Solid Earth Physics and Computational Geoscience

The Solid Earth Physics and Computational Geoscience Group at the Niels Bohr Institute is engaged in inverse theory and algorithm development for the solution of complex problems in the study of the Earth's interior. Of particular interest to us is the integration of quantitative geophysical and geological models and the related computational challenges.

Our projects span from large-scale planetary studies to Earth resource exploration, including drinking water, geothermal energy and mineral resources. All these activities share common themes that continue to fascinate us: nonlinear inverse problems, the search for feasible solutions, probabilistic Earth models, and the complex flow of information from uncertain observations, through numerical modeling, to final interpretions and decisions.





[pdf] Hansen, T.M., Vu. L.T., Mosegaard, K., and Cordua, K. S. (2018) Multiple point statistical simulation using uncertain (soft) conditional data. Copmuters and Geosciences (114), May 2018, Pages 1-10.
[pdf Madsen. R.B., and Hansen, T.M. (2018) Estimation and accounting for the modeling error in probabilistic linearized AVO inversion.  Geophysics, 2018. 83(2), 601-606. doi:10.1190/geo2017-0404.1.
[pdf] Efficient Monte Carlo sampling of inverse problems using a Neural Network based forward - applied to GPR crosshole traveltime inversion
Hansen, T.M. and Cordua, K.S. 
Geophysical Journal International, 211(2), 2017, 1524--1533.. doi:10.1093/gji/ggx380.
[pdf] Multiple-point statistical simulation for hydrogeological models: 3D training image development and conditioning strategies
Høyer, A.S, Vignoli, G., Hansen, T.M., Vu, L.T., Keefer, D.A., and Jørgensen, F. 
Hydrology and Earth System Sciences, 2017, 21(12), 6069--6089. doi:10.5194/hess-2016-567.
[pdf] On inferring the noise in probabilistic seismic AVO inversion using hierarchical Bayes.
Madsen. R.B., Zunino, A., and Hansen, T.M.
SEG Technical Program Expanded Abstracts 2017. Society of Exploration Geophysicists, 2017. 601-606. doi:10.1190/segam2017-17725822.1.
[pdf] Automatic mapping of base of aquifer – A case study from Morill Nebraska
Gulbrandsen, M.L., Ball. L., Minsley, B., and Hansen, T.M., 2017
Interpretation 5(2), p. doi:10.1190/INT-2016-0195.1
Smart Interpretation - Automatic geological interpretations based on supervised statistical models
Gulbrandsen, M.L., Cordua. K.S., Bach, T., and Hansen, T.M., 2017
Computational Geosciences 21(3), pp 427-440. doi:10.1007/s10596-017-9621-8.
[pdf] Semi-Automatic Mapping of Permafrost in the Yukon Flats - Alaska
Gulbrandsen, M.L., Minsley, B., Ball. L., and Hansen, T.M., 2016.
Geophysical Research Letters 43(13), pp 12131-12137. doi:10.1002/2016GL071334.
[pdf] Mixed-point geostatistical simulation: A combination of two- and multiple-point geostatistics
Cordua. K.S., Hansen, T.M., Gulbrandsen, M.L., Barnes, C., and Mosegaard, K., 2016
Geophysical Research Letters 43(17), pp 9030-9037.. doi:10.1002/2016GL070348.
Revealing multiple geological scenarios through unsupervised clustering of posterior realizations from reflection seismic inversion
Gulbrandsen, M.L., Cordua. K.S., Hansen, T.M., and Mosegaard, K.
in Geostatistics Valencia 2016, Editors: Gómez-Hernández, J.J., Rodrigo-Ilarri, J., Rodrigo-Clavero, M.E., Cassiraga, E., Vargas-Guzmán, J.A. (Eds.)
