HPHT viscosities measurements of mixtures of methane/nitrogen and methane/carbon dioxide

Davani, Ehsan; Falcone, Gioia; Teodoriu, Cătălin; McCain, William D.

doi:10.1016/j.jngse.2013.01.005

Cited by 22 publications

(16 citation statements)

References 20 publications

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“…viscosity is in agreement with the study of gas viscosity in high temperature and high pressure reservoirs by Davani et al, (2013) and Ling et al, (2009). They show that in the pressure range of < ܲ < ‫ܽ݅ݏ0007‬ and temperature range of < ܶ < 212℃ variation in gas viscosity is very low.…”

Section: Resultssupporting

confidence: 90%

Development of inflow performance model in high temperature gas-condensate reservoirs

Faraji¹,

Ugwu²,

Nabhani³

et al. 2019

Journal of Petroleum Science and Engineering

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Inflow Performance Relationships (IPRs) are important element for reservoir engineers in the design of new wells and also for monitoring and optimizing existing wells. IPRs are used to determine optimum production of gas rate and condensate rate in a well for any specified value of average reservoir pressure and predict the performance. Jokhio and Tiab proposed a simple method of establishing IPR for gas condensate wells. The method uses transient pressure test data to estimate effective permeability as a function of pressure. Effective permeability data used to convert production bottomhole flow pressure into pseudopressure to establish well performance. Despite the effectiveness of the method, single phase correlations were used in PVT calculations of each phase, which over simplified the fluid flow in gas condensate wells. Single phase dry gas equations do not reflect the multiphase flow behaviour of gas condensate wells below the dew point. Due to this limitation Jokhio and Tiab method modified by this study and new analytical IPRs for gas condensate well proposed. The major improvement of the above method is incorporating new viscosity correlation developed by this study and using two-phase compressibility factor as key parameters for predicting gas condensate inflow performance. Therefore, the main contribution of this study is development of viscosity correlation which is a critical issue in predicting gas condensate inflow performance both above and below the dew point. Optimization techniques and nonlinear regression used to develop a new viscosity correlation for high temperature heavy gas condensate reservoirs under depletion. The application of the new model is illustrated with field example for current IPR curves. Compositional simulation study of the well performed in PIPSIM simulator. The proposal approach provides reasonable estimates of simulator input reservoir properties (e.g. IPRs). Accuracy of the new method compared with compositional simulation study. The proposed method presents average absolute relative deviation (AARD) of 5.8% for gas IPR and 7.5% for condensate IPR compare to compositional simulation results. New method provides a tool for quick estimation of gas condensate wells without need of relative permeability curves and expensive and time consuming compositional simulation.

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Section: Resultssupporting

confidence: 90%

Development of inflow performance model in high temperature gas-condensate reservoirs

Faraji¹,

Ugwu²,

Nabhani³

et al. 2019

Journal of Petroleum Science and Engineering

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“…Each sweep direction required t  40 min, for a maximum measurement time per reported point of 4.7 h. Table 3 also lists the Type A uncertainties [25] of the measured viscosity that were determined from the standard deviation of up to 7 measurements, and the combined standard uncertainty at a coverage factor of k = 1 [25] obtained by combining in quadrature the Type A of Table 3 with the Type B uncertainties of Table 1. The viscosities listed in Table 3 along five isotherms are shown in Figure 1 along with the viscosities predicted from both the ECS model in REFPROP [13,14] and the SUPERTRAPP based model within MultiFlash. [17] The results deviate by a statistically significant margin of between -2 % at ( < 20 kgm -3 ), increasing to +11 % at  > 600 kgm -3 .…”

Section: Resultsmentioning

confidence: 99%

“…(We note the existence of literature data from 1956 of Jackson [12], but have not included this data in our comparisons as they are limited to viscosities of {xCO2 + (1-x)CH4} measured at room temperature and pressure, and are not particularly relevant to the range of pressures and temperatures of this work.) Recently Davani et al [13], using an oscillating piston viscometer, determined the viscosity of {xCO2 + (1-x)CH4} with x = 0.1 at pressures from (35 to 170) MPa.…”

Section: Introductionmentioning

confidence: 99%

“…Measured viscosity, for {xCO 2 + (1+x)CH 4 } with x = 0.5174 as a function of (a) mass density,  EOS , and, (b) pressure, p. , T = 229 K; , T = 258 K; , T = 288 K; , T = 318 K; , T = 348 K. Viscosity estimated from the ECS model within REFPROP[13,14] are shown as solid lines, _____ ; predictions obtained from SUPERTRAPP within MultiFlash[17] are shown as dash-dotted lines, __ _ .…”

mentioning

confidence: 99%

“…Fractional differences between the measured viscosity, and viscosity calculated,  calc using the REFPROP ECS model[13,14] for {xCO 2 + (1+x)CH 4 } with x = 0.5174 as a function of density,  EOS . , T = 229 K; , T = 258 K; , T = 288 K; , T = 318 K; , T = 348 K. Vertical lines are Type A uncertainties.The viscosities of {xCO2 + (1-x)CH4} reported by De Witt and Thodos[9] (x = 0.536) and…”

mentioning

confidence: 99%

See 2 more Smart Citations

Viscosity of {xCO2+(1−x)CH4} with x=0.5174 for temperatures between (229 and 348)K and pressures between (1 and 32)MPa

Locke

Stanwix

Hughes

et al. 2015

The Journal of Chemical Thermodynamics

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Dynamic Viscosity of Binary Fluid Mixtures: A Review Focusing on Asymmetric Mixtures

Thol

Richter

2021

Int J Thermophys

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A literature review on experimental data for binary mixtures of methane and carbon dioxide with hydrocarbons up to n-hexadecane is presented. Based on these data, the extended corresponding states method, two entropy scaling approaches, and the friction theory are analyzed with respect to their capability of calculating viscosity values with increasing asymmetry of the binary mixture. It is shown that not only the viscosity model but also the underlying thermodynamic equation of state has a significant influence on the result of such calculations. Shortcomings are identified both in the experimental data and in the modeling approaches.

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HPHT viscosities measurements of mixtures of methane/nitrogen and methane/carbon dioxide

Cited by 22 publications

References 20 publications

Development of inflow performance model in high temperature gas-condensate reservoirs

Development of inflow performance model in high temperature gas-condensate reservoirs

Viscosity of {xCO2+(1−x)CH4} with x=0.5174 for temperatures between (229 and 348)K and pressures between (1 and 32)MPa

Dynamic Viscosity of Binary Fluid Mixtures: A Review Focusing on Asymmetric Mixtures

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