The Aptian Shuaiba Formation is among the most important reservoir units in the Middle East. Despite being extensively studied in recent years (Droste, 2016; Murris, 1980; Droste and van Steenwinkel, 2004; Yose et al., 2006;,2010; van Buchem et al., 2002, 2010; Vahrenkamp, 1996), the interpretation of the Shuaiba depositional geometries, and specifically those associated with Shuaiba reservoirs, remains challenging in the seismic realm due to their intrinsic heterogeneity, variability and limited thickness.
An integrated and iterative analysis including regional geology, well and seismic data was conducted to unravel the internal depositional geometries and associated reservoir properties for the Shuaiba Formation in the western region of UAE. In the study area, spatial distribution and geometry of the Shuaiba seismic facies was mapped in detail using full-stack reflectivity, discontinuity, curvature and spectral decomposition seismic attributes and further integrated with available well data and analogues. The Shuaiba Formation is expressed on seismic by mounded facies characterized by an irregular appearance, with discontinuous outline of sub-transparent reflectors, crossing reflectors and a larger thickness than the surrounding facies. Reflectors may locally coalesce and form mounded features up to 70 ms thick. The areas between mounds are characterised by sub-parallel to inclined reflections. The latter could be interpreted as clinoforms, prograding from the isolated nucleation areas to their deeper surroundings. The base of the mounds is located just above the top Thamama B/base Shuaiba reflector and the top coincides with the top Shuaiba. Well data suggest that these mounds consist usually of Bacinella/Lithocodium facies and rudists. The detailed 3D seismic interpretation of the Shuaiba reservoir geometries indicates a complex depositional architecture, which results in a variety of potential stratigraphic trap geometries and a heterogeneous reservoir property distribution. The proposed integrated workflow can therefore be used as a predictive tool to unravel further prospectivity in the Shuaiba Formation and in similar complex carbonate reservoirs, as well as to significantly improve reservoir property distribution prediction in static models.