Abstract It is well known that microbubbles play an important role in heavy oil reservoirs, where the presence of asphaltenes and other charged particles makes it easier to generate microbubbles. Only recently, however, microbubbles are being considered for rigorous analysis of primary depletion in heavy oil reservoirs. Previous studies show that the conventional analysis that relies on PVT data as the only independent variables of the system is not adequate in explaining why recovery is significantly higher than the one predicted by Black-oil reservoir simulators. In this study, the role of microbubbles in altering PVT properties will be quantified through a series of PVT data. It is expected that the PVT properties are significantly altered due to the presence of asphaltenes, with a complex dependence on the asphaltene concentration. Also important is the nature of the gas phase present in the system. The microbubble capture and retention due to the presence of asphaltenes make the bubble release time much longer than when the asphaltenes are absent. This phenomenon has not been accounted for in the past. A new equation of state is generated that satisfies the PVT data for various asphaltene compositions. Also introduced is a transition factor that includes the effect of the history of the bubble generation. This equation helps explain several factors (e.g. delay in bubble release from heavy oil, greater than expected recovery from primary depletion of heavy oil formations) that have eluded scientists in the past. Introduction The context of this paper requires that one discuss the role of microbubbles in heavy oil recovery as well as the useful form of currently used equations of state. The literature on the first topic is scarce. The latter subject, however, has seen extensive research activities in recent years. Microbubbles in heavy oil recovery The study of microbubbles is an active topic of research for petroleum and other fluids applications. Some notable research studies performed outside of the petroleum field determined that microbubbles carry an electric charge 1 . This information was later used to develop the relationship between frequency and ultrasonic generation of microbubbles 2 . Early petroleum research into microbubbles and their relationship to asphaltenes was carried out by numerous researchers (3–6) . Smith 5 was possibly the first researcher to hypothesize that the existence of microbubbles can explain the possibility of recovering more oil from heavy oil reservoirs than that predicted by primary depletion theory. Islam and Chakma 6 conducted a series of experiments to demonstrate that the hypothesis of Smith 5 was correct. They further demonstrated that the capture of microbubbles can be correlated with the asphaltene content of a crude oil. Islam 7 summarized these findings and concluded that the charged nature of asphaltene particles must be responsible for increased bubble captures. He argued that a new theory should be presented in order to accommodate for microbubbles that show considerable delay in release from liquid than do ordinary gas bubbles. This theory, he contended, should be able to explain more-than-expected recovery from heavy oil reservoirs.

Abstract Husky currently operates four major tertiary miscible floods in the Rainbow Basin: Keg River B 1,2 , F 3 , and South E and G Pools. These miscible flood significantly increase their respective pool's ultimate hydrocarbon recovery. A few critical factors for gas injection displacement: effects of interfacial tension (miscibility), viscosity ratio, gravity and wettability, all in the context of the micro scale pore size distribution were reviewed by Thomas et al 4 Theoretically, miscibility (or interfacial tension effect) is the most critical parameter for a successful miscible flood scheme, and fortunately it is controllable. As Husky continues to evaluate other potential tertiary miscible floods and to initiate new miscible flood schemes in Rainbow area, the demand for NGL, which is mixed with lean gas to give a desirable solvent, has been increasing, and will continue to increase. New facilities are being designed, to be added to Husky's existing gas processing facility to extract more NGL (especially C 2 and C 3 ) in order to meet the projected demand for existing and future miscible flood schemes. Furthermore, this will also result in continuous change in the composition of NGL extracted. Consequently, the mixing ratio of NGL and lean gas will have to be adjusted accordingly to yield injection solvent that is always miscible with the reservoir oil. Laboratory measurements such as coreflood, slim tube displacement, rising bubble apparatus (RBA), and IFT 3 have been used for determining the miscible solvent compositions. With the changing nature of NGL composition, a need to minimize costs associated with running laboratory experiments was identified. Subsequently, a cost effective and yet technically sound method, which utilizes both numerical simulation and laboratory measurement, was developed. This paper presents and discusses how a one dimensional, equation of state (EOS) compositional model is successfully used to predict, with confidence, miscibility conditions (i.e. mixtures of NGL with lean gas or acid gas at reservoir temperature and pressure). The 1-D model was first validated with laboratory data: PVT, IFT, slim tube test, and RBA. Very good agreements between the experimental and the simulated miscibility results were obtained. In essence, the I-D model with an injector at one end and a producer at the other simulates the dynamic mixing and/or interface between the displacing solvent and displaced reservoir oil in a slim tube and/or a long core. Whether miscibility is achieved or not can be determined for A specified solvent composition and reservoir condition by examining the profiles of saturation, density, and viscosity of the I-D model after say 0.5 PV of solvent injected. An additional benefit of the model is its ability to evaluate the effect of viscosity ratio. Introduction Over the last 20 years, Husky Oil Operations Ltd. has developed significant expertise in successfully applying vertical gravity-stabilized hydrocarbon miscible floods in the Rainbow Basin in north-west Alberta. While miscible flooding in these Rainbow Keg River reefs was originally implemented as a secondary recovery process, the current activity is more focused on tertiary schemes. Husky currently operates four major tertiary miscible floods in this area, namely in the Keg River B 1,2 , F 3 , and South E and G pools.

