Reservoir simulation requires a realistic spatial distribution of capillary pressure and relative permeability throughout the reservoir. This study aims at deriving relationships between capillary pressure and relative permeability on one hand and porosity, permeability, depositional environment and structural position on the other hand.

This work is illustrated by two sandstone oil reservoirs. Sample permeability ranges from 10 mD to several Darcies. Available data include 1) More than one hundred drainage and imbibition capillary pressure curves. Both gas/water, mercury injection and water/oil data was analysed. 2) More than fifty water/oil relative permeability curves. Both fresh and restored- state, steady and unsteady-state corefloods were analysed.

Main conclusions are:

  1. Drainage capillary pressure curves and irreducible water saturation are strongly correlated with permeability, whatever the experimental technique used.

  2. Irreducible wetting phase saturation is significantly larger for water/oil drainage than for gas/water or mercury injection tests.

  3. There is no clear trend between drainage capillary pressure curves and depositional environment.

  4. Correlation between water/oil imbibition capillary pressure curve and permeability is very weak, unlike drainage.

  5. A significant correlation exists between permeability and end-point water permeability or final recovery.

  6. Both end-point water permeability and final recovery are found strongly correlated with the height above the initial water/oil contact, whatever the experimental technique used. This reflects the combined influence of initial water saturation and wettability variations.

  7. Reservoir trends are often obscured by use of inappropriate laboratory techniques.


There is an increasing agreement that a reservoir model should include a full range of heterogeneities from the lamina scale, to the bedform-scale and then the formation-scale. Fine-grid models are frequently built in order to capture the reservoir heterogeneity and to predict or mimic the field performance. The construction of these fine-grid models is a multi-step process. Over the past decade, several studies illustrated this process for porosity and permeability. Once the large scale reservoir architecture and the sandbody connectivity has been assessed using well and analog outcrop data, the corresponding facies must be populated with petrophysical values. Firstly, fine-scale, three-dimensional (3D), models of porosity and permeability are built for each facies using core and outcrop data. Secondly, suitable values for drainage and imbibition capillary pressure curves or relative permeability are assigned to fine gridblocks Finally, fine-scale models are upscaled and effective permeability values and pseudo relative permeabilities are input in coarse grid cells.

Recently, the generation of petrophysical groups has been proposed to improve the mapping of porosity and permeability. A petrophysical group is a set of reservoir zones with similar porosity, permeability, and grain density. Petrophysical groups are built using clustering techniques and the large amount of routine poroperm data generally available from cored wells.

On the other hand, populating fine-scale 3D models with capillary pressure and relative permeability data has received little attention. This process is largely controlled by the data availability and quality and it is sometimes assumed that a single coreflood test is representative of a whole reservoir unit, genetic facies or depositional environment. A few studies evidenced a significant scatter in two-phase properties but also some fair correlations with permeability, grainsize or structural position.

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