Bio


Jef Caers received both an MSc (’93) in mining engineering / geophysics and a PhD (’97) in engineering from the Katholieke Universiteit Leuven, Belgium. Currently, he is Professor of Geological Sciences (since 2015) and previously Professor of Energy Resources Engineering at Stanford University, California, USA. He is also director of the Stanford Center for Reservoir Forecasting, an industrial affiliates program in reservoir modeling and geostatistics with ~20 partners from the Energy Industry. Dr. Caers’ research interests are in the area of geostatistics, spatial modeling and modeling uncertainty applied to various areas in the Earth Sciences. He was awarded the Vistelius award by the IAMG in 2001, is Editor-in-Chief of Computers and Geosciences and served as chairman for the IAMG 2009 conference. Dr. Caers has received several best paper awards and written three books entitled "Petroleum Geostatistics” (SPE) “Modeling Uncertainty in the Earth Sciences” (Wiley-Blackwell) and "Multiple-point Geostatistics: stochastic modeling with training images" is published with Wiley-Blackwell in 2014. Dr. Caers was awarded the 2014 Krumbein Medal of the IAMG for career achievement.

Academic Appointments


  • Professor, Energy Resources Engineering

Administrative Appointments


  • Professor of Geological Sciences, Stanford University (2015 - Present)
  • Professor of Energy Resources Engineering, Stanford University (2014 - 2015)
  • Associate Professor of Energy Resources Engineering, Stanford University (2006 - 2013)
  • Director, Stanford Center for Reservoir Forecasting, Stanford University (2000 - Present)
  • Assistant Professor of Petroleum Engineering, Stanford University (1999 - 2005)
  • Post-doctoral researcher, Civil Engineering, University of Calgary, Canada (1997 - 1997)
  • Post-doctoral researcher, Geological & Environmental Sciences, Stanford University (1997 - 1999)

Honors & Awards


  • Krumbein Medal, International Association for Mathematical Geosciences (2014)
  • 1st prize software plugin, Schumberger Information Services Global Forum (2010)
  • Top 10 Oral presentations, AAPG Annual Convention, Long Beach, 2007 (2007)
  • Outstanding Technical Editor Award, SPE Journal (2005)
  • Frederick E. Terman Fellowship award, Stanford University (2003)
  • Vistelius Research Award, International Association for Mathematical Geology (2001)
  • Fellow, B.A.E.F. (Belgian American Education Foundation) (1997)
  • Research Fellow, NATO (1997 – 1998)
  • Post-doctoral Fellow, National Science Foundation of Belgium (1997 – 1999)
  • Research Fellow, National Science Foundation of Belgium (1994 – 1997)

Boards, Advisory Committees, Professional Organizations


  • Editor-in-Chief, Computers & Geosciences (2011 - Present)

Professional Education


  • Ph.D., Katholieke Universiteit Leuven, Belgium, Engineering (1997)
  • M.S., Katholieke Universiteit Leuven, Belgium, Mining Engineering & Geophysics (1993)

Current Research and Scholarly Interests


Research
My research occurs at the intersection of statistical science, computer science and the geological sciences. What is the fundamental research question I want to address? I believe that from a data-scientific point of view, most geological data and modeling questions can be broadly classified as problems that are high-dimensional but have small sample size. Data are often sparse and computer experiments we run are CPU demanding, resulting in some low sample size. Yet the understanding we attempt to develop requires complex physical or geochemical models, analysis of multivariate, spatial problems over potentially large areas, require aggregation of data at various scale (in space and time) and hence are high dimensional problems. How do we formulate such problems? What are fundamental mathematical and computer science methods for analyzing such problems? How can we build predictive models for such problems? How do we integrate the various disciplines involved? Most of machine learning and statistics research currently does not take place in this setting.

In terms of machine learning, I do not prescribe to the narrow set of tools it usually encapsulates (e.g. kernel learning), but look at the wider use of the “machine” to study our type of problems, including modern fields such as computer graphics and computer vision. In understanding, modeling and forecasting in complex geological systems I believe there is a need for general methods for 1) quantifying sensitivities in such systems and their various interactions 2) learning with data acquired in the field that can be diverse in nature and different in scales of observation and 3) quantifying our lack of understanding through probabilistic models, which is essential for risk quantification & decision making.

Specific areas I am interested in:

Oil/Gas. The subsurface characterization, both depositional & structural of reservoir systems from seismic, well and production data for forecasting requires an integrated set of approaches involving both physical and statistical modeling. I work on comprehensive approaches to forecasting recovery of fluids from the subsurface.

Groundwater/hydrology. The characterization of groundwater systems evidently has many analogies with petroleum reservoirs. My research will focuses on the aquifer to basin scale. I am interested in saltwater intrusion problems, quantitative characterization of karst systems and predicting with reactive transport models.