Abstract A new mixing rule for using with the commonly employed cubic equations of state is proposed. It is applied for petroleum mixture vapor-liquid equilibrium computations, and the results are compared to those from the conventional calculations and the experiment data obtained by recombining the well streams with added carbon dioxide. The new mixing rule is based on the idea of components deviation from their pure state vapor-liquid equilibrium behavior when they are present in petroleum mixtures, instead of the binary interaction basis for limited binary systems. Its application with the cubic equations of state (EOS) for petroleum mixtures eliminates the use of the binary interaction parameters matrix used for compositional reservoir simulation and chemical engineering calculations. The utilization of the new vector form mixing rule has lead to significant improvements on the computation efficiency and convergence behavior for our petroleum mixture compositional vapor-liquid equilibrium computations with EOS such as the Soave-Redlich-Kwong EOS and Peng-Robinson EOS. The introduction of the mixing rule with component deviation factors for each real and pseudo-components is flexible, easy to control, and comprehensive for mediating the gaps between the theory and practical engineering problems. Although the convergence problem is alleviated in our calculations, especially for those cases with high CO 2 concentrations, when the mixing rule is applied, the problem cannot be totally solved for a number of reasons. Further investigation results in a new generalized three term cubic EOS which satisfies the newly established critical requirement obtained on both analytical and numerical basis. The new three term EOS can be reduced to encompass many two term cubic EOS of similar forms, and it has the promising form to be shaped for extended applicable physical conditions for better accuracy and convergence behavior. An explanation and discussion are given on the critical point convergence problem based on the newly developed EOS. With the new EOS, it becomes obvious that the critical convergence problem is not purely a mathematical one, the EOS models themselves may have some inherent restrictions for the phase equilibrium computation schemes to work for complex mixtures when the critical points are approached. Introduction Phase equilibrium computations for petroleum mixtures containing heavy hydrocarbon fractions or near critical point conditions have been regarded as being difficult and mysterious for many years. In some cases, it is even hard to get the converged results without considering their accuracy. Because this problem has not been solved with satisfaction, compositional reservoir simulators that use cubic EOS to model the reservoir fluid phase behavior will most likely to inherit the problem and create confusing. When this kind of problem is encountered in compositional reservoir simulation, a lot of times it will not be clearly understood. The reason that this is important is because reservoir fluid phase conditions reflect the energy level of the reservoir and petroleum recovery potential. Another problem with compositional reservoir simulators that use an EOS, is that the computing time and storage requirements for a simulation increase sharply with the number of components for each grid and iteration step, and soon become prohibitively large.

