EVALUATION OF OIL RECOVERY EFFICIENCY OF WATER-FLOODING, GAS-FLOODING AND WAG INJECTION IN A TURBIDITE RESERVOIR

Transcription

1 EVALUATION OF OIL RECOVERY EFFICIENCY OF WATER-FLOODING, GAS-FLOODING AND WAG INJECTION IN A TURBIDITE RESERVOIR A THESIS PRESENTED TO THE DEPARTMENT OF Petroleum Engineering African University of Science and Technology, Abuja In Partial Fulfillment of the Requirements For the Degree of MASTER OF SCIENCE By AYAWAH, Akansah Evaristus Prosper Abuja, Nigeria December, 2014 i

2 EVALUATION OF OIL RECOVERY EFFICIENCY OF WATER-FLOODING, GAS-FLOODING AND WAG INJECTION IN A TURBIDITE RESERVOIR By AYAWAH, Akansah Evaristus Prosper A THESIS APPROVED BY THE PETROLEUM ENGINEERING DEPARTMENT RECOMMENDED:. Dr. Saka Matemilola (Supervisor) Prof. David Ogbe (Committee Member) Dr. Alpheus Igbokoyi (Committee Member) Head, Department of Petroleum Engineering APPROVED BY:.. Chief Academic Officer... Date ii

3 ABSTRACT Worldwide awareness of thin-bedded reservoirs (including turbidites) has become increasingly important with about 30-40% of the world s oil in-place resources confined within thin-bed laminated reservoirs (Tyagi et al. 2008). The Niger delta petroleum province is characterized by turbidite formations which are a form of thin-bed laminated reservoirs. They are characterized by intercalation of sand and shale beds with the sand beds, containing a substantial amount of shale lenses. The distribution of the shale lenses results in gross heterogeneity in reservoir properties such as porosity and permeability. With the natural reservoir energy, averagely, only 10-40% of the oil originally in place can be recovered from the reservoir. To recover more of the oil in place, additional energy must be injected into the system to enhance/improve the recovery. The common improved oil recovery (IOR) methods include water flooding and gas injection. Water Alternating Gas injection (WAG) is another applicable IOR method that combines water and gas injection in a cyclic alternating manner. This study was conducted to evaluate the recovery efficiency of water-flood, gas-flood and WAG injection by simulation of a mature turbidite reservoir model from the Niger Delta. In the execution of the study, the rates of injection of water and gas in the water flooding and gas-flooding, respectively, were sensitized. Sensitivity analyses of factors affecting WAG efficiency including the WAG rate, WAG ratio, WAG cycle and preferential fluid with which to begin the WAG with were conducted. The simulations were done in ECLIPSE 100. The optimal reservoir fluid volume rate of water and gas for water- and gas-flooding respectively were obtained to be rb/day and rb/day. The optimal WAG procedure obtained was; WAG rate (15000 rb/day water, rb/day gas), WAG ratio (1:14), WAG cycle (50 days gas, 200 days water) and gas injected first. From the simulations of the optimal procedures conducted, water-flooding yielded the highest oil recovery of 55.56% followed by gas-flood with a recovery factor (RF) of 54.16% and then WAG came last with RF = 52.83%. Economic analysis conducted on the three IOR methods showed that water-flooding is the most profitable with an additional profit between MM$ to MM $ 1, in a 90% confidence interval. It is therefore, the recommended IOR method to be implemented. iii

4 ACKNOWLEDGEMENT I would first of all shout my hallelujah to God Almighty for His graces and favour upon me all day every day. Thank You BABA. My stay on campus has been made possible by my number one mentor and his lovely wife, Mr. and Mrs. Francis Ayawah Akansah. I don t even have the words I want to use to thank you. I couldn t have done this without you. The favour and blessings of God will follow you all the days of your lives. AMEN! I would secondly like to acknowledge the effort of all the lecturers that I had contact with while in AUST. God will surely reward your efforts. To my supervisor, Dr. Saka Matemilola, I say thank you for all the advice, motivation and direction you gave in doing this work. God bless your every effort in life. And to the other members of my committee, Dr. A. Igbokoyi and Prof. D. Ogbe, thank you so much for agreeing to be on my committee and for all the support u gave me. The countless efforts of Prof. G. Chukwu can never go unacknowledged. Daddy thank you very much. Special thanks to Mr. Haruna Onuh (Boss), Mr. Arinkoola Akeem Olatunde and Mr. Lekan Keshinro for their continuous assistance throughout this work. I say thank you to my mentor Mrs. Chiamaka Kingsley for wise counsel during my stay on campus. God bless! My appreciation also goes to the Faculty and Staff of AUST for all you have done for me. In all things, give glory to God. Last but not the least, all my colleagues and friends in AUST, thank you all for not picking up fights with even when I am very annoying. Thanks for the all kinds of supports you have been giving me. God bless you all wherever you go. GLORY HALLELUJAH!!! iv

5 DEDICATION I dedicate this work to my mum, Mrs. Victoria Ayawah, the entire Ayawah family and my lovely girlfriend, Erms. v

6 TABLE OF CONTENT ABSTRACT... iii ACKNOWLEDGEMENT... iv DEDICATION... v TABLE OF CONTENT... vi LIST OF TABLES... x LIST OF FIGURES... xi CHAPTER 1 INTRODUCTION Overview Problem Definition Research Objectives Methodology Scope of Work Thesis Layout... 4 CHAPTER 2 LITERATURE REVIEW Challenges Encountered in Thin Bed-Laminated Reservoirs Detection and Characterization of Thin Beds Well Placement and Completion in Thin-Bed Laminated Reservoirs Thin-Bed-Laminated Reservoir Properties Porosity Permeability Saturation Reservoir Pressure and Distribution of Fluid Phases Reservoir Fluid Properties Bubble Point Formation Volume Factor Gas Oil Ratio vi

7 2.4 Basic concepts of fluid displacement Rock Wettability Surface/interfacial Tension Capillary pressure Relative permeability Mobility and mobility ratios Viscous fingering Fluid displacement efficiency Volumetric displacement efficiency Total recovery efficiency Geology of the Niger Delta (Overview of Study Area) Location and General Overview Stratigraphy Depo-belts Hydrocarbon Source Rock Reservoir Rock Formation of Turbidites (Thin-Bed Laminated Reservoirs) Some Concepts Applied for Oil Recovery from Thin-Bed Reservoirs Commingled Production from Vertical Wells Production from Thin Beds Through Horizontal Well Intelligent Well Completion Oil Recovery Mechanisms Water Alternating Gas Injection (WAG) and Simultaneous Water and Gas Injection (SWAG) CHAPTER 3 METHODOLOGY AND DATA ANALYSIS Recovery Mechanisms Thin Bed-Laminated Reservoirs Active Aquifer Presence vii

8 3.1.2 Gas Cap Presence Volumetric Depletion and Solution Gas Contribution to Oil Recovery Description of the Reservoir Model Properties Well Placement Well Controls Water-Flood, Gas-Flood and WAG Injection Sensitivity Analyses Water Injection Rate for Water-Flooding Gas Injection Rate for Gas-Flooding WAG Ratio WAG Cycle Time Water and Gas Injection Rates Comparative Analysis CHAPTER 4 RESULTS AND DISCUSSIONS Optimization Results of the Factors Affecting Gas-flood, Water-flood and WAG Efficiency Gas Injection Rate in the Gas-Flooding Water Injection Rate in the Water-flooding WAG Ratio WAG Cycle Timing Water and Gas Injection Rates Comparison of Optimal Water, Gas and WAG Injection Obervations Discussions Economic Analysis CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS Conclusions Recommendations viii

9 NOMENCLATURE REFERENCES APPENDIX A APPENDIX B ix

10 LIST OF TABLES Table 3.1 Model Grid Size Table 3.2 Field and Regions Reservoir Properties of Model Table 3.3 Reservoir Fluids in Place Table 3.4 Movable Oil Originally in Place with Respect to Water and Gas Table 3.5 Reservoir Fluid Properties Table 3.6 WAG Cycles Table 3.7 Water and Gas Rates for WAG Table 3.8 Optimal Injection Procedures Table 4.1 Summary of Recovery Factors and Other Parameters of the Various Recovery Methods..40 Table 4. 2 Recovery Parameters at 90% Water-Cut Table 4.3 Input Parameters for Economic Analysis Table 4.4 Profit Estimations Table 4.5 Stochastic Distribution of Economic Input Parameters Table 4.6 Additional Profit Made from IOR in 90% Confidence Interval Table B1 Recovery Parameters for Natural Depletion & Gas-Flooding 54 Table B2 Recovery Parameters for Water-Flooding & WAG Injection x

11 LIST OF FIGURES Fig. 3.1 Reservoir Model Fig. 3.2 Well Placement in Reservoir Model Fig. 3.3 A Schematic of Gas-Flooding Process Fig. 3.4 A Schematic of a WAG Process Fig. 4.1 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various Gas RESV..33 Fig. 4.2 A Plot of Field Pressure Against Time for Various Gas RESV Fig. 4.3 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various Water RESV Fig. 4.4 A Plot of Average Reservoir Pressure Against Time for Various Water RESV.. 35 Fig. 4.5 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various WAG Ratios Fig. 4.6 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various WAG Cycles Fig. 4.7 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various WAG Rates Fig. 4.8 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Gas-First WAG and Water-First WAG Fig. 4.9 A Plot of Field Oil Recovery Efficiency Against Time for Natural Depletion, Gas- Flood, Water-flood and WAG Fig A Plot of Field Oil Production Total Against Time for Natural Depletion, Gas- Flood, Water-flood and WAG Fig A Plot of Average Reservoir Pressure Against Time for Natural Flow, Gas-Flood, Water-flood and WAG Fig Plots of Field Water-Cut & Field Oil Production Rate Against Time for Natural Flow, Gas-Flood, Water-flood and WAG Fig. A1 Cumulative production, Production Rate and Water-cut Graphs for Gas-Flood..49 Fig. A2 Cumulative production, Production Rate and Water-cut Graphs for Water-Flood Fig. A3 Cumulative production, Production Rate and Water-cut Graphs for WAG Cycles Fig. A4 Reservoir Pressure and Gas Oil Ratio Graphs for WAG Cycles xi

