The Simulation and Design of Polymer Flooding
Author(s)
AlSofi, Abdulkareem Mohamad
Type
Thesis
Abstract
Most polymers used in Enhanced Oil Recovery exhibit shear-thinning behaviour.
An in-house streamline simulator was modified and used to study the effects of
both shear-thinning and shear-thickening on oil recovery. First, we describe how
to simulate Newtonian and non-Newtonian polymer flooding. In contrast to
current simulators, our methodology: (1) implements an iterative approach to
solve the pressure field opposed to the common approach where this viscosity-pressure
interdependence is ignored, (2) defines non-Newtonian viscosities to be
cell-centred while current simulators use a face-approach and (3) uses a
physically-based rheological model where non-Newtonian viscosities in two-phase
flow are those exhibited in single-phase flow at the same pressure gradient not
the same flow rate. To validate the simulator, we constructed one-dimensional
analytical solutions for waterflooding with a non-Newtonian fluid. We then
compared our results to those from commercial simulators illustrating the
significance of current assumptions and their effects on the simulation results as
well as the design of polymer flooding. The simulator was also used to investigate
non-Newtonian effects on sweep and recovery. The results of this work prove the
importance of taking polymers’ non-Newtonian behaviour into account for the
successful design and evaluation of polymer flooding projects. Shear-thinning
impairs sweep through exacerbated fingering and channelling. Increased
channelling is due both to an overall reduction in viscosity as well as local
viscosity variations, the latter factor being less significant. In addition, our
results illustrate the potential of using shear-thickening agents for channelling
reduction.
The numerical simulation of such processes is also a challenge as the
solutions should minimise numerical dispersion. Traditional numerical
simulations of polymer flooding give excessive front smearing compared to pure
waterfloods, requiring many thousands of gridblocks in one dimension to resolve
the fronts adequately and rendering the predictions from three-dimensional
simulations dubious at best. Investigating numerical dispersion in simulations of
polymer flooding, we showed that these erroneous predictions occur because of
the coupling of compositional dispersion with fractional flow. Small errors in
composition alter the fractional flow, causing the development of incorrect
wavespeeds. Rather than implementing a higher-order discretisation method, we
propose a simple scheme based on segregated-flow within a gridblock. Compared
to current mixing schemes, it differs in that segregation not only affects fluid
properties but the transport, too. The scheme was shown to reestablish self-sharpness
across the trailing shock. After validating the approach in one
dimension, we performed multi-dimensional simulations demonstrating that
traditional simulation methods can vastly overestimate recovery, potentially
leading to poor injection design and management decisions. Finally, we
illustrated the extendibility of this technique to low-salinity flooding as well as
compositional simulations of miscible and near-miscible gas injection processes.
At the end, since one of the main purposes of reservoir simulation is to
optimally design the exploitation and production of petroleum resources, we
investigated various aspects of the design of polymer flooding processes. First, we
investigated the design of such processes in terms of finding the optimal solution
and the characteristics of optimal strategies. The results suggest that polymer-flooding
design – in terms of concentration, slug size and initiation – is more
intuitive than expected previously. In terms of optimisation, polymer flooding is
unimodal. In terms of optimal design, we found that: (1) it is always beneficial to
start polymer flooding as soon as possible preferably before any waterflooding; (2)
optimal slugs are very close to being continuous and (3) shear-thinning floods
require higher polymer concentrations to compensate for losses in mobility
control. Second, we quantified the impact of uncertainty on both the optimal
design and profitability. The uncertainty results provide a quantitative ranking
of the various factors affecting polymer flooding. This serves as a guide to
associated data-acquisition efforts. Pre-polymer flooding initiation efforts can be
focused on reducing uncertainties of high impact factors, thereby increasing the
probability of success. Finally, we investigated upscaling effects. The main
limitation to the use of upscaled models was found to be injectivity-related. For
cases where polymer-flooding injectivity was not a factor, the results illustrate
the potential utility of upscaled models for the preliminary design of polymer
floods in terms of optimal polymer concentrations. This is despite the significant
mismatch in polymer flooding predictions obtained with the different upscaled
models.
