Method and system for predicting non-linear well system dynamics performance in green energy generation utilizing physics and machine learning models

A well system, comprising:

• a well site;
• a physics-based modeling server that outputs modeled well dynamics behavior data for the well site based on a physics-based model;
• and
• a digital twin manager, coupled to the physics-based modeling server and the well site, that includes a processor,
• wherein the digital twin manager:
• obtains, based on a predetermined monitoring criterion, well dynamics behavior data of the well system;
• obtains modeled well dynamics behavior data for the well system using the physics-based model;
• trains a physics constrained machine learning model using one or more machine learning algorithms based on the well dynamics behavior data and the modeled well dynamics behavior data as input data;
• obtains real-time well dynamics behavior data of the well system;
• outputs predicted well dynamics behavior data using the real-time well dynamics behavior data, the physics-based model, and the trained physics constrained machine learning model;
• and
• transmits a command to the well system that adjusts a well operation based on the predicted well dynamics behavior data.

A non-transitory computer readable medium storing instructions executable by a computer processor, the instructions comprising functionality for:

• obtaining well dynamics behavior data of a well system based on a predetermined monitoring criterion;
• obtaining modeled well dynamics behavior data for the well system using a physics-based model;
• training a physics constrained machine learning model using one or more machine learning algorithms based on the well dynamics behavior data and the modeled well dynamics behavior data as input data;
• obtaining real-time well dynamics behavior data of the well system;
• outputting predicted well dynamics behavior data using the real-time well dynamics behavior data, the physics-based model, and the trained physics constrained machine learning model;
• and
• transmitting a command to the well system that adjusts a well operation based on the predicted well dynamics behavior data.