12 Fig. A5 Cumulative production, Production Rate and Water-cut Graphs for WAG Rates Fig. A6 Reservoir Pressure and Gas Oil Ratio Graphs for WAG Rates Fig. A7 Cumulative production, Production Rate and Water-cut Graphs for WAG Ratios Fig. A8 Reservoir Pressure and Gas Oil Ratio Graphs for WAG Ratios Fig. A9 Cumulative production, Production Rate and Water-cut Graphs for Water or Gas 1 st in WAG Fig. A10 Reservoir Pressure and Gas Oil Ratio Graphs for Water or Gas 1 st in WAG Fig. A11 Reservoir Pressure and Gas Oil Ratio Graphs for Water or Gas and WAG Injections xii

13 CHAPTER 1 INTRODUCTION 1.1 Overview Oil recovery may be defined as the withdrawal of oil from the reservoir using available technology with reservoir energy and/or external energy. It is usually expressed as a ratio of the volume of oil recovered to the volume of oil initially in place. This ratio is known as the recovery factor when economic limit of the reservoir is reached. Depending on the energy system of the reservoir and fluid distributions in the reservoir, different mechanisms are applied to recover oil from the reservoir. Recovery from some reservoirs are more challenging than from others. Thinly laminated (turbidite) reservoirs are one set that pose a lot of challenges to reservoir engineers. Worldwide awareness of thin-bedded reservoirs including turbidites, has become increasingly important with about 30-40% of the world s oil in-place resources confined within thin-bed laminated reservoirs (Tyagi et al. 2008). Records have it that thin-bedded reservoirs have produced large quantities of hydrocarbons over long reservoir production lives (Tyagi, et al, 2008). In a thinly laminated reservoir, the beds may consist of an intercalation of sand-shale units or may just be a stack of sand units with lenses of shale. In the case of intercalated sandshale units, there may be no cross flow from the sand units. However, in the case of a stack of sand units, there may be variation of reservoir properties such as porosity and permeability which results in pressure differential and hence cross-flow during production since there are no no-flow barriers. The various recovery mechanisms used to produce reservoirs depending on the dominant natural reservoir energy include: compaction drive; oil expansion drive; solution gas drive; gas-cap drive; water drive; gravity drainage and combination drive. Producing with natural reservoir energy is known as primary recovery. With the natural reservoir energy, averagely, only 10-40% of the oil originally in place can be recovered. To recover more of the oil in place, additional energy must be injected into the system in what is known as secondary recovery. The common secondary recovery methods include water flooding and gas injection. After secondary recovery, there may still be the need to recover more oil depending on the efficiency of the secondary recovery. In such a situation, tertiary recovery is then applied. The tertiary recovery methods alter the rock-fluid properties to aid better oil recovery. For low viscosity oil, miscible gas injection, water alternating gas (WAG) 1

14 injection, polymer flooding, flow diversion using polymer gel and surfactants injection are the applicable EOR techniques. In heavy oil reservoirs however, steam injection and in situ combustion, generally classified as thermal methods, are the applicable techniques. In reservoir management, it is required that the dominant reservoir energy be known so that the appropriate recovery mechanisms can be used to recover most of the oil in place. All the various recovery mechanisms have different recovery efficiencies depending on the reservoir properties and characteristics. 1.2 Problem Definition The Niger delta petroleum province is characterized by turbidite formations which are generally, a form of thin-bed laminated reservoirs. Thin-bed laminated reservoirs are characterized by intercalation of sand and shale beds with the sand beds containing a substantial amount of shale lenses. The distribution of the shale lenses results in gross heterogeneity in reservoir properties such as porosity and permeability. The degree of heterogeneity varies from bed to bed depending on the amount and distribution of shale and the depositional history of the formation. This intra- and inter-bed heterogeneity pose a serious problems to oil recovery from thin bed laminated reservoirs. These problems include: Viscous fingering in reservoirs with substantial water drive. In general, as the reservoir heterogeneity increases, the recovery will decrease, due to the uneven advance of the displacing water. This phenomenon cause a lot of movable oil to be trapped behind resulting in low recoveries. The rate of water advancement is usually faster in the zones of higher permeability. This results in earlier high water-oil ratios and consequent earlier well economic limits (Ahmed, 2006). Earlier water breakthrough in the more permeable layers than the less permeable layers which retards oil production from the oil saturated, less permeable units. Severe gas channeling, gas coning and gas production through the more permeable layers in a case of significant gas cap. The reservoir in question has low pressure of about psia. This pressure is obviously not enough for significant oil recovery. All the problems listed above have a great toll on oil recovery from the turbidite (thin-bed laminated) reservoir. Getting a way around these problems will result in a great deal of additional oil recovery from these kind of reservoirs. 2

15 Water-flooding and gas-flooding are usually the first port of call in terms of improved oil recovery in light oil reservoirs. A combination of these processes in Water Alternating Gas (WAG) injection, is also a feasible IOR method to be evaluated in this reservoir model. From literature, these methods have thrived in these kinds of reservoirs. This coupled with the relatively lower cost of their implementation influence their selection for evaluation in this reservoir. This study therefore set out to evaluate the recovery efficiencies of water-flood, gas-flood and WAG injection by simulation of the mature turbidite reservoir model from the Niger Delta using ECLIPSE 100 and to perform economic analysis to determine the most profitable IOR method for this reservoir. 1.3 Research Objectives The objectives of this research are as follows: 1. To obtain an optimal fluid injection procedure for maximum recovery in waterflooding, gas-flooding and WAG injection. 2. To evaluate the efficiency of water-flooding and gas-flooding in the reservoir. 3. To compare the performance of water and gas-flooding to that of WAG the said reservoir. 4. To determine the most profitable IOR method among the three methods evaluated. 1.4 Methodology The following procedures were followed for the execution of this research: 1. Review of relevant literature. 2. Obtaining turbidite reservoir model. 3. Evaluation of primary recovery from the model using ECLIPSE Sensitivity analyses of water, gas and WAG injections. 5. Evaluation of the recovery efficiencies of water-flooding, gas-flooding and WAG injection using ECLIPSE. 6. Data analyses. 7. Interpretation and discussion of results. 3

16 8. Conclusions and recommendations. 1.5 Scope of Work This work involved the simulation of water-flooding, gas-flooding and WAG injection in a turbidite reservoir model from the Niger Delta using ECLIPSE 100. The simulation was done for only vertical wells (both producers and injectors). 1.6 Thesis Layout This report starts with an introduction which gives an overview of the topic, defines the problem of the research and details the research objectives and the methodology employed for the execution of the project. These are all contained in chapter 1. This chapter also contains the scope of the project and the organization of the thesis report. Chapter 2 contains background information on Niger Delta and reviews of relevant literature. The next, chapter 3, is the execution of the project, i.e., the reservoir simulation processes and analysis of data. The results are presented in chapter 4 together with discussions and interpretation of results. The conclusions and recommendations contained in chapter 5, the last chapter of this report. After chapter 5 are references and appendix. 4

17 CHAPTER 2 LITERATURE REVIEW 2.1 Challenges Encountered in Thin Bed-Laminated Reservoirs Detection and Characterization of Thin Beds In a Petrophysical sense, thin beds can be defined as beds that are thinner than the resolution of the logging tools used to characterize them. This implies that the direct log values do not represent the true bed-or layer properties, but an average of multiple beds. Therefore, there is a need to find out a way to properly characterize the beds and to find its true potentials by integrating the different tools and techniques. Thin beds of clay, silt and fine-grained sand distributed within a hydrocarbon bearing sand significantly reduce the apparent resistivity measured by a conventional induction or lateralog tool (Tyagi et al., 2008). The tools lack the capability to resolve resistivity values for the individual beds of sand and shale. Instead, they give an average resistivity measurement over the thinly bedded sequence. The potential thin-bed reservoirs clearly stretch the limits of reservoir characterization and modeling studies and put a new perspective on standard questions such as: What can be resolved by seismic? Can we discriminate between lithology and fluid effects? How do we upscale the reservoir characterization results from seismic to the reservoir simulator? A more efficient tool for thin bed detection is known as thin bed Rt tool. It is a microlateralog device with about 5 cm resolution and depth of investigation about cm (12-20 in). That is about 2 3 times deeper than the earlier microlateralogs (Crain, 2000). Other thin bed logging tools according to Crain (2000), include; microlog, microlateralog, proximity log, microspherical focused log. In some laminated reservoirs, these tools are capable of giving the net to gross sand ratios. None of the above tools gives useful deep resistivity information when the sand layers are thinner than the tool resolution. In this case, unconventional methods have to be adopted to determine the resistivity. Resistivity anisotropy approach is commonly used for this purpose. Reservoir characterization plays an important role in selecting the efficient exploitation process for reservoirs and also helps in the interpretation and management of the performance of the field. 5

18 2.1.2 Well Placement and Completion in Thin-Bed Laminated Reservoirs Two well placement styles have proved to give efficient oil recovery from thin-bed laminated reservoirs (Tewari, et al., 2005). 1. More vertical wells with closer well spacing with each well assigned to a particular bed. 2. Horizontal wells with varying drain-hole length. These give better sweep for maximizing the recovery with optimized production and control on sand and water production. Although structurally, the well placement seems to be an easy task, the challenge is in landing the well in the thin beds (0.5-1 m) since a small deviation ends up in an unproductive region. After a successful well placement, adequate completion is now required for good oil recovery with little or no sand and water production. A careful perforation is required in order not to damage the formation and cause sand production and early water cut. Depending on the wellbore and formation pressures conditions, either underbalance or overbalanced perforation is done to achieve a successful completion. In managing sand production, one needs to predict the propensity of the reservoir to produce sand using the geomechanical properties of the reservoir. If the reservoir has the tendency of producing sand then steps are taken to prevent it through the completion process. The sand is then monitored and remediation processes executed in case of any sand production. 2.2 Thin-Bed-Laminated Reservoir Properties Porosity Porosity is the proportion of the bulk reservoir rock volume that is occupied by void spaces. Porosity constitutes the part of the total porous rock volume which is not occupied by rock grains or fine mud rock, acting as cement between grain particles. There are two main categorization of porosity, absolute and effective porosities. They are distinguished by their accessibility to reservoir fluids. Absolute porosity is defined as the ratio of the total pore volume Vpa, whether the voids are interconnected or not, to the bulk volume Vb of a rock V sample. It is expressed as; a V pa b. It could be expressed as a percentage or a fraction. On 6

