| Stochastic reservoir characterization using prestack seismic data J Eidsvik, P Avseth, H Omre, T Mukerji, G Mavko Geophysics 69 (4), 978-993, 2004 | 236 | 2004 |
| Estimation and prediction in spatial models with block composite likelihoods J Eidsvik, BA Shaby, BJ Reich, M Wheeler, J Niemi Journal of Computational and Graphical Statistics 23 (2), 295-315, 2014 | 175 | 2014 |
| Value of information in the earth sciences: Integrating spatial modeling and decision analysis J Eidsvik, T Mukerji, D Bhattacharjya Cambridge University Press, 2015 | 139 | 2015 |
| Analysis of prior models for a blocky inversion of seismic AVA data U Theune, IØ Jensås, J Eidsvik Geophysics 75 (3), C25-C35, 2010 | 100 | 2010 |
| Approximate Bayesian inference for large spatial datasets using predictive process models J Eidsvik, AO Finley, S Banerjee, H Rue Computational Statistics & Data Analysis 56 (6), 1362-1380, 2012 | 91 | 2012 |
| Toward adaptive robotic sampling of phytoplankton in the coastal ocean TO Fossum, GM Fragoso, EJ Davies, JE Ullgren, R Mendes, G Johnsen, ... Science Robotics 4 (27), eaav3041, 2019 | 85 | 2019 |
| Parameter estimation in high dimensional Gaussian distributions E Aune, DP Simpson, J Eidsvik Statistics and Computing 24, 247-263, 2014 | 77 | 2014 |
| Estimation of geological attributes from a well log: An application of hidden Markov chains J Eidsvik, T Mukerji, P Switzer Mathematical Geology 36, 379-397, 2004 | 77 | 2004 |
| A class of covariate-dependent spatiotemporal covariance functions BJ Reich, J Eidsvik, M Guindani, AJ Nail, AM Schmidt The annals of applied statistics 5 (4), 2265, 2011 | 74 | 2011 |
| Approximate Bayesian inference in spatial generalized linear mixed models J Eidsvik, S Martino, H Rue Scandinavian journal of statistics 36 (1), 1-22, 2009 | 67 | 2009 |
| Information‐driven robotic sampling in the coastal ocean TO Fossum, J Eidsvik, I Ellingsen, MO Alver, GM Fragoso, G Johnsen, ... Journal of Field Robotics 35 (7), 1101-1121, 2018 | 66 | 2018 |
| The value of information in spatial decision making D Bhattacharjya, J Eidsvik, T Mukerji Mathematical Geosciences 42, 141-163, 2010 | 64 | 2010 |
| Approximate Bayesian inference in spatial GLMM with skew normal latent variables F Hosseini, J Eidsvik, M Mohammadzadeh Computational Statistics & Data Analysis 55 (4), 1791-1806, 2011 | 55 | 2011 |
| Value of information of seismic amplitude and CSEM resistivity J Eidsvik, D Bhattacharjya, T Mukerji Geophysics 73 (4), R59-R69, 2008 | 51 | 2008 |
| Bayesian networks for prospect analysis in the North Sea G Martinelli, J Eidsvik, R Hauge, MD Førland AAPG bulletin 95 (8), 1423-1442, 2011 | 50 | 2011 |
| Iterative numerical methods for sampling from high dimensional Gaussian distributions E Aune, J Eidsvik, Y Pokern Statistics and Computing 23, 501-521, 2013 | 46 | 2013 |
| Rock classification using multivariate analysis of measurement while drilling data: Towards a better sampling strategy VS Vezhapparambu, J Eidsvik, SL Ellefmo Minerals 8 (9), 384, 2018 | 43 | 2018 |
| Forming a geological model BT Bruun, E Nyrnes, J Eidsvik US Patent 8,442,770, 2013 | 41 | 2013 |
| Local and spatial joint frequency uncertainty and its application to rock mass characterisation SL Ellefmo, J Eidsvik Rock mechanics and rock engineering 42, 667-688, 2009 | 40 | 2009 |
| Building Bayesian networks from basin-modelling scenarios for improved geological decision making G Martinelli, J Eidsvik, R Sinding-Larsen, S Rekstad, T Mukerji EAGE/Geological Society of London 19 (3), 289-304, 2013 | 39 | 2013 |
Gabriele MartinelliHead of European Power Research at RefinitivVerified email at refinitiv.com
