Adel M. Elsharkawy

Predicting PVT data for CO2-brine mixtures for black-oil simulation of CO2 geological storage

Accurate modeling of the storage or sequestration of CO2 injected into subsurface formations requires an accurate fluid model. This can be achieved using compositional reservoir simulations. However, sophisticated equations of state (EOS) approaches used in current compositional simulators are computationally expensive. It is advantageous and possible to use a simple, but accurate fluid model for the very specific case of geological CO2 storage. Using a black-oil simulation approach, the computational burden of flow simulation can be reduced significantly. In this work, an efficient and simple algorithm is developed for converting compositional data from EOS into black-oil PVT data. Our algorithm is capable of predicting CO2‐brine density, solubility, and formation volume factor, which are all necessary for black-oil flow simulations of CO2 storage in geological formations. Numerical simulations for asimple CO2storage case demonstrate that the black-oil simulationruns are atleast fourtimes fasterthan thecompositional oneswithout lossof accuracy. Theaccuracy in prediction of CO2‐brine black-oil PVT properties and higher computational efficiency of the black-oil approach promote application of black-oil simulation for large-scale geological storage of CO2 in saline aquifers.

Wax deposition from Middle East crudes

This paper reports measurements of wax content by acetone precipitation techniques as well as wax appearance temperature (WAT) by viscosity measurements and differential scanning calorimetry (DSC) of eight different stock-tank crude oils from the Middle East. Comparison of WAT measured by DSC and viscosity indicates that the viscosity method overestimates the WAT. Crude oil gravity measured, by digital density meter, and molecular weight, by vapor pressure osmometer, were used to characterize the plus fraction and predict WAT and amount of wax formed at a given condition by the thermodynamic model. Comparison between predicted and measured results shows that measured WAT by DSC compares very well with that predicted from the model for most crudes. Generally, wax contents measured by the modified UOP method 46-64 and that predicted by the thermodynamic model are in good agreement.

Models for predicting the viscosity of Middle East crude oils

New empirical models for predicting the viscosity of Middle East crude oils; dead, saturated, and undersaturated, are presented. The accuracy and limitations of previously published models for predicting the viscosity of crude oils are also reviewed and discussed. The study uses viscosity data of 254 crude oil samples collected from the Middle East for the development of the proposed empirical models. These models can be used to predict viscosity of crude oils from the Middle East where experimentally measured data become unavailable, at temperatures other than reservoir temperature for the design of production equipment and pipelines, and for planning thermal methods of enhanced oil recovery.

An empirical model for estimating the saturation pressures of crude oils

Abstract Recently, there has been an increasing interest in enhanced oil recovery (EOR) calculations of saturation pressures when various gases contact crude oils. Equations of state are usually used for calculations of saturation pressure at initial condition of discovery or later during EOR design. However, the equations of state results are not reliable unless they are properly tuned using some experimental data of reservoir fluid. The availability of extended analysis of reservoir fluids, characterization of heavy fraction, and number of components are influencing the saturation pressure estimated by equations of state. A simple empirical model to calculate the saturation pressures of crude oil systems was developed. Experimentally measured compositions and saturation pressures of 60 crude oil samples from the Middle East were used to develop the model. Compositions and saturation pressures of 75 crude oil samples from the literature were used to test the accuracy and validity of the model against measured data and simulations by equations of state. The results indicate that the model is accurate, valid, reliable, and eliminates the splitting and characterizing of the heavy fraction, which is necessary for the equations of state. The model is useful for estimating the saturation pressure where experimental data is not available. For EOR processes, the model can be used to calculate the saturation pressure during single contact by hydrocarbon gases.