Minerals. The exploration/ exploitation of minerals deposits will be increasing in importance considering the increasing importance of battery technologies. This would also mean that there will be an increased interest in developing geostatistical methods for the purpose of mineral potential mapping as well as ore body evaluation (economic geology). I am interested in the multi-variate & compositional nature of this problem (geochemistry) as well as scaling issues.

2014-15 Courses


All Publications


  • Prediction-Focused Subsurface Modeling: Investigating the Need for Accuracy in Flow-Based Inverse Modeling MATHEMATICAL GEOSCIENCES Scheidt, C., Renard, P., Caers, J. 2015; 47 (2): 173-191
  • MS-CCSIM: Accelerating pattern-based geostatistical simulation of categorical variables using a multi-scale search in Fourier space COMPUTERS & GEOSCIENCES Tahmasebi, P., Sahimi, M., Caers, J. 2014; 67: 75-88
  • Quantifying Asymmetric Parameter Interactions in Sensitivity Analysis: Application to Reservoir Modeling MATHEMATICAL GEOSCIENCES Fenwick, D., Scheidt, C., Caers, J. 2014; 46 (4): 493-511
  • Simulation of Earth textures by conditional image quilting WATER RESOURCES RESEARCH Mahmud, K., Mariethoz, G., Caers, J., Tahmasebi, P., Baker, A. 2014; 50 (4): 3088-3107
  • Comparing Training-Image Based Algorithms Using an Analysis of Distance MATHEMATICAL GEOSCIENCES Tan, X., Tahmasebi, P., Caers, J. 2014; 46 (2): 149-169
  • Multiple-point geostatistics: stochastic modeling with training images Mariethoz, G., Caers, J. Wiley-Blackwell. 2014
  • SGEMS-UQ: An uncertainty quantification toolkit for SGEMS COMPUTERS & GEOSCIENCES Li, L., Boucher, A., Caers, J. 2014; 62: 12-24
  • (submitted) Uncertainty Quantification in Inverse Problems: Model-Based versus Prediction-Focused Inversion Mathematical Geosciences Scheidt, C., Renard, P., Caers, J. 2014
  • Training image-based scenario modeling of fractured reservoirs for flow uncertainty quantification COMPUTATIONAL GEOSCIENCES Jung, A., Fenwick, D. H., Caers, J. 2013; 17 (6): 1015-1031
  • Conditioning Surface-Based Geological Models to Well and Thickness Data MATHEMATICAL GEOSCIENCES Bertoncello, A., Sun, T., Li, H., Mariethoz, G., Caers, J. 2013; 45 (7): 873-893
  • History matching and uncertainty quantification of facies models with multiple geological interpretations COMPUTATIONAL GEOSCIENCES Park, H., Scheidt, C., Fenwick, D., Boucher, A., Caers, J. 2013; 17 (4): 609-621
  • Image transforms for determining fit-for-purpose complexity of geostatistical models in flow modeling COMPUTATIONAL GEOSCIENCES Aydin, O., Caers, J. 2013; 17 (2): 417-429
  • A special issue on benchmark problems, datasets and methodologies for the computational geosciences COMPUTERS & GEOSCIENCES Caers, J. 2013; 50: 1-3
  • Fast multiple point geostatistical simulation using a multi-scale approach IAMG 2013, Madrid, Sept 2-6, 2013 Pejman, T., Caers, J. 2013
  • Modeling Spatial and Structural Uncertainty in the Subsurface Computational Challenges in the Geosciences Institute for Mathematics and its Applications, The IMA Volumes in Mathematics and its Applications Gerritsen, M., Caers, J. 2013; 156: 143-167
  • Simulation of Earth textures by Conditional Image Quilting Water Resources Research Mahmud , K., Tahmasebi, P., Mariethoz, G., Caers, J., Baker, A. 2013
  • Comparing training-image based algorithms using an analysis of distance Mathematical Geosciences Tan, X., Tahmasebi, P., Caers, J. 2013
  • Assessing the probability of training image-based geological scenarios using geophysical data IAMG 2013 Hermans, T., Caers, J., Nguyen, F. 2013
  • Possibility as a complement to probability in quantifying geological scenario uncertainty: a deep-water reservoir case study IAMG 2013 Li, L., Caers, J. 2013
  • Updating of uncertainty in fractured reservoirs driven by geological scenarios IAMG 2013 Jung, A., Fenwick, D., Caers, J. 2013
  • Learning Needed Complexity in Structural Modeling Using Procrustes Analysis IAMG 2013 Aydin, O., Caers, J. 2013
  • A distance-based generalized sensitivity analysis for energy resources modeling IAMG 2013 Scheidt, C., Fenwick, D., Caers, J. 2013
  • SGEMS-UQ: An Uncertainty Quantification Toolkit for SGEMS Computers & Geosciences Li, L., Boucher, A., Caers, J. 2013
  • A quantitative comparison of multiple-point algorithms using an analysis of distance method IAMG 2013 Tan, X., Tahmasebi, P., Caers, J. 2013
  • Modeling Geological Scenario Uncertainty from Seismic Data using Pattern Similarity IAMG 2013 Jeong, C., Scheidt, C., Caers, J., Mukerji, T. 2013
  • Use of Tank Experiment Data In Surface-based Modeling IAMG 2013 Xu, S., Jung, A., Mukerji, T., Caers, J. 2013
  • Updating uncertainty in the conceptual geological representation of fractured reservoirs using production data 75th EAGE Conference & Exhibition Jung, A., Fenwick, D., Caers, J. 2013
  • Training-image based scenario modeling of fractured reservoir for flow uncertainty quantification Computational Geosciences Jung, A., Fenwick, D., Caers, J. 2013
  • Probability perturbation applied to the use of groundwater flow models in HydroGeoSphere 3rd International HydroGeoSphere User Conference Hermans, T., Scheidt, C., Caers, J., Nguyen, F. 2013
