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Summary To predict the phase and volumetric behavior of hydrocarbon mixtures by using an Equation of State; e.g. the Peng and Robinson Equation of State "PREOS", the critical properties in terms of the critical pressure "pc" and critical temperature "Tc" as well as the acentric factor ""? must be given for each component present in the mixture including the plus-fraction. For pure compounds, the required properties are well-defined, but nearly all naturally occurring gas and crude oil fluids contain some heavy fractions that are not well defined and are not mixtures of discretely identified components. These heavy fractions often are lumped and called the "plus-fraction" (e.g. C7+ fraction). Adequately characterizing these undefined plus fractions in terms of their critical properties and acentric factors has long been a problem. Changing the characterization of the plus fraction can have a significant effect on the volumetric and phase behavior of a mixture predicted by the PREOS. The inaccuracy of any the cubic equation of state results from the following two apparent limitations:improper procedure of determining coefficients a, b, and a for the plus fraction Equations of state treatment of hydrocarbon components with critical temperatures less than the system temperature (i.e. methane and nitrogen). Numerous authors have suggested that the EOS is generally not predictive and extensive splitting of the C7+ fraction is often required when matching laboratory data. This paper presents a practical approach for calculating the coefficients a, b, and a of the plus-fraction from its readily available measured physical properties in terms of molecular weight "M" and specific gravity "??? with the objective of improving the predictive capability of equation of state. The predictive capability of the relationship is displayed by matching a set of laboratory data on several crude oil and gas-condensate systems. In addition; the performance of the proposed method was also compared with predictive PVT results as generated by using PVTSimTM software of Calsep. Additional comparisons are made by comparing the proposed modified PR EOS results with those of Coats and Smart 4 regression methodology with PR EOS. This study concludes that when the coefficients of the plus-fraction, i.e. a, b, and a, are determined based on the proposed methodology; splitting of the C7+ into a number of pseudo-components is essentially unnecessary.
- Research Report > New Finding (0.86)
- Research Report > Experimental Study (0.54)
- North America > United States > Wyoming > Powder River Basin > NPR-3 > Teapot Dome Field > Wall Creek Formation (0.99)
- North America > United States > Wyoming > Powder River Basin > NPR-3 > Teapot Dome Field > Tensleep Formation (0.99)
- North America > United States > Wyoming > Powder River Basin > NPR-3 > Teapot Dome Field > Sussex Formation (0.99)
- (7 more...)
Generation of a Compositional Model To Simulate EOR Processes for the Complex Fluids System of the Carito-Mulata Field, Venezuela
Rodriguez, Fernancelys Del Carmen (PDVSA Gas & Oil) | Lopez G., Leonardo (Petroleos de Venezuela S.A.) | Bello, Joaquin Antonio (Petroleos de Venezuela S.A.) | Skoreyko, Fraser A. (Computer Modelling Group Inc)
Abstract The Carito-Mulata field is located in eastern Venezuela. This field is ranked as a giant oil producer because of its 240,000 STB/D current oil production and its 6.5 MMMSTB original oil in place. It is possible to observe a significant compositional gradient from seventy-five fluid samples taken at different depths, over a column of fluids of approximately 4000 feet thick. This complex system changes from a gas condensate at the top to an under saturated black oil down the flank. The depth of the Gas-oil contact is estimated at 14,040 feet. The Carito-Mulata field has been operated and characterized traditionally in four blocks (Central, West, North and South). The fundamental goal of this study is to establish a compositional model that can represent areally and vertically the complex fluid system using an Equation of State (EOS), which represents a big challenge considering the huge number of laboratory experiments. This EOS will be used for EOR simulations under gas and nitrogen injection processes. The Peng-Robinson EOS was used to match the PVT experiments. Included in the matching parameters was the variation of the saturation pressure of the gas condensate due to nitrogen injection. A swelling test using black oil crude with the injection of gas condensate was also fitted, as well as stacked core miscible experiments of gas condensate displaced by nitrogen injection. Finally, a set of PVT tables were generated for the compositional numerical reservoir simulator. The most important result that has been obtained of this project is to prove that a single Equation of State can model the complex thermodynamic behavior of three areas that were previously modeled as isolated. Considering that the field could be under nitrogen or natural gas injection, the Equation of State generated in this study will allow the numerical simulation to predict the impact of these processes on the ultimate hydrocarbon recovery. Introduction The Carito-Mulata field is located in the Eastern Basin of Venezuela, about 50 km west from city of Maturรn, Monagas state. It is defined an asymmetrical anticline witch is characterized by a production of fluids whose composition varies with depth, from the condensate gas, at the crestal part of the structure, to under-saturated black oil in deep areas. The field is situated in the northern part of Monagas State, between the El Furrial and Santa Barbara oilfields. Its production started in 1988 with the MUC-1E well. The reservoirs present a considerable level of heterogeneity as a result of a combination of complex geological events, including compressional tectonics, faulting and a diversity