A method for evaluating and performing a hydrocarbon operation for a subsurface region comprising: obtaining a first data set associated with a subsurface region, wherein the first data set comprises one of seismic data, well log data, well test data, production data, and any combination thereof; obtaining a metric for an operational decision; creating two or more reservoir models for the subsurface region from the first data set, wherein the two or more reservoir models are based on the first data set; obtaining a second data set associated with the subsurface region and the two or more reservoir models, wherein the second data set comprises one of generated or observed seismic data, generated or observed well log data, generated or observed well test data, generated or observed production data, and any combination thereof; CHARACTERIZED IN THAT the method comprises: transforming the second data set to alter dimensionality of at least a portion of the second data set; creating a feature space and defining a plurality of elements of the feature space corresponding to each reservoir model; obtaining production data associated with the subsurface region disposing at least a portion of the production data and at least a portion of the transformed second data set into the feature space; determining a region of interest within the feature space; evaluating the metric for the operational decision at the region of interest in the feature space by performing one or more mathematical, statistical, or machine learning techniques combined with reservoir model simulation data, model-form error and metrics; and performing a hydrocarbon operation based on the evaluation of the metric for the operational decision at the region of interest. obtaining a first data set associated with a subsurface region, wherein the first data set comprises one of seismic data, well log data, well test data, production data, and any combination thereof; obtaining a metric for an operational decision; creating two or more reservoir models for the subsurface region from the first data set, wherein the two or more reservoir models are based on the first data set; obtaining a second data set associated with the subsurface region and the two or more reservoir models, wherein the second data set comprises one of generated or observed seismic data, generated or observed well log data, generated or observed well test data, generated or observed production data, and any combination thereof; CHARACTERIZED IN THAT the method comprises: transforming the second data set to alter dimensionality of at least a portion of the second data set; creating a feature space and defining a plurality of elements of the feature space corresponding to each reservoir model; obtaining production data associated with the subsurface region disposing at least a portion of the production data and at least a portion of the transformed second data set into the feature space; determining a region of interest within the feature space; evaluating the metric for the operational decision at the region of interest in the feature space by performing one or more mathematical, statistical, or machine learning techniques combined with reservoir model simulation data, model-form error and metrics; and performing a hydrocarbon operation based on the evaluation of the metric for the operational decision at the region of interest. transforming the second data set to alter dimensionality of at least a portion of the second data set; creating a feature space and defining a plurality of elements of the feature space corresponding to each reservoir model; obtaining production data associated with the subsurface region disposing at least a portion of the production data and at least a portion of the transformed second data set into the feature space; determining a region of interest within the feature space; evaluating the metric for the operational decision at the region of interest in the feature space by performing one or more mathematical, statistical, or machine learning techniques combined with reservoir model simulation data, model-form error and metrics; and performing a hydrocarbon operation based on the evaluation of the metric for the operational decision at the region of interest.