[pdf,www] MPSLIB: A C++ class for sequential simulation of multiple-point statistical models
Hansen, T.M., Vu. L.T., and Bach, T.
in SoftwareX, doi:10.1016/j.softx.2016.07.001.
[] Probabilistic Integration of Geo-Information
Hansen, T.M., Cordua. K.S., Zunino, A., and Mosegaard, K.
in Integrated Imaging of the Earth: Theory and Applications, pp 93-116. ISBN:978-1-118-92905-6.
[] Inverse Methods: Problem Formulation and Probabilistic Solutions
Mosegaard, K. and Hansen, T.M.
in Integrated Imaging of the Earth: Theory and Applications, pp 9-28 ISBN:978-1-118-92905-6.
[] Constitution and Structure of Earth’s Mantle: Insights from Mineral Physics and Seismology
Zunino, A., Khan, A., Cupillard, P., and Mosegaard, K.
in Integrated Imaging of the Earth: Theory and Applications, pp 219-244 ISBN:978-1-118-92905-6.
[pdf] A general probabilistic approach for inference of Gaussian model parameters from noisy data of point and volume support
Hansen, T.M., Cordua. K.S., and Mosegaard, K.
Mathematical Geosciences 47(7), pp 843-865. published online 09-2014. doi:10.1007/s11004-014-9567-5 
An example application using the SIPPI Matlab toolbox
[pdf] Monte Carlo reservoir analysis combining seismic reflection data and informed priors
Zunino, A., Mosegaard, K., Lange, K., Melnikova, Y., and Hansen, T.M.
Geophysics 80(1), pp R31–R41, 2014. doi:10.1190/geo2014-0052.1 
[pdf] History Matching through a Smooth Formulation of Multiple-Point Statistics
Melnikova,. Y., Zunino, A., Lange, K., Cordua, K. S., and Mosegaard, K.
Mathematical Geosciences, May, 2014. doi:10.1007/s11004-014-9537-y
[pdf] Improving the pattern reproducibility of multiple-point-based prior models using frequency matching
Cordua, K. S., Hansen, T.M., and Mosegaard, K.
Mathematical Geosciences, April 2014. doi:10.1007/s11004-014-9531-4
[pdf] Accounting for imperfect forward modeling in geophysical inverse problems - exemplified for cross hole tomography.
Hansen, T.M., Cordua, K. S., Jacobsen, B. J., and Mosegaard, K.
Geophsyics, 79(3) H1-H21, 2014. doi:10.1190/geo2013-0215.1
[pdf,code] SIPPI : A Matlab toolbox for Sampling the solution to Inverse Problems with complex Prior Information: Part 1 - Methodology.
Hansen, T.M., Cordua, K. S., Looms. M.C., and Mosegaard, K.
Computers & Geosciences, 52, 470-480, 2013. doi:10.1016/j.cageo.2012.09.004.
SIPPI Matlab toolbox
[pdf, code] SIPPI : A Matlab toolbox for Sampling the solution to Inverse Problems with complex Prior Information: Part 2 - Application to cross hole GPR tomography. 
T.M., Cordua, K. S., Looms. M.C., and Mosegaard, K.
Computers & Geosciences, 52, 481-492-480, 2013. doi:10.1016/j.cageo.2012.09.001.
SIPPI Matlab toolbox
Modeling and detection of oil in sea water.
Xenaki, A., Gerstoft, P., and Mosegaard, K.
Journal of the Acoustical Society of America, 134(4), pp 2790-2798, 2013. doi:10.1121/1.4818897.
[pdf] A Frequency Matching Method: Solving Inverse Problems by Use of Geologically Realistic Prior Information.
Lange, K., Frydendall, J., Cordua, K. S., Hansen, T.M., Melnikova, Y., and Mosegaard, K.
Mathematical Geosciences, 44(7), 783-803, 2012. doi:10.1007/s11004-012-9417-2.