19 the other hand, effective porosity implies the ratio of the total volume of interconnected Vp voids, Vp, to the bulk volume of rock. It is expressed as;. V Effective porosity depends on several factors like rock type, heterogeneity of grain sizes and their packing, cementation, weathering, leaching, type of clay, its content and hydration, etc. It should be noted that porosity is a static parameter, unlike permeability which makes sense only if fluid is moving through a porous medium Permeability Reservoir rock permeability is defined as the ability of the rock to transmit fluid through its interconnected pores i.e. communication of interstices. In general terms, the permeability is a tensor, since the resistance towards fluid flow is directionally dependent. Permeability is only considered to be a scalar when the reservoir is said to be for isotropic and homogeneous in nature. A rock is said to be impermeable if there exist no interconnected pores in the rock volume. It is, therefore, natural to assume that there exists certain correlations between permeability and effective porosity. All factors affecting porosity will affect permeability to some extent but not to the same degree and since rock permeability is difficult to measure in the reservoir, porosity correlated permeabilities are often used in interpolating reservoir permeability between wells. Absolute permeability could be determined in the laboratory by using inert gas (nitrogen is frequently used) that fills the porous rock sample completely and limits the possibility of chemical interaction with the rock material to a minimum. Since the gas molecules will penetrate even the smallest pore-throats, all pore channels are included in the averaging process when permeability is measured. When several phases of fluids are passing through a rock locally and simultaneously, each fluid phase will counteract the free flow of the other phases. This interaction reduces the phase s permeability. The permeability of one fluid in the presence of other fluids is known as effective permeability of that fluid Saturation Saturation may be defined as the percentage of the total pore spaces in a porous medium that is occupied by a particular fluid. Considering a representative elementary volume of the reservoir rock, with the pores filled with oil, gas and water, it can be written in b 7

20 volumetric terms as follows: Vp =Vo +Vg+Vw, which culminates from the definition of saturation, S, as a fraction of the pore volume occupied by a particular fluid: S i Vi V p, i = 1,...,n where n denotes the total number of fluid phases present in the porous medium, Vi volume of a particular fluid and Vp pore volume. Consequently, S i 1. Importantly, it must be noted that the fluid saturation (So, Sg and Sw) in a reservoir varies spatially, most notably from the water-oil contact to the top of the reservoirs, and also in time during the production. In short, different parts of the reservoir may have quite different fluid saturations, and also the saturation in any elementary volume of the reservoir changes progressively during the production. Not all the oil can be removed from the reservoir during production. Depending on the production method, or the actual "drive mechanism" of the petroleum displacement, the oil- recovery factor may be as low as 5-10% and is rarely higher than 70%. Part of the oil will remain as residue, this is called the residual oil. One has to distinguish between the residual oil and possible gas saturation reached in a reservoir after the production stage, and the residual saturation of fluid phases in a reservoir-rock sample after a well coring operation Reservoir Pressure and Distribution of Fluid Phases. The migration and accumulation of petroleum in a reservoir leads to the replacement of the original pore water by gas and oil, even though the rock pores may remain water-wet. The density difference makes the gas accumulate at the top of the reservoir, and the oil directly below. Water underlies the petroleum, as an aquifer, but is continuously distributed throughout the reservoir as the wetting fluid. The following fluid interfaces in the reservoir are of significance: The surface separating the gas cap from the underlying oil zone ( oil leg or oil column ) is known as the Gas-Oil Contact (GOC). Below the GOC, gas can be present only as a dissolved phase in oil. Another interface is the Oil-Water Contact (OWC). It is the surface separating the oil zone from the underlying water zone. Oil is generally absent below the OWC. 8

21 There is also an imaginary surface at which the pressure in the oil zone equals to that in the water zone, i.e. po = pw. This interface is known as the Free-Water Level (FWL). The FWL can be seen as the oil-water contact in the absence of the capillary forces associated with a porous medium. The total pressure at any reservoir depth, due to the weight of the overlying fluid saturated rock column, is called the overburden pressure, Pov. The overburden pressure is the sum of the overlaying fluid-column pressure (Pf) and the overlying grain- or matrix-column pressure (Pm), and thus, P ov = P m + P f. This means that any reduction of the fluid pressure, as occurs during production, will lead to a corresponding increase in the grain pressure. Rock compressibility is therefore an important parameter to consider when petroleum (preferably oil) production is estimated. 2.3 Reservoir Fluid Properties Bubble Point Bubble point is known as the reservoir pressure at which dissolved gas begin to evolve out of solution. A reservoir with pressure greater than bubble point has all its gas dissolved in the oil and is said to be undersaturated. On the other hand, when the reservoir pressure is at or below the bubble point, the reservoir is said to be saturated Formation Volume Factor Oil formation volume factor, Bo, is defined as the volume of oil in barrels occupied in the reservoir at the prevailing pressure and temperature divided by the volume of oil in stock Vo tank barrels. It is expressed as; Bo V ( resc) o( sc) ; where Vo(resc) and Vo(sc) are oil volumes under reservoir conditions and standard conditions respectively. Its unit is RB/STB. Gas formation volume factor, Bg, is defined as the ratio of the volume of gas in cubic feet under reservoir temperature and pressure conditions to the volume of the same gas in Vg standard cubic feet under standard conditions. It is expressed as; Bg V ( resc) g( sc) ; where Vg(resc) and Vg(sc) are gas volumes under reservoir conditions and standard conditions respectively. Its unit is cf/scf. 9

22 2.3.3 Gas Oil Ratio Gas-oil ratio (GOR) or R, is the volume of gas in standard cubic feet produced divided by volume of stock tank barrel of oil produced at surface conditions expressed as V g( sc) R. V o( sc) It has a unit of scf/stb. Solution gas-oil ratio, Rs, is the volume of gas in scf dissolved in one stb of oil. 2.4 Basic concepts of fluid displacement Rock Wettability Rock wettability is the tendency of a fluid to spread or adhere to the rock surface in the presence of other fluids. A rock is termed water-wet if water preferentially wets the rock surface in the presence of oil and/or gas and oil-wet if oil preferentially wets the rock surface in the presence of water and/or gas. Gas never wets the surface of the rock. Most of the world s reservoir rocks are water-wet with only few being oil-wet. In a water-wet brine-oil-rock system, water will occupy the smaller pores and wet the major portion of the surfaces in the larger pores. In areas of high oil saturation, the oil rests on a film of water spread over the surface. If the rock surface is preferentially water-wet and the rock is saturated with oil, water will imbibe into the smaller pores, displacing oil from the rock when the system is in contact with water. Primary recovery and water flooding are highly favored in water-wet reservoirs. If the rock surface is preferentially oil-wet, even though it may be saturated with water, the rock will imbibe oil into the smaller pores, displacing water from the rock when it is contacted with oil. Thus, a rock saturated with oil is water-wet if it will imbibe water and, conversely, a rock saturated with water is oil-wet if it will imbibe oil. In oil-wet reservoirs, however, the attractive forces between the rock surface and the oil tend to retard the movement of the oil resulting higher residual oil saturation therefore causing lower oil recovery. If no preference is shown by the rock to either fluid, the system is said to exhibit neutral wettability or intermediate wettability, a condition that is visualized as being equally wet by both fluids (Tiab & Donaldson, 2004). 10

23 2.4.2 Surface/interfacial Tension Petroleum reservoirs always contain two or three fluids phases namely; water, oil and gas. These fluids are immiscible in nature. Because of their immiscible nature, there exist some forces of interaction at the interfaces of these fluids. These forces are as a result of unbalanced molecular attraction of molecules at the fluid-fluid interface. In a liquid-gas interface, this force is termed, surface tension, while in an immiscible liquid-liquid interface, the force is termed as interfacial tension. The surface or interfacial tension has the units of force per unit of length, dynes/cm, and is usually denoted by the symbol σ. The magnitude of surface or interfacial tension depends on the fluid composition. There is always connate water present in the reservoir. Therefore, an oil reservoir will contain oil and water and maybe gas. And a gas reservoir will contain gas and water. During production, the surface or interfacial tension tends to retard the movement of the oil or gas. As the saturation of the oil/gas is reduced to some level, this surface or interfacial tension totally inhibits the movement of the remaining saturation. The oil/gas then becomes discontinuous and immobile (irreducible oil/gas saturation). This tension tends to reduce oil/gas recovery Capillary pressure Fluid pressure varies from fluid to fluid depending on the fluid density. When two immiscible fluids are in contact, there is a discontinuity in pressure between the two fluids. This discontinuity depends upon the curvature of the interface separating the fluids. The discontinuity is as a result of pressure difference between the two immiscible fluids. This pressure difference between the two fluids is termed as capillary pressure. It is the pressure difference between the non-wetting and wetting phase. That is, the pressure excess in the non-wetting fluid is the capillary pressure, and this quantity is a function of saturation. It is expressed as: P c P nw P ; Where Pc capillary pressure, Pnw pressure in the non-wetting fluid phase w and Pw pressure in the wetting fluid phase. Depending on the fluids present in the reservoir, there are three types of capillary pressure: Water-oil capillary pressure (denoted as Pcwo), Gas-oil capillary pressure (denoted as Pcgo) and Gas-water capillary pressure (denoted as Pcgw) 11

24 By convention, the capillary pressure in a water-wet rock is positive while it is negative in an oil-wet rock. Since most of the hydrocarbon reservoirs are water-wet, capillary pressure in the reservoirs is mostly positive. The capillary forces in a petroleum reservoir are the result of the combined effect of the surface and interfacial tensions of the rock and fluids, the pore size and geometry, and the wetting characteristics of the system (Ahmed, 2006). The higher the interfacial tension the higher the capillary pressure. Capillary pressure is inversely proportional pore size, that is, the smaller the pore sizes the higher the capillary pressure. This implies that, the less permeable the reservoir the higher the capillary. The displacement of one fluid by another in the pores of a porous medium is either aided or opposed by the surface forces of capillary pressure (Ahmed, 2006). Consequently, to maintain a reservoir partially saturated with non-wetting fluid while the medium is also exposed to wetting fluid, it is necessary to maintain the pressure of the non-wetting fluid at a value greater than that in the wetting fluid. In oil production, high capillary pressure impedes oil recovery since the water traps the oil behind as it tends to move ahead Relative permeability Permeability is a property of the reservoir that allows the transmission of fluid through it. This is termed as absolute permeability. When more than one fluid exist in the reservoir, the ability of the reservoir to transmit each of the fluids varies depending on the fluid properties. When one fluid moves in the reservoir in the presence of another fluid, that transmissibility is termed as effective permeability to that fluid. Relative permeability of a particular fluid is the ratio of its effective permeability to a base permeability (absolute permeability or permeability of air) of the porous medium. That is, the relative transmissibility of the various fluids when they are moving together. It is represented as: K K e r ; where Kr relative permeability, Ke effective permeability and K base K permeability. Effective permeability of any reservoir fluid is a function of the reservoir fluid saturation and the wetting characteristics of the formation. It is imperative, therefore, to specify the fluid saturation when stating the effective permeability and relative permeability of any particular fluid in a given porous medium. 12