Abstract Oil characterization plays an important role in integrated geophysical, geological and reservoir engineering studies. From project inception, correctfluid characterization can provide useful information -about reservoirdescription and compartmentalization as well as properly defining fluidbehavior for engineering calculations. In this paper four field examples arepresented to illustrate (1) how to use equation of state (EOS) oilcharacterization to check the accuracy of fluid sampling procedures andlaboratory fluid property measurements, and (2) how to use EOS oilcharacterization to check for consistency between the geological/geophysicalreservoir description and actual field performance (e.g. produced gas-oilratio). This results in a better reservoir model and makes further engineeringand simulation tasks much easier. Introduction Integrated reservoir studies are usually initiated after the reservoir inquestion has been on production for many years. This provides sufficient dataon field performance to ensure that some matching of calculations to actualhistory can be done. To conduct such studies engineers generally have to useavailable data including existing PVT data. In most cases the existing PVTdata, which may have been collected right after completion of the initialdevelopment wells before field production or after many years of production, can show considerable inconsistency. In addition, some key data may not havebeen measured or some of the data may not reflect actual reservoir performance, such as gas-oil ratio (GOR). It is therefore important, from the outset of aproject, to check the consistency of available PVT data with the productiontest data and with the geological description before using it in a reservoirsimulation study. EOS models are used by engineers to identify such inconsistencies in the PVTdata and to calculate data which may not have been measured or is obviouslyincorrect. Before an EOS can be used, one must first correctly tune itsparameters l , that is, characterize the oil. Hence oilcharacterization plays an important role in the integrated reservoir study. Correct fluid characterization enables accurate EOS fluid property predictionswhich can provide useful information about reservoir description and compartmentalization, as well as properly defining fluid behavior forengineering calculations. In this paper we use four actual field examples toillustrate the procedures used. EOS OIL CHARACTERIZATION Reservoir fluids are comprised of a very complex mixture of naturally occurringcompounds. These compounds are principally hydrocarbons ranging from methane toasphalt. There are no fixed rules on the distribution of hydrocarbons inreservoirs. Fluids in reservoirs can exist as either single phase (gas orliquid), two phase (gas and liquid) or multiphase (gas, liquid, liquid) fluidsdepending on the reservoir conditions and the components present. The abilityto predict production rates, optimize production strategies' and designproduction facilities depends on a knowledge of the properties of the reservoirfluid, not just at the original reservoir conditions, but also at a great manyconditions on the subsequent depletion and production path. It is usually impractical, due to cost, time or lack of sufficient sample toconduct laboratory analyses for such a wide range of conditions.

Abstract A novel acoustic dewpoint and bubblepoint detector may be a valuable device for natural gas processing industries. The device is free from mercury and can be applied to a broad range of phase transitions. Even in very lean gas systems or opaque heavy oils, this technique has application when high accuracy and automation are required. In the new state of the art Acoustic Resonance Technology (ART) system at Hycal Energy Research Laboratories Ltd., two acoustic transducers are used, one to stimulate and the other to detect normal mode vibrations of reservoir fluids in a small cylindrical resonator. The acoustic spectra, along with temperature, pressure and volume measurements, are recorded at close intervals throughout the phase envelope. The time domain data collected are processed to obtain the specific condition of phase transition. The high pressure ART system is capable of operation from -40 °C to 150 °C (-40 °F to 300 °F) and pressures up to a maximum of 70 MPa (10,000 psia). The system is capable of operation in an isothermal mode with variable volume or in a constant volume mode with variable temperatures. The accurate determination of bubblepoint and dewpoint pressures at reservoir temperature are crucial for natural gas processing, transportation and metering. Results of two systems (a binary mixture and live reservoir fluid) are presented. The onset of bubblepoint and dewpoint are easily obtained from the processed data. Since the frequency response of sonic speed is influenced by density, micro- and macroscopic structural features, at the phase boundaries, the acoustic response shows a sharp abrupt change. The interpretation of results can be free from operator subjectivity. Comparison of the ART results with those obtained using visual methods and equation of state calculations show excellent agreement. These results will be presented in this paper. Introduction In reservoir engineering, detailed knowledge of the phase behavior of reservoir fluids is very important in planning, managing operations involving production, transporting, processing and utilization of fluids. Although visual techniques have been used commonly in the petroleum industry, when it comes to very lean gas mixtures and very dark fluids, detection of phase change can be a serious problem. The recent AR technique is a highly accurate, independent method and can be complementary to, or a substitute for, visual method. It is fast and additional information can be obtained in one measurement. AR exploits the advancement in PC technology for data collection and control of measurements. The evolution of the resonance response of reservoir fluids as a function of changing conditions of pressure, volume and temperature is measured in AR in real time. The results yield accurate information related to reservoir fluid phase behavior (bubblepoint, dewpoint, etc.). It has been shown in earlier work that some useful information about fluids can be inferred reliably from the acoustic signature. 1,2,3 This paper illustrates the use of a versatile acoustic system in determining accurately the dewpoint or bubblepoint of gas condensates and reservoir fluids.

