ABSTRACT
A production engineer is responsible for generating the production forecast for a well or a field. Once production drops from the peak or plateau rate, the engineer needs an estimate of decline rate. Production forecasts use risk analysis techniques to help quantify the uncertainty. History matching is the process of building one or more sets of numerical models representing a reservoir which accounts for observed and measured data. The assessment of uncertainty is always subjective; history matching should assist in creating the model of uncertainty, which is subsequently used for decision making. This study makes use of the ECLIPSE simulator in which different runs of reservoir simulations were performed. The data were obtained from well XYZ in the Niger Delta region which is currently under natural depletion and requires a measure to enhance the amount of oil to be recovered, and then predict future performance and analysis. This model is based on the physical model that emerges from data obtained from the geological, geophysical, petrophysical, and log information.
TABLE OF CONTENT
Content Page
Declaration i
Certification ii
Dedication iii
Acknowledgement iv
Abstract v
Table of content vi
List of tables viii
List of figures ix
Nomenclature x
CHAPTER ONE: INTRODUCTION 1
1.1 Background of the study 1
1.2 Drive Mechanism 1
1.2.1 Water Drive 4
1.2.2 Gas Expansion 5
1.2.3 Solution Gas 6
1.2.4 Rock Drive 6
1.2.5 Gravity Drainage 7
1.2.6 Combination Drive 7
1.2.7 Decline Curves for Drive Types 7
1.3 Statement of the problem 8
1.4 Aim and Objectives of the study 9
1.5 Significant of the study 9
CHAPTER TWO: LITERATURE REVIEW 10
2.1 Introduction 10
2.2 Decline Curve Analysis 15
2.3 Simulation Model Building 20
CHAPTER THREE: MATERIALS AND METHODS 23
3.1 Reservoir Simulation 23
3.2 Research Methods 23
3.3 Research Models 24
3.4 Description of Eclipse Model 24
CHAPTER FOUR: RESULTS AND DISCUSSION 34
CHAPTER FIVE: CONCLUSION AND RECOMMENDATION 40
5.1 Conclusion 40
5.2 Recommendation 40
REFERENCES 41
LIST OF TABLES
Table Page
Table 2.1: Initial rates and forecasts to production limit, Evans H unit (LaSalle) 22
Table 2.2: Production history for well 1, Hawkville unit, LaSalle County 22
Table 2.3: Models for medium without natural fractures 26
Table 2.4: Models parameters for medium with natural fractures 26
Table 3.1: Oil relative permeability and saturation data 32
Table 3.2: Gas relative permeability and saturation data 33
Table 3.3: PVDG (PVT properties for Dry Gas) 34
Table 3.4: PVTO (PVT properties of dead oil) 34
LIST OF FIGURES
Figures Page
Figure 1.1: Typical decline curve for a well bore draining a reservoir system with a strong water drive (A) and a partial water drive (B) 6
Figure 1.2: Comparison of typical production decline curve for the different drive mechanisms 9
Figure 2.1: Theoretical P.I versus Actual P.I. 13
Figure 2.2: Decline curve of a well in months 14
Figure 2.3: Example project average well production history 16
Figure 2.4: Eagle Ford Shale counties 21
Figure 2.5 (a-d): Decline curve diagnostic ploys for well 1, STS 2 unit (LaSalle County) 22
Figure 2.6: Fracture permeability multiplier 25
Figure 2.7: Simulation production profile and forecast for different portion of curve 25
Figure 3.1: Reservoir model (Base Case). 31
Figure 4.1: Well oil production cumulative total 34
Figure 4.2: Well bottom hole pressure 35
Figure 4.3: Effect of rate change on production 36
Figure 4.4: Effect of rate change on bottom hole pressure 37
Figure 4.5: Effect of porosity change on bottom hole pressure 38
Figure 4.6: Re-modeled reservoir model 39
ABBREVIATIONS
b Decline exponent
DCA Decline Curve analysis
Di Initial decline rates
FEM Finite Element Method
K Permeability
MSCF/D One thousand cubic feet per day
P.I Production Index
Pnc Net confining pressure