25 According to Ahmed (2006), when wetting and non-wetting phase fluids flow together in a reservoir rock, each phase follows separate and distinct paths. The distribution of the two phases according to their wetting characteristics results in characteristic wetting and nonwetting phase relative permeabilities. The wetting phase tends to occupy the smaller pore spaces at small saturations, but these pore spaces do not contribute substantially to fluid flow. Small saturations of the wetting phase, therefore, do not have a significant effect on the flow of the non-wetting phase. Small non-wetting phase saturation, however, affect the flow of the wetting phase drastically since the non-wetting phase occupies the central or larger pore openings that contribute the major part to fluid flow in the reservoir. In water-wet reservoirs, the more water-wet the reservoir is, and the lower the water saturation the better the relative permeability of oil and hence the better the oil recovery Mobility and mobility ratios Fluid mobility is the ease with which the fluid moves through the reservoir. It encompasses rock and fluid properties. It is defined as the ratio of the fluid effective permeability to its viscosity, thus: Ke. Therefore, for a given effective permeability, the mobility is higher with light fluid than more viscous fluid. Oil is usually more viscous than water, therefore, at the same effective permeability, water tends to be more mobile than oil and will tend to out run the oil. Mobility ratio is defined as the mobility of the displacing phase divided by the mobility of the displaced phase. Mobility ratio is written as: M displacing displaced. Mobility ratios are typically defined with reference to saturations at specific locations of the displacement process. When the displacing fluid, in this case water, is more mobile than the displaced fluid, oil, M>1 and recovery is greatly affected. But when M</=1, that is, oil is as mobile or more mobile than water then, there is a piston-like displacement of oil and hence, oil recovery is greatly enhanced Viscous fingering Viscous fingering is a condition in oil production when water, the displacing phase is more mobile than oil, the displaced phase, due to viscosity differences. The water tends to 13

26 overrun the oil in an irregular manner towards the producing well. This together with heterogeneity in reservoir permeability traps lots of oil behind therefore lowering significantly, the oil recovery. Viscous fingering causes low sweep efficiencies which leads to poor oil recoveries. There are enhanced/improved oil recovery mechanisms that address the issue of viscous fingering Fluid displacement efficiency Fluid or microscopic displacement efficiency is defined as the ratio of the volume of oil displaced from the flood zone to the volume of oil initially in place in the flood zone. Fluid displacement efficiency is affected by rock wettability, capillary pressure, relative permeability, and mobility ratios of the fluids Volumetric displacement efficiency Volumetric or macroscopic displacement efficiency is the fraction of the reservoir volume swept by the displacing fluid. It is made up of two parts: Areal sweep efficiency, and Vertical sweep efficiency. Areal sweep efficiency is the fraction of the reservoir area contacted by the displacing fluid while vertical sweep efficiency is the fraction of the vertical reservoir section contacted by the displacing fluid. Volumetric displacement efficiency is therefore, the product of the areal sweep efficiency and the vertical sweep efficiency. The higher the sweep efficiency the better the oil recovery Total recovery efficiency Total recovery efficiency is the volume of oil displaced divided by the initial volume of oil in place in the swept portions of the reservoir. It is a product of the fluid displacement efficiency and volumetric displacement efficiency. In order to enhance oil recovery efficiency, there is the need to improve the sweep efficiency by altering the wettability, surface/interfacial tension, capillary pressure and relative permeability to generate favorable mobility ratios for good oil recovery. 14

27 2.5 Geology of the Niger Delta (Overview of Study Area) Location and General Overview The Niger Delta is located in the Gulf of Guinea at the southernmost part of Nigeria. The age range of the Delta ranges from Eocene to present, with a southwesternward prograde forming a series of depo-belts. These depo-belts cover an area of about 300,000 km 2 forming one of the largest regressive deltas in the world (Kulke, 1995). The sediments have an average thickness of about 10 km in the center of the depo-belts with an estimated sediment volume of 500,000 km 3 (Kaplan, et al., 1994). The onshore section of the Niger Delta is bounded from the south by the Benin Flank, a hinge line that trends east-northeast and is south of the West Africa basement massif. To the northeast it is bounded the Cretaceous on the Abakaliki High. There is a hinge line bordering the precambrian and delta to the south-east of the Calabar flank. The offshore section is bounded by the Cameroon volcanic line to the east, a two kilometer sediment thickness contour to the east and 4000-meter bathymetric contour to the south and southwest. The province covers 300,000 km 2, the geologic extent of the Tertiary Niger Delta (Akata-Agbada) Petroleum System inclusive Stratigraphy The Niger Delta Basin is composed of an overall regressive clastic sequence reaching a maximum thickness of 9,000 m to 12,000 m, covering an area of about 75,000 km 2. There are mainly three distinct formations in the Niger Delta petroleum system representing prograding depositional facies that are distinguished mostly by their sand-shale ratios. These formation are; Akata, Agbada and Benin formations. The Akata Formation forms the base of the delta. It is of marine origin composed of a thick shale sequence (potential source rock), turbidite sand (potential reservoirs in deep water) and minor amounts of clay and silt. This formation spans from Paleocene through to Recent. It underlies the entire delta, and is characterized by over pressure. It is approximately 6 km thick. The Agbada formation overlies the Akata. Its deposition occurred from Eocene and continues into the Recent. This is the main petroleum bearing formation in the Niger Delta. This formation represents the actual deltaic portion of the sequence consisting of paralic siliciclastics approximately 3.7 km in thickness. 15

28 The Agbada Formation is overlain by the Benin Formation. The Benin formation formed during the latest part of Eocene through to Recent. It is made of deposits of alluvial and upper coastal plain sands that are up to 2 km thick ( (Avlbovbo, 1978)) Depo-belts The three formations of the Niger Delta were deposited each in the five off lapping siliciclastic sedimentation cycles that make up the Niger Delta. These cycles (depo-belts) are km wide (Stacher, 1995). These are defined by syn-sedimentary faulting (growth faulting) that resulted from the different rates of subsidence and sediment supply (Doust & Omatsola, 1990). Each depo-belt is a distinct unit that corresponds to changes in regional dip of the delta. The northern part of the delta which overlies relatively shallow basement, has the oldest growth faults that are generally rotational, evenly spaced with increasing steepness seaward. The depo-belts in the central portion of the delta have well-defined structures such as successively deeper rollover crests that shift seaward for every given growth fault. The most structurally complex part of the delta is the distal part. This is as a result of the internal gravity tectonics on the modern continental slope Hydrocarbon Source Rock It is believed that the Niger Delta petroleum has two main source rocks, the marine shale inter-bedded with paralic sandstone in the Agbada Formation and the marine Akata shale. Evamy et al., (1978), based on organic matter content and type, suggested that both the Akata Formation shale and the shale inter-bedded with paralic sandstone in the Lower Agbada Formation were the source rocks for the Niger Delta oils with variable contributions. Stacher, (1995), however, suggested that the Akata Formation is the only source rock with a significant volumetrically contribution. His argument was based on the depth of burial which is consistent with the depth of the oil generation window as well as the level of maturity of the oil Reservoir Rock The reservoir rock of the Niger Delta petroleum province is made of unconsolidated sands predominantly in the Agbada Formation. The depositional environment and the depth of burial control the characteristics of the reservoirs in the Agbada Formation. The reservoir 16

29 rocks are mostly Eocene to Pliocene in age (Evamy, et al., 1978). The most important reservoir types are described by Kulke (1995) as point bars of distributary channels and coastal barrier bars intermittently cut by sand-filled channels. Porosity only decreases sparingly with depth because of the young age of the sediments and the coolness of the delta complex. Fig. 2.1 Niger Delta Depo-belts 2.6 Formation of Turbidites (Thin-Bed Laminated Reservoirs) Newtonian flows known as turbidity current in which sediments are buoyed by turbulence in the current are what cause the formation of turbidites. This current causes the downslope movement of sediments due to gravity and density difference between the flow and the surrounding ambient fluid. At low velocity, the flow is no longer able to support the denser coarse sediments. They therefore, settle out from suspension (Middleton, 1993; Shanmugam, 1997; Boggs, 2006). Sediments which are deposited by turbidity currents are called turbidites. Low density turbidity flows are associated with low sediment concentration. Deposits from these are characterised by thin-bed, graded deposits with lamination and cross-bedding. These turbidites characteristically represent over bank deposits or thin sheet deposits which is further away from the source (Lowe, 1976 and Boggs, 2006). 17

30 Fig. 2.2 Supposed structure of a turbidity current (Boggs, 2006) Coarse-grained, massive and poorly laminated turbidites are those deposited in close proximity to the sediment source where suspended sediment concentrations are high. Coarse-grained turbidites are deposited within the main channel but could also be observed at considerable distances from the source. There may also be deposition of thin, finegrained turbidites near the source, where turbidity currents overflow the banks of a channel. Away from the source, turbidity current deposits become progressively more dilute and spread out over the seafloor (Boggs, 2006). 2.7 Some Concepts Applied for Oil Recovery from Thin-Bed Reservoirs Commingled Production from Vertical Wells In a multilayered reservoir, production from a vertical well is prudential if the layers are commingled to flow into the same wellbore. Commingled productions in multilayered reservoirs, by way of definition, are systems comprising of two or more zones of hydrocarbon-producing formations through which a well is drilled and completed in such a manner to allow the production from each zone to flow through the same tubing string to the surface. 18