[pdf] Monte Carlo Full Waveform Inversion of Crosshol GPR Data Using Multiple-point Geostatistical a Priori Information. Cordua, K. S., Hansen, T. M., and Mosegaard, K., 
Geophysics, 77(2), pp H19-H31, 2012. doi:10.1190/geo2011-0170.1.
[pdf ] Inverse problems with non-trivial priors - Efficient solution through Sequential Gibbs Sampling. 
Hansen, T. M., Cordua, K. S., and Mosegaard, K.
Computational Geosciences, 16(3), pp 593-611, 2012. doi:10.1007/s10596-011-9271-1 
We thank Ian Lynam for allowing us to use one of his Neojaponsime patterns.
[] Mosegaard, K., 2011. Quest for consistency, symmetry and simplicity : The Legacy of Albert Tarantola, Geophysics, 76, pp. W51-W61. doi:10.1190/geo2010-0328.1
[pdf] Mosegaard, K., 2010. Albert Tarantola Memorial, The Leading Edge (), pp 874-875.
[] Looms, M. C., Hansen, T. M., Cordua, K. S., Nielsen, L., Jensen, K. H., Binley, A., 2010. Geostatistical inference using crosshole ground-penetrating radar : Geostatistical inference using GPR, Geophysics, 75(6), pp J29-J41. doi:10.1190/1.3496001
[] Nielsen, L., Looms, M. C., Hansen, T. M., Cordua, K. S., Stemmerik, L., 2010. Estimation of Chalk Heterogeneity from Stochastic Modeling Conditioned by Crosshole GPR Traveltimes and Log Data, in Advances in Near-Surface Seismology and Ground-Penetrating Radar, eds. Miller, R., Bradford, J., and Holliger, K., Society of Exploration Geophysicists, Tulsa, Oklahoma, ISBN: 978-1-56080-224-2 , pp 379-396. 10.1190/1.9781560802259.ch23
[] Hansen, T. M., Mosegaard, K., and Schiøtt, C. R., 2010. Kriging interpolation in seismic attribute space applied to the South Arne Field, North Sea. Geophysics, 75(6), pp 31-41.doi:10.1190/1.3494280
[] Hansen, T. M., Mosegaard, K., Pedersen-Tatalovic, R., Uldall, A., and Jacobsen, N. L., 2008. Attribute guided well log interpolation. Geophysics, 73(6), pp R83-R95.doi:10.1190/1.2996302
[] Pedersen-Tatalovic, R., Uldall, A., Jacobsen, N.L., Hansen, T.M., and Mosegaard, K., 2008. Event Based Low Frequency Impedance Modelling using Well Logs and Seismic Attributes. The Leading Edge 27(5), pp 592-603.
[] Hansen, T. M., Looms, M. C., and Nielsen, L., 2008. Infering the sub-surface structural covariance model using corss bore-borehole ground penetrating radar tomography. Vadose Zone Journal, special issue on Ground Penetrating Radar in Hydrogeophysics 7(1), pp 249-262. doi:10.2136/vzj2006.0144
[] Hansen, T. M. and Mosegaard, K., 2008. VISIM : Sequential simulation for linear inverse problems, Computers and Geosciences 34(1), pp 53-76, doi:10.1016/j.cageo.2007.02.003.
If you intend to use VISIM please visit
[] Hansen T. M., Journel A. G, Tarantola A., and Mosegaard, K., 2006. Linear Inverse Gaussian Theory and Geostatistics, Geophysics 71(6), pp R101-R111. doi:10.1190/1.2345195





















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Bekkevold, Ivanka M Orozova External Postdoc +4535324213 E-mail
Dahl-Jensen, Trine Affiliate Associate Professor +4520475962 E-mail
Feng, Runhai Postdoc +4550286028 E-mail
Jóhannsson, Óli D. PhD Student   E-mail
Mosegaard, Klaus Professor +4521664566 E-mail
Youssof, Mohammad Research Assistant +4535332169 E-mail


Name Titel
Jacob Henriksen MSc. Student
Klaus Ortving Lindholmer MSc. Student
Lana Zupancic MSc. Student
Pedro Martinez MSc. Student
Peter Bagnegaard MSc. Student
Tomasso Ferrari MSc. Student