Abstract Hydraulic fracturing of low permeability reservoirs with multiple fractures is an effective stimulation treatment in the serial techniques of horizontal well production. The comprehensive mathematical model of predicting the production performance of a hydraulically fractured horizontal well with multiple fractures, combined the reservoir model and type of reservoir derive with the hydraulic fracture model is first established in this paper. The numerical models and the corresponding solution are first derived. Both fracture performance and reservoir performance in the transient producing period or pseudosteady producing period are taken into account. These models are applied to simulate the pressure performance of reservoir and multiple fractures in the horizontal well, to forecast the well production in the transient producing period and pseudosteady producing period. This paper investigates optimization of fracture numbers in the horizontal well, added the fracturing economic evaluation model to the comprehensive mathematical model. A case study is shown which demonstrates the method of forecasting production and optimizing fractures numbers. These models and the methodology can be employed in fracturing design of a horizontal well and evaluation of fracturing effectiveness. Introduction Hydraulic fracturing of horizontal wells, which enhances the oil reserves in the low permeability reservoir and keeps the oil wells high productivity is becoming an effective stimulation treatment in the serial techniques of horizontal well exploitation. Forecasting the production performance of a hydraulically fractured horizontal well plays an important role in the optimization design of hydraulically fracturing the horizontal well, furthermore it is the main basis of evaluating the effectiveness of post-fractured wells. Segment fracturing in the horizontal wells commonly induces multiple fractures which are oriented near the wellbore. Predicting the production performance of a fractured horizontal well with single fracture or several fractures can be used to determine the optimum fracture numbers and to improve the design of hydraulic fracturing treatment. This paper first presents the comprehensive mathematical model of predicting the production performance of a hydraulically fractured horizontal well with multiple fractures. The reservoir model, type of reservoir drive and hydraulic fracture model are included in the comprehensive model. Both pressure behaviors in the fractures or in the reservoir and well production in the transient producing period and pseudosteady producing period can be simulated. The fracturing economic evaluation model is introduced to investigate the optimization of numbers of fractures in fractured horizontal wells. A case study is presented which demonstrates the method of forecasting production and optimizing fracture numbers. These models and methodology can be employed in fracturing design of a horizontal well and evaluation of fracturing effectiveness. ESTABLISHMENT OF PHYSICAL MODEL Assumptions The object of this study is shown in figure 1 in which a fractured horizontal well with multiple fractures is located in the rectangular reservoir. The following assumptions are involved in the derivations of the mathematical model. The fractures are perpendicular to the wellhole and vertically penetrate the partial reservoir thickness. The horizontal well fully penetrates the reservoir or unfully penetrates the reservoir.

Abstract Reservoir fluids containing paraffin's and asphaltene's are common in the petroleum industry. The presence of these components causes significant operational problems during the life of the producing wells. The identification of wax and asphaltene precipitation conditions is the first step towards applying any remedial options. There are various procedures applicable in determining the onset of wax and asphaltene precipitation conditions. These techniques are dependent on the oil characteristics. The most important criterion is the colour of the oil. For dark coloured oil, the popular light-scattering technique becomes inadequate. In this case, near-infrared (NIR) light spectrum is necessary to identify any changes in the response due to phase change phenomenon. An emerging technology, called Acoustic Resonance Technology (ART), has been tested at Hycal Energy Research Laboratories Ltd. to identify the onset conditions of wax and asphaltene precipitation. The system is applicable to any type and colour of oil. The basic principle behind the technique is the transmitting of sound waves through the fluid while it is exposed to wax or asphaltene precipitation conditions by changing pressure, temperature or composition conditions. The acoustic response shows drastic changes during the phase transition (i.e. nucleation of wax or asphaltene) in the fluid. Initial results of the onset of wax and asphaltene precipitation are extremely promising. Comparison of the onset values of wax and asphaltene precipitation using ART showed excellent agreement with that obtained using a light-scattering technique. Introduction Acoustic Resonance Technology (ART) is based on measurement of the response of a fluid or fluids, contained in a cylindrical cavity, to acoustic variable stimulation. The most powerful use of ART is to study the state and time evolution of the resonance response of fluids under variable and well controlled conditions of pressure, volume and temperature. 1,2,3 In these cases, one can obtain information related to fluid phase behavior or phase transitions and transport properties. ART offers a sensitive, objective method for probing and measuring bulk fluid properties and processes. Asphaltene's are dark brown to black solid compounds with no definite melting point. They decompose while heating and leave a carbonaceous residue. They are non-crystalline substances or mixtures of relatively high molecular weight fractions 4 of bitumen with characteristics of strong aromatic polar substances. 5,6 Asphaltene's are defined as the n-heptanes insoluble fraction of crude oil. 7,8 They are classified by the particular solvent used to precipitate them. 9 They are generally soluble in benzene and insoluble in low molecular weight n-alkenes. 10 Asphaltene precipitation can be determined experimentally. Waxes are defined as normal paraffin's as well as other molecules containing long chain alkyl groups usually ranging from C 18 to C 60 . Solid waxes crystallize or precipitate when cooled below their cloud point temperature. The wax precipitation process is thermodynamically reversible. 11 The viscosity of crude oil is increased by the presence of the wax crystals. 12 lf the temperature is reduced sufficiently, the crude can become highly viscous and approach its pour point temperature. Solid (waxes and asphaltenes) precipitation from reservoir fluids causes severe operational problems in the subsurface, surface equipment, wellhead equipment, separators and tanks. 13,14 Clean-up costs can be very high in off-shore oil product

