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The history of reservoir characterization has been based on and currently rests on static data. Indeed, entire technologies, academic majors, and even commercial enterprises have sprung up to gather, interpret, and use core data, logs, geology and seismic data. The saturations, porosities, permeabilities, relative permeabilitiies, to name a few, from these technologies form the basis of volumetric calculations (original hydrocarbon in place), and recovery estimates (recoverable hydrocarbon). Ironically, it is dynamic data or data from flowing wells that are of commercial interest because revenue streams are directly proportional to it. But, aside from use in pressure transient analysis and as targets in simulation history matching, these data are little used in characterization. This situation is about to change. The large-scale use of near-continuous (real-time) surface and downhole measurements of rates (all fluids), pressures, and temperatures will augment and in some cases supplant reliance on static measurements. Such measurements are common now on new production facilities. Indications are that they are cost-effective on existing or legacy production. But these measurements will only be useful if there are means to interpret them. The objective of this presentation is to discuss the capacitance-resistance model that will use the coming "tsunami" of data to characterize reservoirs. Larry W. Lake is a professor in the Department of Petroleum and Geosystems Engineering at The University of Texas at Austin. He holds B.S.E and Ph.D. degrees in Chemical Engineering from Arizona State University and Rice University, respectively. Dr. Lake is the author or co-author of more than 100 technical papers, four textbooks and the editor of three bound volumes. He has served on the Board of Directors for the Society of Petroleum Engineers (SPE), won the 1996 Anthony F. Lucas Gold Medal of the AIME, the Degoyer Distinguished Service Award in 2002, and has been a member of the National Academy of Engineers since 1997.