Solvent-additive processes (SAP) are a promising, but challenging technology. Perhaps the biggest challenge from an engineering point of view, is that simulators probably work some of the time, but not all of the time; and there is no information about where the line between occurs, or what the correct answer should be, after the line is crossed. Other serious problems are the many degrees of freedom in SAP process design, and the non-linear relationships between process inputs and economic results. There are too many possible designs to try randomly for even a single reservoir, and there is limited theory to interpolate or scale available experimental data.

This paper attempts to assemble some known pieces of the puzzle, and to explore how they may fit together to explain and predict SAP performance characteristics

First, some familiar PVT relationships are presented, with examples using temperature as the independent variable. This helps to clarify the choice of solvent, as a function of reservoir pressure, and also to understand the effect of the increasing solvent "dose". It is shown that SAP will create a double front, one where the water is condensed, and a second where the solvent is absorbed by, and drains with, the oil. A vapor blanket separates the two fronts.

Secondly, simple estimates are given for the temperature distribution in the vapor blanket (i.e. solvent-active zone). Together with PVT data for the same pressure, these allow the thickness of a vapor blanket to be estimated.

Finally, SAP mass transport limits are considered, by observing that the second front essentially constitutes VAPEX. The Butler-Mokrys theory is discussed, in view of its failure to predict certain experimental results; it is argued that this results from neglect of capillary pressure effects, which in fact are dominant at the front. A purely empirical correlation by Nenniger is introduced, which can be rearranged to predict the maximum solvent speed, also as a function of temperature.

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