Abstract Pyrite (FeS 2 ) is a common and ubiquitous constituent of reservoir rocks and forms geologically under extremely reducing conditions. Pyrite is easily oxidized by exposure to moderately oxidizing conditions, including de-oxygenated injection or process water. When pyrite is oxidized in water, the resulting products include sulfuric acid (H2S04) and sulfate ion (SO 4 2- ). In the near well bore, the resulting waters are far from equilibrium with Portland type well cements. A small amount of pyrite oxidation can result in total removal of well cement and the replacement of the cement by structurally less stable products, such as calcium sulfate. In addition, the sulfuric acid may result in corrosion of well tubing or above ground facilities. Casing leaks, particularly in injection wells, may lead to failures of casing due to cement collapse, tubing corrosion, or both. In the reservoir during waterflooding or steam injection, pyrite oxidation may release sulfate ion (SO 4 2- ) which can promote the activity of sulfate reducing bacteria, resulting in "souring" and the production of the acids gases H 2 S and CO 2 , where no production of acid gas was noted before injection. The results of pyrite oxidation are examined using reaction path modeling, in which the effects on reservoir fluids and rocks of these complex chemical reactions, including corrosion and scaling, can be determined. Introduction Pyrite (FeS 2 ) is an ubiquitous constituent of carbonate and clastic teservoir tocks. Pyrite is particularly abundant in shales, and may be an unrecognized cause of well bore or casing failures in shaly intervals. Pyrite is only stable at very low oxidation states, partly depending on the pH and temperature, and consequently is very susceptible to oxidation during injection of fluids of relatively high oxidation state, such as steam or water from water floods. The objective of this paper is to show the possible consequences of pyrite oxidation for well bore cement stabiliry and the effect on the composition of formation fluids, Chemical models are used to determine whether the changes in fluid chemistry can have significant effects on the stability of well cement (portlandite) and common reservoir minerals, such as calcite. One of the consequences of oxidation of a sulfide mineral is the release of sulfate to the aqueous fluid. In the typical hydrocarbon reservoir environment this provides a sulfate source for anaerobes that reduce sulfate to sulfide, resulting in the creation of sour gas in water flooded reservoirs that previously were not subject to sour production. Limited data from steam and water flood operations suggest that pyrite oxidation may occur, leading to the possibility that such pilots may become subject to sour production as production proceeds. PYRITE OXIDATION AND CEMENT DISSOLUTION The oxidation of pyrite does not require a source of "free" oxygen, but can utilize the oxygen in water. Observation of reaction [I] below shows that, in addition to the release of sulfate, oxidation of pyrite will release hydrogen ions, producing acidic conditions. Effectively, the product of pyrite oxidation and dissolution is sulfuric acid. Equation (1) (Available in full paper)

Abstract Fluid flow in narrow reservoirs or aquifers is predominantly linear. However, this linear-flow system may possess variations in rock and fluid properties and/or presence of faults due to a number of geological phenomena. Such systems are modeled as linear, compartmentalized systems. In this study, a new generalized transient-flow model has been developed analytically for an n-region compartmentalized system. Each compartment or region may have distinct rock and fluid properties. A time-dependent production rate from each compartment is modeled in a general way. The conditions at the extreme boundaries of this compartmentalized system are taken as non-homogeneous, time-dependent, Cauchy-type that can be modified to Dirichlet- or Neumann-type as a special case. A possible situation of poor communication between neighboring compartments has been incorporated into the model by considering the presence of a thin skin at each interface. A generalized solution for the dimensionless pressure has been derived using an integral transformation technique. This solution deals directly with the situations like production rates and extreme boundary conditions being time dependent without the need for using the principle of superposition in time and/or Duhamel's principle. Some limiting cases of this new solution have been used for validation purposes. Several advantages and practical applications of this model are also discussed in detail. With some example problems, the utility of the new solution has been shown for the situations where the transient and compressibility effects of the reservoir are not negligible while calculating the cumulative water influx through the reservoir-aquifer interface. INTRODUCTION Fluid flow in narrow reservoirs or aquifers is predominantly linear. Because of the geological processes, the rock and/or fluid properties in these linear systems may be non-uniform. Levorsen (l) mentioned that the extent of a reservoir boundary may be sharp or it may be gradational as is more often the case. This heterogeneous character of a reservoir makes it difficult to model. To alleviate the mathematical difficulties of modeling such a system, the concept of compartmentalization may be used. Using this concept, a heterogeneous system is assumed to be comprising a number of homogeneous compartments. The communication of fluid between adjoining compartments may be hindered due to the presence of faults, permeability pinch-outs or any other flow barriers. This study presents a generalized, analytical solution for transient-pressure responses that incorporates a number of useful features. In the literature, most of the studies on linear systems are related to homogeneous reservoirs or aquifers. (2.3,4) However, several studies with two-region, composite systems with or without a linear discontinuity have been reported. Bixel et al. (5) developed a mathematical model for a composite system with two regions having a fully-communicating interface with the well located near it. Ambastha and Sageev (6) obtained an analytical solution using Laplace transformation for a linear, composite system of a finite region and an infinite region being separated by a boundary skin. Yaxley (7) presented a mathematical model for a homogeneous system with a linear, partially-communicating fault of finite thickness and finite conductivity.

