A Facies-Based Approach to Distribution of Petrophysical Properties in an Aeolian Sandstone Reservoir, Unayzah Formation, Saudi Arabia

Abstract

AbstractDefining and distributing petrophysical reservoir property within a simulation ready geocellular model is an industrywide dilemma; the result of which has a large business impact on reservoir management decisions. The objective of this study is to develop porosity-to-permeability transforms, multiphase relative permeability and capillary pressure curves for each distinct depositional facies. The key to this process is the ability to recognize each of the four eolian facies and demonstrate that even at deep formation; the original depositional facies controls the petrophysical properties.Through core and image-log studies, the geologist divided the reservoir into the four distinct depositional facies that comprise a "wet" eolian depositional system: dune, sand sheet, paleosol, and playa. Each facies was distributed proportionately by zone (vertically) and by region (area) in a 3D geocellular model using an object based modeling technique and a wet eolian depositional model. The dune facies is the best reservoir unit followed by sand sheet; together the dune and sand sheet comprise a high proportion of the reservoir gross thickness. Conventional and special core analysis measurements were conducted on hundreds of core samples from three gas wells. The core data were thoroughly evaluated for pertophysical properties, and then grouped by depositional facies. Porosity-to-permeability transforms, multiphase dynamic relative permeability and capillary pressure were derived for each facies. The reservoir properties were then geostatistically distributed within each facies object using the facies and zone specific transforms.Results showed a quantifiable porosity-to-permeability transform, and corresponding capillary pressure and condensate-gas relative permeability for each depositional facies in the reservoir. This paper shows that by grouping the reservoir into recognizable depositional faceis has significantly enhanced the distribution of reservoir and fluid properties, which were incorporated into a compositional model. This will result in a dependable fluid-flow model that will support investment, reservoir development and reservoir management decisions.