ABSTRACT

Two new interpretation techniques have been developed for the purpose of providing more accurate permeability information. The first is an improved approach to determining ElectroFacies using a k-means clustering algorithm, and the second involves using separate permeability / porosity relationships for each ElectroFacies to be used for calculating permeability curves. The study for which these techniques were developed, included wells drilled over the last forty to fifty years with well logs that cover a wide vintage. The earlier ES and IES logs needed to be interpreted along with more modem log suites in order to provide sufficient data for detailed reservoir descriptions suitable for reservoir simulation. The techniques developed proved to be very successful in dealing with the variations in log types and vintages. The clustering technique used was based on log characteristics and the ElectroFacies were determined using a k-means method. Alternative clustering techniques are described and compared in the paper. The derived ElectroFacies were then compared to core data, particularly to determine "Rock Types" with identifiable fluid flow characteristics. Porosity / Permeability relationships were then assigned to the various ElectroFacies and used to calculate permeabilities during the log analysis. Core and log data are presented for a number of wells to show the success of the method over a variety ci fluvial to shoreface clastic systems with variations in diagenetic overprints. The data presented are from the Alto de Ceuta Field in Lake Maracaibo, Venezuela.

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