Blar i NTNU Open på forfatter "Omre, Karl Henning"
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Bayesian Gaussian Inversion of Time-Lapse Seismic AVO Data
Forberg, Ole Bernhard (Master thesis, 2017)The goal of this study is to characterize an oil reservoir along a depth profile at two different points in time, based on seismic AVO data gathered at these times. We apply Bayesian methodology to the inversion problem. ... -
Bayesian Inversion and Inference of Categorical Markov Models with Likelihood Functions Including Dependence and Convolution
Fjeldstad, Torstein Mæland (Master thesis, 2015)A convolutional two-level Markov model is studied in this thesis. The bottom level contains a latent Markov chain, and given the variables, the middle contains a latent Gaussian random field. We observe the second level ... -
Bayesian Inversion of Time-lapse Seismic Data using Bimodal Prior Models
Amaliksen, Ingvild (Master thesis, 2014)The objective of the current study is to make inference about reservoir properties from seismic reflection data. The inversion problem is cast in a Bayesian framework, and we compare and contrast three prior model settings; ... -
Bayesian Inversion of Well Log Data into Facies Units based on a Spatially Coupled Model
Vigsnes, Maria (Master thesis, 2006)Through a study of cored wells from the Statfjord Formation in the Tampen Area, we derive a spatially coupled classification model for facies units. We consider a Bayesian framework for the problem. A likelihood model is ... -
Bayesian Seismic Lithology/Fluid Inversion Constrained by Rock Physics Depth Trends
Rimstad, Kjartan (Master thesis, 2008)In this study we consider 2D seismic lithology/fluid inversion constrained by rock physics depth trends and a prior lithology/fluid Markov random field. A stochastic relation from porosity and lithology/fluid to seismic ... -
Classification of seismic waveform attributes in a Bayesian framework
Haugeto, Vegard Torje (Master thesis, 2009)The work conducted in this thesis is an extension of an existing methodology developed at Schlumberger Stavanger Research. The Extrema Classification method (Borgos, 2003) provides a framework for automated mapping of ... -
Closed-skew Distributions: Simulation, Inversion and Parameter Estimation
Iversen, Daniel Høyer (Master thesis, 2010)Bayesian closed-skew Gaussian inversion is defined as a generalization of traditional Bayesian Gaussian inversion. Bayesian inversion is often used in seismic inversion, and the closed-skew model is able to capture the ... -
Ensemble Kalman Filter on the Brugge Field
Vo, Paul Vuong (Master thesis, 2012)The purpose of modeling a petroleum reservoir consists of finding the underlying reservoir properties based on production data, seismic and other available data. In recent years, progress in technology has made it possible ... -
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 ... -
Estimation of Thermal Properties of an Ice Pad using the Parameter Particle Filter
Lundquist, Fredrik Elis (Master thesis, 2017)Heating is the primary energy consumer in an ice rink and being able to optimise its use is a key factor in minimising energy expenditures. This study seeks to perform parameter estimation on site specific thermal parameters ... -
Hierarchical Ensemble Kalman Filter: for Observations of Production and 4-D Seismic Data
Sætrom, Jon (Master thesis, 2007)Hierarchical Bayesian sequential Reservoir History matching, seismic inversion, Ensemble Kalman Filter, -
Image Analysis Bayesian Inversion in Hidden Markov Models
Fjelltveit, Marte (Master thesis, 2021)I denne studien blir Bayesiansk inversjon i skjulte Markov modeller brukt til å analysere bilder. Den rekursive bakvendte algoritmen, som regner ut sannsynlighetene i posterior-modellen til en Markov random profil direkte, ... -
In silico Investigation of Possible Mitotic Checkpoint Signalling Mechanisms
Kirkeby, Håkon (Master thesis, 2007)The mitotic checkpoint is the major bio-chemical pathway acting to ensure stable genome content in cell division. A delay in chromosome segregation is enforced as long as at least one kinetochore is in lack of proper ... -
Markov Random Field Modelling of Diagenetic Facies in Carbonate Reservoirs
Larsen, Elisabeth Finserås (Master thesis, 2010)Bayesian inversion is performed on real observations to predict the diagenetic classes of a carbonate reservoir where the proportions of carbonate rock and depositional properties are known. The complete solution is the ... -
Parameter estimation in convolved categorical models
Lindberg, David (Master thesis, 2010)In this thesis, we solve the seismic inverse problem in a Bayesian setting and perform the associated model parameter estimation. The subsurface rock layers are represented by categorical variables, which depends on some ... -
Rapid Seismic Inversion for Isolated Singularities
Førland, Maren Drange (Master thesis, 2008)Thin layers can cause problems in inversion algorithms as the material parameters and the thickness of the layer are inseparable. Here a thin layer model is developed where a thin sand layer embedded in shale is considered ... -
Simulering av betingede, monotone stokastiske felt
Johnsen, Marie Fjær (Master thesis, 2007)Vi studerer en monoton prosess i én dimensjon i en Bayesiansk setting. Vi formulerer to monotone a priorimodeller: en trunkert `Gaussian Random Field'-modell og en markovkjedemodell, samt algoritmer for å simulere fra ... -
Soil classification from geotechnical data by Bayesian inversion with Markov fields
Krogstad, Ask S. (Master thesis, 2016)Soil classification from geotechnical data by Bayesian inversion with Markov fields. -
Spatio-temporal Inversion using the Selection Kalman Model
Conjard, Maxime; Omre, Karl Henning (Peer reviewed; Journal article, 2021)Data assimilation in models representing spatio-temporal phenomena poses a challenge, particularly if the spatial histogram of the variable appears with multiple modes. The traditional Kalman model is based on a Gaussian ... -
Spatio-temporal modelling of infectious diseases using the ensemble Kalman model
Spremic, Mina (Master thesis, 2020)I denne oppgaven modellerer vi spredningen av en smittsom sykdom ved å bruke Bayesiansk inversjon og forener rom-tid modellen med modellen for spredningen av smittsomme sykdommer. Variablene av interesse er hendelser og ...