Sustainability recommendations for hydrocarbon operations

Non-transitory computer-readable media comprising instructions that are executable by a processing device for causing the processing device to perform operations comprising:

• receive a sustainability target for a level of assessment for a hydrocarbon production operation which includes multiple hydrocarbon assets;
• receive operational data for an activity associated with the hydrocarbon production operation via sensor networks deployed at the multiple hydrocarbon assets;
• generate a sustainability metric based in substantially real-time directly from the operational data and one or more parameters of the activity which indicate the type of energy source and equipment used for the activity using computational algorithms that process sensor measurements of physical parameters including temperature, pressure, flow rates, and chemical compositions;
• generate, by at least one forecasting algorithm, a predicted sustainability state for the level of assessment at a subsequent point in time based on the sustainability metric, the operational data, and the one or more parameters of the activity, wherein the forecasting algorithm includes a machine learning model trained on historical data relating to hydrocarbon assets that are similar to the multiple hydrocarbon assets and wherein the machine learning model automatically adjusts weighting coefficients based on real-time feedback from physical monitoring systems;
• generate a recommendation for at least one activity based on the predicted sustainability state and the sustainability target for the hydrocarbon operation, wherein the recommendation includes specific equipment configuration changes and operational parameter adjustments;
• determine adjusted parameters of the at least one activity to thereby change sustainability performance of the hydrocarbon production operation to be more sustainable;
• execute the at least one activity using the adjusted parameters by automatically controlling physical equipment at the hydrocarbon production operation;
• recording changes to the sustainability performance of the hydrocarbon operation through continuous monitoring of physical system outputs;
• and
• adjusting the forecasting algorithm based on the changes to the sustainability performance of the hydrocarbon operation.