Experimental Investigation into the Screening of New Surfactant Flowback Aids and Statistical Interpretation of Their Imbibing Capacity for Selected Core Substrates

Abstract

AbstractSpontaneous imbibition is a pervasive part of many natural and industrial processes. As an inherent feature of fluid transport in porous media, it is a driver for oil recovery. Understanding spontaneous imbibition and leveraging surface science is fundamental for fluid recovery; specifically, the role of the surfactant in the imbibition processes and the potential to alter capillarity and wettability of reservoir rock. Surfactant success relies on the understanding of the factors governing the interfacial phenomena among crude oil, and formation properties under reservoir conditions. Developing a methodology coupling chemical performance with analytical techniques, and statistical interpretation of core/surfactant/oil interactions, can help establish workflows to advance new chemistries and enhance oil recovery. This article discusses a study of flowback aids formulated as microemulsions corresponding to the thermodynamically stable Winsor Type IV solutions. Neat formulated microemulsions, when dosed at field treatment concentrations, provide either oil‐in‐water droplet microemulsions or nanoemulsions. The solvency potential was measured, and the Kauri‐butanol (Kb) value was determined. Parameters such as critical micelle concentration (CMC) and interfacial tension (IFT) were determined to characterize microemulsion solutions. These systems were tested using either in the column flow test with formation material sieved to match mineral grain size, or sandstone cores of various permeabilities. The results indicate that surfactant‐based flow‐enhancing aids are desirable for improved oil recovery when compared to the control fluid. The statistical analysis of core‐fluid interaction includes an ANOVA followed by assumption evaluations and model interpretation, which demonstrates that the core permeability term, followed by the surfactant term, has the highest contribution whereas oil has no statistical significance to the model.