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2020 SCERF 3rd Annual Affiliates Meeting

Event Details:

Wednesday, May 27, 2020 - Thursday, May 28, 2020

2020 SCERF 3rd Annual Affiliates Meeting

  • View & download all reports HERE

Day 1: May 27

  1. Introduction Tapan Mukerji
  2. Uncertainty quantification of facies using proportion trends from seismic data David Yin Zhen
  3. Consistent posterior spatial and non-spatial parameters: a joint Bayesian solution of spatial linear inverse problems Lijing Wang
  4. Bayesian updating of discrete realizations with hard data and well-test Céline Scheidt
  5. Designing an Intelligent Agent for solving Inverse Problems in the Geosciences Yizheng Wang
  6. Comparison of a Bayesian and non-Bayesian method for UQ using ABC and the ensemble smoother as examples Markus Zechner
  7. Gradient-based Falsification Detector and Automated Falsifying Process Junling Fang
  8. Bayesian inferred distribution of accumulations Marcelo Silka
  9. Seismic inversion for reservoir facies under geologically realistic prior uncertainty with 3D convolutional neural networks Anshuman Pradhan
  10. Uncertainty quantification using seismic data: a deep marine channel case study Tong Wang
  11. Seismic facies classification using Deep Learning Sergei Petrov
  12. Geological and physical constraints on seismic velocity model: a way to quantify subsurface properties uncertainty Josue Fonseca
  13. Geomodeling of karst morphology: motivation and initial ideas Rayan Kanfar

Day 2: May 28

  1. Uncertainty quantification of lithological variation using level set optimization Francky Fouedjio
  2. Uncertainty quantification of implicit geological structures using randomized pilot points: Application to an iron ore deposit with dense data Liang Yang
  3. Local uncertainty reduction using randomized quadratic programming Céline Scheidt
  4. Modern portfolio theory applied to mineral exploration Tyler Hall
  5. Stochastic inversion of gravity data for quantifying structural uncertainty Noah Athens
  6. Stochastic structural inversion of geophysical, well log, and tracer data at Patua Geothermal Field Ahinoam Pollack
  7. Uncertainty quantification of paleo valley structural models with uncertain geological interpretations Lijing Wang
  8. Understanding and Measuring Incised-Valley-Fill Deposit Geometry in the Central Valley Alex Miltenberger
  9. Conditional Facies Modeling Using an Improved Progressive Growing of Generative Adversarial Networks (GANs) Suihong Song
  10. Final thoughts Jef Caers

Day 3: June 4
*Subset of the above talks*

  1. Introduction Tapan Mukerji
  2. Uncertainty quantification of facies using proportion trends from seismic data David Yin Zhen
  3. Uncertainty quantification using seismic data: a deep marine channel case study Tong Wang
  4. Uncertainty quantification of paleo valley structural models with uncertain geological interpretations Lijing Wang
  5. Uncertainty quantification of lithological variation using level set optimization Francky Fouedjio
  6. Conditional Facies Modeling Using an Improved Progressive Growing of Generative Adversarial Networks (GANs) Suihong Song
  7. Stochastic structural inversion of geophysical, well log, and tracer data at Patua Geothermal Field Ahinoam Pollack
  8. Solving linear inverse problems for discrete spatial and global variables Jef Caers
  9. Towards an intelligent agent for decision making under uncertainty Jef Caers

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