Association parameters for Cubic-Plus-Association equation of state determined by molecular dynamics and Petroleomics: Prediction of asphaltene precipitation

[Display omitted] •Advanced characterization techniques were used to obtain molecular descriptors.•Reliable molecular structures were proposed for representing real crude oil.•Molecular dynamics simulations were conducted to obtain association parameters.•Asphaltene onset pressure predicted by Cubic-Plus-Association equation of state.•Oxygenated aromatics determined experimentally are highly active in aggregation terms. In this study, petroleomics characterization, molecular dynamics (MD) simulations, and a cubic-plus-association (CPA) equation of state (EoS) were conducted to understand how the structural characteristics affect the phase behavior of a fluid. To do this, the asphaltene onset pressure (AOP) was estimated by CPA EoS using association parameters determined from MD simulations. Petroleomics characterization and gas chromatography were conducted to identify appropriate representative molecular structures for describing a live crude oil. The American Petroleum Institute (API) gravity, dead and live crude oil densities, and viscosities at reservoir conditions were calculated from the MD simulation results and were found to differ from the experimental measurements by less than 5%, indicating accurate characterizations for both real dead and live crude oil. A formation damage diagnosis from a compositional perspective was conducted because oxygenated aromatic compounds, which are highly active in aggregation terms, were identified in the aromatic fraction by Fourier-transform ion cyclotron resonance mass spectrometry (FT–ICR MS). The association parameters for the self-associating organics (So: asphaltenes and oxygenated aromatics) and the cross-interaction between these Sos and the maltenes were calculated from the MD simulation results. To the best of our knowledge, this is the first time that association parameters have been obtained from an MD model and successfully implemented in a CPA EoS, allowing the prediction of AOP with an accuracy close to 1% compared to the experimentally determined value for live crude oil. This study provides a promising framework to develop an EoS for crude oils based on their molecular characteristics, reducing the need to perform parametric tuning with experimental data. In addition, this structural characterization proposed could be important to other key topics such as enhanced oil recovery (EOR) and carbon capture use and storage (CCUS), relating the structural composition to phase behavior.