  • Direct Pattern-Based Simulation of Non-stationary Geostatistical Models MATHEMATICAL GEOSCIENCES Honarkhah, M., Caers, J. 2012; 44 (6): 651-672
  • Method for Stochastic Inverse Modeling of Fault Geometry and Connectivity Using Flow Data MATHEMATICAL GEOSCIENCES Cherpeau, N., Caumon, G., Caers, J., Levy, B. 2012; 44 (2): 147-168
  • Direct non-stationary multiple-point modeling by distance-based pattern simulation 9th International Geostatistics Congress Honarkhah, M., Caers, J. 2012
  • History matching under uncertain geological scenario 9th International Geostatistics Congress Park, H., Caers, J. 2012
  • Transformation spaces for determining spatial model complexity 9th International Geostatistics Congres Aydin, O., Caers, J. 2012
  • Data inversion under geological scenario uncertainty SEG Technical Program Caers, J. 2012: 1-2
  • On internal consistency, conditioning and models of uncertainty 9th International Geostatistics Congress Caers, J. 2012
  • Conditioning Facies Simulations with Connectivity Data MATHEMATICAL GEOSCIENCES Renard, P., Straubhaar, J., Caers, J., Mariethoz, G. 2011; 43 (8): 879-903
  • A Methodology for Establishing a Data Reliability Measure for Value of Spatial Information Problems MATHEMATICAL GEOSCIENCES Trainor-Guitton, W. J., Caers, J. K., Mukerji, T. 2011; 43 (8): 929-949
  • A multiscale method for subsurface inverse modeling: Single-phase transient flow ADVANCES IN WATER RESOURCES Fu, J., Caers, J., Tchelepi, H. A. 2011; 34 (8): 967-979
  • A multi-resolution workflow to generate high-resolution models constrained to dynamic data COMPUTATIONAL GEOSCIENCES Scheidt, C., Caers, J., Chen, Y., Durlofsky, L. J. 2011; 15 (3): 545-563
  • Geological modelling and history matching of multi-scale flow barriers in channelized reservoirs: methodology and application PETROLEUM GEOSCIENCE Li, H., Caers, J. 2011; 17 (1): 17-34
  • Modeling Uncertainty in the Earth Sciences Caers, J. Wiley-Blackwell. 2011
  • Topological uncertainties in structural geology and assimilation of dynamic data: parametrization and sampling Water Resources Research Cherpeau, N., Caumon, G., Caers, J., Levy, B. 2011
  • Distance-based sampling of posterior distributions in spatial inverse problems IAMG 2011 Caers, J., Park, K., Scheidt, C. 2011
  • Integration of engineering and geological uncertainty for reservoir performance prediction using a distance-based approach AAPG Memoir on Modeling Geological Uncertainty Caers, J., Scheidt, C. 2011: 191–202.
  • Assessing the impact of fault connectivity uncertainty in reservoir studies using explicit discretization SPE Reservoir Characterisation and Simulation Conference and Exhibition Cherpeau, N., Caumon, G., Caers, J., Lévy, B. 2011
  • Bayesian inverse problem and optimization with iterative spatial resampling WATER RESOURCES RESEARCH Mariethoz, G., Renard, P., Caers, J. 2010; 46
  • A flow-based pattern recognition algorithm for rapid quantification of geologic uncertainty COMPUTATIONAL GEOSCIENCES Alpak, F. O., Barton, M. D., Caers, J. 2010; 14 (4): 603-621
  • Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling Honarkhah, M., Caers, J. SPRINGER HEIDELBERG. 2010: 487-517
  • Special Issue on Computational Methods for the Earth, Energy and Environment-IAMG 2009 MATHEMATICAL GEOSCIENCES Caers, J. 2010; 42 (5): 453-455
  • Laudatio Guillaume Caumon, Vistelius Award 2009 MATHEMATICAL GEOSCIENCES Caers, J. 2010; 42 (5): 595-596
  • A multiscale adjoint method to compute sensitivity coefficients for flow in heterogeneous porous media ADVANCES IN WATER RESOURCES Fu, J., Tchelepi, H. A., Caers, J. 2010; 33 (6): 698-709
  • Combining geologic-process models and geostatistics for conditional simulation of 3-D subsurface heterogeneity WATER RESOURCES RESEARCH Michael, H. A., Li, H., Boucher, A., Sun, T., Caers, J., Gorelick, S. M. 2010; 46
  • Bootstrap confidence intervals for reservoir model selection techniques COMPUTATIONAL GEOSCIENCES Scheidt, C., Caers, J. 2010; 14 (2): 369-382
  • Sampling Multiple Non-Gaussian Model Realizations Constrained to Static and Highly Nonlinear Dynamic Data Using distance-based Techniques IAMG 2010 Annual Conference Park, K., Caers, J. 2010
  • Value of Information Methodology for Dynamic, Spatial Earth Problems Water Resources Research Trainor-Guitton, W. J., Caers, J. K., Mukerji, T., Knight, R. 2010
  • Modeling Uncertainty of Complex Earth Systems in Metric Space Handbook of Geomathematics Caers, J., Scheidt, C., Park, K. Springer. 2010: 865-889
  • Uncertainty Quantification in Reservoir Performance Using Distances and Kernel Methods-Application to a West Africa Deepwater Turbidite Reservoir SPE JOURNAL Scheidt, C., Caers, J. 2009; 14 (4): 680-692
  • Representing Spatial Uncertainty Using Distances and Kernels MATHEMATICAL GEOSCIENCES Scheidt, C., Caers, J. 2009; 41 (4): 397-419
  • Incorporating 4D seismic data into reservoir models while honoring production and geologic data The Leading Edge Castro, S., Otterlei, C., Meisinget, H., Hoye, T., Gomel, P., Zachariassen, E., Caers, J. 2009; 28: 1498-1505

