Browsing NTNU Open by Author "Eidsvik, Jo"
Now showing items 1-20 of 88
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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 ... -
Adaptive spatial designs minimizing the integrated Bernoulli variance in spatial logistic regression models - with an application to benthic habitat mapping
Anyosa, Susan; Eidsvik, Jo; Pizarro, Oscar (Peer reviewed; Journal article, 2022)Constructing efficient spatial sampling designs is important for monitoring, understanding and characterizing environmental processes acting over large-scale spatial domain. Multiple types of devices can accomplish informative ... -
Adaptive Underwater Robotic Sampling of Dispersal Dynamics in the Coastal Ocean
Berget, Gunhild Elisabeth; Eidsvik, Jo; Alver, Morten; Py, Frédéric; Grøtli, Esten Ingar; Johansen, Tor Arne (Chapter, 2022)To get a better understanding of the highly nonlinear processes driving the ocean, efficient and informative sampling is critical. By combining robotic sampling with ocean models we are able to choose informative sampling ... -
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 ... -
Approximate Filtering Approaches for Switching Linear Dynamical Systems
Simonsen, Mads Adrian (Master thesis, 2022)«State-observation model» er et dynamisk Bayesiansk nettverk (DBN) som inneholder to mengder stokastiske variabler som utvikler seg over tid; en skjult mengde og en observert mengde. De mest kjente «state-observation» ... -
Assessing the value of seismic monitoring of CO2 storage using simulations and statistical analysis
Anyosa, Susan; Bunting, Scott William Christopher; Eidsvik, Jo; Romdhane, Mohamed Anouar; Bergmo, Per Eirik Strand (Peer reviewed; Journal article, 2021)Successful storage of CO2 in underground aquifers requires robust monitoring schemes for detecting potential leakage. To aid in this challenge we propose to use statistical approaches to gauge the value of seismic monitoring ... -
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 ... -
Batch seismic inversion using the iterative ensemble Kalman smoother
Gineste, Michael; Eidsvik, Jo (Peer reviewed; Journal article, 2021)An ensemble-based method for seismic inversion to estimate elastic attributes is considered, namely the iterative ensemble Kalman smoother. The main focus of this work is the challenge associated with ensemble-based inversion ... -
Bayesian rock physics inversion using a localized ensemble-based approach - with an application to the Alvheim field
Eidsvik, Jo; Avseth, Per Åge (Peer reviewed; Journal article, 2023)We describe, implement and show results of a localized ensemble-based approach for seismic AVO inversion with uncertainty quantification. Ensembles are simulated from continuous prior probability distributions for fluid ... -
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 ... -
Breakpoint detection on latent autoregressive time series of counts using integrated nested Laplace approximation.
Ahmed, Amir (Bachelor thesis, 2020)Abrupt changes in a data source can weaken models that fail at addressing these. Structural change detection has traditionally been done with a frequentist approach, but recently approaches based on Bayesian models and ... -
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 ...