Investigating the effect of transient flow behavior from HSW to LSW on oil recovery in low-salinity water flooding simulation

Abstract

Low-salinity water (LSW) flooding is one of the newest EOR techniques which has more advantageous over other EOR techniques. This research employed a heterogeneous synthetic three-dimensional reservoir to model LSW flooding for a two-phase system including brine (high salinity to low salinity) and oil. The obtained results show that exact determination of salinity threshold and its wettability alteration coefficients are very important since they affect the maximum value of oil recovery. The oil recovery has been varied between 55.79 and 60.34% for a given injection brine salinity (500 ppm) at different salinity threshold values. Furthermore, the result reveals that aging time has a low effect on oil recovery which is around 0.066% after more than 12 years of injection. However, the fine-grid 1D simulation of a small sample demonstrates that the aging time effect should be considered in small-scale models. Furthermore, we prove that there is an optimum value of injection brine salinity for each reservoir according to its salinity threshold. Highest recovery changes occur at the salinity of 5000, 3400 and 1200 ppm for three different salinity thresholds approximately. This paper demonstrates that before any implementation of LSW flooding, many laboratory tests must be done at reservoir condition to precisely detect wettability alteration coefficient, the best injection brine salinity and flow behavior from high-salinity water to LSW. Keywords Enhanced oil recovery • Wettability alteration • Low-salinity water flooding • Salinity threshold • Aging time List of symbols k rw Relative permeability to water k ro Relative permeability to oil S o Oil saturation S w Water saturation S orw Residual oil saturation S wr Residual water saturation k z Permeability of grid block in vertical direction C m Salt concentration of each block c b Brine compressibility k LSW rw Low-salinity water relative permeability k HSW ro High-salinity oil relative permeability P LSW c Low-salinity capillary pressure F 1 Weighting coefficient k x , k y Permeability of grid block in horizontal direction T Reservoir temperature p 0 Reference pressure (70 MPa) P c Capillary pressure k HSW rw High-salinity water relative permeability k LSW ro Low-salinity oil relative permeability P HSW c High-salinity capillary pressure Greek symbols Porosity of each block w Water viscosity st b Brine density at standard condition 0 w (20 o C) Water viscosity at temperature of 20 °C and zero pressure w0 Pure water density at reference pressure b0 Brine density at reference pressure b Brine density Abbreviations EOR Enhanced oil recovery HSW High-salinity water MIE Multiple ion exchange 1D One dimensional EDL Electrical double layer

Modeling Wettability Alteration During Low Salinity Waterflooding in Sandstone Reservoirs: A Brief Review

“…Different physicochemical mechanisms have been proposed to explain wettability alteration as one of the primary causes of oil recovery enhancement by LSW flooding in sandstone rocks. These mechanisms are classified as salting-in, multiple ion exchange (MIE) and double layer expansion (DLE) [14].…”

“…Wettability alteration mechanism describes that LSW would change the wettability toward less oil-wet or more water-wet states contributing to a more favorable condition which results in additional oil recovery [13]. Multiple mechanism can contribute to wettability alteration during LSW, for instance salting-in mechanism, multiple ion exchange (MIE) mechanism and double layer expansion (DLE) [14].…”

Effect of Temperature on Bitumen/Water Relative Permeability in Oil Sands

“…Essentially, the history-matching process is an optimization exercise in which the relative permeability curves are tuned until the best match between the estimated pressure drop and oil or water production data from reservoir simulation and the experimental data points is obtained. In the present study, our inhouse reservoir simulator 41 was employed, and the generalized Corey 31 relative permeability model was assumed to apply to the oil and water relative permeability curves. The Corey exponent form is convenient for history matching because it possesses only one degree of freedom for the shape of each relative permeability curve, that is, the oil exponent or water exponent, while other complex relative permeability models, such as LET correlation, add more degrees of freedom in order to accommodate the shape of measured relative permeability curves.…”

Optical measurements of oil release from calcite packed beds in microfluidic channels

“…Different IOR strategies are being explored to retrieve more oil (while also minimizing the ecological footprint of the recovery process itself). Most common are methods based on water injection (Goolsby and Anderson 1964;Rausch and Beaver 1964;Hussain et al 2013;Esmaeili and Maaref 2019), for which different strategies are followed: adding alkali, polymers, surfactants or nanoparticles, or adjusting the ion composition. The latter, also known as Smart Water Flooding (SWF) is a relatively recent technique which has been reported to give higher yields than conventional (sea) water injection, (Bernard 1967) in both sandstone (Tang and Morrow 1999;Morrow and Buckley 2011) and carbonate (Gupta et al 2011;Yousef et al 2011;Shehata et al 2014;Nasralla et al 2016Nasralla et al , 2018 reservoirs.…”