THE ACCURACY OF PREDICTING COMPRESSIBILITY FACTOR FOR SOUR NATURAL GASES

This paper presents the initial stage of an effort aimed at developing a new correlation to estimate pseudo critical properties for sour gas when the exact composition is not known. Several mixing rules and gas gravity correlations available in the literature are first evaluated and compared. The evaluation is performed on a large database consisting of more than 2106 samples of sour gas compositions collected worldwide. Several evaluation criteria are used including the average absolute deviation (AAD), the standard deviation (SD), the coefficient of correlation, R, and cross plots and error histograms. The mixing rules include: Kays mixing rule combined with Wichert–Aziz correlation for the presence of non-hydrocarbons, SSBV mixing rule with Wichert and Aziz, Corredor et al. mixing rule, and Piper et al. mixing rule. These methods, in one form or another, use information on gas composition. Three different other methods that are based on gas gravity alone were also analyzed. These are: Standing, Sutton, and Elsharkawy et al. gas gravity correlations. While the methods based on knowledge of composition showed reasonable accuracy, those based on gas gravity alone showed weak accuracy with low correlation coefficients. A new gas gravity correlation that is based on the fraction of non-hydrocarbons present in the sour gas was proposed. Preliminary results indicate that a good improvement over past gravity correlations was achieved. The compositional correlations, still show, however, better accuracy. Research is still going on to come up with more accurate correlations that are based on only readily available descriptors.

Correlations for predicting solution gas/oil ratio, oil formation volume factor, and undersaturated oil compressibility

Abstract Careful estimation of reservoir fluid behavior is necessary for evaluating of hydrocarbon reserves, predicting future performance, designing production facilities, and planning methods of enhanced oil recovery. Over the last decade increased attention has been focused on models for predicting reservoir fluid properties from reservoir pressure, temperature, crude oil API gravity, and gas gravity. The present study develops new empirical PVT correlations for estimating the solution gas/oil ratio, bubblepoint oil formation volume factor, and isothermal oil compressibility above bubblepoint for crude oils. Multiple regression analysis was used in developing those correlations. A total of 175 PVT analyses of crude oil samples collected from different Kuwaiti oil fields were used to develop the new correlations. Some of the recently developed correlations and those frequently used in the literature were compared to the new correlations. The correlations developed in this study exhibit significantly lower average absolute error and standard deviation than the other published correlations.

Assessment of the PVT correlations for predicting the properties of Kuwaiti crude oils

Abstract Several correlations have been proposed for determining PVT properties. Limitations concerning the validity of these correlations for different types of hydrocarbon systems, accuracy, range of applicability, corrections for non-hydrocarbons contents, etc., have been controversial. Because crude oils from different regions have different properties, it is recommended to assess the accuracy of the available correlations. The present study is concerned with the assessment of these correlations for a variety of oils from Kuwaiti fields. The study evaluated recently developed correlations in the Middle East region and the Arabian Gulf as well as those most often used. The limitations of these correlations have been analyzed. Forty-four individual crude oil samples from Kuwaiti oil fields were used in this study. Corrections due to the presence of non-hydrocarbon gases, adjustment to oil composition, and correction of gas gravity to common separation conditions were taken into consideration. It was found that Standings correlation showed the best accuracy for predicting the bubble-point pressure among all others, though such accuracy is beyond desirable engineering limits. All the correlations examined in the present study showed a comparable accuracy in predicting OFVF at the bubble point with Al-Marhouns correlation having the least deviation.

Predicting Volumetric and Transport Properties of Sour Gases and Gas Condensates Using EOSs, Corresponding State Models, and Empirical Correlations

Abstract Compressibility, density, and viscosity of natural gases are necessary in most petroleum engineering calculations. Some of these calculations are gas metering, gas compression, design of processing units, and design of pipeline and surface facilities. Properties of natural gases are also important in calculation of gas flow rate through reservoir rock, material balance calculations, and evaluation of gas reserves. Usually the gas properties are measured in laboratory. Occasionally, experimental data become unavailable and these properties are estimated from equations of state, corresponding state models or empirical correlations. This article presents the results of using various equations of state, corresponding state methods, and correlations to predict the volumetric and transport properties of sour gases and gas condensates. Capabilities of PR-EOS, SRK-EOS, and PT-EOS to predict gas compressibility and density of 2100 gas samples under various schemes of binary interaction number are thoroughly investigated. This study also reports a comparison between recently developed EOS-based viscosity models and other methods to estimate the viscosity of highly sour gases and rich gas condensates.