of sedimentary environments. At the present time, the central and western blocks of the field are subject to natural gas injection, the northern block undergoes water injection while the southern one flows naturally. Despite of the good definition of the fluid distribution throughout the field, the actual compositional modeling was still carried out in an isolated way previous to this study. In order to create an integrated simulation model taking into account the observed communication between blocks, it is indispensable to have a correct areal and vertical fluid characterization based on revision and validation of the available laboratory data. These include PVT studies, production data, RFT logs, etc. In case of EOR process modeling, it is necessary to also consider the special fluid tests (swelling test and displacement measures on cores) which permit the evaluation of the injected gas effect on the original fluid properties in the reservoir, particularly at the saturation pressure. The compositional modeling which is the subject of the present paper was aimed at reproducing the fluid behavior under reservoir and surface conditions through the equation of state (EOS) and experimental data. The objective is optimizing the field exploitation strategies considering the injection of nitrogen or natural gas.
- South America > Venezuela > Anzoรกtegui (1.00)
- North America > United States > Texas (0.87)
- South America > Venezuela > Monagas > Maturin (0.24)
- South America > Venezuela > Anzoรกtegui > Eastern Venezuela Basin > Oficina Area > Mulata Field > Oficina Formation (0.99)
- South America > Venezuela > Monagas > Eastern Venezuela Basin > Maturin Basin > Santa Barbara Field (0.94)
- South America > Venezuela > Eastern Venezuela Basin > Furrial Field (0.94)
- Oceania > Australia > Victoria > Bass Strait > Gippsland Basin (0.89)
Abstract A numerical model for the analysis of multiphase flow on vertical or slightly inclined wells has been developed. The model calculates flow properties (velocity of each phase, volumetric fraction of each phase, pressure and fluids properties) on gas-oil-water wells as function of depth. Fluids properties are obtained under the assumption of black oil model by means of correlations taken from literature, requiring only petroleum ยฐAPI and the gas specific gravity as input data. The model may be applied to simulate both liquid flow and gas-liquid flow. In this case, different flow patterns are taken into account: -bubble, slug, dispersed bubble and annulardepending on flow conditions, which are determined from fluid properties and production rates of oil, gas and water. Flow in tubings consisting of several sections with different diameters and inclinations may also be simulated. The model was validated by comparisons of measured and calculated the pressure variation along the well Good agreement was found between the numerically predicted pressure drop and measurements taken from different databases from open literature. As a consequence the proposed model proves to be a reliable tool to describe the flow on oil-gas-water wells. The developed numerical model takes into account the most relevant effects that take place in a production well including multiphase flow, presence of different flow pattern, mass transfer from gaseous to liquid phase and influence of gas-liquid flow pattern on wall friction. Special attention is paid to the velocity profile of each phase along the well. Ishii's model for two-fluid flow is used to prescribe the slip velocity between liquid and gaseous phases and to determine the acceleration term contribution to the pressure gradient. This model is actually being employed for corrosion rate calculations inside production wells. Introduction The study of the multiphase flows (water - oil - gas) is of major importance in oil industry since it is found quite frequently during the production process. The physics involved in these flows is very complex due to interactions between the different phases. In order to deal with this complexity, sophisticated numerical models with several parameters (most of them determined from experiments) are required. The complexity of the problem leads to a number of simplifying assumptions and to the use of correlations to model some terms of the equations. Many numerical methods have been proposed in order to prescribe flow variables (velocities of each phase, volume fraction of each phase, flow pattern, pressure gradient) along the tubing for vertical upward flow. There is a wide variety of numerical methods, including simple models where liquid and gas are supposed to have same velocity [1โ3], models that account for slippage between gas and liquid but do not consider the existence of different flow patterns [4โ6], models that take into account different flow patterns [7โ12] to complex mechanistic models [13โ17]. In this work an alternative numerical model to estimate the flow characteristics along a vertical or near vertical pipe is presented. The proposed method belongs to the class of models described in references [7โ12]. However, instead of using a correlation for liquid hold up we use a correlation for the slip velocity between liquid and gaseous phases and calculate the hold up from conservation equations. It was codified in a FORTRAN code named GOW flow. In the next section the general equations of the model are introduced. Then the modeling of different terms taking part in the equations is presented, followed by the description of the algorithm. There is a section devoted to the validation and another one to the application. In the last section conclusions and future work are discussed. Equations Governing equations were obtained from mass conservation for each component and global momentum conservation principles in steady state [18]. The equations were averaged across the -assumed circular- section S of the pipe in order to obtain a one-dimensional model.
