Predicting and assuring well deliverability is often an important concern during the development of gas-condensate reservoirs, especially offshore fields. In addition, production of gas is usually bound with long-term contracts where it is necessary to assure well deliverability for a long period. Undesirably, well deliverability in gas-condensate reservoirs can be impaired by the formation of a condensate blockage once the bottomhole flowing pressure drops below the dewpoint pressure. In this case, the relative permeability of the gas phase can be significantly reduced due to this condensate accumulation around the wellbore. Therefore, quantifying this negative effect is essentially required to obtain reliable predictions of well deliverability in gas-condensate reservoirs. The evaluation of condensate blockage phenomenon requires an appropriate understanding of flow characteristics of both gas and condensate liquid through reservoir rocks. In this study, the impact of condensate blockage on gas well deliverability was investigated by examining a number of flow parameters such as absolute permeability (K), critical condensate saturation (Scc), relative permeability shape and end-points (krgmax, kromax). A single well radial and cartesian models were both used in different simulators (modified black-oil and compositional). The outcomes of this study showed that the condensate blockage can have a severe negative impact at low permeability reservoirs (K≈5md), while the impact can be small at moderate permeability (k≈50md) and diminishable at high permeability reservoirs (k≈200md). This negative impact can double at high critical condensate saturation (Scc>30%). It was found out that the relative permeability curves applied in the model define the magnitude of the blockage, especially in low permeability reservoirs, whereas relative permeability end-points (krgmax and kromax) affect mainly the overall gas recovery. Previous lab measurements showed that gas-condensate relative permeabilities are sensitive to flow velocity only in low permeability reservoirs. This effect was modeled using a compositional model through the capillary number. Velocity-dependent relative permeability model applied in this case showed that the plateau period can be improved by a factor of two in low permeability. On the other hand, no positive effect was observed at moderate and high permeability since the blockage effect was already small or dimensionless. Finally, the benefit of methanol injection was investigated for improving well deliverability at low permeability reservoirs. Based on this analysis, methanol treatment can improve gas well deliverability and substantially prolong the plateau period by a factor of 2-3.

The minimum miscibility pressure (MMP) is one of the most important parameter to be determined in miscible gas injection projects to ensure and maximize the displacement sweep efficiency inside the reservoir. Usually the most effective way of determining the MMP is to run slim tube experiments. However, in the early screening stage, we often relay on the published empirical correlations to estimate the MMP and identify the candidate fields for EOR gas injection projects. The main objective of this paper was to examine different published empirical CO 2 MMP correlations using measured data mainly obtained from Libya and other published resources, and also to develop a new simple reliable correlation to be applied in the oil industry. The data collected covered a wide range of CO 2 MMP (1544-6244 psia) and oil API gravity (28-50ºAPI). Minitab regression tool was extensively used in our study and a wide range of new constructed correlations ranging from simple to complex ones were developed and statistically evaluated. The proposed simple CO 2 MMP correlation is mainly function of the measured Pb, API, T and Rsi and has very reliable degree of accuracy (SD=6.7%, ARE=0.44%, AARE=5.74%, R 2 =95.22%) for the examined data and has shown better performance when compared with the industry popular correlations. The new correlation was validated against 100 measured PVT variables (Pb, Rsi, T and API) obtained from Libya, and the predicted CO 2 MMP results have demonstrated very reliable trend (within the measured CO 2 MMP trend) with no anomalies.

Compositional models based on cubic equations of state (EOS) are generally employed for simulation of the reservoir performance in gas injection processes. Tuning of the EOS to experimental equilibrium data generated at static conditions, PVT data, prior to its use for compositional studies is the current practice in the oil industry. The displacement of oil in a slim tube by the injection gas simulates the phase behaviour resulting from the continuous contact between the two phases in the reservoir more realistically than any other laboratory tests. It has therefore been suggested that the comparison of the displacement data with simulated results of a compositional model using the tuned EOS can be employed to evaluate and, if necessary, further tune the phase behaviour model. As the flow parameters and numerical methods incorporated in the simulation model can strongly affect the prediction results, the value of such an exercise has been seriously questioned. A systematic study of the applicability of the gas-oil displacement data for tuning of the phase behaviour model to simulate gas injection processes was conducted in this study. The flow characteristics of a number of slim tubes packed with glass beads were evaluated by displacing binary oil mixtures with equilibrated gases to measure the relative permeabilities of the phases at no mass transfer conditions. A large amount of data at different interfacial tension values were used to develop relative permeability-saturation correlations as a function of the interfacial tension. Liquid-Liquid displacement tests were conducted to measure the physical dispersion in the slim tube. The information was used to select the grid block/time step size of the simulator to match the numerical dispersion, due to the truncation error, to that of the physical dispersion. The reliability of the developed parameters was confirmed by comparing predicted and measured displacement data using multicomponent and real reservoir fluids at no mass transfer conditions. Having identified all the parameters of the slim tube and simulation model, a series of gas-oil displacements were conducted using multicomponent and real reservoir fluids at miscible and immiscible conditions. The fluids were initially tested at static conditions and the generated experimental data were used to tune the phase behaviour model prior to simulation of the dynamic gas injection tests. The simulated displacement results, for miscible and immiscible conditions, matched the experimental data favourably where the tuned model was capable of adequately predicting the static data covering the whole range of compositional variations. The study highlighted the value of displacement data for evaluating phase behaviour models particularly at conditions where significant mass exchange occurs between the phases. Introduction An essential tool for predicting the performance of gas injection processes is an equation of state (EOS) compositional simulator. The volumetric behaviour calculation algorithm is the principle part of such a simulator in which the phase behaviour changes are modelled by an EOS. Tuning of EOS is necessary for characterising the reservoir fluids and evaluating their volumetric performance at various pressure levels. Such a tuning exercise is performed against static measured data by adjusting the EOS parameters systematically. Typical laboratory data used in the tuning process include conventional PVT data such as flash and differential vaporisation, single contact, and multiple contact vapour- liquid phase equilibria measurements. P. 201^

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PVT properties are very important in reservoir and production engineering analyses such as material balance calculations, well testing, reserve estimation, inflow performance, production operations and design of surface facilities. New empirical PVT correlations have been developed for Libyan crudes with reliable degree of accuracy. These include; bubble point pressure (P b ), oil formation volume factor (Bo), gas solubility (R s ), stock tank oil molecular weight (M wt ), dead oil viscosity (µ od ), saturated oil viscosity (µ ob ), under-saturated oil viscosity (µ o ), and oil compressibility (C o ). Around 300 PVT samples collected exclusively from Libya, mainly Sirte, Ghadames and Murzuq basins, were used in our study to develop the above PVT correlations and covered wide range of API gravity (26 to 51°API) and reservoir temperature (100 to 313°F) normally found in Libyan reservoirs. Minitab regression tool was extensively used in our study to develop the PVT correlations and to statistically appraise them against the industry published correlations. The new proposed PVT correlations have demonstrated much better performance compared to the industry published correlations when tested for Libyan crudes. Also, Artificial Neural Network (ANN) models have been developed for Libyan PVT properties predictions. The models show acceptable accuracy and generally are more accurate than the empirical correlations.