  We present a multi-level delumping method suitable for thermal enhanced oil
recovery processes, for which hydrocarbon components are vaporized under high
temperatures, move downstream in the gas phase and condense back to the liquid
phase. To reduce the computational cost, it is standard practice to reduce the
number of (pseudo-)components used in thermal reservoir simulation. Depending
on the number and type of hydrocarbon pseudo-components retained in the
simulations, we may not be able to capture the correct displacement due to
large errors in the lumped phase behavior (flash) computations. We address that
problem through a multi-level method: we use data obtained from a short
simulation using the most detailed fluid description available, and leverage
that information to guide a delumping process. We use temperature as a proxy
variable for composition, and select reference temperatures. We extract the
corresponding reference compositions from the detailed run and use them to
extend the lumped pseudo-components to an approximate detailed composition. We
test our method using six heavy oil samples, and under two different recovery
processes: hot nitrogen injection and in-situ combustion (air injection and
exothermic oxidation reactions). The average error on the liquid mole fraction
is reduced by 4-12 times (depending on the oil samples) compared to the flash
using pseudo-components, and the maximum error by 6-48 times. We illustrate
that the method is amenable to manually adding more information about the
physics of some oil samples. We also discuss how to efficiently pick the
reference temperatures. For uniformly sampled temperatures (between a minimum
and maximum temperature), we conduct a sensitivity study which led us to use
six temperatures. We ran both local (Pattern Search, PS) and global (Particle
Swarm Optimization, PSO) gradient-free optimization methods.