Abstract The sampling of oil and gas condensate reservoirs require that representative fluid samples be removed by either surface or subsurface sampling techniques. This paper briefly reviews both of these techniques and discusses their relative merits. Several practical examples are provided that demonstrate the utility of an equation of state model to verify the quality of separator samples to be used in a recombination. In situations where free gas has been entrained with the separator samples, the equation of state model can frequently be used to synthesize an appropriate gas to be used in a recombination. Introduction Obtaining representative reservoir fluid samples has become of increasing importance in the development and exploitation of oil and gas condensate reservoirs. This is especially true of reservoirs where extensive computer simulations are used to scope out developmental strategies or where enhanced oil recovery options are investigated, Often times these decisions are based on properties measured on relatively small fluid volumes produced from the reservoir at one point in time. Therefore it is imperative that the fluid samples used to make these decisions closely match the characteristic properties of the reservoir fluids at actual reservoir conditions. Representative fluid samples can usually be obtained from producing reservoirs at either surface or subsurface locations. Surface samples are removed at either the separator or at the wellhead, with the associated gas and liquid subsequently recombined in proportions to represent the actual reservoir fluid. Subsurface samples are removed from within the wellbore at actual reservoir conditions using bottom hole sampling tools and techniques. The suitability of the particular sampling technique will depend on a large number of factors which may include economic considerations such as the cost of sampling and associated loss of production, the type of surface facilities that are available, the fluid volumes that will be required and the type of reservoir and fluid to be sampled. The sampling technique employed can be of particular importance in saturated oil or gas condensate reservoirs where the possibility of entrainment of disassociated phases decreases the likelihood of obtaining a truly representative fluid. In some of these situations, various techniques can be employed to compensate for entrainment of these dissociated phases. The focus of this paper is aimed at determining the techniques used to recombine the separator samples to represent oil and gas condensate systems along with many situations where they have been depleted into the two-phase region. A brief review of those situations where bottom hole sampling will more likely provide a representative sample will also be discussed. Sampling Techniques A thorough review of the equipment and techniques used to obtain these different types of fluid samples is outside the scope of this discussion and individuals who are interested in more extensive information on sampling procedures should refer to the cited literature (1,2,3) and information available from equipment vendors and service companies that specialize in sampling. However, a brief review of the most common sampling techniques will be useful to establish the fundamental principles that will discussed later in this paper

Abstract This paper gives a comparative study of empirical viscosity correlation expressions. The documented expressions include Lee et al.'s exponential expression, Dempsey-Standing's polynomial expression, Dranchuk-Islam- Bentsen's representation of Carr et al's data, Gurbanov and Dadash-Zade's expression, Lohrenz et al's expression, and a regression expression of Gonzalez and Lee's data. The first four expressions are two-step procedures, while the equation representing Gonzalez and Lee's data is a one-step procedure, and Lohrenz et al's expression is basically a semi-empirical composition dependent method. Some of these expressions are capable of estimating viscosities of impure natural gases which contain non-hydrocarbon components like N 2 CO 2 and H 2 S. A detailed analysis of application region, accuracy, and computational superiority for these empirical expressions of viscosity correlations is presented and a two-step procedure with combined equations is recommended. Introduction In the petroleum industry, natural gas viscosities at reservoir conditions or elevated pressures and temperatures are of particular importance for reservoir engineering calculations. The only accurate way to obtain the viscosity of a gas is to determine it experimentally, using apparatus such as a rolling-ball pressure viscometer or a capillary-tube viscometer. In the early petroleum industry, many experimental efforts were made and many data were obtained. In practical applications, however, petroleum engineers always rely on empirical correlations of natural gas viscosities. The reason is perhaps twofold: performing good experiments is quite tedious, and