Modeling groundwater levels in California's Central Valley by hierarchical Gaussian process and neural network regression

no code implementations • 23 Oct 2023 • Anshuman Pradhan, Kyra H. Adams, Venkat Chandrasekaran, Zhen Liu, John T. Reager, Andrew M. Stuart, Michael J. Turmon

Modeling groundwater levels continuously across California's Central Valley (CV) hydrological system is challenging due to low-quality well data which is sparsely and noisily sampled across time and space.

Gaussian Processes regression +1

Seismic Bayesian evidential learning: Estimation and uncertainty quantification of sub-resolution reservoir properties

no code implementations • 14 May 2019 • Anshuman Pradhan, Tapan Mukerji

We present a framework that enables estimation of low-dimensional sub-resolution reservoir properties directly from seismic data, without requiring the solution of a high dimensional seismic inverse problem.

Uncertainty Quantification