Browsing Institutt for matematiske fag by Author "Eidsvik, Jo"
Now showing items 21-40 of 91
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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 ... -
Dynamic stochasticmodeling for adaptive sampling of environmental variables using an AUV
Berget, Gunhild Elisabeth; Eidsvik, Jo; Alver, Morten Omholt; Johansen, Tor Arne (Peer reviewed; Journal article, 2023)Discharge of mine tailings significantly impacts the ecological status of the sea. Methods to efficiently monitor the extent of dispersion is essential to protect sensitive areas. By combining underwater robotic sampling ... -
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 and Self-supervised Learning for Improved Classification of Seismic Signals from the Åknes Rockslope
Lee, Daesoo; Aune, Erlend; Langet, Nadege; Eidsvik, Jo (Journal article; Peer reviewed, 2022)A case study with seismic geophone data from the unstable Åknes rock slope in Norway is considered. This rock slope is monitored because there is a risk of severe flooding if the massive-size rock falls into the fjord. The ... -
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 ... -
Estimation and model criticism for categorical and Gaussian Markov random fields
Wilhelmsen, Mathilde (Master thesis, 2007)We consider two different spatial models to describe the correlation structure on a lateral two dimensional grid. First, a discrete first order Markov random field is studied, where the spatial dependence is represented ... -
Estimation of Resrvoir Properties by Joint Inversion of Seismic AVO and CSEM data
Holm, Andreas (Master thesis, 2007)Porosity and water saturation in a horizontal top-reservoir are estimated from seismic AVO (Amplitude Versus Offset) data and Controlled Source Electromagnetic (CSEM) data jointly. A model connecting porosity and saturation ... -
Exact Optimization Methods for the Mixed Capacitated General Routing Problem
Gaze, Kevin Anders (Master thesis, 2013)This thesis is about using exact optimization algorithms to solve the routing problemknown as the Mixed Capacitated General Arc Routing Problem (MCGRP) that is a generalizationof many other well known routing problems. The ... -
Forecasting Day-Ahead Electricity Spot Prices, With Applications to the German Electricity Market
Johnsen, Angela Maiken (Master thesis, 2019)Denne masteroppgaven har studert det tyske elektrisitetsmarkedet, i den hensikt å predikere neste dags elektrisitetsspotpriser. Tre modeller er presentert; den første modellen er en "persistence"-modell, som fungerer som ... -
Generative Adversarial Networks for Seismic Interpretation
Huso, Erik Arne (Master thesis, 2020)Arbeidsprosesser der tolkning av seismikk inngår, er en nødvendig del av prosjekter der olje- og gassforekomster oppdages. Selv om nylige fremskritt i forskningen rundt dyp læring har gjort det mulig å forenkle noe av ... -
Graph Gaussian Process Classifier with Anchor Graph and Label Propagation
Ovanger, Oscar (Master thesis, 2021)Gaussiske prosesser er en viktig metode for maskinlæring da den lar oss sette en prioritet p˚a formen til en funksjon, og den arver fine egenskaper fra normalfordelingen. Den har blitt brukt b˚ade som en regresjons- og ... -
Inference in cylindrical models having latent Markovian classes - with an application to ocean current data
Lie, Henrik Syversveen; Eidsvik, Jo (Peer reviewed; Journal article, 2021)Spatial direction vector data can be represented cylindrically by linear magnitudes and circular angles. We analyze such data by using a hierarchical Markov random field model with latent discrete classes and conditionally ... -
Information-driven robotic sampling in the coastal ocean
Fossum, Trygve Olav; Eidsvik, Jo; Ellingsen, Ingrid H.; Alver, Morten; Fragoso, Glaucia Moreira; Johnsen, Geir; mendes, renato; Ludvigsen, Martin; Rajan, Kanna (Journal article; Peer reviewed, 2018)Efficient sampling of coastal ocean processes, especially mechanisms such as upwelling and internal waves and their influence on primary production, is critical for understanding our changing oceans. Coupling robotic ... -
LIDAR Extended Object Tracking of a Maritime Vessel Using an Ellipsoidal Contour Model
Ruud, Kristian Amundsen (Master thesis, 2018)Extended object tracking (EOT) have numerous applications and can be integrated in autonomous systems like self-driving cars or autonomous surface vehicles. These systems can be improved by using robust tracking algorithms ... -
Lineær mikset modell for kompressor data med en applikasjon
Herdahl, Mads (Master thesis, 2008)StatoilHydro is the operator of the Åsgard oil and gas field outside of Trøndelag, Norway, where large compressors for injection, recompression and export of natural gas are installed. The facility transports and stores ...