    View details for DOI 10.1190/1.3272706

  • Solving spatial inverse problems using the probability perturbation method: An S-GEMS implementation COMPUTERS & GEOSCIENCES Li, T., Caers, J. 2008; 34 (9): 1127-1141
  • Identifying discrete geologic structures that produce anomalous hydraulic response: An inverse modeling approach WATER RESOURCES RESEARCH Ronayne, M. J., Gorelick, S. M., Caers, J. 2008; 44 (8)
  • A distance-based prior model parameterization for constraining solutions of spatial inverse problems MATHEMATICAL GEOSCIENCES Suzuki, S., Caers, J. 2008; 40 (4): 445-469
  • Dynamic data integration for structural modeling: model screening approach using a distance-based model parameterization COMPUTATIONAL GEOSCIENCES Suzuki, S., Caumon, G., Caers, J. 2008; 12 (1): 105-119
  • Distance-based Representation of Reservoir Uncertainty: the Metric EnKF Proceedings of the 11th European Conference on the Mathematics of Oil Recover (ECMOR XI) Caers, J., Park, K. 2008: 8p.
  • Conditioning facies simulations with connectivity data 8th International Geostatistical Congress, Santiago, Chile, Dec. 1-5, 2008 Renard, P. H., Caers, J. 2008
  • Ensemble Kalman Filtering in Distance-based Kernel Space EnKF Workshop Park, K., Schiedt , C., Caers, J. 2008
  • Assessing the Value of Information of Geophysical Data for Groundwater Management AGU Fall Meeting Trainor, W., Caers, J., Mukerji, T., Auken, E., Knight, R. 2008
  • Simultaneous Conditioning of Multiple Non-Gaussian Geostatistical Models to Highly Nonlinear Data Using Distances in Kernel Space 8th International Geostatistical Congress Park, K., Schiedt, C., Caers, J. 2008
  • Streamline Assisted History Matching of Naturally Fractured Reservoirs Using the Probability Perturbation Method 8th International Geostatistical Congress Fadaei, S., Thiele, M., Caers, J. 2008
  • Distance-based random field models and their applications 8th International Geostatistical Congress Caers, J. 2008
  • Comparison of Probabilistic and Forward Modeling Workflow Approaches for Integrating 4D Seismic into Reservoir Models: Application to a North Sea Reservoir 70th EAGE Conference & Exhibition Castro, S., Caers, J., Meisingset, H., Høye, T., Gomel, P., Zachariassen, E. 2008
  • Hybridization of the probability perturbation method with gradient information COMPUTATIONAL GEOSCIENCES Johansen, K., Caers, J., Suzuki, S. 2007; 11 (4): 319-331
  • History matching by jointly perturbing local facies proportions and their spatial distribution: Application to a North Sea reservoir JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING Hoffman, B. T., Caers, J. 2007; 57 (3-4): 257-272
  • History matching of naturally fractured reservoirs using elastic stress simulation and probability perturbation method Suzuki, S., Daly, C., Caers, J., Mueller, D. SOC PETROLEUM ENG. 2007: 118-129
  • Conditional simulation with patterns MATHEMATICAL GEOLOGY Arpat, G. B., Caers, J. 2007; 39 (2): 177-203
  • Comparing the gradual deformation with the probability perturbation method for solving inverse problems MATHEMATICAL GEOLOGY Caers, J. 2007; 39 (1): 27-52
  • Hierarchical modeling of multi-scale flow barriers in channelized reservoirs PROCEEDINGS OF THE IAMG '07: GEOMATHEMATICS AND GIS ANALYSIS OF RESOURCES, ENVIRONMENT AND HAZARDS Li, H., Caers, J. 2007: 381-385
  • Solving spatial inverse problems using the probability perturbation method: an S-GEMS implementation PROCEEDINGS OF THE IAMG '07: GEOMATHEMATICS AND GIS ANALYSIS OF RESOURCES, ENVIRONMENT AND HAZARDS Li, T., Caers, J. 2007: 727-729
  • A geostatistical approach to integrating data from multiple and diverse sources: An application to the integration of well data, geological information, 3d/4d geophysical and reservoir-dynamics data in a north-sea reservoir Subsurface Hydrology: Data Integration for Properties and Processes Caers, J., Castro, S. 2007; 171: 61-71
