Abstract
Vapex (vapor extraction) is a non-thermal process using vaporized solvents with promising potential to reduce steam consumption in heavy oil recovery. The key recovery mechanism is molecular diffusion enhanced by velocity variations at different scales; i.e., dispersion. The efficiency of diffusion/dispersion depends significantly on reservoir heterogeneities, which exhibit a wide range of length scales. This paper demonstrates a procedure for quantifying the scaling characteristics of effective mass transfer accounting for heterogeneities based on the volume averaging approach.
Volume averaging is a mathematical technique to derive continuum equations at coarse scales given representative transport equations at fine scales. Although treatment of transport problems has been published in the past, application to stochastic geological systems is lacking. In the proposed procedure, results from a fine-scale numerical flow simulation reflecting the full physics of Vapex over a small element of the reservoir is integrated using the volume averaging technique to provide effective description of mass transfer at the coarse scale.
Scaling characteristics of effective mass transfer are systematically investigated for different heterogeneity distributions. Results show 1) spatial variability of effective mass transfer coefficients increases as solvent chamber advances through the reservoir; 2) mean and variance of effective mass transfer vary with length scale in a fashion similar to that of recovery statistics; 3) variability in effective mass transfer is a strong, non-linear function of heterogeneity.
An original contribution is to provide a general framework for developing scaling relationships of effective mass transfer in Vapex accounting for reservoir heterogeneities. It also presents an important potential in modeling of other solvent injection applications. Results demonstrate that effective mass transfer vary with length scale and heterogeneity; hence it should be properly represented for accurate prediction of recovery performance in simulations using scaled-up reservoir models.