31 With this type of completion arrangement, each zone s properties such as porosity, permeability and thickness affect the final production at the wellhead and the performance of the reservoir in general. According to Onwunyili and Onyekonwu (2013), there is currently, a state-of-the-art flow rate and pressure measurement equipment that can be installed downhole for manipulation of the commingled production system, so as to be able to carry out production testing of each zone and production allocation to each zone. There is the possibility for the reservoir fluids from different layers interact either in the reservoir (cross flow) or in the wellbore. The controlling factors of this interaction is pressure difference between the layers and the vertical permeability of the shale intercalations. This interaction between the fluids in the zones pose a challenge in the modeling of the production from each zone. Pressure difference between the zones of the reservoir allows wellbore inter-flow during any stage of the reservoir life. Reservoir cross flow on the other hand, will occur due to reservoir pressure difference between the productive zones and presence of substantial vertical permeability in the shale breaks until a balance reservoir pressure is finally established. This implies that the pressure decline for each zone affects the overall production of the well and would amount to further flow or inter-flow between the reservoir zones. It therefore, results in early depletion of the energy some of the zones (Onwunyili & Onyekonwu, 2013) Production from Thin Beds Through Horizontal Well Almutairi, et al. (2007) cited cases of horizontal wells placed in thin bed-laminated reservoirs that have achieved a lot of success through the following: 1. Minimal gas coning and cusping due to reduced drawdown. 2. Alleviated sand problems as a result of the same reduced drawdown. 3. A larger volume of the reservoir drained due to the well geometry. Almutairi et al., (2007) also observed that control strategies that aim to delay the unwanted fluids breakthrough prior to controlling the unwanted fluid s production yields the greatest value in thin oil column reservoirs. According to Tewari et al. (2005), a horizontal well with ESP that was placed in a thin bed (about 0.5 m thick) in a certain field in India produced 1800 bopd without any water cut. A production that is 4-5 times higher than that achieved using vertical wells in the same field. 19

32 According to Almutairi et al. (2007), installation of intelligent completions in a horizontal well that produced successfully from a thin oil column in a compartmentalized reservoir is that of a well in the Iron Duke Field with a forecast to produce an extra 38% cumulative oil compared to a conventional well. This was done by managing production from the five production zones, all of which had different reservoir characteristics Intelligent Well Completion According to Yadav & Surya (2012), intelligent completion may be defined as a completion system capable of collecting, transmitting, and analyzing wellbore production, reservoir, and completion-integrity data, and enabling remote action to enhance reservoir control and well production performance. Intelligent-well technologies actively modify the well configuration and performance through flow control and monitoring of responses and performance through downhole data acquisition. Analysis of these data combined with predictive reservoir simulations makes the value of the technology immeasurable. Intelligent wells are more advantageous than conventional well completions in many regards. These basically include, but not limited to, accelerated production, increased recovery, reduced or eliminated intervention, and improved reservoir performance. The applications and benefits of remote completion monitoring and control depend on the type of wells considered in each development. Remote completion is particularly beneficial in the cases of multizone or multilateral wells (both injectors and producers). Incremental initial-well capital costs for intelligent-completion systems vary from U.S. $200,000 for a permanent downhole-gauge system to U.S. $2,500,000 for a fully specified multizone remote-controlled completion (Yadav and Surya, 2012). But the benefit accrued as a result of the intelligent completion far outweigh the capital cost. Intelligent completion also goes a long way to beat down well operating cost in many ways. Therefore, it cannot be overemphasized that the technology is very cost-effective. According to Yadav and Surya (2012), a large percentage of the planned Intelligent Well System (IWS) completions are used to control wells that penetrate multiple production zones with commingled production. This will obviously result in, accelerated production, efficient production of marginal reserves, increased recovery and improved reservoir 20

33 knowledge. These are actually the main motivation behind the application of The IWS technology. Intelligent-well technology has proved to deliver improved hydrocarbon production and increased recovery with fewer wells in addition to the interventionless nature of the completions in the high-cost arena of subsea and deepwater wells where well interventions are both expensive and technically challenging. Roughly 70% of intelligent well completions are in high-cost critical wells (Yadav and Surya, 2012). Deepwater wells account for most of these. The remaining 30% of intelligent well systems are installed in mature oil fields to boost hydrocarbon recovery or to accelerate production. Intelligent well technology can improve the efficiency of water-flooding and gas-flooding programs in heterogeneous or multilayered reservoirs when applied to injection wells, production wells, or both. Production and reservoir data acquired with downhole sensors can improve the understanding of reservoir behavior and assist in the appropriate selection of infill-drilling locations and well designs (Yadav and Surya, 2012). 2.8 Oil Recovery Mechanisms Alvarado & Manrique, (2010) stated that due to the capital intensive nature of other IOR/EOR methods aside water-flooding and gas injection in offshore environment coupled with the volatility of the energy markets, the risk associated with this type of projects is excessive, reducing the probability of their implementation. Therefore, water-flooding and gas injection and their combined injection schemes (WAG and SWAG) in conjunction with injection profile modification and/or gas or water shut-off (i.e., foams, gels, and in-depth gel treatments such as BrightWater ) strategies will continue to support offshore production in the short term. This indirectly applies to turbidites (thin bed) reservoirs since these are mostly offshore reservoirs. The Water Alternating Gas (WAG) process is an improved oil recovery method defined as a cyclic method of injecting alternating cycles of gas followed by water and repeating this process several cycles desired by the operator. WAG injection is an oil recovery method initially aimed to improve sweep efficiency during gas injection. In simultaneous water and gas injection (SWAG) technique, water and gas are injected at the same time into the reservoir through a single injection well either premixed at the surface or separately in what is known as selective simultaneous water and gas injection (SWAG). 21

34 Because the residual oil after gas-flooding is usually lower than the residual oil after waterflooding, and three-phase zones may obtain lower residual oil saturation, WAG injection has the potential for increased microscopic displacement efficiency. Thus, WAG injection can lead to improved oil recovery by combining better mobility control and contacting upswept zones, and by leading to improved microscopic displacement (Srivastava & Mahli, 2012). WAG injection can thus lead to improved oil recovery through combination of factors such as mobility control, contact of unswept zones, improved microscopic displacement efficiency and oil vaporization due to mass transfer between reservoir oil and injected gas Water Alternating Gas Injection (WAG) and Simultaneous Water and Gas Injection (SWAG) Sohrabi et al. (2012) in their paper Performance Of Swag Injection Versus Alternating And Continuous Injection Of Water And Gas In Low Gas-Oil Ift And Mixed-Wet Systems observed that for many oil reservoirs, poor sweep efficiency has been a problem in gas/water injection processes. They attributed this situation to high gas/water mobility relative to the oil. Therefore, only continuous gas injection or only continuous water flooding may not result in economically significant additional oil recovery especially in highly heterogeneous reservoirs. In order to mitigate this problem, gas can be injected alternately with water (WAG) (Sohrabi, et al., 2012). Another option is the re-injection of the produced associated gas together with water in a SWAG (simultaneous water and gas) injection scheme would provide reservoir pressure support, better sweep and hence increased recovery. Both WAG and SWAG are believed to reduce the gas mobility and hence increase the sweep efficiency. Sohrabi et al. (2012) quoted from a laboratory study carried out by Caudle & Dyes (1958) that the increase in the sweep efficiency for a five-spot pattern can reach 90% with SWAG, whereas, if continuous gas injection is implemented, only 60% of oil is recovered. Field studies on miscible CO2 flooding shows that SWAG appears to provide better control of the gas mobility than WAG, resulting in improved sweep efficiency as well as more steady gas production and GOR response (Sohrabi, et al., 2012). The main contributions to increased recovery come from improved sweep efficiency, oil swelling and reduced residual oil saturation. It was also observed that combined water and 22

35 gas injection (WAG or SWAG) lowers injectivity volumes compared to single-phase injection. Sohrabi et al. (2012) performed coreflood experiments, at near miscible conditions, performed on a 65 md and a 1000 md core sample. They conducted WAG injection, SWAG injection and SWAG-tail gas injection scenarios. From their experiments, the following conclusions were drawn: 1) In order of decreasing performance, the various methods tested are arranged as follows; WAG, water flooding, SWAG and gas injection 2) The WAG performance is be adversely affected if WAG injection begins with a gas injection period (instead of water), in mixed-wet rocks. Another study was conducted by Srivastava & Mahli (2012) in which they carried out different scenarios of WAG in the laboratory on core samples from a mature light oil field. The various scenarios that were tested are single cycle WAG, five cycle WAG (with hydrocarbon gas and CO2 separately), tapered WAG (with increasing and decreasing WAG ratio) under reservoir temperature and pressure conditions. They preceded the WAG injection with water-flooding. From their experiment, they observed and concluded that the five-cycle WAG with CO2 gave the maximum incremental displacement efficiency over the water-flood. The different WAG injections scenarios were ordered in terms of decreasing effectiveness as follows; five-cycle WAG with CO2, five-cycle WAG with hydrocarbon gas, tapered WAG (decreasing WAG ratio), tapered WAG (increasing WAG ratio) and single-cycle WAG. They also observed that the number of cycle had an effect on the recovery efficiency with the five-cycle being more efficient than the one-cycle even though the same volumes of water and gas were injected in both cases. They attributed the better efficiency of the fivecycle CO2 to possible better miscibility of the CO2 with the oil at reservoir conditions than that of hydrocarbon gas. Srivastava & Mahli (2012) recommended a field-wide simulation of the various WAG injection methods since the laboratory tests are limited in scale and conditions. Mahdavi, et al. (2012) also did some work on WAG and SWAG injection. In their work, they simulated various scenarios of WAG and SWAG and compared the results to obtain 23

36 an optimal injection method between the two. They also compared the ultimate oil recovery, residual oil saturation, daily and total oil production for the various scenarios. They used a commercial simulator (FloGrid Software-An Eclipce Module) in their study in which they simulated different injection scenarios. The following WAG ratios were used; 1:1, 2:1, 3:1, 4:1, 1:2 and 1:3. From their work, the following conclusion where drawn: This field case study shows that gas injection before water injection profits from better sweep efficiency than reverse injection order. The following is the order of decreasing recovery efficiency discovered from the study: gas injection only, SWAG, WAG, water injection only, natural depletion. Amongst different WAG injection scenarios, SWAG method with associated injection ratio of 2:1 has highest recovery factor with lowest residual oil saturation. Another simulation of WAG and SWAG was carried out by Nangacovie (2012) in her thesis work tittled Application of WAG and SWAG Injection Techniques in Norne E- Segment. Nangacovie (2012) used a black-oil, three phase (oil, gas and water) model, programmed with ECLIPSE100 to simulate the E-segment reservoir. Her model was discretized by grid blocks with 8733 active cells. In total, the E-segment had 8 wells. These comprised one observation well, 2 injector and 5 producers. In order to determine the best WAG cycle time in her study, she considered three cases: Three months WAG cycle, Six months WAG cycle and One year WAG cycle. These three cases were simulated using the original Eclipse model of the E-Segment, predicting 14 years of production injection response, using a constant low injection rates of 2000 sm 3 /day for water and 4500 sm 3 /day for gas; and high injection rate sm 3 /day of water and sm 3 /day of gas. In order to find the optimal WAG ratio in the study area, she run a number of ratios in the simulator to determine the one that yields the highest recovery. The iterations were performed by injecting at 6 months cycle time interval. Nangacovie (2012) drew the following conclusions from her study: 24