Abstract In the Eastern Venezuela gas assets, mid to long term planning business portfolio considers an increasing gas production potential and recoverable reserves under secondary or improved recovery methods. Most gas reservoirs are originally under or near saturation pressure. Native thermodynamic conditions along with typical production practices favor in-situ liquid condensation, leaving behind considerable non-recoverable liquid hydrocarbons. This liquid condensation is triggered by unfavorable pressure gradients developed under natural production as reservoir static pressure drops below saturation pressure, primarily in the near wellbore region. In addition, as gas expands due to the adiabatic real-gas-expansion Joule-Thompson effect, a reduction in the surrounding temperature is also expected. This effect, in turn, often favors a sharp reduction in the relative permeability to gas when "In Situ" liquid condensation takes place at interstitial level hence promoting a drastic decay in the gas productivity. Consequently, a considerable amount of liquid hydrocarbon is left behind in the reservoirs. Based on the nature of the experimental findings, the availability for flue gas in the Eastern Venezuelan region, and the environmental concerns, a breakthrough improved Condensate Recovery (ICR) project is being considered by "Cyclic Supercritical CO2 Injection". The cyclic nature of the process combined with the favorable equivalent density for the CO2 at reservoir condition is expected to positively impact thermal diffusion and accelerated mass transfer processes respectively mainly in the near wellbore region. In this project, pilot temperatures are expected to be in the range of 350 to 450 oF. A combined effort to integrate experimental results into a numerical model was undertaken. A number of laboratory tests were programmed to typify both fluid and rock interactions and also to characterize the thermodynamic profile for the CO2 and In Situ live fluid. The interaction coefficients of the equation of state (EOS) for the enhanced process were experimentally characterized reproducing the multiple contact events between the in situ liquid hydrocarbon and the foreign fluid (CO2) as a function of temperature. Expected sweep efficiencies and residual liquid saturation after multiple contacts with CO2 were experimentally determined via core displacement tests using actual core samples. Soaking time extent was also optimize for energy diffusion purposes. At a second stage, a single well model will be assembled, to numerically reproduce the experimental results, to match primary depletion and to predict enhanced recovery production profile. For field implementation, a pilot area was selected in the Santa Rosa Field belonging to Petroleos de Venezuela assets. Introduction "Anaco Gas" is compounded by two major areas: "Area Mayor de Anaco", with mostly volatile and Gas condensate bearing sands, and "Area Mayor de Oficina", with medium to light hydrocarbon sands. As can be seen in Figure Nยบ 1, Santa Rosa field is part of the "Area Mayor de Anaco", and is also one of the main areas of the asset in terms of gas remaining reserves. Typical stratigraphic column is 10.000 feet width, distributed among 150 hydrocarbon sands (Figure Nยบ 2). These sands are mostly associated to gas condensate production with relatively small API gradients both laterally and vertically. Most of these reservoirs are in advanced state of depletion. As pressure drops within the reservoir, a significant volume of unrecoverable liquid hydrocarbon is gradually left behind, mainly given by phase migration and saturation gradient related damage mechanisms which in turn promote a considerable reduction in productivity to gas mainly in the near wellbore region. Efforts are being undertaken by PDVSA to increase final recovery of liquid hydrocarbon by Improved Condensate Recovery (ICR) techniques. A pilot ICR project is being developed in the Santa Rosa Field, VEE3 Sands, based on the experimental findings, as well as on the availability of flue gas from both upstream and downstream processes.
