We investigate the relationship between saturation and height in fields where oil or gas is present below current day free water level. Such situations arise in a number of fields in Oman with complex charge, structural and regional hydrodynamic history. The change in saturation with height – and importantly whether intervals contain mobile or immobile hydrocarbons – is a key parameter influencing volumetrics and field performance.
The correct identification and interpretation of this phenomenon is hindered by the inability to reconcile core-based saturation-height relationships with field observations including saturation from logs. This difficulty arises as core-based saturation-height modeling traditionally only considers the primary drainage (hydrocarbon displacing water) flow sequence. We present a simple analytical model incorporating both core-based primary drainage and imbibition (water displacing hydrocarbon) flow sequences which is able to describe the complex saturation scenarios discussed. The model has been validated against numerical simulations, can handle multiple rock types and is easily coded in a spreadsheet.
We compare our simple core-based model with log observations from example fields. The model can replicate observed saturation profiles within measurement uncertainty including the mobile hydrocarbon saturation above the current free water level as well as the immobile hydrocarbon saturation below. The implications for correct log and core data gathering and interpretation are summarized and the impact on field performance is discussed.
The work highlights the important role the imbibition flow sequence can play in describing hydrocarbon saturation changes with height in some fields: this is often overlooked yet critical for the correct description of some fields. Model inputs require imbibition experiments to be considered in data gathering campaigns.
A companion paper published in parallel discusses the processes that affect fluid distributions and outlines recommended diagnostic tools and workflows (Boya Ferrero et al., 2016).