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ABSTRACT: Characterisation and prediction of clastic reservoir quality: an integrated model for use in exploration, appraisal and production projects

Bray, Antony A.1, Rob H. Lander2, Carl A. Watkins3, Caroline Jane Lowrey4, and Mark Owen5
(1) Fortum Petroleum AS, Oslo, Norway 
(2) Geologica AS, Stavanger, Norway
(3) Robertson research International Ltd, Llandudno, United Kingdom
(4) Geology Institute, University of Oslo, Oslo, Norway
(5) Robertson Research International Ltd, Llandudno, United Kingdom

This paper presents a new technique for generating continuous high resolution porosity and permeability curves in clastic reservoirs. This is based on integration of geological data, burial and thermal history and sandstone diagenesis modelling, utilising EXEMPLAR software. This software was originally developed in order to predict porosity by modelling the compaction and diagenesis experienced by a reservoir of known texture and composition and given a particular burial and thermal history. In the paper we describe a method for developing continuous pseudo-petrographic data based on core descriptions and processed digital core images. The input of such continuous petrographic data allows computation of continuous porosity and permeability curves. For the present study a sample density of 1 cm was chosen; the smallest increment possible is one pixel (millimetre scale).

The principal benefit of the new technique is that the level of resolution more accurately captures reservoir heterogeneity. The modelling procedure is based on the evolution of the porosity system and thus allows the user to test for the important controlling factors (e.g. thermal history, grain size, facies). The procedure can be (but need not be) wholly independent of wireline log data and is applicable to a range of problems in the full asset cycle (exploration, appraisal, development). In this paper we concentrate on description of an exploration project the aim of which was to more accurately assess the potential reservoir quality in undrilled prospects. By incorporating sensitivity analysis it is possible to provide a quantitative assesment of the important factors controlling reservoir quality. This results in a much more detailed evaluation of reservoir risk.

AAPG Search and Discovery Article #90913©2000 AAPG International Conference and Exhibition, Bali, Indonesia