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Smart Wells and Techniques for Reservoir Monitoring 287

• Chlorides of 10,000ppm, the required water salinity to generate an opti-
mum balance for the surfactant injection and reduce its absorption level
to the rock.
• Water viscosity of 3.5cP, the required viscosity for the polymer cocktail
to displace the oil with an appropriate mobility ratio less than 10.0
(k ro /μ o k rw /μ w ).
• Surface temperature of around 90°F, the maximum temperature to
reduce the polymer degradation.
Fig. 7.23 also shows chemical sensors setup at the oil and water treatment in
the separation system. Before the water breakthrough, it is expected
that produced water from the well formation has original chemical
levels such as pH of approximately 6.0, chlorides of approximately
25,000–35,000ppm, viscosity of around 1.0cP, and no emulsions or
micro-emulsion formed in oils. After breakthrough, it is essential to monitor
and survey the trend and tendency of pH, ions, chlorides, emulsions, and
water/oil viscosity through time in producer wells.
Chemical sensors and a 3D numerical model coupled with an optimizer
should be integrated to improve the injection and maximize the oil-
recovery factor, while reducing ASP costs. A numerical model performs
calculations on gravity, viscosity, and capillary forces. The injection can
be adapted and controlled by
• Changing the ICV choke size.
• Monitoring the chemical propagation into the reservoir using
preexisting or observed wells.
• Using traditional production behavior, that is, water cut%, GOR, and
chemical tracers for ASP and by comparing with chemical sensors shown
in Fig. 7.23.
The optimization process should aim to optimize the required injected pore
volume (PV) of ASP agents (generally PV can reach a value of 1–2at
reservoir condition) to maximize the oil production (the barrels of oil per
$/pound of ASP are incremental) by changing
• Optimum size of the chemical slug.
• Rate of injection.
• Mixed, sequential, or alternated alkaline, surfactant, polymers, or all.

REFERENCES
Ajayi, A., Konopczynski, M., 2003. A Dynamic Optimization Technique for Simulation of
Multiple-Zone Intelligent Well Systems in a Reservoir Development. SPE-83963-MS.
https://doi.org/10.2118/83963-MS.