Reconstructing the ground displacement time series for injection induced geomechanical activity using LSTM autoencoders

Abstract

We use LSTM autoencoders to reconstruct the displacement time series for grid points on the top surface of a faulting due to water injection problem. The reason is that we aim to use this LSTM autoencoder based model instead of the high fidelity model in the Bayesian inference framework to estimate injection rate from displacement input.