Evaluating Uncertainty in the Volumes of Fluids in Place in an Offshore Niger Delta Field

Description

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Abstract

The purpose of this work is to evaluate the uncertainty in the volumes of fluids in place in Fault Block A (Segment 3) of the G-1 Sands in the OND field located offshore Niger Delta. The evaluation was performed in three parts: (1) building of the static model and division into three hydrocarbon zones with reference to the oil-water-contact (OWC).

Stimating the distribution of petrophysical properties such as porosity, water saturation and net-to-gross ratio in the reservoir and; (3) generation of various realizations of the volumes of fluids in place (STOOIP) and evaluation of uncertainty of STOOIP in the OND field.

The first part was executed by building a grid-based model of the reservoir using eclipse and Petrel. A 100 x 60 x 4 grid was built and the faults were created in the model to delineate the reservoir into six segments.

The second part of the study involved the calculation of the petrophysical properties that affect the volumes of fluids in place and distributing them in the geologic model.

This was done by assigning various probability distribution functions to porosity, water saturation and net-to-gross; and calculating STOOIP for the three hydrocarbon zones using the method of Monte Carlo simulation. One hundred realizations of STOOIP were generated for each zone in the reservoir.

Introduction

Reservoir Characterization is a process of integrating various qualities and quantities of data in a consistent manner to describe reservoir properties of interest in inter well locations (Ezekwe and Filler, 2005). The main purpose of reservoir characterization is to generate a more representative geologic model of the reservoir properties.

More so, the goal of any reservoir characterization or reservoir modeling is to understand the reservoir connectivity in static and dynamic conditions by integrating data from different sources (Mondal, 2010).

Thus, in building a Geologic representation of what a reservoir is most likely to be, it is necessary to adequately capture the uncertainty associated with not knowing its exact picture (Odai and Ogbe, 2010).

The success of any hydrocarbon exploration and exploitation program depends on the building of a reliable reservoir model. Furthermore, a reservoir’s commercial life begins with exploration that leads to discovery, followed by characterization of the reservoir.

However, the main challenge in reservoir development is the availability of limited data and huge uncertainty. Thus, this makes the evaluation of reservoir uncertainty very important in achieving a good understanding of reservoir management risks.

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