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Building And Ranking Of Geostatistical Petroleum Reservoir Models
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CHAPTER ONE – INTRODUCTION
1.1 PROBLEM DEFINITION
In
Geostatistical reservoir characterization, it is a common practice to
generate a large number of realizations of the reservoir model to assess
the uncertainty in reservoir descriptions for performance predictions.
However, only a limited fraction of these models can be considered for
comprehensive fluid flow simulations because of the high computational
costs. There is therefore the need to rank these equiprobable reservoir
models based on an appropriate performance criterion that adequately
reflects the interaction between reservoir heterogeneity and flow
mechanisms.
Most techniques used in ranking of realizations are based
on static properties such as highest pore volume, highest average
permeability, and closest reproduction of input statistics. The drawback
of these simple techniques is that they do not account for dynamic flow
behavior which is very essential in predicting future reservoir
performance.
This thesis work seeks to build and rank equally
probable representations of the reservoir using petrophysical properties
such as porosity, water saturation, and permeability. The multiple
reservoir descriptions are ranked using both static (Stock tank oil
originally in place) and dynamic (geometric average permeability,
connected hydrocarbon pore volume, average breakthrough times and
cumulative recovery) measures.
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ABSRACT - [ Total Page(s): 1 ]ABSTRACTTechniques in Geostatistics are increasingly being used to generate reservoir models and quantify uncertainty in reservoir properties. This is achieved through the construction of multiple realizations to capture the physically significant features in the reservoir. However, only a limited number of these realizations are required for complex fluid flow simulation to predict reservoir future performance. Therefore, there is the need to adequately rank and select a few of the realizations ... Continue reading---