  • Hybridization of the probability perturbation method with gradient information EAGE Petroleum Geostatistics conference Johansen, K., Caers, J. 2007
  • Modeling, Upscaling and History Matching Thin, Irregularly-Shaped Flow Barriers; A Comprehensive Approach for Predicting Reservoir Connectivity 26th Annual GCSSEPM Foundation Meeting Stright, L., Caers, J., Li, H., Van der Vlugt, F., Pirmez, C., Barton, M. 2007
  • History matching in low-dimensional connectivity vector space EAGE Petroleum Geostatistics conference Park , K., Caers, J. 2007
  • Multiple-Point Geostatistics and Near-Surface Geophysics for Modeling Heterogeneity in a Coastal Aquifer AGU Fall Meeting Supplement Trainor, W. J., Knight, R. J., Caers, J. K. 2007
  • Stochastic simulation with patterns Mathematical Geology Arpat, B., Caers, J. 2007; 39 (2): 177-203
  • A Workflow for Modeling Multi-scale Flow Barriers in Deep Water Turbidite Reservoirs AAPG Annual meeting Hongmei, L., Caers, J. 2007
  • Hierarchic Modeling and History Matching of Multiscale Flow Barriers in Channelized Reservoirs SPE Annual Technical Conference and Exhibition Li, H., Caers, J. 2007
  • History matching of reservoir structure subject to prior geological and geophysical constraints EAGE Petroleum Geostatistics Conference Suzuki, S., Carmon, G., Caers, J. 2007
  • A practical data-integration approach to history matching: Application to a deepwater reservoir Hoffman, B. T., Caers, J. K., Wen, X., Strebelle, S. SOC PETROLEUM ENG. 2006: 464-479
  • Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations ADVANCES IN WATER RESOURCES Feyen, L., Caers, J. 2006; 29 (6): 912-929
  • Coupled Geological Modeling and History Matching of Fine-Scale Curvilinear Flow Barriers EAGE 10th European Conference on the Mathematics of Oil Recovery Stright, L., Caers, J., Li, H., Van der Vlugt, F., Pirmez, C., , C., Barton, M., M. 2006
  • Improved modeling of 4D seismic response using flow-based downscaling of coarse grid saturations ECMOR X Castro, S., Caers, J., Durlofsky, L. 2006
  • A probabilistic approach to integration of well log, geological information, 3D/4D seismic and production data ECMOR X Castro, S., Caers, J. 2006
  • A Probabilistic Integration of Well Log, Geological Information, 3D/4D Seismic, and Production Data: Application to the Oseberg Field SPE Annual Meeting Castro, S., Caers, J., Otterlei, C., Høye, T., Andersen, T., Gomel, P. 2006
  • Probabilistic integration of geological information, seismic and production data The Leading Edge Caers, J., Hoffman, B. T., Strebelle, S., Wen, X. 2006; 25: 240-244
  • History Matching with an Uncertain Geological Scenario SPE Annual Technical Conference and Exhibition Suzuki, S., Caers, J. 2006
  • The probability perturbation method: a new look at Bayesian inverse modeling Mathematical Geology Caers, J., Hoffman, T. 2006; 38: 81-100
  • Preserving Fine-Scale, Irregularly-Shaped Geological Features in Reservoir Flow Models Using Edge Properties American Association of Petroleum Geologists Annual Convention Stright, L., Caers, J. 2006
  • Discrete Space Optimization Method for History Matching under Uncertain Geological Scenario 10th European Conference on the Mathematics of Oil Recovery (ECMOR X) Suzuki, S., Caers, J. 2006
  • A parallel, multiscale approach to reservoir modeling COMPUTATIONAL GEOSCIENCES Tureyen, O. I., Caers, J. 2005; 9 (2-3): 75-98
  • Regional probability perturbations for history matching JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING Hoffman, B. T., Caers, J. 2005; 46 (1-2): 53-71
  • A direct sequential simulation approach to streamline-based history matching GEOSTATISTICS BANFF 2004, VOLS 1 AND 2 Caers, J., Gross, H., Kovscek, A. R. 2005; 14: 1077-1086
  • A combined geostatistical and source model to predict super-permeability from flowmeter data: application to the Ghawar field Quantitative Geology and Geostatistics Volume Voelker, J., Caers, J. A. 2005; 14: 591-600