37 Recovery from a WAG process isn t a function of cycle time when low injection rate is used, but, when high injection rate is used 3 months cycle results in a slightly higher residual oil recovery. Simulation results showed that Norne E-segment would have a maximum recovery of 73% at a 1:3 SWAG ratio when high gas injection rates are considered. The implementation of SWAG injection gave 73% oil recovery, the best oil recovery while WAG injection technique gave 63% oil recovery. In all the work done on WAG and SWAG evaluation, it is obvious that the applicability of these methods varies from formation to formation. In order to apply the methods to any type of formation, there is the need to perform a simulation study for the particular reservoir type and the economic feasibility of these methods before their field-wide application. 25

38 CHAPTER 3 METHODOLOGY AND DATA ANALYSIS 3.1 Recovery Mechanisms Thin Bed-Laminated Reservoirs Active Aquifer Presence In a thin bed-laminated reservoir with an active aquifer, the aquifer serves to supply most of the reservoir s energy for oil production. It dominates the other drive mechanisms. The reservoir is therefore produced under water drive. This is most especially the case when there is a small or no gas cap. Due to the intra- and inter-layer permeability heterogeneity in conjunction with unfavorable mobility ratio (M>1) between water and oil, there is bound to be what is known as viscous fingering. This phenomenon usually causes the trapping of significant quantities of movable oil in the reservoir. Another phenomenon likely in these kinds of reservoirs is early water breakthrough in the more permeable layers. These are a great deal of impediments to oil recovery. Mitigating early water breakthrough and minimizing the volume of oil bypassed by the water will improve the oil recovery by significant amounts Gas Cap Presence Gas cap becomes the main drive in a reservoir when the reservoir is contains a gas cap with a weak or no active aquifer available. The gas cap may still contributes significantly to oil recovery in the presence of an active aquifer provided the ratio of gas reservoir volume to that of oil is large. Under this kind of drive mechanism in thin bed-laminated reservoirs, the looming threat to good oil recovery is gas coning which would eventually lead to increased produced GOR (Gp) and low oil production rates. The more permeable layers turn to have earlier gas breakthrough than the less permeable layers. Gas coning would eventually kill the well Volumetric Depletion and Solution Gas Contribution to Oil Recovery When the reservoir pressure is above the bubble point of the hydrocarbons, it is said to be under-saturated and can dissolve more gas. All the gas in such a reservoir is in solution. The only primary energy available for oil production in the case of no aquifer support is the expansion of the formation, oil and connate water. This gives rise to what is known as depletion drive. It could be supported by gravity drainage if the oil column is significant. When the reservoir pressure drops below the bubble point pressure however, the oil becomes saturated with dissolved gas. In a saturated reservoir with no significant gas cap 26

39 and no/weak aquifer support, the expansion of gas evolving from solution provides the energy required for oil production in a drive mechanism known as solution gas drive. The main challenge to oil recovery from these kinds of reservoirs is low energy to recover most of the oil. The energy is not enough to give a good recovery. It therefore needs to be supplemented in order to improve the recovery. Water-flooding and gas-flooding are the commonest improved oil recovery methods available especially for offshore reservoirs which include the Niger Delta turbidites. Another possible means of improving oil recovery is a combination of these two in an alternating cyclic manner, Water Alternating Gas (WAG) injection. These methods were therefore simulated for the thin-bed laminated (turbidite) reservoir model in ECLIPSE 100 to obtain the best and most economical IOR method to be implemented in this reservoir. 3.2 Description of the Reservoir Model Properties The reservoir model that was used for the purpose of this study is a black-oil, 3-phase, 3-D model of a Niger Delta turbidite reservoir. It was gridded as follows: The grid size is given in the table below. The model is shown in Fig. 3.1 below. Table 3.1 Model Grid Size Grid Range (ft) DX DY DZ The depth to the tops of the reservoir ranges from 4365 ft at the shallowest part to 5000 ft at the deepest part with an average reservoir pressure of psia. The datum was taken to be 4500 ft. The reservoir is divided by faults into three regions. The region and fieldwide average reservoir properties are given in Table 3.2 below. The low average vertical permeabilities are as a result of averaging the shale permeabilities which are majority together with the sand permeabilities. The sand vertical permeabilities range from 150 md to 500 md while the shale vertical permeabilities range from to 10 md. Table 3.2 Field and Regions Reservoir Properties of Model REGIONAL AVERAGED GRID QUANTITIES REGION PERMX, md PERMY, md PERMZ, md PORO DZ, ft FIELD

40 Fig. 3.1 Reservoir Model The reservoir fluids originally in place and the movable oil with respect to water and gas are presented in Tables 3.2 & 3.3 respectively. Table 3.3 Reservoir Fluids in Place FLUID OIL ORIGINALLY IN PLACE WAT, OIL, STB GAS, MSCF STB LIQUID VAPOUR TOTAL TOTAL FREE DISSOLVED TOTAL 8.83E E E E E E E+07 Table 3.4 Movable Oil Originally in Place with Respect to Water and Gas REGION MOBILE OOIP (W.R.T. WATER), STB MOBILE OOIP (W.R.T. GAS), MSCF FIELD 5.92E E E E E E E E+06 Table 3.5 Reservoir Fluid Properties DENSITY OIL WATER GAS Pressure Rs Viscosity Oil FVF Well Placement In the simulation model, 11 producer wells and 6 injector wells were placed taking into consideration the oil, gas and water saturations, reservoir pressure, permeability and transmissibility. The wells were perforated in zones of high oil saturation and high permeability as well as high transmissibility. The placement was not based on any regular 28

41 pattern since the reservoir and the oil occurrence are not regular. The well placement is shown in Fig. 3.2 below. Fig. 3.2 Well Placement in Reservoir Model 3.3 Well Controls The production wells were controlled by liquid production rate and bottom-hole pressure (BHP). The bottom-hole pressure target was 1500 psia while the liquid production rate was 5000 stb/day. ECLIPSE key word WECON was used to control the upper limit of water production and the lower limit of oil production rate. The commands issued were that: if water-cut exceeds 90%, the worst offending connection should shut; if oil production falls below 200 stb/day, the well should shut. There was no limit placed on gas production. The injectors were controlled by reservoir fluid volume rate (RESV) and BHP as well. Here, the BHP target was 2000 psia and the RESV varied in order to select the RESV with the best results. 3.4 Water-Flood, Gas-Flood and WAG Injection Sensitivity Analyses The rate of injection of water and gas is critical to the efficiency of water- and gas-floods. These must therefore be optimized to yield the best recovery efficiencies. Their effects on recovery efficiency were studied as in the following sections Water Injection Rate for Water-Flooding In the injection well control section of the simulation, reservoir fluid volume rate (RESV) was used to control the injection. Four runs were made with different RESV. The RESV used were rb/day, rb/day, rb/day and rb/day. With this the the optimal injection rate would be selected and used for the comparison. 29

42 3.4.2 Gas Injection Rate for Gas-Flooding Similar to the water injection rate optimization, four different RESV were simulated so that the optimal rate could be selected. The rates simulated were; rb/day, rb/day, rb/day and rb/day. The results of these simulations are presented in the next chapter. Below is Fig. 3.3 showing a schematic of a gas-flooding process. Fig. 3.3 A Schematic of Gas-Flooding Process (Abdulkadir, 2014) In the application of WAG as an IOR method, the resulting recovery greatly depend on several factors including: water and gas injection rates; time to initiate the WAG process; the WAG ratio; and the WAG cycle timing. These parameters should be optimized one after the other to produce the best results from the WAG process. These parameters were therefore optimized in simulation processes as described in the following next section WAG Ratio WAG ratio is defined as the ratio of the volume of injected water to the volume of injected gas. High WAG ratios may cause oil trapping by water, blocking or not allowing sufficient solvent-oil contact, causing the production performance to behave like a water flood. Very low WAG ratios, on the other hand, may cause gas channeling resulting in early gas breakthrough in which case, the production performance would tend to behave as a gasflood, with rapid pressure declines, which would lead high decline in oil production rates. The optimal WAG ratio is reservoir dependent. Studies show that the WAG ratio strongly depends on reservoir s wettability and availability of the injection fluids. To find the optimal WAG ratio, it is necessary to perform sensitivity analysis, proposing different relations of WAG ratios to study the effect on oil recovery. 30

43 The following ratios; 1:1 ( rb/day water: rb/day gas), 1:2 ( rb/day water: rb/day gas) and 1:10 (20000 rb/day water: rb/day gas) were simulated in ECLIPSE 100. The results are presented in the next chapter WAG Cycle Time The time to switch from injection of water to gas in crucial to the recovery obtained from the WAG process. In this study, different cycle lengths were simulated to determine the best injection timing for each fluid. The cycle length that were simulated are tabulated below. The results of the cycle time optimization are shown in chapter 4. Table 3.6 WAG Cycles Water Timing (Days) Gas Timing (Days) Water and Gas Injection Rates The rate of fluid injection is another important and sensitive parameter in the evaluation of WAG performance. The injection rates need to be optimized to yield the best results from the WAG process. Iterative simulation of different injection rates in terms of reservoir volume rate of injected fluid would result in the optimal injection rates for the water and gas. Four simulation runs were made with the following reservoir volume injection rates in Table 3.6 and the results are presented in the next chapter. Table 3.7 Water and Gas Rates for WAG Water Rate, rb/day Gas Rate, rb/day The figure below shows a schematic of a WAG process. Fig. 3.4 A Schematic of a WAG Process 31

44 3.5 Comparative Analysis After the optimization studies of gas-flooding, water-flooding and WAG injection, the optimal procedures selected were then simulated and their recovery efficiencies and other parameters compared. The optimal procedures used are summarized below. Table 3.8 Optimal Injection Procedures Water rate for water-flood rb/day Gas rate for gas-flood rb/day WAG ratio 1:14 WAG cycle 200 days of water: 50 days of gas WAG injection rate rb/day of water & rb/day of gas 32

