Method and system for predicting real plant dynamics performance in green energy generation utilizing physics and artificial neural network models

A well system, comprising:

• a well site;
• a physics-based model server that outputs modeled 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, dynamics behavior data of the well site, where the dynamics behavior data includes a plurality of measurements comprising:
• an incomplete measurement that is missing data for a time interval;
• and
• a complete measurement that includes data for the time interval;
• obtains modeled dynamics behavior data for the well site using a physics-based model;
• trains a physics constrained machine learning model using one or more machine learning algorithms based on the dynamics behavior data and the modeled dynamics behavior data as inputs;
• updates dynamics behavior data of the well site based on the physics-based model and the physics constrained machine learning model;
• outputs updated dynamics behavior data for the well site;
• and
• transmits a command to the well system that adjusts a well operation based on the updated dynamics behavior data,
• wherein the updated dynamics behavior data completes the missing data in the incomplete measurement for the time interval.

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

• obtaining dynamics behavior data of a well system based on a predetermined monitoring criterion, where the dynamics behavior data includes a plurality of measurements comprising:
• an incomplete measurement that is missing data for a time interval;
• and
• a complete measurement that includes data for the time interval;
• obtaining modeled dynamics behavior data for the well system using a physics-based model using a physics-based model;
• training a physics constrained machine learning model using one or more machine learning algorithms based on the dynamics behavior data and the modeled dynamics behavior data as inputs;
• updating dynamics behavior data of the well system based on the physics-based model and the physics constrained machine learning model;
• outputting updated dynamics behavior data for the well system;
• and
• transmitting a command to the well system that adjusts a well operation based on the updated dynamics behavior data,
• wherein the updated dynamics behavior data completes the missing data in the incomplete measurement for the time interval.