TY - GEN
T1 - A practical method for minimum miscibility pressure estimation of contaminated gas mixtures
AU - Johns, R. T.
AU - Ahmadi, Kaveh
AU - Dengen, Z.
AU - Meisong, Y.
PY - 2009
Y1 - 2009
N2 - Minimum miscibility pressure (MMP) is a key parameter in the design of gas floods. Injection gas compositions often vary during the life of a gas flood owing to reinjection and mixing of fluids in situ. Understanding the impact of the gas compositional changes on the MMP is essential to optimal design of field-wide pressure management and CO2 utilization. Determining the MMP by slim tube or other methods for each possible gas mixture is impractical. This paper gives an easy and accurate way to determine MMPs for any multicomponent gas based solely on a few estimates of MMPs from binary gas mixtures. We use the method of characteristics (MOC) and our newly developed mixing-cell method to estimate MMPs for binary gases, where the primary component is contaminated by another component. We demonstrate how to calculate MMPs for multicomponent solvents using two example reservoir oils displaced by CO2 contaminated by various mixtures of N2, CH 4, C2, C3, and H2S. We also examine the sensitivity of local displacement efficiency to dispersion for binary gas mixtures using one-dimensional simulation. The results show that the MMP for gases composed of two or more components can be very accurately estimated from a linear mole-fraction weighted function of the MMPs determined from each binary gas mixture, such as CO2-CH4 and CO2-C 2. For a West Texas crude, the MMPs for contaminated CO2 injection streams are determined accurately over a wide range using only the pure-component MMPs. The accuracy of the MMPs are within +/- 15 psia of those calculated using mixing cell and slim-tube simulations. That is, the MMP for all possible gas compositions is nearly a linear combination of the pure-component MMPs. For the second oil displacement by impure CO2, however, the linear interpolation is accurate as long as the contaminant levels are less than about 20% by mole fraction. For this volatile oil we use an extrapolation of the MMPs for small contaminant concentrations in our linear MMP estimation function.
AB - Minimum miscibility pressure (MMP) is a key parameter in the design of gas floods. Injection gas compositions often vary during the life of a gas flood owing to reinjection and mixing of fluids in situ. Understanding the impact of the gas compositional changes on the MMP is essential to optimal design of field-wide pressure management and CO2 utilization. Determining the MMP by slim tube or other methods for each possible gas mixture is impractical. This paper gives an easy and accurate way to determine MMPs for any multicomponent gas based solely on a few estimates of MMPs from binary gas mixtures. We use the method of characteristics (MOC) and our newly developed mixing-cell method to estimate MMPs for binary gases, where the primary component is contaminated by another component. We demonstrate how to calculate MMPs for multicomponent solvents using two example reservoir oils displaced by CO2 contaminated by various mixtures of N2, CH 4, C2, C3, and H2S. We also examine the sensitivity of local displacement efficiency to dispersion for binary gas mixtures using one-dimensional simulation. The results show that the MMP for gases composed of two or more components can be very accurately estimated from a linear mole-fraction weighted function of the MMPs determined from each binary gas mixture, such as CO2-CH4 and CO2-C 2. For a West Texas crude, the MMPs for contaminated CO2 injection streams are determined accurately over a wide range using only the pure-component MMPs. The accuracy of the MMPs are within +/- 15 psia of those calculated using mixing cell and slim-tube simulations. That is, the MMP for all possible gas compositions is nearly a linear combination of the pure-component MMPs. For the second oil displacement by impure CO2, however, the linear interpolation is accurate as long as the contaminant levels are less than about 20% by mole fraction. For this volatile oil we use an extrapolation of the MMPs for small contaminant concentrations in our linear MMP estimation function.
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M3 - Conference contribution
AN - SCOPUS:78349274010
SN - 9781615675753
T3 - Proceedings - SPE Annual Technical Conference and Exhibition
SP - 3638
EP - 3648
BT - Society of Petroleum Engineers - SPE Annual Technical Conference and Exhibition 2009, ATCE 2009
T2 - SPE Annual Technical Conference and Exhibition 2009, ATCE 2009
Y2 - 4 October 2009 through 7 October 2009
ER -