Abstract
To examine the need to incorporate in situ wettability measurements in direct numerical simulations, we compare waterflooding experiments in a mixed-wet carbonate from a producing reservoir and results of direct multiphase numerical simulations using the color-gradient lattice Boltzmann method. We study the experiments of Alhammadi et al. (Sci Rep 7(1):10753, 2017. https://doi.org/10.1038/s41598-017-10992-w) where the pore-scale distribution of remaining oil was imaged using micro-CT scanning. In the experiment, in situ contact angles were measured using an automated algorithm (AlRatrout et al. in Adv Water Resour 109:158–169, 2017. https://doi.org/10.1016/j.advwatres.2017.07.018), which indicated a mixed-wet state with spatially non-uniform angles. In our simulations, the pore structure was obtained from segmented images of the sample used in the experiment. Furthermore, in situ measured angles were also incorporated into our simulations using our previously developed wetting boundary condition (Akai et al. in Adv Water Resour 116(March):56–66, 2018. https://doi.org/10.1016/j.advwatres.2018.03.014). We designed six simulations with different contact angle assignments based on experimentally measured values. Both a constant contact angle based on the average value of the measured values and non-uniform contact angles informed by the measured values gave a good agreement for fluid pore occupancy between the simulation and the experiment. However, the constant contact angle assignment predicted 54% higher water effective permeability after waterflooding than that estimated for the experimental result, whereas the non-uniform contact angle assignment gave less than 1% relative error. This means that to correctly predict fluid conductivity in mixed-wet rocks, a spatially heterogeneous wettability state needs to be taken into account. The novelty of this work is to provide a direct pore-scale comparison between experiments and simulations employing experimentally measured contact angles, and to demonstrate how to use measured contact angle data to improve the predictability of direct numerical simulation, highlighting the difference between the contact angle required for the simulation of dynamic displacement process and the contact angle measured at equilibrium after waterflooding.
Highlights
Multiphase flow in porous media has a wide range of applications including oil recovery, carbon storage and water flow in the unsaturated zone (Blunt 2017; Pruess and García 2002)
Since the measurements of wettability were obtained on a pore-by-pore basis, it is of interest to determine how to incorporate this information in direct numerical simulation of two-phase flow
Several studies investigating a spatially heterogeneous wettability state using pore network modeling can be found in literature (McDougall and Sorbie 1995; Øren et al 1998; Valvatne and Blunt 2004), there are few studies on direct numerical simulation of 3D porous media considering a distribution of contact angles from experimental measurements
Summary
Multiphase flow in porous media has a wide range of applications including oil recovery, carbon storage and water flow in the unsaturated zone (Blunt 2017; Pruess and García 2002). Several studies investigating a spatially heterogeneous wettability state using pore network modeling can be found in literature (McDougall and Sorbie 1995; Øren et al 1998; Valvatne and Blunt 2004), there are few studies on direct numerical simulation of 3D porous media considering a distribution of contact angles from experimental measurements. The experiments were performed at reservoir temperatures and pressures after more than 3 weeks of aging in crude oil They conducted three simulations with different wettability states assuming Gaussian distributions with different mean contact angles: θ = 45◦ ± 15◦, θ = 90◦ ± 15◦ and θ = 135◦ ± 15◦. We show comparisons between waterflooding experiments in a mixed-wet carbonate from a producing reservoir (Alhammadi et al 2017) and the results of direct numerical simulations using the color-gradient lattice Boltzmann method.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
