Céline Scheidt has worked extensively in uncertainty modeling, sensitivity analysis, geostatistics and in the use of distance-based methods in reservoir modeling. She obtained her PhD at Strasbourg University and the IFP (France) in applied mathematics, with a focus on the use of experimental design and geostatistical methods to model response surfaces.

Academic Appointments

Professional Education

  • Ph.D, ULP Strasbourg and IFP (France), Applied Mathematics (2006)
  • MS, ULP, Strasbourg (France), Mathematics for Industry – Specialty in Quality/Reliability (2003)

All Publications

  • Assessing and visualizing uncertainty of 3D geological surfaces using level sets with stochastic motion COMPUTERS & GEOSCIENCES Yang, L., Hyde, D., Grujic, O., Scheidt, C., Caers, J. 2019; 122: 54–67
  • Exploring viable geologic interpretations of gravity models using distance-based global sensitivity analysis and kernel methods GEOPHYSICS Phelps, G., Scheidt, C., Caers, J. 2018; 83 (5): G79–G92
  • Quantifying Uncertainty in Subsurface Systems PREFACE QUANTIFYING UNCERTAINTY IN SUBSURFACE SYSTEMS Scheidt, C., Li, L., Caers, J., Scheidt, C., Li, L., Caers, J. 2018; 236: VII-IX
  • Direct forecasting of reservoir performance using production data without history matching COMPUTATIONAL GEOSCIENCES Satija, A., Scheidt, C., Li, L., Caers, J. 2017; 21 (2): 315-333
  • DGSA: A Matlab toolbox for distance-based generalized sensitivity analysis of geoscientific computer experiments COMPUTERS & GEOSCIENCES Park, J., Yang, G., Satija, A., Scheidt, C., Caers, J. 2016; 97: 15-29
  • Quantifying natural delta variability using a multiple-point geostatistics prior uncertainty model JOURNAL OF GEOPHYSICAL RESEARCH-EARTH SURFACE Scheidt, C., Fernandes, A. M., Paola, C., Caers, J. 2016; 121 (10)
  • Probabilistic falsification of prior geologic uncertainty with seismic amplitude data: Application to a turbidite reservoir case GEOPHYSICS Scheidt, C., Jeong, C., Mukerji, T., Caers, J. 2015; 80 (5): M89-M100
  • Updating joint uncertainty in trend and depositional scenario for reservoir exploration and early appraisal COMPUTATIONAL GEOSCIENCES Scheidt, C., Tahmasebi, P., Pontiggia, M., Da Pra, A., Caers, J. 2015; 19 (4): 805-820
  • 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
  • Quantifying Asymmetric Parameter Interactions in Sensitivity Analysis: Application to Reservoir Modeling MATHEMATICAL GEOSCIENCES Fenwick, D., Scheidt, C., Caers, J. 2014; 46 (4): 493-511
  • 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
  • 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
  • Bootstrap confidence intervals for reservoir model selection techniques COMPUTATIONAL GEOSCIENCES Scheidt, C., Caers, J. 2010; 14 (2): 369-382
  • 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
  • Toward a reliable quantification of uncertainty on production forecasts: Adaptive experimental design IFP International Conference on Quantitative Methods for Reservoir Characterization Scheidt, C., Zabalza-Mezghani, I., Feraille, M., Collombier, D. EDITIONS TECHNIP. 2007: 207–24