An Updated Fractional Flow Model of Low Salinity Water Flooding with Respect to the Impact of Salt Diffusion

2018 ◽  
Author(s):  
Hasan Al-Ibadi ◽  
Karl Stephen ◽  
Eric Mackay
Keyword(s):  
Flow Model ◽  
Water Flooding ◽  
Fractional Flow ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Salinity Water ◽  
Salt Diffusion ◽  
The Impact

Extended Fractional-Flow Model of Low-Salinity Waterflooding Accounting for Dispersion and Effective Salinity Range

SPE Journal ◽  
2019 ◽  
Vol 24 (06) ◽  
pp. 2874-2888 ◽  
Author(s):  
Hasan Al–Ibadi ◽  
Karl D. Stephen ◽  
Eric J. Mackay
Keyword(s):  
Relative Permeability ◽  
Flow Behavior ◽  
Flow Analysis ◽  
Salinity Range ◽  
Fractional Flow ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Low Salinity Waterflooding ◽  
Salinity Water ◽  
The Impact

Summary Low–salinity waterflooding (LSWF) is an emergent technology developed to increase oil recovery. Laboratory–scale testing of this process is common, but modeling at the production scale is less well–reported. Various descriptions of the functional relationship between salinity and relative permeability have been presented in the literature, with respect to the differences in the effective salinity range over which the mechanisms occur. In this paper, we focus on these properties and their impact on fractional flow of LSWF at the reservoir scale. We present numerical observations that characterize flow behavior accounting for dispersion. We analyzed linear and nonlinear functions relating salinity to relative permeability and various effective salinity ranges using a numerical simulator. We analyzed the effect of numerical and physical dispersion of salinity on the velocity of the waterflood fronts as an expansion of fractional–flow theory, which normally assumes shock–like behavior of water and concentration fronts. We observed that dispersion of the salinity profile affects the fractional–flow behavior depending on the effective salinity range. The simulator solution is equal to analytical predictions from fractional–flow analysis when the midpoint of the effective salinity range lies between the formation and injected salinities. However, retardation behavior similar to the effect of adsorption occurs when these midpoint concentrations are not coincidental. This alters the velocities of high– and low–salinity water fronts. We derived an extended form of the fractional–flow analysis to include the impact of salinity dispersion. A new factor quantifies a physical or numerical retardation that occurs. We can now modify the effects that dispersion has on the breakthrough times of high– and low–salinity water fronts during LSWF. This improves predictive ability and also reduces the requirement for full simulation.

scholarly journals Mechanisms of Microscopic Displacement During Enhanced Oil Recovery in Mixed-Wet Rocks Revealed Using Direct Numerical Simulation

2019 ◽  
Vol 130 (3) ◽  
pp. 731-749 ◽  
Author(s):  
Takashi Akai ◽  
Amer M. Alhammadi ◽  
Martin J. Blunt ◽  
Branko Bijeljic
Keyword(s):  
Numerical Simulation ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Water Flooding ◽  
Surfactant Flooding ◽  
Displacement Efficiency ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Salinity Water ◽  
The Impact

Abstract We demonstrate how to use numerical simulation models directly on micro-CT images to understand the impact of several enhanced oil recovery (EOR) methods on microscopic displacement efficiency. To describe the physics with high-fidelity, we calibrate the model to match a water-flooding experiment conducted on the same rock sample (Akai et al. in Transp Porous Media 127(2):393–414, 2019. 10.1007/s11242-018-1198-8). First we show comparisons of water-flooding processes between the experiment and simulation, focusing on the characteristics of remaining oil after water-flooding in a mixed-wet state. In both the experiment and simulation, oil is mainly present as thin oil layers confined to pore walls. Then, taking this calibrated simulation model as a base case, we examine the application of three EOR processes: low salinity water-flooding, surfactant flooding and polymer flooding. In low salinity water-flooding, the increase in oil recovery was caused by displacement of oil from the centers of pores without leaving oil layers behind. Surfactant flooding gave the best improvement in the recovery factor of 16% by reducing the amount of oil trapped by capillary forces. Polymer flooding indicated improvement in microscopic sweep efficiency at a higher capillary number, while it did not show an improvement at a low capillary number. Overall, this work quantifies the impact of different EOR processes on local displacement efficiency and establishes a workflow based on combining experiment and modeling to design optimal recovery processes.

scholarly journals Semi-Analytical Solution of Chemical Flooding in Heterogeneous Non-Communicating Layers with a Focus on Low Salinity Water Flooding

2020 ◽  
Vol 135 (1) ◽  
pp. 101-135
Author(s):  
Hasan Al-Ibadi ◽  
Karl D. Stephen ◽  
Eric J. Mackay
Keyword(s):  
Analytical Solutions ◽  
Water Flooding ◽  
Salinity Range ◽  
Chemical Flooding ◽  
Fractional Flow ◽  
Sweep Efficiency ◽  
Flow Equations ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Salinity Water

Abstract Chemical flooding has been implemented intensively for some years to enhance sweep efficiency in porous media. Low salinity water flooding (LSWF) is one such method that has become increasingly attractive. Historically, analytical solutions were developed for the flow equations for water flooding conditions, particularly for non-communicating strata. We extend these to chemical flooding, more generally, and in particular for LSWF where salinity is modeled as an active tracer and changes relative permeability. Dispersion affects the solutions, and we include this also. Using fractional flow theory, we derive a mathematical solution to the flow equations for a set of layers to predict fluid flow and solute transport. Analytical solutions tell us the location of the lead (formation) waterfront in each layer. We extend a correlation that we previously developed to predict the effects of numerical and physical dispersion. We used this correction to predict the location of the second waterfront in each layer which is induced by the chemical’s effect on mobility. We show that in multiple non-communicating layers, mass conservation can be used to deduce the interlayer relationships of the various fronts that form. This is based on similar analysis developed for water flooding although the calculations are more complex because of the development of multiple fronts. The result is a predictive tool that we compare to numerical simulations and the precision is very good. Layers with contrasting petrophysical properties and wettability are considered. We also investigate the relationship between the fractional flow, effective salinity range, salinity dispersion and salinity retardation. The recovery factor and vertical sweep efficiency are also very predictable. The work can also be applicable to other chemical EOR processes if they alter the fluid mobility. This includes polymer and surfactant flooding.

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