arXiv · 2109.08779
Capacitance Resistance Model and Recurrent Neural Network for Well Connectivity Estimation : A Comparison Study
Abstract
In this report, two commonly used data-driven models for predicting well production under a waterflood setting: the capacitance resistance model (CRM) and recurrent neural networks (RNN) are compared. Both models are completely data-driven and are intended to learn the reservoir behavior during a water flood from historical data. This report serves as a technical guide to the python-based implementation of the CRM model available from the associated GitHub repository.
Explore related subjects
Keep this discovery
Deepthi Sen. 2021-09-17. Capacitance Resistance Model and Recurrent Neural Network for Well Connectivity Estimation : A Comparison Study. https://arxiv.org/abs/2109.08779
Cite the original work for its findings. Save a collection to share your selection of sources.