East crude oils were derived as a function of reservoir temperature, total surface gas relative density, solution GOR, and stocktank oil relative density. These empirical equations should be valid for all types of oil and gas mixtures with properties falling within the range of the data used in this study. PVT DataThe pVT analyses of 69 bottomhole fluid samples from 69 Middle East oil reservoirs were made available for this study. The experimentally obtained data points were 160 each for the bubblepoint pressure, Pb, and bubblepoint oil FVF, Bob, correlations, and 1,556 for the total FVF, B t , correlation. The ranges of the data used are shown in Table 2.
Empirical equations for estimating viscosity: above, at, and below the bubble point pressure were developed based on data from Saudi Arabian crude oils. Both statistical and graphical techniques have been employed to evaluate these equations as compared to other published crude oil viscosity correlations using the same data. It is shown that the developed correlations provide more accurate estimates of viscosity in all three regimes of pressure. Introduction Viscosity is the measure of resistance to fluid flow. Knowledge of viscosity is required in reservoir simulation, fluid flow through porous media and pipelines, well testing, and design of production pipelines, well testing, and design of production equipment. Crude oil viscosity can be classified into three regimes. Bubble Point Oil Viscosity It is the viscosity of crude oil at the bubble point pressure and a given temperature. point pressure and a given temperature. Oil Viscosity Above the Bubble Point It is defined as the crude oil viscosity at a pressure higher than the bubble point pressure and a pressure higher than the bubble point pressure and a given temperature. Oil Viscosity Below the Bubble Point It is the viscosity of crude oil below the bubble point pressure and a given temperature. With the point pressure and a given temperature. With the lowering of pressure below the bubble point pressure, gas is released leaving behind a saturated oil at the new pressure. When the pressure is lowered to atmospheric pressure, there is no dissolved gas left in the oil and such oil is called dead oil whose viscosity is referred to as the dead oil viscosity. In many cases, the only information available from PVT analysis of an oil sample are simple and readily PVT analysis of an oil sample are simple and readily measurable parameters such as gas relative density, oil API gravity, and gas-oil ratio. Direct viscosity measurements or complete compositional analyses of crude oils are expensive, therefore, empirical correlations, which are functions of these readily measurable PVT properties, are used to estimate oil viscosity. A number of different viscosity correlations have been presented in the literature, as shown in Table 1, and reviewed in detail by Khan. Most of these correlations were based on limited data from different geographical locations which introduced large potential errors. Moreover, these correlations involve complex mathematical expressions which do not explain the behavior of oil viscosity very clearly. In this study, an alternative approach to viscosity correlation development, along with new viscosity equations have been derived. In this approach, emphasis is placed on the natural variation of viscosity with PVT parameters. In this paper, the new correlations and four of the published correlations, namely those of Beal, Chew and Connally, Beggs and Robinson, and Vazquez, will be evaluated using Saudi Arabian crude oil viscosity data which was used to develop the new correlations. VISCOSITY DATA This study utilized viscosity data for 75 bottom hole samples taken from 62 Saudi Arabian oil reservoirs. P. 251
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractReservoir fluid properties are very important in reservoir engineering computations such as material balance calculations, well test analysis, reserve estimates, and numerical reservoir simulations. Ideally, these properties should be obtained from actual measurements. Quite often, however, these measurements are either not available, or very costly to obtain. In such cases, empirically derived correlations are used to predict the needed properties. All computations, therefore, will depend on the accuracy of the correlations used for predicting the fluid properties.This study presents Artificial Neural Networks (ANN) model for predicting the formation volume factor at the bubble point pressure. The model is developed using 803 published data from the Middle East, Malaysia, Colombia, and Gulf of Mexico fields. One-half of the data was used to train the ANN models, one quarter to cross-validate the relationships established during the training process and the remaining one quarter to test the models to evaluate their accuracy and trend stability. The results show that the developed model provides better predictions and higher accuracy than the published empirical correlations. The present model provides predictions of the formation volume factor at the bubble point pressure with an absolute average percent error of 1.789%, a standard deviation of 2.2053% and correlation coefficient of 0.988. Trend tests were performed to check the behavior of the predicted values of B ob for any change in reservoir temperature, Gas Oil Ratio (GOR), gas gravity and oil gravity. The trends were found to obey the physical laws.
