Challenges of Modelling Volatile Oil Reservoir (Case Study: Fushia Prospect)
Sugiyanto Suwono, Eko Yuniarto Wibowo
Abstract
The Fushia prospect is situated in the Hammamet Offshore Exploration Permit. The prospect has been discovered since the drilling of Fushia-1 well targeted in the Birsa Formation drilled in 2010. The well logs indicate high quality sandstone with a porosity of approximately 25-30% with a hydrocarbon saturation of approximately 85%. Lab analysis of the sample confirmed that the reservoir fluid is a volatile oil. Preliminary reservoir modeling of this prospect has been built, and this paper is intended to share the challenges of developing this prospect especially related to its volatile oil behavior.
A clear demarcation between volatile and black oils is not easily made, although a gas-oil ratio of about 750 SCF/STB is probably a good indicator. Stock tank gravity is usually 40° API or higher. Volatile oils exhibit an initial oil FVF in the range of 1.5 to 6.0. Because the oil FVF is greater for volatile oils than black oils, the latter yield greater OOIP per unit volume. Another characteristic of volatile oil reservoirs is that the reservoir gas that evolves and flows into the wellbore will contain significant quantities of liquids that may eventually contribute the majority of surface oil production.
As the reservoir pressure depleting, a volatile oil may become more gas-like such that can flash mainly to gas and have a relatively low liquid content. This condition is not preferable since the oil price is generally higher than the gas. Accordingly, it is important to conduct a detail modeling of production separation to maximize the liquid recovery from it gas phase.
In order to characterize the fluid behavior, detail PVT modeling have to be performed. In the first stage, fluid have to be quality checked. Afterward, EOS tuning and lumping process should be conducted to ensure the PVT model ready for simulation. Finally, production forecast and estimate of recovery by component can be provided based on compositional reservoir simulation.
Key words: volatile, compositional, EOS
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