- South America > Venezuela (1.00)
- Africa > Angola > South Atlantic Ocean (0.65)
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > South America Government > Venezuela Government (0.54)
- South America > Venezuela > Anzoรกtegui > Eastern Venezuela Basin > Maturin Basin > Santa Rosa Field (0.99)
- Africa > Angola > South Atlantic Ocean > Kwanza Basin > Block 17 > Rosa Field (0.99)
Abstract Enhanced Oil Recovery (EOR) methods include injection of different fluids into reservoirs to improve oil displacement. Analytical models for 1-D displacement of oil by gas have been developed during the last 15 years. It was observed from semi-analytical and numerical experiments that several thermodynamic features of the process are not dependent on transport properties. The model for one-dimensional displacement of oil by miscible fluids is analyzed in this paper. The main result is the splitting of thermodynamical and hydrodynamical parts in the EOR mathematical model. The introduction of a potential associated with one of the conservation laws and its use as an independent variable reduces the number of equations. The reduced auxiliary system contains just thermodynamical (equilibrium fractions of each phase, sorption isotherms) variables and the lifting equation contains just hydrodynamical (phases relative permeabilities and viscosities) parameters while the initial EOR model contains both thermodynamical and hydrodynamical functions. So, the problem of EOR displacement was divided into two independent problems: one thermodynamical and one hydrodynamical. Therefore, phase transitions occurring during displacement are determined by the auxiliary system, i.e. they are independent of hydrodynamic properties of fluids and rock. For example, the minimum miscibility pressure (MMP) is independent of relative permeabilities and phases viscosities. The new technique developed permits splitting for both self-similar continuous injection problems and for non-self-similar slug injection problems. Splitting significantly reduces amount of calculations for sensitivity study with respect to transport properties: auxiliary thermodynamic problem may be solved once for given reservoir and injected compositions; variation of relative permeabilities and viscosities should be performed just in the solution of one transport equation. In this paper, different analytical solutions for 4-component gas injection problems are analysed. It was considered the injection of nitrogen and hydrocarbon gases into a three-component liquid reservoir fluid. The eigenvalues of the system are related to the propagation velocity of each component in porous media. The existence of elliptic regions (complex eigenvalues) is well known in three-phase flow, but for the first time it is shown that this feature may also occur in two-phase flow. The independence of compositional dynamics on transport properties can be used for testing numerical compositional simulators. If the mobility ratio is close to one, this model may be applied in the development of streamlines simulators. Introduction The injection of fluids not present in reservoirs is the technical definition of Enhanced Oil Recovery (EOR) methods 1. These methods may be classified into three main categories: chemical, solvent and thermal. Solvent methods of EOR may be either miscible or immiscible, depending on the thermodynamic behavior of the mixture of fluids at reservoir temperature and pressure. It was one of the earliest methods used to improve oil recovery. Immiscible solvent displacement reduces oil viscosity and swells reservoir fluid, whereas miscible flooding; besides the characteristics already cited also develops miscible displacement, eliminating interfacial forces. Miscible solvent flooding techniques always involve some mass transfer between phases, like vaporization or condensation of components. The choice of kind and amount of fluid to be injected is strongly dependent on economical aspects. Although liquefied petroleum gas (LPG) has already been the most used solvent injection fluid, now carbon dioxide plays an important role. Usually, a solvent slug is injected into reservoir and driven by a "follow up" fluid.
