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Reservoir Modelling of a Bioclastic Calcarenite Complex on Favignana, Southern Italy: The Application of
Multi-point Statistics*

Robert Kil1 and Andrea Moscariello2,3

Search and Discovery Article #50548 (2012)

Posted January 30, 2012

*Adapted from oral presentation at AAPG International Convention and Exhibition, Milan, Italy, October 23-26, 2011

1Chevron Exploration and Production Netherlands B.V. - NL
2Delft University of Technology, The Netherlands (a.moscariello@tudelft.nl)
3Earth and Environmental Sciences, University of Geneva - CH

Abstract

The island of Favignana provides an exceptional three-dimensional insight of the internal architecture of a Lower Pleistocene complex
bioclastic calcarenitic wedge. Field data indicate that these calcarenites consist of foramol association, originated during cool to
temperate water conditions in a high-energy, storm dominated, open shelf environment. Predominant sedimentary structures vary from
small-scale trough cross bedding, large foresets to large scours filled by structureless massive bioclastic material. Overall a main
transport direction to the SE indicates the prograding nature of these deposits. Based on the sedimentological characteristics and
reservoir properties, this sedimentary complex is believed to be a relevant analogue for several important hydrocarbon fields
worldwide such as the Perla Field in Venezuela.

A detailed reconstruction of facies distribution and description of sedimentary body dimensions and relative position have been
carried out in order to model the reservoir heterogeneity and flow properties of a similar buried sedimentary complex. The rock
properties could in fact change significantly during burial, as sedimentary bodies consisting of different primary textural and
compositional characteristics could be subject to different type of diagenetic modifications.

The internal architecture of the Favignana calcarenite was thus reconstructed on a 3D geo-cellular model using a multi-point statistics
(MPS) approach. For this, the following main types of input data were used:

1) pseudo-well data with stratigraphic and compositional information;
2) probability maps of each facies, created from field data and conceptual model;