The compressibility factor (z-factor) of gases is a thermodynamic property used to account for the deviation of real gas behavior from that of an ideal gas. Correlations based on the equation of state are often implicit, because they require iteration and are computationally expensive. A number of explicit correlations have been derived to enhance simplicity; however, no single explicit correlation has been developed for the full range of pseudoreduced temperatures 1:05 T pr 3 À Á and pseudo-reduced pressures 0:2 P pr 15 À Á , which represents a significant research gap. This work presents a new z-factor correlation that can be expressed in linear form. On the basis of Hall and Yarborough's implicit correlation, we developed the new correlation from 5346 experimental data points extracted from 5940 data points published in the SPE natural gas reservoir engineering textbook and created a linear z-factor chart for a full range of pseudo-reduced temperatures ð1:15 T pr 3Þ and pseudo-reduced pressures ð0:2 P pr 15Þ.
This paper presents new correlations for formation volume factors (FVF) at, above and below bubblepoint pressure for oil and gas mixtures as empirical functions of solution gas oil ratio, gas relative density, oil relative density pressure, and reservoir temperature. The correlations are developed from a total of 11 728 experimentally obtained FVF at above and below bubblepoint pressure on oil-gas mixtures collected from fields allover the world. The data encompassed a wide range of gas-oil ratios, oil and gas relative densities, pressure and reservoir temperature. The newly developed correlations outperform the existing correlations for FVF of oil and gas mixtures based on high correlation coefficient and on low values of average per cent relative error, average absolute per cent relative error and standard deviation. Introduction The evaluation of FVF at, above and below bubblepoint pressure of oil-gas mixtures is an important tool in reservoir performance calculations and the design of various stages of oilfield operations. The following presents a review of the development of FVF correlations. The empirical equations that form these published correlations are provided in the Appendix. Oil FVF at Bubblepoint Pressure In 1947, Standing(1,2) proposed a correlation for determining the formation volume factor of a gas-saturated oil. A total of 105 experimentally determined data points on 22 different crude oil gas mixtures from California fields were utilized in arriving at the correlation. In 1980, Vazquez and Beggs(3,4) presented relationships for determining the formation volume factor. A total of 6004 data points were obtained from fields all over the world. In 1980, Glas Φ (5) presented a correlation for calculating the formation volume factor. A total of 41 data points, obtained mostly from the North Sea Region, were used in the correlation. In 1988, Al-Marhoun(6) presented a correlation for calculating the formation volume factor. A total of 160 experimentally determined data points on 69 different crude oils from the Middle East were used in the correlation. Oil FVF Above Bubblepoint Pressure In 1947, Calhoun(7) presented a chart correlation for calculating the undersaturated oil compressibility. The following equation is proposed here instead of chart reading: Equation 1 (available in full paper) In 1980, Vazquez and Beggs(3,4) presented a correlation for determining the undersaturated oil compressibility. A total of 2000 data points obtained from fields all over the world were used in the correlation. The undersaturated oil compressibility is utilized in the following equation to calculate oil FVF above bubblepoint pressure: Equation 2 (available in full paper) Total FVF Below Bubblepoint Pressure In 1980, Glass Φ (5) presented a correlation for calculating the total formation volume factor below bubblepoint pressure, A total of 36 data points from 15 crude samples, obtained mostly from the North Sea Region, were used in the correlation. In 1988, Al-Marhoun(6) presented a correlation for calculating the total formation volume factor. A total of 1556 experimentally determined data points on 69 different curde oils from the Middle East were used in the correlation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.