Universal Neural Network Based Model for Estimating The PVT Properties of Crude Oil Systems

This study presents a universal neural-network-based model for the prediction of PVT properties of crude oil samples obtained from all over the world. The data, on which the network was trained, contains 5200 experimentally obtained PVT data sets of different crude oil and gas mixtures from all over the world. They were collected from major-producing oil fields in North and South America, the North Sea, Southeast Asia, the Middle East, and Africa. This represents the largest data set ever collected to be used in developing PVT models. An additional 234 PVT data sets were used to investigate the effectiveness of the neural-network models to predict outputs from inputs that were not used during the training process. The neural network model is able to predict the solution gas−oil ratio and the oil formation volume factor as a function of the bubble-point pressure, the gas relative density, the oil specific gravity, and the reservoir temperature. The neural-network models were developed using back-propagatio...

Planning Miscibility Tests And Gas Injection Projects For Four Major Kuwaiti Reservoirs

The escalating oil demand and maturity of most of the giant oil fields in the world, especially in the Middle East, the techniques for improving oil recovery have became more feasible and essential. Kuwait long term strategy is to increase oil production to meet marked demand. Currently, miscible gas injection is considered for enhancing oil production from Kuwaiti oil reservoirs. A key parameter for assessing the applicability of gas injection for a given reservoir is the minimum miscibility pressure (MMP). In this paper various miscibility experiments for planning gas injection projects in major producing fields in Kuwait are discussed. These experiments include swelling tests, slim-tube tests, and core flooding studies. These tests are useful tool for screening of the potential reservoirs for improving their future oil production and for developing suitable EOS for planning gas injection projects of the chosen fields. INTRODUCTION Many definitions of miscible displacement have been widely discussed in the literature (Benham et. al., 1965, Stalkup, 1983, Holm, 1987, and Lake, 1989). These definitions clearly convey a consensus that miscibility refers to the absence of an interface between the injected fluids and the reservoir crude oil. The absence of an interface means, in terms of a measurable variable, the value of the interfacial tension between the displacing and displaced fluids is zero. Miscible displacement is only achieved at pressures greater than a certain minimum. This minimum is called the Minimum Miscibility Pressure (MMP). The MMP of a gas/oil pair is traditionally determined by flooding an oil-saturated slim-tube with a gas at four or five different pressures; the MMP is defined as the lowest pressure at which essentially all oil available for recovery can be displaced by 1.2 of the pore volume of solvent injected. This pressure can be located graphically by the intersection of two lines that define both an immiscible and miscible performance regimes on a plot of recovery versus pressure, or recovery versus composition. The methods for estimating MMM are classified into experimental and calculation methods. The experimental methods for measuring MMP are; slim tube apparatus, rising bubble apparatus, PVT Cell, variable interfacial tension, and other methods. Slim-tube method is the most common and has been accepted as the standard method to determine MMP. The MMP calculation methods are divided into; correlation, numerical (simulation), and analytical (EOS) methods. Because of their improved speed, analytical methods offer significant promise for developing improved fluid correlations and for use in compositional streamline simulations. Minimum Miscibility Pressure Experimental Methods Slim-Tube Test In this method, the miscibility conditions are determined by conducting the displacements at various pressures or gas enrichment levels in the oil-saturated Slim-tube and monitoring the oil recovery. Then, the oil recovery is plotted against the pressure (Stalkup, 1983). The minimum miscibility pressure is defined as the pressure at which the oil recovery versus pressure curve shows a sharp change in slope. The MMP is traditionally defined as the lowest pressure at which essentially all oil available for recovery can be displaced by 1.2 PV solvent injected. The disadvantages of this method are; it is very time consuming, expensive, does not account for third fluid water, and several points are required to establish the MMP (a minimum of five points are recommended). Furthermore, Slimtube may give a lower MMP that it actually is because the way the porous medium is packed. On the other hand, Slim-tube test can mimic porous medium and hence are capable of representing multicontact fluid dispersions mechanism due to mixing in the porous medium. Rising Bubble Apparatus (RBA) In the rising bubble experiments, the MMP is inferred from the pressure dependent behavior of rising bubbles. The MMP is determined from the observations of changes in shape and appearance of bubbles of the injected gas as they rise through a thin column of crude oil. The pressure at which a rising gas bubble vanishes in a column of oil is termed as the MMP (Christianson and Haines, 1984). This method is considerably faster with low cost and requires smaller quantities of fluids, compared