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An exhaustive list of publications is available on Google Scholar. Below is a list of what I would consider the most important contributions over the last few years, as well as recent software and code based on these papers.





Multiple-point Geostatistics: Stochastic Modeling with Training Images (co-authored with Gregoire Mariethoz), 2014. Wiley-Blackwell. with accompanying website.


Modeling Uncertainty in the Earth Sciences, 2011, Wiley-Blackwell.


Petroleum Geostatistics, 2005, Society of Petroleum Engineers.



Selected Papers


Satija, A., & Caers, J., 2015. Direct forecasting of subsurface flow response from non-linear dynamic data by linear least-squares in canonical functional principal component space. Advances in Water Resources. DOI 10.1016/j.advwatres.2015.01.002


Fenwick, D., Scheidt, C.. Caers, J., 2014. Quantifying asymmetric parameter interaction in sensitivity analysis: application to reservoir modeling. Mathematical Geosciences, 46, 493-511. DOI 10.1007/s11004-014-9530-5


Mahmud, K., Mariethoz, G., Caers, J., Tahmasebi, P., Baker, A., 2014. Simulating of earth textures by conditional image quilting. Water Resources Research. DOI 10.1002/2013WR015069


Jung, A., Fenwick, D. & Caers, J, 2013. Training image-based scenario modeling of fractured reservoirs for flow uncertainty quantification. Computational Geosciences, 2013. DOI 10.1007/s10596-013-9372-0


Park, H., Celine, C., Fenwick, D., Boucher, A. and Caers, J. (2013). History matching and uncertainty quantification of facies models with multiple geological interpretation, Computational Geosciences, 2013, DOI 10.1007/s10596-013-9343-5


Cherpeau N., Caumon G., Caers J. and Lévy, B., 2012. Method for Stochastic Inverse Modeling of Fault Geometry and Connectivity Using Flow Data, Mathematical Geosciences, Volume 44, Number 2, 147-168, DOI: 10.1007/s11004-012-9389-2


Mariethoz G, Renard P, Caers, J. 2010, Bayesian inverse problem and optimization with iterative spatial resampling, Water Resources Research, vol. 46, W11530, doi:10.1029/2010WR009274, 2010.


Honarkhah, M and Caers, J, 2010, Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling, Mathematical Geosciences, 42: 487 - 517 (best paper award IAMG 09). doi:10.1007/s11004-010-9276-7


Michaels, H., Gorelick, S., Sun, T. Li, H, Boucher, A and Caers, J., 2009, Combining geologic-process models and geostatistics for conditional simulation of 3-D subsurface heterogeneity. Water Resources Research, 46, W05527, doi 10.1029/2009WR008414.


Castro, S., Caers, J, Otterlei, C., Meisingset, H., Hoye T., Gomel, P. and Zachariassen E., 2009. Incorporating 4D seismic data into reservoir models while honoring production and geological information: a case study. The Leading Edge, 28: 1498-1505. (top 10 presentations AAPG Long Beach, 2007). doi:10.1190/1.3272706


Scheidt C. and Caers J., 2008, A new method for uncertainty quantification using distances and kernel methods: application to a deepwater turbidite reservoir. SPE J, 14 (4): 680-692. doi:10.2118/118740-PA


Suzuki, S and Caers, J., 2008, A Distance-Based Prior Model Parameterization for Constraining Solutions of Spatial Inverse Problems. Mathematical Geosciences, v40, no. 4, 445-469. 10.1007/s11004-008-9154-8


Suzuki, S. Caumon, G. and Caers, J. 2008, Dynamic Data Integration Into Structural Modeling: Model Screening Approach Using a Distance-based Model Parameterization, Computational Geosciences, 105119. doi:10.1007/s10596-007-9063-9


Arpat, B. and Caers, J. 2007, Conditional simulation with patterns. Mathematical Geology, v39, no2, 177-203. (best paper award 2007). doi:10.1007/s11004-006-9075-3


Caers, J. and Hoffman, T., 2006, The probability perturbation method: a new look at Bayesian inverse modeling. Math. Geol., v 38, no 1, p 81-100. doi:10.1007/s11004-005-9005-9




I use github for code distribution, version control and collaboration, please visit https://github.com/SCRFpublic