Thermodiffusion in multicomponent n-alkane mixtures

Abstract

Compositional grading within a mixture has a strong impact on the evaluation of the pre-exploitation distribution of hydrocarbons in underground layers and sediments. Thermodiffusion, which leads to a partial diffusive separation of species in a mixture due to the geothermal gradient, is thought to play an important role in determining the distribution of species in a reservoir. However, despite recent progress, thermodiffusion is still difficult to measure and model in multicomponent mixtures. In this work, we report on experimental investigations of the thermodiffusion of multicomponent n-alkane mixtures at pressure above 30 MPa. The experiments have been conducted in space onboard the Shi Jian 10 spacecraft so as to isolate the studied phenomena from convection. For the two exploitable cells, containing a ternary liquid mixture and a condensate gas, measurements have shown that the lightest and heaviest species had a tendency to migrate, relatively to the rest of the species, to the hot and cold region, respectively. These trends have been confirmed by molecular dynamics simulations. The measured condensate gas data have been used to quantify the influence of thermodiffusion on the initial fluid distribution of an idealised one dimension reservoir. The results obtained indicate that thermodiffusion tends to noticeably counteract the influence of gravitational segregation on the vertical distribution of species, which could result in an unstable fluid column. This confirms that, in oil and gas reservoirs, the availability of thermodiffusion data for multicomponent mixtures is crucial for a correct evaluation of the initial state fluid distribution.

Results of the DCMIX1 experiment on measurement of Soret coefficients in ternary mixtures of hydrocarbons under microgravity conditions on the ISS

“…The project originated from the collaboration between several academic research centers with partners from the oil industry during which binary, ternary, and quaternary Soret coefficients were obtained in microgravity conditions in the SCCO experiment. [17][18][19] Three chemical species were selected to represent three major families of compounds found in crude oils: THN, IBB, and nC 12 , respectively, for the families of naphthenic, aromatic, and aliphatic compounds. The selected systems involve three components and are away from the dilution limits.…”

Analytical solution for compositional profile driven by gravitational segregation and diffusion

“…The general aim is to predict how compositional profiles change over geological time--2 -scales, the steady-state profile and to estimate time scales to reach steady-state. Although large advances have been made [17][18][19][20][21][22][23][24][25][26][27][28][29][30], the lack of experimental thermophysical data, the incomplete characterization of geological heterogeneities, unknown boundary and initial conditions and incomplete understanding of some of the processes have led to only moderate success in predicting the observed distributions in composition, even when fully general numerical simulators are used. It is therefore useful to have range of simple analytical solutions that can be used to predict end member cases and thus bound the compositional profiles that may be expected in different circumstances, as well as to validate numerical simulations.…”

“…As the injected fluid changes the pressure distribution in the reservoir a careful consideration of the vertical compositional gradient has to be carried out [14,16] to ensure that the requirement for miscibility is achieved at all depths. Temperature, which also increases with depth in most reservoirs, can also drive segregation of components through temperature diffusion (the Soret effect), [17][18][19][20] sometimes counteracting the gravity driven segregation. Typically, temperature has the greatest effect when there is also a horizontal temperature gradient which may alter the compositional distribution via natural convection or when the system is near its critical point [5,17,[20][21].…”

“…Most models have focussed on predicting the vertical distribution of components, although some have also examined the 3D distribution [17,18,27]. The level of sophistication varies from models assuming an isothermal reservoir to those considering thermal diffusion, convection, external fluxes and biochemical degradation [5,16,[19][20][21][22][23][24][25][26][27]. The general aim is to predict how compositional profiles change over geological time--2 -scales, the steady-state profile and to estimate time scales to reach steady-state.…”

“…Over the years a number of models [5,16,[19][20][21][22][23][24][25][26][27] and references therein] have been developed to predict the distribution of components within the oil reservoirs. Most models have focussed on predicting the vertical distribution of components, although some have also examined the 3D distribution [17,18,27].…”