Extraction and characterization of crude oil acids for increased accuracy in computational microemulsion predictions

Abstract

Microemulsion modelling is a computational tool developed to predict the optimal salinity of a crude-surfactant-brine ternary phase system. Whilst optimal salinity is associated with the desirable Windsor Type-III microemulsion, other types of microemulsion can be determined from the model given the surfactant type, the brine concentration, and the components of the crude oil. The main challenge is to identify the surface active acid compounds of the crude oil that is responsible for the formation of emulsion in a ternary system. Therefore, it is important to characterize the full range of acidic species from crude oil because their chemical structures are crucial inputs to accurately predict the type of microemulsion formed. In this work, crude oil acids were extracted using two different methods – liquid-liquid extraction and acid-ion exchange resin (acid-IER), and were characterized using gas chromatography-mass spectrometry (GC-MS) and tandem liquid-chromatography tandem mass spectrometry (LC-MS/MS), respectively. For liquid-liquid extraction with derivatization, GC-MS results showed that low molecular weight acid (C4) can be identified. With the IER-extracted acids, the LC-MS/MS separated out low to medium molecular weight acids (C5-C18) with 1 cyclic acid (naphthenic acid) identified. Limitations of both extraction methods and characterization of crude oil acids using different instrumentation are discussed.