and the expected profits an applicant represents to a credit card company. In addition, the EMP cut-off selection procedure ... -
A Simulation Analysis of CO2 Capture and Underground Storage Monitoring in Smeaheia
Anyosa, Susan; Bunting, Scott William Christopher; Eidsvik, Jo; Romdhane, Mohamed Anouar (Chapter, 2019)The emissions of CO2 are an environmental problem and one possible solution is its capture and conduct underground storage (CSS). However, there is potential risk of leakage, and to aid in this challenge we propose to use ... -
Adaptive Monitoring of Snowpack Development using a Dynamic Linear Model.
Berg-Jensen, Jens Georg (Master thesis, 2021)Snøskred er en av de vanligste naturfarene i Norge, med stor trussel mot menneskeliv og infrastruktur, siden snøskred er en av de vanligste årsakene for blokkering av veier. Varsom er et overvåkings- og varslingssystem ... -
Adaptive Sampling of Ocean Processes Using an AUV with a Gaussian Proxy Model
Berget, Gunhild Elisabeth; Fossum, Trygve Olav; Johansen, Tor Arne; Eidsvik, Jo; Rajan, Kanna (Journal article; Peer reviewed, 2018)This paper presents methods for building and exploiting compact spatial models on board an autonomous underwater vehicle (AUV) towards tracking suspended material plumes. The research is aiming to improve real-time monitoring ... -
Analysis of Longitudinal Data with Missing Values.: Methods and Applications in Medical Statistics.
Dragset, Ingrid Garli (Master thesis, 2009)Missing data is a concept used to describe the values that are, for some reason, not observed in datasets. Most standard analysis methods are not feasible for datasets with missing values. The methods handling missing data ... -
Bankruptcy prediction for Norwegian enterprises using interpretable machine learning models with a novel timeseries problem formulation
Moen, Petter Aarseth (Master thesis, 2020)Prediksjon av konkurs hos selskaper er et emne som er relevant både hos investorer, kreditorer, banker og regulatorer. I denne oppgaven bruker vi et datasett bestående av årsrapporter fra mer enn 175 000 norske små- og ... -
Bayesian Text Categorization
Næss, Arild Brandrud (Master thesis, 2007)Natural language processing is an interdisciplinary field of research which studies the problems and possibilities of automated generation and understanding of natural human languages. Text categorization is a central ... -
Compact models for adaptive sampling in marine robotics
Fossum, Trygve Olav; Ryan, John; Mukerji, Tapan; Eidsvik, Jo; Maughan, Thom; Ludvigsen, Martin; Rajan, Kanna (Journal article; Peer reviewed, 2019)Finding high-value locations for in situ data collection is of substantial importance in ocean science, where diverse bio-physical processes interact to create dynamically evolving phenomena. These cover a variable spatial ... -
Cylindrical hidden Markov random field models with applications to ocean surface currents
Lie, Henrik Syversveen (Master thesis, 2020)Observasjoner av overflatestrømmer i havet gir opphav til romlige sylindriske data, som er bivariate representasjoner av en lineær styrke og en sirkulær vinkel. For å kunne analysere disse dataene utvikler vi en skjult ... -
Data assimilation for a geological process model using the ensemble Kalman filter
Skauvold, Jacob; Eidsvik, Jo (Journal article, 2017)We consider the problem of conditioning a geological process‐based computer simulation, which produces basin models by simulating transport and deposition of sediments, to data. Emphasising uncertainty quantification, we ... -
Development of Penalized Complexity Priors for Stationary and Invertible Time Series Processes
Srivastav, Himanshu (Master thesis, 2017)In the thesis, the PC prior framework is applied to construct the prior distributions for dependencies of the AR(1) processes, the MA(1) processes and the ARMA(1,1) processes. -
Dynamic exploration designs for graphical models using clustering with applications to petroleum exploration
Martinelli, Gabriele; Eidsvik, Jo (Journal article, 2014)The paper considers the problem of optimal sequential design for graphical models. Oil and gas exploration is the main application. Here, the outcomes at prospects or reservoir units are highly dependent on each other. The ... -
Efficient spatial designs using Hausdorff distances and Bayesian optimization
Paglia, Jacopo; Eidsvik, Jo; Karvanen, Juha (Peer reviewed; Journal article, 2021)An iterative Bayesian optimization technique is presented to find spatial designs of data that carry much information. We use the decision theoretic notion of value of information as the design criterion. Gaussian process ... -
Energy Efficient Monitoring using Kalman Filter - A case study on environmental variables collected from solar panels
Dahlen, Anne-Line Evenstad (Master thesis, 2018)An Internet of Things (IoT) environment uses information gathering and sharing to draw conclusions, make decisions and predict future occurrences. The technology connects devices such as mobile phones and sensors in private ... -
Ensemble-based data assimilation methods applied to geological process modeling
Skauvold, Jacob (Doctoral theses at NTNU, 2018:404, Doctoral thesis, 2018)Summary: Data assimilation is the art of conditioning a numerical simulation of a physical process on observations of the real process. That is, adjusting estimates so that they agree not only with a mathematical model ... -
Ensemble-based seismic inversion for a stratified medium
Gineste, Michael; Eidsvik, Jo; Zheng, York (Peer reviewed; Journal article, 2020)Seismic waveform inversion is a nontrivial optimization task, which is often complicated by the nonlinear relationship between the elastic attributes of interest and the large amount of data obtained in seismic experiments. ... -
Estimating the Value of Information Using Bayesian Optimization with Gaussian Process Surrogate Models - An Application to Failure Rates at Offshore Wind Farms
Myklebust, Hans Olav Vogt (Master thesis, 2018)Finding operation and maintenance (O&M) strategies that increase the profitability of an offshore wind farm is essential in order to be competitive with other sources of renewable energy. An O&M strategy is characterized ...