Céline Scheidt - Concepedia

Author

Céline Scheidt

Stanford University ORCID

Also Known As

C. Scheidt, C. Scheidt*, Celine SCHEIDT, Celine Scheidt, Céline Scheidt

Publications

1.5K

Citations

H-Index

Concepts

All Affiliations

Stanford University Shell (United States)Abeam Technologies (United States)

About

Céline Scheidt is an author at Stanford University specializing in engineering, uncertainty quantification, and modeling and simulation.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	15	16	1.1K
2	Management	2	2	65
3	Social Sciences	2	2	169
4	Business	1	1	22
5	Natural Sciences	1	1	53

Céline Scheidt

Publications

1.2K

Citations

H-Index

Page 1

	Year	Citations
Representing Spatial Uncertainty Using Distances and Kernels Céline Scheidt, Jef Caers Mathematical Geosciences Machine VisionEngineeringData ScienceUncertainty QuantificationPattern Recognition	2008	260
Uncertainty Quantification in Reservoir Performance Using Distances and Kernel Methods—Application to a West Africa Deepwater Turbidite Reservoir Céline Scheidt, Jef Caers SPE Journal EngineeringMachine LearningSpatial UncertaintySimulationSummary Stochastic Simulation	2009	166
Quantifying Asymmetric Parameter Interactions in Sensitivity Analysis: Application to Reservoir Modeling Darryl Fenwick, Céline Scheidt, Jef Caers Mathematical Geosciences Reservoir EngineeringEngineeringUncertainty QuantificationAsymmetric Parameter InteractionsSensitivity Analysis	2014	123
History matching and uncertainty quantification of facies models with multiple geological interpretations Hyucksoo Park, Céline Scheidt, Darryl Fenwick, Computational Geosciences Facies AnalysisEngineeringStructural GeologyGeomorphologyGeography	2013	100
DGSA: A Matlab toolbox for distance-based generalized sensitivity analysis of geoscientific computer experiments Jihoon Park, Guang Yang, Addy Satija, Computers & Geosciences Environmental MonitoringEngineeringUncertainty QuantificationCalibrationSpatial Uncertainty	2016	76
Antarctic Topographic Realizations and Geostatistical Modeling Used to Map Subglacial Lakes Emma MacKie, Dustin M. Schroeder, Jef Caers, Journal of Geophysical Research Earth Surface GlacierGeostatistical ModelingEngineeringGeomorphologyClimate Modeling	2020	69
Probabilistic falsification of prior geologic uncertainty with seismic amplitude data: Application to a turbidite reservoir case Céline Scheidt, Cheolkyun Jeong, Tapan Mukerji, Geophysics	2015	57
Prediction-Focused Subsurface Modeling: Investigating the Need for Accuracy in Flow-Based Inverse Modeling Céline Scheidt, Philippe Renard, Jef Caers Mathematical Geosciences Numerical AnalysisEngineeringFlow-based Inverse ModelingCivil EngineeringNumerical Simulation	2014	56
Assessing and visualizing uncertainty of 3D geological surfaces using level sets with stochastic motion Liang Yang, David Hyde, Ognjen Grujic, Computers & Geosciences Geometric ModelingNatural SciencesStochastic MotionGeographyGeological Surfaces	2018	53
Stochastic simulation by image quilting of process-based geological models Júlio Hoffimann, Céline Scheidt, Adrian A. S. Barfod, Computers & Geosciences Stochastic SimulationEngineeringMonte Carlo MethodNumerical SimulationSimulation	2017	46

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