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Reservoir simulation studies require good knowledge of permeabilities, but reliable measurements are only available from laboratory core tests. These are usually taken from a small percentage of wells. Frequently, this information is extrapolated to calculate permeabilities over the field, but insufficient data points usually cause unreliable predictions. This article proposes a method to estimate formation permeabilities from standard well logs and core data. The method should be applicable to any reservoir as long as sufficient core and log data are available. The method assumes that the Carman-Kozeny equation holds for the reservoir rocks, which is a fairly reasonable assumption, and that the available well logs contain intrinsic information on tortuosity, sand size distribution, cementing characteristics, etc., which ultimately determine flow performance.
This hypothesis is usually strong because the available logs are not able to fully read the physical phenomena that cover the complex dynamics of flow through reservoir rocks. The method was tested in a sandstone formation in Chihuido de la Salina, Neuquen basin, Argentina. Some core data points were not used to train the neural network and were subsequently useful for validation and comparison. In spite of certain drawbacks, the method was shown to outperform both standard-regression and hydraulic-flow-unit approaches.
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