Browsing NTNU Open by Author "Skauvold, Jacob"

Now showing items 1-6 of 6

    • 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 ...

    • 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 ...

    • Læringsressurser i grunnutdanningen i matematikk - kvalitet, tilgjengelighet og differensiering 

      Langaas, Mette; Buan, Aslak Bakke; Rønning, Frode; Tjelmeland, Håkon; Skauvold, Jacob; Thaule, Marius (Journal article, 2017)
      For studenter ved sivilingeniørutdanningen ved NTNU inngår fem grunnemner i matematikk i studieplanen. Tre av disse emnene, Matematikk 1 (første semester, 1700 studenter), Matematikk 2 (andre semester, 1400 studenter) og ...

    • Parametric spatial covariance models in the ensemble Kalman filter 

      Skauvold, Jacob; Eidsvik, Jo (Peer reviewed; Journal article, 2019)
      Several applications rely on data assimilation methods for complex spatio-temporal problems. The focus of this paper is on ensemble-based methods, where some approaches require estimation of covariances between state ...

    • Parametric Wavelet Estimation 

      Skauvold, Jacob (Master thesis, 2014)
      A method for parametric estimation of seismic wavelets from well logs and seismic data is developed. Parameters include amplitude, skewness, length and fluctuation order, and the link between parameters and wavelet properties ...

    • A revised implicit equal-weights particle filter 

      Skauvold, Jacob; Eidsvik, Jo; van Leeuwen, Peter Jan; Amezcua, Javier (Peer reviewed; Journal article, 2019)
      Particle filters are fully nonlinear data assimilation methods and as such are highly relevant. While the standard particle filter degenerates for high‐dimensional systems, recent developments have opened the way for new ...