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2018 SCERF 1st Annual Affiliates Meeting

Event Details:

Wednesday, May 2, 2018 - Thursday, May 3, 2018


Quadrus Conference Center
2400 Sand Hill Road
Menlo Park, CA 94025
United States

2018 SCERF 1st Annual Affiliates Meeting


01. Welcome and Overview Tapan Mukerji

02. Bayesian Evidential Learning Jef Caers

03. Bayesian Evidential Learning Applied to an Austrian Brown Field Markus Zechner

04. Seismic estimation of reservoir properties with Bayesian evidential learning Anshuman Pradhan

05. Updating Initial OGIP Forecasts with New Well Data Celine Scheidt

06. Chevron project on reservoir geological model updating and uncertainty quantification David Yin

07. Implicit Dynamic Uncertainty Quantification for Automation of Data Fusion & Decision Making in Mineral Resources Evaluation and Planning Jef Caers

08. Quantifying Uncertainty on 3D Geological Surfaces Using Level Sets with Stochastic Motion Liang Yang

09. Generation of Geostatistical Velocity Fields for Implicit Dynamic Surfaces with Cloud Computing Alexandre Boucher (ar2Tech)

11. Sensitivity Analysis Using Level Sets with Stochastic Motion Celine Scheidt

12. VRGE: A Virtual Reality System for the Visualization of Uncertainty Associated with 3D Geological SurfacesTyler Hall & David Hyde

14. Value of information of time-lapse seismic data by simulation-regression: comparison with rigorous Monte Carlo Geetartha Dutta 

15. Maximizing value of Information of a Horizontal Polymer Pilot Under Uncertainty Dominik Steineder (OMV)

17. Basis for uncertainty Quantification in Shale Reservoirs with Various Information Sources Alexander Bakay

18. Bayesian Evidential Learning with Joint Spatial and Global Parameter Uncertainty Jef Caers

19. Sensitivity Analysis of Reservoir Forecasts with both Global and Local Model Variables Jihoon Park

20. Joint Reduction of Local and Global Model Uncertainty with Geophysical Data: Application to Groundwater Management in Denmark Lijing Wang

21. Reservoir facies estimation from seismic data by semantic segmentation with deep convolutional networks Anshuman Pradhan

22. Simulation of Fluvial Styles with Generative Adversarial Networks and Satellite Data Erik Nesvold

23. Stochastic Fracture Network Modeling Constrained by Geo-physical Information: Some Initial Ideas Alex Miltenberger

24. Building robust priors for anisotropic full waveform velocity inversion Anshuman Pradhan

25. Uncertainty in the Estimation of Geochemical Properties of Organic Rich Mudrocks from Seismic Data Mustafa Al Ibrahim

26. Recognition of Sub-resolution Stacking Patterns from Seismic Data: Preliminary Ideas Riyad Muradov

27. Statistical Learning of Surface Processes for Creating Realistic Stratigraphic Models Julio Hoffimann

28. Characterization of Fluvial Patterns using Graph Theory Erik Nesvold

29. Can Computational Sediment Transport Models Reproduce the Natural Spectrum of River Deltas? Erik Nesvold

30. Sensitivity of Temperature Predictions in Basin-Scale Hydrothermal Models Noah Athens

31. What properties most influence the productivity of an EGS system? Ahinoam Pollack

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