The injection of nanoparticles is a promising and novel approach to enhancing oil recovery in depleted fields. Nanoparticles have one dimension that is smaller than 100 nm and have many unique properties that are useful when it comes to oil recovery. Their small size and the ability to manipulate particle properties are a couple of the advantageous properties. The small size of nanoparticle allows them to easily pass through porous media. Manipulating nanoparticle properties allows for wettability modifications or controlled release of chemicals at a precise location in the formation. Injection of nanoparticle dispersions for secondary or tertiary recovery in corefloods has yielded positive results. Field tests using nanoparticles have also yielded positive results with increased oil recovery. While there has been a sizable amount of work related to corefloods, limited investigation has been reported using micromodels. Micromodels are valuable because they allow for pore scale viewing of the oil recovery, which is not possible with corefloods. In this research both polydimethylsiloxane (PDMS) and glass microfluidic devices were fabricated to test the EOR potential of different types of nanoparticles. Much of the work described in this thesis involved the use of a dead-end pore geometry to trap oil. First the pore space was filled with oil and then waterflooded. This left some oil trapped in the dead-end pores. PDMS micromodels proved difficult to trap oil in the dead-end pores; because of this glass micromodels were tested. After trapping oil, a nanoparticle dispersion was injected into the pore space to test the potential of the dispersion to reduce the residual oil saturation in the dead-end pores. The nanoparticle dispersion was injected at different flow rates (1 [mu]l/hr to 50 [mu]l/hr) to test the effect of flow rate on residual oil recovery. / text
Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/26460 |
Date | 10 October 2014 |
Creators | Van Bramer, William Christopher |
Source Sets | University of Texas |
Language | English |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
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