Combined Geostatistical and Dynamic Simulations for Developing a Reservoir Management Strategy: A Case History
Authors: Rossini Claudia , Brega Fausto , Piro Luigi , Rovellini Marco , Spotti Giuseppe 
Published: December 2007

This case history describes a complete methodology from reservoir characterization to reservoir management for a producing field. A two-stage geostatistical approach was applied to distribute the reservoir heterogeneity coherently over the field. Ten 3D facies distributions were simulated. In a second step, 10 porosity and permeability images were geostatistically simulated on the basis of facies distributions. After suitable upscaling, all 10 reservoir images were initialized in the dynamic simulation model. The production history match was the discriminating criterion for the selection of the reservoir image to be used in the forecast phase.

Introduction

The study was aimed at piloting the drilling of the future 30 wells of the second and third development platforms in the northern area of an offshore field. The first platform wells had been producing since 1988, while six wells from the second and third platforms had a production history of 8 months.

To obtain a reliable tool for reservoir management, the study was developed with the following goals:to preserve the effect of the petrophysical reservoir heterogeneity in the fluid-flow simulation model andto minimize the "adjustments" to the static model necessary to match the production history during the dynamic simulation phase.

It is widely accepted that the quality of a flow simulation model (and the resulting forecasts) depends strongly on the accuracy of the static model on which it is based. When a dynamic simulation model is built, the reservoir characterization must focus on describing and quantifying the reservoir heterogeneities that control the fluid flow to reproduce the reservoir production behavior as accurately as possible. Unfortunately, to achieve the history match, the static model can sometimes be modified so severely that, after the final match, its results can be radically changed.

Taking these considerations into account, the multidisciplinary team in charge of this study chose an integrated approach based on a combination of geostatistical and dynamic simulations.

A geostatistical approach is particularly suitable to reproduce reservoir heterogeneities. It allows the use of all available geological knowledge, hard and soft, and provides n reservoir images, all respecting the input data and all equally probable from a static point of view. Consequently, only the past production behavior of the field can provide a guide for the selection of the reservoir image that is closer to reality.

The n equiprobable images must therefore be initialized in the dynamic model, and the production history must be run for all images before a selection can be made. The reservoir image that best reproduces the production history should need only slight "adjustments" to obtain the final match and can therefore be considered a reliable basis for forecasts and decisions.

Geological Setting and Reservoir Characteristics. The field structure is an anticline with a major axis that is northwest/southeast-trending. No remarkable tectonic phenomena have occurred, and no relevant faults have been recognized in the reservoir. The reservoir formation is made up of a complex lithology defined as "gray silty sandy dolomites passing to medium fine-grained quartz sands with dolomitic cement, with intercalations of tight dolomites and dolomitic limestones."