also compared with the inaccuracy of some of the other data that are used in the same equations with the gas viscosity, the viscosity might be the most accurate even though it comes from empirical data which were correlated graphically for engineering convenience. With the advent of computers, many semi-empirical equations for gas viscosities were developed to meet the industry's demand. Most of these equations stemmed directly from the regression of experimental charts that were already well correlated, while others were developed based on experiment, supported by molecular theories. The viscosity of a pure gas depends on temperature and pressure, but for a natural gas, or a gas mixture, it is also a function of the composition of the gas. In addition, when a natural gas is not pure, or there are some non-hydrocarbon components (such as N 2 , CO 2 and H 2 S) present in the gas, its viscosity under pressure and temperature has to be corrected. Conventionally, a two-step procedure is usually used to estimate natural gas viscosities under pressure and temperature.. In the first step, µ g the viscosity at low pressure or atmospheric pressure and the desired temperature T is estimated if the apparent molecular weight M g or the gas gravity G and the desired temperature are known. When it is not a pure hydrocarbon gas, the viscosity µ g has then to be corrected for all non-hydrocarbon components. In the second step, the viscosity of the natural gas under pressure and temperature is calculated through equations that predict the ratio of µ to µ g based on the principle of corresponding states, that is, the ratio of µ to µ g is expressed as a function of both the reduced pressure.

Abstract The representation and characterization of the heavy traction of reservoir oils are crucial for accurate predictions of multiple-contact gas injection processes using cubic equations of state. The mechanisms in most rich-gas processes were recently identified as combined condensing/vaporizing phenomena, which are more complex than the traditional condensing phenomena. Similar interpretations apply to CO 2 processes. To capture these phenomena, current techniques involve the use of a sizeable number (4 or more) of pseudocomponents to represent the heavy fraction (e.g. CO 2 ) making field-scale simulation prohibitively expensive. A technique is proposed to represent the heavy fractions by a small number of components (one or two), while maintaining accurate predictions of condensing/vaporizing phenomena. The highlights of the technique are: the allowance for the critical temperature of the heaviest pseudocomponent to vary with composition and the reproduction of the critical point on pressure-composition diagram. Test runs show that the proposed method gives predictions of CO 2 and rich-gas multiple-contact processes with 4 to 6 components with the same level of accuracy as with 14 components. Introduction Rich-gas and CO 2 injection arc import.1nt enhanced-oil recovery processes, where multiple contacts between the injected gas and the reservoir oil result in efficient displacement of oil. The traditional interpretation of the mechanisms occurring in rich-gas drive corresponds to a condensing process where the intermediate components condense from the injection gas and enrich the reservoir oil towards the point of miscibility (Stalkup. 1984). However, recent studies indicate that the mechanisms in most rich-gas drives correspond lO a combined condensing/vaporizing phenomena or a liquid-extraction phenomena (Zick, 1986; Mansoori and Gupta, 1988; Novosad and Costain, 1988, 1989). Thus, the phenomena which occur in rich-gas drives are in many ways similar to those in CO 2 processes (Novosad and Costain, 1989). The above phenomena arc usually modelled with a cubic equation of state (EOS). With this approach, the number of components representing the hydrocarbon system has a large impact on accuracy and computational cost. The computational costs arc an overriding factor if EOS calculations are used in a compositional simulator to predict reservoir performance. Thus, it is essential to reduce the number of components in field-scale simulation, while still preserving the accuracy of the phase behavior predictions. The most important factor in reducing the number of components is the representation of the heavy fraction (e.g. C 6 .) of the reservoir fluid. A number of methods have been proposed to split the heavy fraction into several pseudocomponents and to characterize these pseudocomponents. This characterization involves the estimation of component critical properties and acentric factors. Some of these techniques are described in Whitson (1983), Pedersen el al (1984), Li el al (1985), Coats and Smart (1986), Wu and Batycky (1988), and Newley and Merrill (1989). These techniques usually require a sizeable number of pseudocomponents to represent the heavy fraction (four or more) in order to obtain accurate predictions of the phase behavior or multiple-contact processes.

