The project proposes to develop and mature computational tools for flow diagnostics that are specifically designed to quantify uncertainty in reservoir characterization. Flow diagnostic tools are based on controlled numerical flow experiments that yield q uantitative information regarding the flow behavior of a model in settings much simpler than would be encountered in the actual field. While full-featured simulators are capable of making these predictions, they generally cannot do so in a computationally efficient manner unless an unacceptably large degree of upscaling is applied. Industrial applications require fast tools that can be applied directly to high resolution reservoir models.The main R&D challenges are to develop appropriate numerical formu lations and implement a set of prototypes that can be used for comparing, ranking, and clustering high resolution reservoir models. The tools will also be applied to suggest appropriate model updates during data integration and optimization.Flow diagnos tics will be tested for use in evaluating upscaling errors, assessing discretization errors, ranking earth models, and clustering reservoir models based on flow information. The primary application that will initially be targeted is waterflood optimizatio n for mature fields, for which simpler modeling tools are often favored over full-featured simulation to generate multiple history matched models for optimization. Flow diagnostics on fine-scale models have the potential for improved estimation of sweep e fficiency, which is the basis for many optimization strategies. They are also of interest for unconventional resources, such as tight gas/oil and shale gas, for which unstructured grids are already being used. In general, the tools have the potential for widespread use within earth sciences and will help with overall integration of reservoir modeling workflows.