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We use neural networks in conjunction with fuzzy logic to high-grade prospects containing hydrocarbon saturated reservoirs. We accomplish this by using fuzzy logic to formulate general rule of thumbs derived from rock physics data and interpreter's knowledge and experience. Integration of such linguistic rules with neural network ranking of most relevant attributes for prospect risking improves the process when compared against conventional "thresholding" methods. We show the benefits of combining neural network and fuzzy logic approaches where the strength of each method is combined. An example from onshore North America demonstrates the advantages of use of this technique. % 10 30 50 70

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SummaryA workflow is presented where modern seismic interpretation techniques are integrated with well logs, regional geology and modern analogs, to show the advantage a multi-data/multi-disciplinary approach to geological interpretation. The seismic interpretation techniques are aimed at extracting specific geological information from the data using sequence stratigraphy interpretation and geomorphologic interpretation. This form of interpretation is very useful for cross-disciplinary communication and interpretation. In this extended abstract an outline of the techniques and workflow is given and then the workflow is illustrated with examples from a case study.