- Materials > Chemicals > Commodity Chemicals > Petrochemicals (1.00)
- Energy > Oil & Gas > Upstream (1.00)
Abstract A three-parameter model relating the decline of the oil cut with the fractional oil recovery for waterflooded petroleum fields or reservoirs is described. The model is based on observation of the behavior of several Brazilian oil fields, in which the oil displacement occurs either by water injection or by natural aquifer influx, or both. The model is used to derive equations to forecast the oil and water production rates in waterflooded systems. These equations may also be used to design a waterflood expansion in any phase of a field's life. An example of the application of the model equations to forecast the behavior of a waterflood in a mature heavy oil field is presented. Because the results of the analysis indicated that the field will still be profitable at the end of the concession period, the model equations are applied to design and forecast an augmented waterflood for the field. The model equation may be used to estimate the oil reserves at any stage of maturity of an oil field. The model parameters are obtained by fitting the model equation to historical field data by means of a least square algorithm. A type-curve procedure is applied to obtain the initial guesses of the model parameters required by the mathematical algorithm. A relation between the oil cut decline model and the classical rate-time decline is derived for the case in which the total liquid flow rate is constant. Examples of oil cut decline of several Brazilian fields are presented and the decline model is used to determine the ultimate oil recoveries of these fields. The ultimate oil recovery is proportional to the amount of water produced during the field's life, which is related to the water-oil ratio at abandonment conditions. When the operating conditions of a field change, so does the oil-cut decline trend. An example of the change in the oil-cut decline trend is presented for a heavy oil field submitted to a late steam drive. Introduction Water injection and natural water influx are very effective mechanisms to displace oil towards the production wells and to maintain the reservoir pressure. Due to the nature of multiphase flow in porous media, such mechanisms always lead to an increasing water-oil ratio in the producing wells. Forecasting both oil and water rates is of utmost importance for the design and implementation of waterflood projects in the several phases of the field's life. Historical data of oilfields show that it is possible to keep the oil throughput nearly constant for very long time by continuously increasing the water injection rate. For instance, by keeping constant bottom-hole pressures in both producers and injectors wells, the increase in the liquid rate is natural in heavy oil fields, since the low mobility oil is displaced by the high mobility chasing water. Infill drilling also helps to increase the injection rate, and consequently the total liquid production, due to the increase in the reservoir pressure gradient. In both cases, there is an increase in the drainage velocity and, when the capillary and gravitational effects are small, the ultimate oil recovery will not be affected by increasing the drainage velocity. In this case the increase in the water injection rate anticipates the oil recovery. Here we use simple methods to extrapolate the oil cut in order to forecast the capacity of the surface facilities required to handle the produced water, once a restriction in produced water rate leads to a decrease in the oil production rate. In fields under water injection or water drive mechanisms, the water breakthrough occurs after a period of primary production, where a given fraction of the initial oil in place is recovered. This period is followed by both a continuous increase in the water-oil ratio and a continuous reduction in the oil cut. Arps 1 presented a hyperbolic equation to describe the decline of the oil rate with time. Such equation has shown to be of restricted use for waterflooded reservoirs, where an infill drilling campaign can even cause an increase in the oil rate. However, even in this scenario the oil cut always decline.
- North America > United States (0.46)
- Asia > Middle East > Israel > Mediterranean Sea (0.34)
- South America > Brazil (0.28)
- Water & Waste Management > Water Management > Lifecycle > Disposal/Injection (1.00)
- Energy > Oil & Gas > Upstream (1.00)
Abstract Successful design and implementation of a miscible gas injection project depends upon the minimum miscibility pressure (MMP) and other factors such as reservoir and fluid characterization. The experimental methods available for determining MMP are both costly and time consuming. Therefore, the use of correlations that prove to be reliable for a wide range of fluid types would likely be considered acceptable for preliminary screening studies. This work includes a comparative evaluation of MMP correlations and thermodynamic models using an equation of state by PVTsim 1 software. We observed that none of the evaluated MMP correlations studied in this investigation is sufficiently reliable. EOS-based analytical methods seemed to be more conservative in predicting MMP values. Following an acceptable estimate of MMP, several compositional simulation runs were conducted to determine the sensitivity of the oil recovery to variations in injection pressure (at pressures above, equal to and below the estimated MMP), stratification and mobility ratio parameters in miscible and immiscible gas injection projects. Simulation results indicated that injection pressure was a key parameter that affects oil recovery to a high degree. MMP determined to be the optimum injection pressure. Stratification and mobility ratio could also affect the recovery efficiency of the reservoir in a variety of ways. Introduction Through the past decades, miscible displacement processes have been developed as a successful oil recovery method in many reservoirs. The successful design and implementation of a gas injection project depends on the favorable fluid and