An in-house streamline simulator was modified and used to study the effects of
both shear-thinning and shear-thickening on oil recovery. First, we describe how
to simulate Newtonian and non-Newtonian polymer flooding. In contrast to
current simulators, our methodology: (1) implements an iterative approach to
solve the pressure field opposed to the common approach where this viscosity-pressure
interdependence is ignored, (2) defines non-Newtonian viscosities to be
cell-centred while current simulators use a face-approach and (3) uses a
physically-based rheological model where non-Newtonian viscosities in two-phase
flow are those exhibited in single-phase flow at the same pressure gradient not
the same flow rate. To validate the simulator, we constructed one-dimensional
analytical solutions for waterflooding with a non-Newtonian fluid. We then
compared our results to those from commercial simulators illustrating the
significance of current assumptions and their effects on the simulation results as
well as the design of polymer flooding. The simulator was also used to investigate
non-Newtonian effects on sweep and recovery. The results of this work prove the
importance of taking polymers’ non-Newtonian behaviour into account for the
successful design and evaluation of polymer flooding projects. Shear-thinning
impairs sweep through exacerbated fingering and channelling. Increased
channelling is due both to an overall reduction in viscosity as well as local
viscosity variations, the latter factor being less significant. In addition, our
results illustrate the potential of using shear-thickening agents for channelling
reduction.
The numerical simulation of such processes is also a challenge as the
solutions should minimise numerical dispersion. Traditional numerical
simulations of polymer flooding give excessive front smearing compared to pure
waterfloods, requiring many thousands of gridblocks in one dimension to resolve
the fronts adequately and rendering the predictions from three-dimensional
simulations dubious at best. Investigating numerical dispersion in simulations of
polymer flooding, we showed that these erroneous predictions occur because of
the coupling of compositional dispersion with fractional flow. Small errors in
composition alter the fractional flow, causing the development of incorrect
wavespeeds. Rather than implementing a higher-order discretisation method, we
propose a simple scheme based on segregated-flow within a gridblock. Compared
to current mixing schemes, it differs in that segregation not only affects fluid
properties but the transport, too. The scheme was shown to reestablish self-sharpness
across the trailing shock. After validating the approach in one
dimension, we performed multi-dimensional simulations demonstrating that
traditional simulation methods can vastly overestimate recovery, potentially
leading to poor injection design and management decisions. Finally, we
illustrated the extendibility of this technique to low-salinity flooding as well as
compositional simulations of miscible and near-miscible gas injection processes.
At the end, since one of the main purposes of reservoir simulation is to
optimally design the exploitation and production of petroleum resources, we
investigated various aspects of the design of polymer flooding processes. First, we
investigated the design of such processes in terms of finding the optimal solution
and the characteristics of optimal strategies. The results suggest that polymer-flooding
design – in terms of concentration, slug size and initiation – is more
intuitive than expected previously. In terms of optimisation, polymer flooding is
unimodal. In terms of optimal design, we found that: (1) it is always beneficial to
start polymer flooding as soon as possible preferably before any waterflooding; (2)
optimal slugs are very close to being continuous and (3) shear-thinning floods
require higher polymer concentrations to compensate for losses in mobility
control. Second, we quantified the impact of uncertainty on both the optimal
design and profitability. The uncertainty results provide a quantitative ranking
of the various factors affecting polymer flooding. This serves as a guide to
associated data-acquisition efforts. Pre-polymer flooding initiation efforts can be
focused on reducing uncertainties of high impact factors, thereby increasing the
probability of success. Finally, we investigated upscaling effects. The main
limitation to the use of upscaled models was found to be injectivity-related. For
cases where polymer-flooding injectivity was not a factor, the results illustrate
the potential utility of upscaled models for the preliminary design of polymer
floods in terms of optimal polymer concentrations. This is despite the significant
mismatch in polymer flooding predictions obtained with the different upscaled
models.
Date Issued
2011-07
Date Awarded
2011-08
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Blunt, Martin
LaForce, Tara
Sponsor
Saudi Aramco and EXPEC Advanced Research Center
Creator
AlSofi, Abdulkareem Mohamad
Publisher Department
Earth Science and Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)