An experimental study of the influence of the preflush salinity on enhanced oil recovery using silica-based nanofluids

Tola Sreu, Kyuro Sasaki, Yuichi Sugai, Ronald Nguele

Research output: Contribution to journalArticlepeer-review

Abstract

The underlying effect of preflush salinity and silica nanofluid (Si-NF) on oil production is examined. The influence of salinity on the stability of Si-NFs is studied. A series of sand-pack floodings evaluating oil production was conducted at different concentrations of preflush salinity (0 to 4 wt.%), followed by the injection of a Si-NF (0.5 wt.%) at the trail of which postflush water was injected. The effluent water and solids were collected and analyzed using X-ray fluorescence (XRF). Interfacial tension (IFT) and contact angle measurements were conducted on the Si-NF in the presence of salinity to confirm the effect. The Si-NF became unstable and formed precipitate in the presence of salinity. The sand-pack flooding showed that when the preflush salinity was increased, the displacement efficiency (ED) using the Si-NF and postflush injection was increased (ED = 44%). The XRF of the precipitated effluent revealed that the preflush salinity and Si-NF caused mineral leaching, which triggered pore clogging. The IFT value reduced from 13.3 to 8.2 mN/m, and the wettability was altered to be more strongly water-wet when the salinity increased. The primary mechanisms of oil recovery using the Si-NF after preflush salinity is attributed mainly to the clogging mechanism. This clogging helps block the high-perm area, shift the fluid flow to the oil-trapped zone, and free the oil out. Other contribution mechanisms are IFT reduction and wettability alteration.

Original languageEnglish
Article number6922
JournalEnergies
Volume14
Issue number21
DOIs
Publication statusPublished - Nov 1 2021

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

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