ABSTRACT

Reservoir development planning and well placement significantly affect hydrocarbon recovery. Therefore, strategic well placement and development techniques are essential to minimize the risk of unproductive drilling and also to maximize production within the reservoir.

This study presents an approach to well placement and production in a green field. A 3D static model of the green field was built using geostatistical techniques to distribute the various model petrophysical properties such as porosity, thickness, and permeability in order to provide reliable reservoir description for dynamic modeling. A dynamic model was constructed to evaluate various reservoir development problems, including well placement, number and types of wells to be drilled in the green field. The drilling of both vertical and horizontal wells was considered in the analysis. Finding the optimal length of the horizontal well to be drilled in order to maximize oil recovery and to properly develop the reservoir was considered a significant problem to address. A sensitivity analysis was carried out to evaluate the impact of horizontal well length on oil recovery. The vertical to horizontal permeability anisotropy (kvkh) was also studied in this work.

The results of the analysis indicate that horizontal well length influences cumulative oil production. Drilling a 3000ft. long horizontal well was found to produce a higher cumulative volume of oil than the oil recovery obtained from similarly placed horizontal wells but with shorter lengths of 2000 ft. and 1500 ft.

It is concluded that the methodology proposed in this study will find application in the development of a green field.

Keywords: Reservoir development, well placement, simulation, petrophysical property distribution, geostatistics, permeability, porosity, thickness

CHAPTER 1

INTRODUCTION

1.1         Statement of Problem

Reservoir development and well placement have been one of the existing challenges in the petroleum industry over the years. This is because different engineering, geological and economic variables affecting reservoir performance are practically involved.

More importantly, the decision on how to increase oil recovery and maximize the economic profitability of field development projects is the pivot point. Therefore, an extensive evaluation of certain decision variables such as reservoir properties, production scheduling parameters, type of well, location to drill new wells and an effective technique to obtain the best economic strategies are required. Also, consideration should be given to the spatial distribution of geological and rock properties such as porosity and permeability in order to locate potential hydrocarbon zones for drilling activities. This involves critical evaluation of development strategies to produce the greatest amount of hydrocarbons within the physical and expected economic limits.

Several techniques have been adopted to achieve efficient reservoir development process which significantly affects the productivity and economic benefits of an oil reservoir. However, the aim of this work is to evaluate the impact of well placement on cumulative oil recovery during the development of a green field.

In this study, reservoir simulation and spatial based modeling approaches will be used as key evaluating elements for the development of the greenfield oil reservoir to improve its productivity.

1.2         Objectives

The objectives of this study are to:

·         Use geostatistical methods to distribute the petrophysical properties in building a 3D static model of the reservoir;

·         Find the optimum number, type, and placement of wells required to develop the greenfield.

1.3         Methodology

The methods to be used include;

·         Build a 3D static model of the green field by

o   Digitization of structural and isopach maps of the A-1 reservoir

o   Estimation  and  distribution  of  Porosity,  Permeability,  and  Thickness  at  all

locations in the reservoir

o   Estimation of Original Oil in Place (STOOIP)

·         Construction of a 3D dynamic reservoir model

·         Use of the 3D dynamic model to find the optimum number, type, and placement of wells to develop the reservoir.

1.4         Facilities and Resources

The facilities and resources used for this project include;

·         AUST library and internet facilities

·         Technical and academic expertise of supervisor

·         Structure and Isopach maps of A-1 reservoir

·         Isopermeability map of A-1 reservoir

·         Isoporosity map of A-1 reservoir

·         Computer software programs such as: GIS, SGeMS, Sensor Simulator

1.5         Organization of Report

This report is organized into five chapters. Chapter one is the introductory chapter giving general information about the entire project. Chapter two gives in-depth information of the study area and reviews relevant literature related to this work. Chapter three places emphasis on data.