Recommendation engine for a cognitive reservoir system

One or more non-transitory tangible computer-readable storage media storing computer-executable instructions for performing a computer process on a computing system, the computer process comprising:

• receiving a reservoir model of a reservoir at a fuzzy inference engine, the reservoir model including a static model and a dynamic model, the static model including one or more clusters of a three-dimensional volume of the reservoir and an uncertainty quantification generated using a neural network, the dynamic model including pressure values and fluid saturation values propagated across the three-dimensional volume through a nodal connectivity of neighboring clusters;
• generating a set of input features from the static model and the dynamic model associated with a target region of the reservoir via the fuzzy inference engine;
• determining a drilling attractiveness of the target region of the reservoir based on the set of input features and using two or more fuzzy inference stages, each stage associated with a set of one or more rules, wherein an output of each stage is an intermediary value or a final value;
• determining a ranking of the target region based on the final value output;
• and
• outputting a recommendation for drilling in the reservoir, wherein the recommendation includes a list of ranked potential regions including the ranked target region.

A system for developing reservoir recommendations, the system comprising:

• a static modeler generating a static model of a reservoir, the static model including one or more clusters of a three-dimensional volume of the reservoir and an uncertainty quantification generated using a neural network;
• a dynamic modeler generating a dynamic model of the reservoir including pressure values and fluid saturation values propagated across the three-dimensional volume through a nodal connectivity of neighboring clusters;
• and
• a fuzzy inference engine in communication with the static modeler and the dynamic modeler, the fuzzy inference engine:
• generating a set of input features from the static model and the dynamic model associated with a target region of the reservoir;
• determining a drilling attractiveness of the target region of the reservoir based on the set of input features and using two or more fuzzy inference stages, each stage associated with a set of one or more rules, wherein an output of each stage is an intermediary value or a final value;
• determining a ranking of the target region based on the final value output;
• and
• outputting a recommendation for drilling in the reservoir, wherein the recommendation includes a list of ranked potential regions including the ranked target region.