Abstract A two-phase flow model has been developed for analyzing and designing gas/condensate distribution pipeline network system. The model is developed based on looped-system approach with some modifications. In this model, a phase behavior model is implemented for predicting the fluid properties required for the governing equations for the network system. By utilizing the Linear Theory Method, the Beggs-Brill's two-phase flow model is implemented in this model to predict the hydrodynamic variables in each leg of the network using the iterative technique which is developed in this study. A generalization of the two-phase network model is provided thereby making it possible for the two-phase flow model used to be replaced with any other that may be more applicable for the particular situation. Using the iterative procedure developed, pressure at all nodes, gas flow rate and liquid holdup at each leg can be predicted. The test results demonstrate that the model can serve as a predictive and design tool for solving a two-phase flow problem in a pipeline network. Introduction The increasing role of natural gas as an energy source, especially in the non-transportation sector of an industrial economy, cannot be over-emphasized. It is also certain to play a major role in the transportation sector of the economy as the technology of natural-gas-driven engine improves. This dramatic increase in gas utilization will necessitate the transportation of higher volumes of natural gas than ever before. This implies a critical need for a more efficient utilization of the existing network of pipelines. Optimal design and operation of the gas pipeline is of the essence. A very important complicating factor in the design of a gas pipeline network is the fact that condensation invariably takes place in these pipelines. The introduction of liquid into a gas pipeline subjects it two-phase flow. The use of pipelines for gathering and transportation of natural gas is standard. Condensation in these gathering lines is a commonoccurrence because of the multi-component nature of the gas which is subjected to varying temperature and pressure. In general, the phase behavior of natural gas is quite sensitive to pressure, temperature and composition. Thus, the amount of condensate formed in the gas-carrying pipeline is dependent upon these variables. What this means is that gas may enter the pipeline as single-phase gas but invariably becomes two contiguous phases somewhere within the pipeline network due to condensation. Furthermore, since the slope and orientation of the pipeline varies, the effect of gravity must also be taken into consideration. It is therefore imperative to utilize a compositional approach in trying to model this system. It is now a fact generally recognized in the gas industry that the adequate design of gas pipelines requires a good knowledge of the impact of condensation on the basic design and operating parameters which, in turn, would affect the deliverability of the pipeline in question. The problem of two-phase flow in pipes and conduits is complex even when flowing in a single pipe.

Abstract In the application of Beggs and Robinson dead oil viscosity-temperature empirical correlation to several hundred dead oil systems we have found consistently significant deviation between measured and calculated viscosity values. This paper presents a modified Beggs and Robinson empirical viscosity correlation. The proposed new correlation has been verified using a data base of about four hundred oil analysis reports (oil systems), and it shows a significantly better correlation, with a standard deviation and average error of at least 12% and 55% respectively, better than the existing correlation of Beggs and Robinson. We have also expanded the applicability of this correlation further by the inclusion of pour point temperature in the empirical equations. The new correlation also appears to apply to a wide range of oil specific gravities and pour point temperatures. Introduction One of the most important physical properties of crude oils is viscosity, which is a critical parameter required in various aspects of petroleum engineering analysis. A laboratory PVT analysis of a crude oil provides viscosity information at reservoir temperature and pressure. However, difficulties arise when viscosities are required at other temperatures. Therefore, if viscosity at a desired temperature can be predicted by less expensive laboratory measurement technique, it will be extremely useful in the reservoir performance prediction. particularly for thermal recovery processes. Until recently the most widely used methods for predicting oil viscosity were those of Beal (i) for dead oil and Chen and Connally (2) for live oil systems. While Beal correlated dead oil viscosity as a function of API gravity and temperature, Chen and Connally presented a correlation for the effect of dissolved gas on oil viscosity. More recently, Beggs and Robinson, (3) presented an empirical viscosity correlation equation for dead or gas-free crude oil as a function of API gravity and temperature. The correlation for dead oil viscosity which was developed by plotting log 10 (T) vs log 10 log 10 (µ OD + 1) on cartesian co-ordinates, enjoys extremely wide application in the petroleum industry. We have examined the correlation equation presented by Beggs and Robinson and found a significant deviation betNeen measured and calculated viscosity values. There is a strong belief in the industry that the chemical composition of a crude oil may be important in its viscosity characteristics. The inclusion into the correlation of any parameter related to crude oil composition (4–6) may improve the viscosity correlation. This i5 particularly 50 when considering the current developments in a wide range of heavy oil reservoirs where viscosity behaviour is extremely Important. Therefore, the need for a better viscosity correlation is apparent. POUR POINT TEMPERATURE In this study, a new parameter, pour point temperature, is introduced into the viscosity correlation. Pour point temperature, (T p ), by definition, is the lowest temperature at which the oil is observed to flow when cooled and examined under conditions prescribed in ASTM 097. Pour point temperature of crude oil appears to be related to the paraffin content; the pour Point temperature increases with crude oil paraffin content.