45 CHAPTER 4 RESULTS AND DISCUSSIONS 4.1 Optimization Results of the Factors Affecting Gas-flood, Water-flood and WAG Efficiency Water and gas injection rates as well as WAG injection processes were optimized as described in Chapter 3 above and the results are presented in the following sections Gas Injection Rate in the Gas-Flooding Obersation: From the field oil recovery efficiency (FOE) and plots in Fig. 4.1, it is observed that increasing the reservoir gas volume rate (RESV) increases the FOE. However, increasing RESV from to rb/day does not result in a commensurate increment in FOPT and FOE. The increment is only marginal. Fig. 4.1 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various Gas RESV Fig. 4.2 A Plot of Field Pressure Against Time for Various Gas RESV 33

46 From the reservoir pressure plot in Fig. 4.2, it is observed that gas injection initially increases the reservoir pressure (FPR) immediately and drops it off gradually till the end of the simulation run. Higher reservoir fluid volume rates corresponds to higher reservoir pressure. This translates into higher FOPT/FOE until the reservoir fluid volume rate increases above rb/day where an increase in reservoir fluid volume rate does not result in any significant increase in FOPT/FOE. Discussion: The observations made from the FOE plots of gas injection indicate that gas injection at rb/day is optimal for oil recovery from this reservoir in a gas-flooding process. The insignificant incremental effect of higher reservoir fluid volume rates may be explained by the fact that the optimal rate provides all the sweep efficiency needed for the movable oil and any additional gas would not have any substantial effect on oil recovery Water Injection Rate in the Water-flooding Observation: When the optimization of water RESV was done for the water-flooding, it was observed, as seen in Fig. 4.3 & 4.4, that an increase in the RESV from to rb/day yielded an increase in the FOE corresponding to a significant increase in reservoir pressure. RESV of rb/day, however, has the same FOE as that of rb/day. The pressure trends in Fig. 4.4 show that the FPR drops steeply at the beginning of the injection, rises steadily after a few days and falls gently till the end of the simulation run. Discussion: The observations indicate that water injection above rb/day RESV has no incremental effect on oil recovery. Actually, at RESV greater than rb/day, the well control is switched from RESV to BHP which makes any increase in RESV inconsequential to the oil recovery even though there is an increase in the reservoir pressure. This may be due the lack of voids to be filled up by the excess water and the lack of significant compressibility of water as compared to gas. It may also be as a result of the bottom-hole pressure constraint imposed on the wells. The increase in reservoir pressure without a corresponding increase in oil recovery may be due to the fact that since the well is now controlled by the BHP, the water required to reach the BHP target is not enough to give an incremental sweep efficiency. The coincidence of the recovery efficiencies of and rb/day implies that under BHP control, the water is required to reach the injector BHP of 2000 psia is equivalent to the water that give the sweep efficiency in the case of rb/day injection. 34

47 Fig. 4.3 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various Water RESV Fig. 4.4 A Plot of Average Reservoir Pressure Against Time for Various Water RESV Fig. 4.5 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various WAG Ratios 35

48 4.1.3 WAG Ratio Observations and discussions: It can be observed from the FOE plots in Fig. 4.5 that WAG ratios of 1:1 and 1:2 ( rb/day water: rb/day gas and rb/day water: rb/day gas respectively) have the same FOE. WAG ratios of 1:10 (20000 rb/day water: rb/day gas), however, yielded a recovery just slightly lower than the others WAG Cycle Timing Observations and discussions: From the FOE plots of the various WAG cycles run in the simulation, it is observed that the WAG cycle does not really have a significant impact on the oil recovery. All the five cycles simulated have apparently the same FOE as seen in Fig Injecting gas for 50 days and water for 200 days appears to give the highest FOE, hence, it is the optimal cycle for the wag processes. Due to the higher compressibility and higher mobility of the gas, it is able to move faster in the reservoir than the water. It therefore, requires less time of injection than the water which has a lower mobility and is less compressible. Fig. 4.6 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various WAG Cycles Water and Gas Injection Rates Observations and discussions: The volume rate of reservoir fluid injected has only little effect on the oil recovery provided the rates are within the optimal rates for gas- and waterflooding. As seen from Fig. 4.7, three of the four rates simulated have about the same FOE (50000 rb/day water: rb/day gas; rb/day water: rb/day gas; and rb/day water: rb/day gas). The fourth one, rb/day water; rb/day gas gave a higher FOPT/FOE. This ratio gave a better recovery probably because 36

49 the water injection periods are controlled by RESV unlike in the cases of higher water rates where the injectors are controlled by BHP. Fig. 4.7 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Various WAG Rates These results are similar to those of the WAG ratio. Therefore, from these results, the optimal WAG rates are rb/day water; rb/day which are in a ratio of 1: Preferable Fluid to be Injected First Fig. 4.8 Plots of Field Oil Recovery Efficiency (FOE) Against Time for Gas-First WAG and Water-First WAG Observations and discussions: Either of the two fluids (water and gas) could be used to initiate the WAG process without any consequences. From Fig. 4.8, it is observed that either starting the WAG process with water or with gas gave the same FOE and FOPT at the end of the 6000 days simulation run. The field water cut (FWCT), field reservoir pressure (FPR) and field oil production rate (FOPR) are about the same for both cases as shown in Fig. in the appendix. 37

50 4.2 Comparison of Optimal Water, Gas and WAG Injection Obervations After optimizing on the various factors that affect WAG performance, an optimal WAG injection was made as follows: rb/day of water RESV, rb/day of gas, that is, in a WAG ratio of 1:14. The process started with gas injection; gas was injected for 50 days and water injected for 200 days. The optimal water-flood and gas-flood recoveries were plotted together with the optimal WAG recovery and the results are shown below. Fig. 4.9 A Plot of Field Oil Recovery Efficiency Against Time for Natural Depletion, Gas- Flood, Water-flood and WAG From the FOE and FOPT plots in Fig. 4.9 & 4.10 respectively, it can be observed that all the three recovery mechanisms have close recovery efficiencies and cumulative oil produced. Water-flooding however, came top with a recovery factor of 57.56% after 6000 days followed by gas-flooding with a recovery factor of 54.16%. WAG injection came last with a recovery factor of 52.82% slightly below gas. Initially, gas-flooding gave better oil recovery than the rest until after about 1400 days (3.8 years) when water-flooding equals its recovery efficiency. All the IOR methods gave an additional recovery of at least 5.90% over the natural depletion. 38

51 Fig A Plot of Field Oil Production Total Against Time for Natural Depletion, Gas- Flood, Water-flood and WAG From the pressure plots in Fig. 4.11, it is observed that the reservoir pressure (FPR) rose sharply within a few days and drop off gradually till the end of the simulation run in the case of gas-flooding while in the case of water-flooding, the pressure drops steeply at the beginning of the injection, rises steadily above that for gas-flooding after a few days and fall gently till the end of the simulation run. The pressure behavior in the water-flood is almost the opposite of gas-flood. The slow picking up of pressure during water injection is as a result of the relatively low mobility of water. It takes time for the reservoir to respond to the effect of the water injection unlike gas which takes effect almost immediately. The pressure trend of the WAG operations shows a zig-zag shape following the almost instantaneous rise in pressure due to gas injection which causes the hike in pressure and the down-turn results from the initial fall of pressure in the water injection process. This process repeats over and over again resulting in the zig-zag pressure trend we have here. Fig shows plots of water-cut and oil production rates for water-flood, gas-flood and WAG. The water-cut from the WAG and water-flood are almost the same throughout the 6000 days of simulation. The water-cut from these floods on the 6000th day is about The gas-flood, however has a lower water-cut of about 0.91 on the 6000th day. Initially, gas-flood gives a slightly higher oil production rate than water-flood but after about 500 days, the oil production rate due to water-flood comes up slightly above that of gas-flood. The production rate from WAG falls below those of water-flood and gas-flood. 39

52 Fig A Plot of Average Reservoir Pressure Against Time for Natural Flow, Gas-Flood, Water-flood and WAG Fig Plots of Field Water-Cut & Field Oil Production Rate Against Time for Natural Flow, Gas-Flood, Water-flood and WAG The recovery factors, production rates, total oil produced, reservoir pressure and water-cut at the 6000th day of the simulation are summarized in Table 4.1 below. Table 4.1 Summary of Recovery Factors and Other Parameters of the Various Recovery Methods Recovery Method TIME, FOPR, FOPT, FPR, FWCT, FOE DAYS STB/DAY STB PSIA % Natural Flow E Gas-Flood E Water-Flood E

53 WAG E Recovery Method Additional Additional TIME, Additional FOPT, FOPR, DAYS FOE STB STB/DAY Natural Flow E E+00 Gas-Flood E E+01 Water-Flood E E+01 WAG E E+02 At 90% field water-cut, there is still quite significant oil rates. Their corresponding pressures too are still quite high. These results are presented on Table 4.2 below. Table 4. 2 Recovery Parameters at 90% Water-Cut Method TIME FOE FOPR FOPT FPR FWCT Nat. Dep E E-01 Gas E E-01 Water E E-01 WAG E E Discussions The results indicate close recovery efficiencies for the three IOR methods simulated. Water-flooding is able to hold the pressure fairly constant over the simulation period, hence the steady increase in the recovery factor. This coupled with a fairly better mobility ratio than gas makes water-flood the most efficient IOR method for this reservoir. The possible reasons for gas-flood having the highest recovery efficiency at the beginning could be because of the spontaneous increase in pressure caused by the gas injection at the initial stages. This pressure is however not been sustained sufficiently and it drops below the water-flood pressure bringing down the gas-flood efficiency below that of water-flood. The non-sustainability of pressure could be attributed to the high reservoir permeabilities and high gas compressibility compared to water. Gas-flood turns to perform better than WAG even though the reservoir pressure is higher during WAG injection. This is due to continuous lightening of the oil and sweeping of the oil bank ahead of the gas in continuous gas injection unlike in the case of WAG where the gas tends to move up towards the top of the reservoir during the period of water injection due to high vertical permeability. The poorer performance of WAG compared the gas-flood and water-flood in the long run could be attributed to the high vertical-horizontal permeability ratio in the reservoir sands. 41