rock properties. The case studies using Eclipse 2 compositional simulator considered the effect of key parameters, such as injection pressure, stratification and mobility ratio on the performance recovery in miscible and immiscible flooding of the reservoir. However, accurate estimation of the minimum miscibility pressure is important in conducting numerous simulation runs. MMP is the minimum miscibility pressure which defines whether the displacement mechanism in the reservoir is miscible or immiscible. Thermodynamic models using an equation of state and appropriate MMP correlations were used in determining the MMP. Compositional simulation runs determined the sensitivity of the oil recovery to the variations in above mentioned parameters. Significant increase in oil recovery was observed when interfacial tension dependent relative permeability curves were used. These relative permeability curves provide an additional accounting for miscibility by using a weighted average between fully miscible and immiscible relative permeability curves. The local interfacial tension determines the interpolation factor which is used in obtaining a weighted average of immiscible and miscible (straight line) relative permeabilities. Simulation runs were performed at pressures below, equal to, and greater than estimated MMP for reservoir fluid/ injection gas system. Oil recovery was greatest when miscibility achieved. To investigate the effect of stratification on the performance recovery of the reservoir, the base relative permeability of two layers changed. Location of the high permeable layer (up or bottom layer) in the stratified reservoir greatly influenced the efficiency of the reservoir. Understanding the effect of interfacial tension and adverse mobility ratio on the efficiency of the gas injection project was the last case study. Injection gas and reservoir fluid compositions differed in such a way to have interfacial tension and mobility dominated mechanism. To investigate the effect of interfacial tension water was considered as a fluid with much higher surface tension values with the oil. Lower surface tension values between rich gas and reservoir fluid (interfacial tension dominated) made gas injection project a more competitive recovery method than waterflooding. In mobility dominated displacement mechanism (lean gas/reservoir fluid system) the viscous instabilities were more important than the interfacial tension effect. For this case, waterflooding with favorable mobility ratio resulted in higher oil recoveries.
- Africa > Middle East > Libya > Wadi al Hayat District > Murzuq Basin > Block NC 186 > I&R Fields > R Field > Mamouniyat Formation (0.99)
- Africa > Middle East > Libya > Wadi al Hayat District > Murzuq Basin > Block NC 115 > I&R Fields > R Field > Mamouniyat Formation (0.99)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Gas-injection methods (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (1.00)
Abstract This paper compares the output of several available empirical black oil model correlations against compositional model results. In this process, the limitations of these models became apparent. Even acknowledging the imperfections of black model implementation, it is possible to improve the quality of the outputs by means of making the definitions consistent and coherent across the prediction ranges. A new method is outlined in order to extend the validity of the models in predicting both reservoir and multiphase flow simulations. This new method is presented here and will be extended in a separated paper. Introduction The behavior of black oil fluid is commonly inferred from two PVT laboratory procedures: flash (or separator test) and differential liberation. Oil formation volume factor and gas solution ratios are calculated as explained by McCain. On the other hand, given a particular EOS is possible to obtain PVT fluid parameters by simulating the same laboratory procedures or making direct flash calculations at any particular condition. The traditional calculation method outlined in 1 can be modified in a simple way to extend the validity of black oil model correlations by accounting the dew point curve. Negative gas solution ratios indicate liquid vaporization, and need not to be masked by any correction method. If we follow definitions literally, Rs diminish towards dew point and reaches a constant negative minimum at dew point and inside monophasic gas area. Oil formation volume factor can be lower than unity and in fact should be zero at dew point. As modern calculations take into account both reservoir and multiphase wellbore and pipeline calculations, is of paramount importance to be able to accurately predict fluid properties in a wider range of pressure and temperature conditions. The first objective of this paper is to make apparent the limitations of current PVT laboratory calculations and propose a revision. A second objective is to present black oil model standard correlations phase diagrams together with phase diagrams calculated with EOS and acknowledge the differences and limitations of empirical correlations. The third objective is to outline a new mathematical method to improve black oil correlations. Definitions The following definitions extracted from Dake will be taken as references: Rs. The solution (or dissolved) gas oil ratio, which is the number of standard cubic feet of gas which will dissolve in one stock tank barrel of oil when both are taken down to the reservoir at the prevailing reservoir pressure and temperature (units - scf. gas/stb oil). Bo. The oil formation volume factor, is the volume in barrels occupied in the reservoir, at the prevailing pressure and temperature, by one stock tank barrel of oil plus its dissolved gas (units - rb (oil + dissolved gas)/stb oil). Bg. The gas formation volume factor, which is the volume in barrels that one standard cubic foot of gas will occupy as free gas in the reservoir at the prevailing reservoir pressure and temperature (units - rb free gas/scf gas). These parameters enable converting fluid volumes at any conditions to volumes at standard conditions.