Proxy modeling workflow and program for reactive transport modeling

A non-transitory, computer-readable medium storing one or more instructions executable by a computer system for training machine learning-based proxy models as surrogates for process-based reactive transport modeling (RTM) to perform operations comprising:

• generating training sample data;
• executing batch training sample cases using the training sample data;
• training a set of parameter-specific proxy models represented by a neural network, wherein each parameter-specific proxy model corresponds to a specific RTM parameter from a set of RTM parameters;
• performing blind tests using the set of parameter-specific proxy models, wherein each blind test tests a specific one of the parameter-specific proxy models;
• and
• generating predictions using the set of parameter-specific proxy models.

A computer-implemented system for training machine learning-based proxy models as surrogates for process-based reactive transport modeling (RTM), comprising:

• one or more processors;
• and
• a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors, the programming instructions instructing the one or more processors to perform operations comprising:
• generating training sample data;
• executing batch training sample cases using the training sample data;
• training a set of parameter-specific proxy models represented by a neural network, wherein each parameter-specific proxy model corresponds to a specific RTM parameter from a set of RTM parameters;
• performing blind tests using the set of parameter-specific proxy models, wherein each blind test tests a specific one of the parameter-specific proxy models;
• and
• generating predictions using the set of parameter-specific proxy models.