--> ABSTRACT: Carbonates versus Clastics: Their Sedimentological Impact on 3-D Reservoir Modeling, by Noad, Jon; #90026 (2004)

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Noad, Jon1 
(1) Shell International Exploration and Production, Rijswijk, Netherlands

ABSTRACT: Carbonates versus Clastics: Their Sedimentological Impact on 3-D Reservoir Modeling

Nothing polarises the field of sedimentology more than the dichotomy between carbonates and clastics. The two categories differ widely in their chemistry, sedimentology, fossils, diagenesis and most importantly in their reservoir architecture. Their contrasting character has a huge impact on how to model such sediments in a static reservoir modelling environment. Using a series of examples from the Middle East, strategies are formulated to demonstrate a preferred approach to modelling across the spectrum of carbonates and clastics. Fields containing fluvial, prograding shoreface and deep marine clastics, and platform carbonates, each with a similar number of wells, provide the supporting data. 
Clastic shoreface deposits are typically laterally extensive, and can be subdivided using parasequence boundaries. Property distributions can be predicted within each parasequence, and coast-parallel homogeneities can be incorporated into property modelling using trends. Uncertainty in permeability ratios is likely in thinner sandstone reservoirs. Coastal and marginal marine deposits are less predictable. 
In contrast the accurate modelling of fluvial and turbidite channels depends on prior knowledge of their dimensions and orientation. Unless the channels are large enough to have been intersected in several wells, interpolating the reservoir properties within them will be based on limited data, and may not reflect the true picture. Correlation of such deposits is also fraught with uncertainty, yet may be critical both for calculating volumes, and for assessing aquifer support and early water breakthrough. 
Carbonate reservoirs are often made up of platform carbonates, particularly in the Middle East, to which a detailed correlation can be applied. Despite this, identifying sweet spots is extremely difficult, and usually requires a stochastic approach. The incorporation of inversion data may improve understanding of reservoir distribution. The modelling of reefal and other build-up carbonates usually uses zonal models. Other carbonate settings may be more like their clastic counterparts (carbonate turbidites, for example).

 

AAPG Search and Discovery Article #90026©2004 AAPG Annual Meeting, Dallas, Texas, April 18-21, 2004.