  • A new multiple-grid method for multiple-scale stochastic Simulation with Patterns GIS AND SPATIAL ANALYSIS, VOL 1AND 2 Li, H. M., Arpat, B. G., Caers, J. 2005: 633-638
  • History matching under geological control: Application to a North Sea reservoir GEOSTATISTICS BANFF 2004, VOLS 1 AND 2 Hoffman, B. T., Caers, J. 2005; 14: 1067-1076
  • Data conditioning with the probability perturbation method Quantitative Geology and Geostatistics Arpat, B. G., Caers, J. A. edited by Leuangthong, O., Deutsch, C. Springer, Dordrecht. 2005: 255-264
  • Petroleum Geostatistics Caers, J. Society of Petroleum Engineers. 2005
  • History Matching of Naturally Fractured Reservoirs Using Elastic Stress Simulation and Probability Perturbation Method SPE ATCE Dallas, TX Suzuki, S., Daly, C., Mueller, D., Caers, J. 2005
  • Reconciling Prior Geologic Information With Production Data Using Streamlines: Application to a Giant Middle-Eastern Oil Field SPE ATCE Fenwick, D., Thiele, M., Agil, M., Hussain, A., Humam, F., Caers, J. 2005
  • A new multiple-grid method for multiple-scale stochastic simulation with patterns 2005 Annual conference of the International Association for Mathematical Geology Hongmei, L., Arpat, B. G., Caers, J. 2005
  • Geologically Consistent History Matching of a Deepwater Turbidite Reservoir SPE ATCE Hoffman, T. B., Strebelle, S., Wen, X., Caers, J. 2005
  • Flow-based downscaling of saturations for modeling 4D seismic data 75th SEG meeting Castro, S., Caers, J. 2005
  • A multiple-scale, pattern-based approach to sequential simulation GEOSTATISTICS BANFF 2004, VOLS 1 AND 2 Arpat, G. B., Caers, J. 2005; 14: 255-264
  • Multiple-point geostatistics: a powerful tool to improve groundwater flow and transport predictions in multi-modal formations GEOSTATISTICS FOR ENVIRONMENTAL APPLICATIONS, PROCEEDINGS Feyen, L., Caers, J. 2005: 197-207
  • Automatic geobody detection from seismic data using minimum message length clustering COMPUTERS & GEOSCIENCES Xu, Y., Caers, J., Arroyo-Garcia, C. 2004; 30 (7): 741-751
  • History Matching with the Regional Probability Perturbation Method in Applications to a North Sea Reservoir ECMOR IX Hoffman, B. T., Caers, J. 2004
  • Geostatistical history matching using the regional probability perturbation method Society of Petroleum Engineers Annual Conference and Technical Exhibition Hoffman, B. T., Caers, J. 2004
  • Streamline-Based History Matching Using Geostatistical Constraints: Application to a Giant, Mature Carbonate Reservoir SPE ATCE Gross, H., Thiele, M. R., Alexa, M., Caers, J. K., Kovscek, A. R. 2004
  • The probability perturbation method: an alternative to traditional Bayesian approaches for solving inverse problems ECMOR IX Caers, J. 2004
  • Assessment of Global Uncertainty for Early Appraisal of Hydrocarbon Fields Society of Petroleum Engineers ATCE Caumon, G., Strebelle, S. B., Caers, J. K., Journel, A. G. 2004
  • Reservoir Characterization Using Multiple-Scale Geological Patterns ECMOR IX Arpat, B. G., Caers, J. 2004
  • Stochastic estimation of facies using ground penetrating radar data Moysey, S., Caers, J., Knight, R., Allen-King, R. M. SPRINGER. 2003: 306-318
  • Modeling of a deepwater turbidite reservoir conditional to seismic data using principal component analysis and multiple-point geostatistics Strebelle, S., Payrazyan, K., Caers, J. SOC PETROLEUM ENG. 2003: 227-235
  • History matching under training-image-based geological model constraints SPE JOURNAL Caers, J. 2003; 8 (3): 218-226
  • Efficient gradual deformation using a streamline-based proxy method Caers, J. ELSEVIER SCIENCE BV. 2003: 57-83
  • The construction of stochastic facies-based models conditioned to ground penetrating radar images CALIBRATION AND RELIABILITY IN GROUNDWATER MODELLING: A FEW STEPS CLOSER TO REALITY Moysey, S., Knight, R., Allen-King, R. M., Caers, J. 2003: 395-401
  • From pattern recognition to pattern reproduction Developments in Petroleum Science Caers, J. Elsevier. 2003: 97-115
