- Houston TX, US Douglas Hakkarinen - Houston TX, US Christopher R. Zaremba - Houston TX, US Everett Robinson - Houston TX, US Morgan Cowee - Houston TX, US R. James Provost - Houston TX, US
International Classification:
G06N 3/08 G06N 3/04
Abstract:
Various aspects described herein relate to a system that utilized deep learning and neural networks to estimate/predict an amount of natural resource production in a well given a set of parameters indicative of physical changes to the well. In one aspect, a virtual flow meter includes memory having computer-readable instructions stored therein and one or more processors configured to execute the computer-readable instructions to receive one or more input parameters indicative of physical changes to at least one well; apply the one or more input parameters to a trained neural network architecture; and determine one or more outputs of the trained neural network architecture, the one or more outputs corresponding to predicted fluid output of the at least one well.