Reservoir characterisation of data-poor fields with regional analogues: A case study from the Lower Shu’aiba in the Sultanate of Oman
Published:January 01, 2010
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Georg Warrlich, Heiko Hillgärtner, Niels Rameil, James Gittins, Issa Mahruqi, Tim Johnson, David Alexander, Bart Wassing, Mia Van Steenwinkel, Henk Droste, 2010. "Reservoir characterisation of data-poor fields with regional analogues: A case study from the Lower Shu’aiba in the Sultanate of Oman", Barremian – Aptian Stratigraphy and Hydrocarbon Habitat of the Eastern Arabian Plate (vol. 2), Frans S.P. van Buchem, Moujahed I. Al-Husseini, Florian Maurer, Henk J. Droste
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When building static reservoir models for fields with limited well data, the use of analogue data can help constrain uncertainty ranges for property modelling. Several Shu’aiba fields in the Ghaba Salt Basin (northern Sultanate of Oman) with good well coverage were used as analogues to model a nearby field with very limited well coverage. The analogue fields are located within a 50 km radius, roughly along strike of the Bab Basin and in a similar stratigraphic position and tectonic setting. Correlations between the modelled and analogue fields were set within a regional sequence-stratigraphic framework and are based on gamma-ray and porosity logs, carbon-isotope stratigraphy, as well as facies successions. Systems tract thicknesses and vertical facies successions were found to follow predictive trends. This allowed their interpretation in three dimensions away from well-data points with more confidence. Porosity histograms were established for each systems tract and porosity-permeability relationships, as well as vertical permeabilities, were determined for three facies from all analogue fields in the area. Diagenetic overprint led to very similar porosity-depth trends and improvement of reservoir properties below the seal in all fields. The established relationships and data ranges considerably helped constrain the rock property uncertainties of the field with limited well data. Furthermore, a common modelling approach for all the genetically related fields was established, which reduced model-building and cycling times for all fields.