  • Combining geological information with seismic and production data Developments in Petroleum Science Caers,, J., Srinivasan, S. Elsevier. 2003: 499-525
  • Feature-based probabilistic interpretation of geobodies from seismic Stochastic Modeling II Caers, J., Arpat, G. B., Arroyo-Garcia, C., Coburn, C. T. American Association of Petroleum Geologist. 2003
  • A method for static-based upgridding ECMOR VII, European Conference on Mathematics of Oil Recovery Younis, R., Caers, J. 2003
  • Sequential Simulation under local non-linear constraints: Application to history matching Annual conference of the Internation Association for Mathematical Geology Hoffman, B. T., Caers, J. 2003
  • A geostatistical method for characterizing superpermeability from flowmeter data: Application to the Ghawar field Society of Petroleum Engineers Annual Conference and Technical Exhibition Voelker, J. J., Liu, J., Caers, J. 2003
  • Stochastic integration of seismic and geological scenarios: a submarine channgel saga The Leading Edge Caers, J., Strebelle, S., Payrazyan, K. 2003: 192-196
  • A two level optimization method for integrating production data on non-uniform grids SPE Annual Conference and Technical Exhibition Tureyen, O. I., Caers, J. 2003
  • History matching under a training image-based geological model constraints SPE Journal Caers, J. 2003: 218-226
  • G(S)TL: the geostatistical template library in C++ COMPUTERS & GEOSCIENCES Remy, N., Shtuka, A., Levy, B., Caers, J. 2002; 28 (8): 971-979
  • A geostatistical approach to streamline-based history matching SPE JOURNAL Caers, J., Krishnan, S., Wang, Y. D., Kovscek, A. R. 2002; 7 (3): 250-266
  • Integrating rock physics, seismic amplitudes, and geological models JOURNAL OF PETROLEUM TECHNOLOGY Caers, J., Avseth, P., Mukerji, T. 2002; 54 (6): 43-43
  • Modeling conditional distributions of facies from seismic using neural nets MATHEMATICAL GEOLOGY Caers, J., Ma, X. L. 2002; 34 (2): 143-167
  • Geostatistical history matching under a training image-based geological model constraints SPE Annual Conference and Technical Exhibition Caers, J. 2002
  • A geostatical approach to history matching flow and pressure data on non-uniform grids ECMOR VIII, European Conference on Mathematics of Oil Recovery Tureyen, I., Caers, J. 2002
  • Feature-based geostatistics: an application to a submarine channel reservoir SPE Annual Conference and Technical Exhibition APR, B., Caers, J., Strebelle, S. 2002
  • Modeling of a deepwater turbidite reservoir conditional to seismic data using multiple-point geostatistics SPE Annual Technical Conference and Exhibition Strebelle, S., Payrazyan, K., Caers, J. 2002
  • Geostatistical reservoir modelling using statistical pattern recognition JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING Caers, J. 2001; 29 (3-4): 177-188
  • Automatic histogram and variogram reproduction in simulated annealing simulation MATHEMATICAL GEOLOGY Caers, J. 2001; 33 (2): 167-190
  • Geostatistical integration of rock physics, seismic amplitudes and geological models in North-Sea turbidite systems The Leading Edge Caers, J., Avseth, P., Mukerji, T. 2001; 20: 308-312
  • GsTL: a geostatistical template library in C++ Proceedings of the IAMG Annual Conference of the International Association for Mathematical Geology Remy, N., Shtuka, A., Levy, B., Caers, J. 2001: 971-979
  • Data integration with multiple-point geostatistics Third IMA Conference on Modeling Permeable Rocks Strebelle, S., Journel, A. G., Caers, J. 2001
  • A fast Markov chain Monte Carlo simulation method for conditioning reservoir models to dynamic data 7th European Conference on Mathematics of Oil Recovery, EAGE Caers, J., Srinivasan, S. 2001
  • Feature-based calibration of an automated seismic interpretation tool from human expert knowledge Annual Meeting, Stanford Center for Reservoir Forecasting Arpat, G. B., Caers, J. 2001