54 Due to the relatively high vertical permeability, gravity segregation occurs in the injected fluid where the injected gas tends to move upward to the top of the reservoir while injected water tends to move downward. In this case, the required effect of the gas and water in the reservoir is not achieved. The lightening of the oil by the gas is not effective and the effective continuous sweep of the water is not also achieved. These result in the low recovery from WAG injection. The poor performance could also be attributed to the pulsating effect of the reservoir pressure caused the alternating injection of water and gas. The pulsating effect destabilizes the equilibrium established for continuous and smooth flow of oil from the reservoir thereby lowering the recovery performance of WAG. 4.3 Economic Analysis Due to the closeness of the recovery efficiencies from the various recovery methods simulated, there was the need to perform an economic analysis to determine the most economically profitable method among them. In performing the economic analysis, profit made by implementing each IOR method was determined by estimated the cost of drilling and completing the 6 injectors and the operating cost of each method and the revenue generated by the additional recovery made by each method. The drilling and completion cost were estimated from a model proposed by (McCoy & Rubin, 2008). In their model, the cost of drilling and completion, C, is given by C = a e bd ; where a and b are constants and D is the depth of the well in meters. Another model proposed by (Anon., 2007) for the estimation cost of equipment installation was used to estimate the cost of equipment installation. This model is Lease Equipment Cost ($/well) = 9, depth (metres). The operating costs of each of the methods were also estimated. The additional oil recovered was calculated by subtracting that recovered by natural depletion from that recovered by each of the methods. An estimated oil price was multiplied by the additional oil recovered to obtain the additional revenue generated from the IOR methods. The additional profit generated by the IOR methods is therefore, the generated revenue less the total cost of drilling and operating the injectors. All these are summarized in Tables 4.3 & 4.4 below. Table 4.3 Input Parameters for Economic Analysis Well Depth a, $ b Inflation Factor m Oil Price, $ ft OPEX, $/stb Gas Water CAPEX, MM$ D & C Equip t

55 Table 4.4 Profit Estimations Recovery Method Gas- Flood Water- Flood No. Of Well WAG 6 Cost of Injector Wells (D & C), $ Drilling & Completion, MM$ Equip t Installation, MM$ Operating Costs, MM$ Total Cost MM$ Additional FOPT, MMSTB Additional Revenue From IOR, MM$ Additional Profit From IOR, MM$ , , After obtaining the additional profit, probability distributions were fitted on some of the input parameters like the inflation factor, the constant (a) in the drilling cost estimation, the operating costs of water and gas injection and the oil price. The distributions fitted are shown on Table 4.5 below. A simulation of iterations were made software and the results are presented in Table 4.6 below. Table 4.5 Stochastic Distribution of Economic Input Parameters Name Distribution Min Mean Max 5% 95% Inflation Factor Triangular 3.03% 6.00% 9.96% 3.84% 8.68% a, MM$ Normal Gas OPEX, $/stb Rectangular Water OPEX, $/stb Rectangular Oil Price, $ Normal From the economic analysis and the stochastic considerations made, there is 90% confidence that the additional profit made by the IOR methods would be as shown in Table 4.6 below. Table 4.6 Additional Profit Made from IOR in 90% Confidence Interval IOR Min Mean Max 5% 95% Gas-Flood, MM$ (480.37) , , Water-Flood, MM$ (430.57) 1, , , WAG, MM$ (441.95) , Water-flooding gave the highest profit due to its relatively low operating cost and higher oil recovery compared to gas and WAG. Gas-flooding is also economically profitable than WAG for the same reasons. 43

56 CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS 5.1 Conclusions From the study conducted, the following conclusions were drawn: 1. The optimal reservoir fluid volume rate for gas-flooding is rb/day. 2. The optimal reservoir fluid volume rate for water-flooding is rb/day. 3. The optimal WAG injection conditions are as follows; WAG cycle: 50 days gas 200 days water WAG ratio: 1:14 WAG rate: rb/day water rb/day 4. It was discovered that, whichever fluid is injected first in the WAG process does not have an effect on the ultimate recovery efficiency of the WAG process. 5. Water-flooding gave the highest recovery efficiency, 57.56%, but at a water-cut of over 90%. 6. Gas-flooding gave the second best recovery efficiency of 54.16%. 7. WAG came last with a recovery efficiency of 52.82%. 8. From the economic analysis carried out, water-flooding is the most economical IOR method among the three. It has a potential profit with 90% confidence of MM$ to MM$ 1, over the natural depletion situation. 9. In a case where water-flooding is not technically feasible, then gas-flooding is the next choice with an additional profit between MM$ to MM$ 1, at 90% confidence. 5.2 Recommendations 1. For vertical well placement, water-flooding is the most profitable IOR method in this reservoir since it has low operating cost and gives the highest recovery. 2. Horizontal wells should be used to evaluate the efficiency of these IOR methods in this reservoir to determine their profitability. 44

57 NOMENCLATURE BHP : Bottom hole pressure EOR : Enhanced oil recovery IOR : Improved oil recovery FGOR : Field gas-oil ratio FOE : Field oil recovery efficiency FOPR : Field oil production rate FOPT : Field oil production total FPR : Field pressure FWCT : Field water-cut GOC : Gas-oil contact GOR : Gas-oil ratio K : Absolute permeability OWC : Oil-water contact RESV : Reservoir fluid volume rate SWAG : Simultaneous water and gas injection WAG : Water alternating gas injection λ : Mobility ratio So : Oil saturation Sg : Gas saturation Sw : Water saturation Po : Oil pressure Pw : Water pressure 45

58 REFERENCES Ahmed, T., Reservoir Engineering Handbook. 3rd ed. Burlington: Elsevier, Gulf Professional Publishing. Almutairi, F. H., Davies, D. R. & Singh, S., Enhancing Production From Thin Oil Column Reservoirs Using Intelligent Completions (SPE ). Jakarta, Indonesia, Society of Petroleum Engineers (SPE), p. 10. Alvarado, V. & Manrique, E., Enhanced Oil Recovery: An Update Review. Energies, pp Anon., MIT Injection Cost Model: Documentation, Boston: s.n. Avlbovbo, A., American Association of Petroleum Geologist, Volume 66, pp Boggs, S. J., Principles of Sedimentology and Stratigraphy. 4th ed. s.l.:s.n. Caudle, B. H. & Dyes, A. B., Improving Miscible Displacement by Gas-Water Injection. s.l., AIME, 213, pp Crain, E. R., Special Cases Laminated Reservoirs. [Online] Available at: Doust, H. & Omatsola, E., American Association of Petroleum Geologist, pp Evamy, B. et al., American Association of Petroleum Geologist, Issue 62, pp Kaplan, A., Lusser, C. & Norton, I., American Association of Petroleum Geologist,, Issue 60, pp Kulke, H., Regional Petroleum Geology of the World Part II: Africa, America, Australia and Antarctica. pp Lowe, D. R., Sub-aqueous liquefied and fluidized sediment flows and their deposits. Sedimentology, Issue 23, pp

59 Mahdavi, S., Bahraini, M. & Kharrat, R., Simulation Study of WAG and SWAG Injection Scenarios in One of Iranian Oil Fields: Case Study, s.l.: s.n. McCoy, S. T. & Rubin, E. S., The Effect of High Oil Prices on EOR Project Economics. ScienceDirect, Energy Procedia, pp Middleton, G. V., Sediment deposition from turbidity currents. Earth and Planetary Science, pp Nangacovie, H. L. M., Application of WAG and SWAG Injection Techniques into the Norne E-segment Field, Norwegian University of Science and Technology: MSc. PROJECT IN PETROLEUM ENGINEERING. Onwunyili, C. C. & Onyekonwu, M. O., Coupled Model for Analysis of Multilayer Reservoir in Commingled Production (SPE ). Lagos, Society of Petroleum Engineers (SPE), p. 9. Shanmugam, G., The Bouma Sequence and the turbidite mindset. Earth-Science Review, Issue 17, pp Sohrabi, M. et al., Performance of SWAG Injection Versus Alternating and Continuous Injection of Water and Gas in Low Gas-Oil IFT and Mixed-Wet Systems. Aberdeen, Scotland, UK, s.n., p. 12. Srivastava, J. & Mahli, L., Water-Alternating-Gas (WAG) Injection a Novel EOR Technique for Mature Light Oil Fields - A Laboratory Investigation for GS-5C Sand of Gandhar Field.. Hyderabad, s.n., pp Stacher, P., Present understanding of the Niger Delta hydrocarbon habitat. s.l.:s.n. Tewari, R., Malik, M., Ali, A. H. A. & Naganathan, S., Improved Heavy Oil Recovery from Thin Reservoirs through Horizontal Well Placement and Intelligent Perforations. Kuala Lumpur, Malaysia, Society of Petroleum Engineers (SPE), p. 13. Tiab, D. & Donaldson, E. C., Petrophysics: Theory and Practice of Measuring Reservoir Rock and Fluid Transport Properties. 2nd ed. Burlington: Elsevier, Gulf Professional Publishing. 47

60 Tyagi, A. K., Bastia, R. & Das, M., Identification and Evaluation of the Thin Bedded Reservoir Potential in the East Coast Deep Water Basins of India. s.l., HYDERADAD, pp Yadav, V. & Surya, N., Evaluating the Performance of Intelligent Completions (SPE ). Utrecht, Society of Petroleum Engineers (SPE), p

61 APPENDIX A Fig. A1 Cumulative production, Production Rate and Water-cut Graphs for Gas-Flood Fig. A2 Cumulative production, Production Rate and Water-cut Graphs for Water-Flood 49

62 Fig. A3 Cumulative production, Production Rate and Water-cut Graphs for WAG Cycles Fig. A4 Reservoir Pressure and Gas Oil Ratio Graphs for WAG Cycles Fig. A5 Cumulative production, Production Rate and Water-cut Graphs for WAG Rates 50

63 Fig. A6 Reservoir Pressure and Gas Oil Ratio Graphs for WAG Rates Fig. A7 Cumulative production, Production Rate and Water-cut Graphs for WAG Ratios Fig. A8 Reservoir Pressure and Gas Oil Ratio Graphs for WAG Ratios 51

64 Fig. A9 Cumulative production, Production Rate and Water-cut Graphs for Water or Gas 1 st in WAG Fig. A10 Reservoir Pressure and Gas Oil Ratio Graphs for Water or Gas 1 st in WAG 52

65 Fig. A11 Reservoir Pressure and Gas Oil Ratio Graphs for Water or Gas and WAG Injections 53