A new approach to thermal segregation in petroleum reservoirs: Algorithm and case studies

In many petroleum reservoirs, the fluid properties vary through the reservoir thickness. Variation of the composition, i.e. compositional grading, can affect reserve estimation, production and enhanced oil recovery strategies. Apart from gravity, the geothermal gradient may also contribute to the fluid distribution.

Thermodiffusion is the governing phenomenon determining the contribution of the geothermal gradient. The non-equilibrium thermodynamics models are applied for the calculation of the compositional gradients under the varying temperature. In order to determine the variations in pressure and composition with depth and to be able to indicate if/where a gas-oil contact exists, we have developed a model based on the principles of irreversible thermodynamics, within the approach to thermodiffusion in porous media proposed by Montel et al. (2019).

Based on the relationships where pressure, chemical potentials, and thermal gradient are linked, the distribution of hydrocarbons in a petroleum reservoir is described. A computational algorithm accounting for non-ideality of the mixture, characterization, and phase transitions has been developed. The model and the computational procedure have been validated by comparison with the case studies reported in the literature for a North Sea reservoir, and with sample component distributions produced by application of molecular dynamics simulations.

It has been shown that the model is capable of predicting the fluid distributions with depth with no or a minimum of adjustable parameters. The thermal gradient modifies the predicted fluid distributions making them closer to the observed data points. Depending on the mixture composition, the thermal diffusion may either enforce the effect of gravity or counteract it.