  • Calibrating an automated seismic interpretation tools from human expert knowledge Third IMA Conference on Modeling Permeable Rocks Caers, J., Haas, A. 2001
  • Characterization of West-Africa Submarine channel reservoirs: a neural network-based approach to integration of seismic data SPE Annual Conference and Technical Exhibition Arpat, B. G., Caers, J., Haas, A. 2001
  • Geostatistical quantification of geological information for a fluvial-type North Sea reservoir Caers, J. K., Srinivasan, S., Journel, A. G. SOC PETROLEUM ENG. 2000: 457-467
  • Adding local accuracy to direct sequential simulation MATHEMATICAL GEOLOGY Caers, J. 2000; 32 (7): 815-850
  • Geostatistical modeling of an offshore diamont deposit 6th International Geostatistics Congress Caers, J., Rombouts, L. 2000
  • Statistics for modeling heavy tailed distributions in geology: Part II. Applications MATHEMATICAL GEOLOGY Caers, J., Beirlant, J., Maes, M. A. 1999; 31 (4): 411-434
  • Statistics for modeling heavy tailed distributions in geology: Part I. Methodology MATHEMATICAL GEOLOGY Caers, J., Beirlant, J., Maes, M. A. 1999; 31 (4): 391-410
  • Conditioning reservoir models to dynamic data - A forward modeling perspective SPE Annual Conference and Technical Exhibition Srinivasan, S., Caers, J. 1999
  • Statistics for Modelling Heavy Tailed Distributions in Geology, Part II: Applications Mathematical Geology Caers, J., Beirlant, J., Maes, M. A. 1999; 31: 411-434
  • Geostatistical modeling of offshore diamond deposits 6th International Geostatistics Congress Caers, J. 1999
  • Statistics for Modelling Heavy Tailed Distributions in Geology, Part I: Methodology Mathematical Geology Caers, J., Beirlant, J., Maes, M. A. 1999; 31: 390-410
  • Nonparametric tail estimation using a double bootstrap method COMPUTATIONAL STATISTICS & DATA ANALYSIS Caers, J., Van Dyck, J. 1998; 29 (2): 191-211
  • Bootstrap confidence intervals for tail indices COMPUTATIONAL STATISTICS & DATA ANALYSIS Caers, J., Beirlant, J., Vynckier, P. 1998; 26 (3): 259-277
  • Identifying tails, bounds and end-points of random variables STRUCTURAL SAFETY Caers, J., Maes, M. A. 1998; 20 (1): 1-23
  • A Neural Network Approach to Stochastic Simulation GOCAD ENSG Conference on 3D Modelling of Natural Objects Caers, J., Journel, A. G. 1998
  • Global Valuation of Primary Diamond Deposits 27th Symposium on the Application of Computer Methods and Operations Research in the Mineral Industry Caers, J., Maes, M. A. 1998
  • Stochastic Reservoir Simulation Using Neural Networks Trained on Outcrop Data SPE Technical Exhibition and Annual Conference Caers, J., Journel, A. G. 1998: 321-337
  • Tail Estimation of Bounded Random Variables IFIP Conference on Optimization and Reliability of Structural Systems Maes, M. A., Caers, J. 1998
  • Assessing the Quality of Diamonds Mineral Resources Engineering Caers, J., Vervoort, A. 1997; 5: 155-177
  • Petrography and X-ray computerized tomography applied as an integral part of a rock mechanics investigation of discontinuities TRANSACTIONS OF THE INSTITUTION OF MINING AND METALLURGY SECTION B-APPLIED EARTH SCIENCE Caers, J., Swennen, R., Vervoort, A. 1997; 106: B38-B45
  • Non-conditional and conditional simulation of a spatial point process GEOSTATISTICS WOLLONGONG '96, VOLS 1 AND 2 Caers, J., Gelders, J., Vervoort, A., Rombouts, L. 1997; 8 (1-2): 270-281
  • Valuation of primary diamond deposits by extreme value statistics ECONOMIC GEOLOGY AND THE BULLETIN OF THE SOCIETY OF ECONOMIC GEOLOGISTS Caers, J., Rombouts, L. 1996; 91 (5): 841-854
  • Extreme value analysis of diamond-size distributions MATHEMATICAL GEOLOGY Caers, J., Vynckier, P., Beirlant, J., Rombouts, L. 1996; 28 (1): 25-43
  • A numerical maximum likelihood method for estimating the mean of a compound lognormal distribution 26TH PROCEEDINGS OF THE APPLICATIONS OF COMPUTERS AND OPERATIONS RESEARCH IN THE MINERAL INDUSTRY Caers, J., Vervoort, A. 1996: 27-32