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Role of Wettability on the Adsorption of an Anionic Surfactant on Sandstone Cores.

Mohammadreza AmirmoshiriLeilei ZhangMaura C PuertoRaj D TewariRidhwan Zhafri B Kamarul BahrimRouhi FarajzadehGeorge J HirasakiSibani Lisa Biswal
Published in: Langmuir : the ACS journal of surfaces and colloids (2020)
We investigate the dynamic adsorption of anionic surfactant C14 - 16 alpha olefin sulfonate on Berea sandstone cores with different surface wettability and redox states under high temperature that represents reservoir conditions. Surfactant adsorption levels are determined by analyzing the effluent history data with a dynamic adsorption model assuming Langmuir isotherm. A variety of analyses, including surface chemistry, ionic composition, and chromatography, is performed. It is found that the surfactant breakthrough in the neutral-wet core is delayed more compared to that in the water-wet core because the deposited crude oil components on the rock surface increase the surfactant adsorption via hydrophobic interactions. As the surfactant adsorption is satisfied, the crude oil components are solubilized by surfactant micelles and some of the adsorbed surfactants are released from the rock surface. The released surfactant dissolves in the flowing surfactant solution, thereby resulting in an overshoot of the produced surfactant concentration with respect to the injection value. Furthermore, under water-wet conditions, changing the surface redox potential from an oxidized to a reduced state decreases the surfactant adsorption level by 40%. We find that the decrease in surfactant adsorption is caused not only by removing the iron oxide but also by changing the calcium concentration after the core restoration process (calcite dissolution and ion exchange as a result of using EDTA). Findings from this study suggest that laboratory surfactant adsorption tests need to be conducted by considering the wettability and redox state of the rock surface while recognizing how core restoration methods could significantly alter the ionic composition during surfactant flooding.
Keyphrases
  • aqueous solution
  • mass spectrometry
  • machine learning
  • drug delivery
  • ionic liquid
  • risk assessment
  • high resolution
  • deep learning
  • big data
  • artificial intelligence
  • drug discovery
  • iron oxide