Quantitative Molecular Representation of Asphaltenes and Molecular Dynamics Simulation of Their Aggregation

Abstract

RECEIVED DATETITLE RUNNING HEAD: QMR representation of asphaltenes and MD simulation of aggregation. CORRESPONDING AUTHOR FOOTNOTE: EBoek@slb.com; Tel +44 1223 325222 2 ABSTRACT We have developed a computer algorithm to generate Quantitative Molecular Representations (QMR) of asphaltenes based on experimental data. First, we generate molecular representations using a Monte Carlo method. For this purpose, we use an extensive set of aromatic and aliphatic building blocks, which are sampled randomly from the corresponding distribution and then linked together using a connection algorithm. The building blocks can be taken from a pre-defined inventory or generated during run-time.Manually pre-fabricated blocks ensure model flexibility while automatically generated blocks allow us to build large aromatic sheets. We allow for both archipelago and peri-condensed structures to be generated. Then, we use a non-linear optimisation procedure to select a small subset of molecules that gives the best match with experimental data. These experimental data consist of Molecular Weight (MW), elemental analysis and NMR spectroscopy, including both 1 H and 13 C data. First, we validate the method by testing a number of single model compounds. Then we use a real asphaltene data set available in the literature. Different values of the MW were used as input parameter. We tested two specific values of the MW in detail, representing the peri-condensed and archipelago structure respectively: MW= 750 and MW = 4190. For both MWs, we generated 10 sets of 5000 samples each.The samples were then optimized with respect to the experimental objective function. Then we calculate the value of the objective function as an average over all the simulation runs. It turns out that the value of the objective function is significantly smaller for MW=750 than for MW=4190. This means that the lower Molecular Weight of 750 provides the best match with the experimental data. As an example, one of the optimised QMR asphaltene structures generated was then used as input in Molecular Dynamics (MD) simulations to study the formation of nano-aggregates.

Asphaltene solubility in common solvents: A molecular dynamics simulation study

“…The aggregation of asphaltene molecules in the absence of solvent (only asphaltene in the simulation box) and in the presence of a solvent, (heptane, toluene, or isopropyl benzene) were simulated and the results were compared with previous simulation results of RED and RDF. [22,23,27,41] The radial distribution function (RDF), g(r), was calculated for a pair of asphaltene molecules in two cases: asphaltene only, and asphaltenes and a solvent. Analysis of the trajectory for full NVT simulation was performed to calculate the asphaltene-asphaltene RDF.…”

“…[21] As mentioned above, molecular simulation can be used to predict the behaviour of asphaltenes on a molecular level and to investigate the effects of various solvents on asphaltene dissolution. [22][23][24][25] Frigerio and Molinari [26] used a multi-scale approach for asphaltene simulation. They determined molecular structures in crude oil and studied their behaviour in the solvents by creating 17 sample structures for asphaltene, and then by using molecular simulations they calculated the intermolecular interactions.…”

Molecular Dynamics Simulation of Spontaneous Imbibition in Nanopores and Recovery of Asphaltenic Crude Oils Using Surfactants for EOR Applications

“…This architecture of asphaltenes corresponds to the generally accepted island model, see e.g. [14]. Please note that the surfactants and asphaltenes considered here are model representation.…”

“…Please note that the surfactants and asphaltenes considered here are model representation. In future work, we aim to create coarse-grained asphaltene models that are consistent with quantitative molecular representations [14]. The pore throat is also constructed from individual particles.…”

A Review of Kinetic Modeling Methodologies for Complex Processes

“…Several molecular reconstruction methods have been developed (Al Halwachi et al, 2012;Allen and Liguras, 1991;Alvarez-Majmutov et al, 2014Boek et al, 2009;Neurock et al, 1994;Peng, 1999;Pyl et al, 2011;Quann and Jaffe, 1992;Sheremata et al, 2004;Zhang, 1999). These methods can be classified into three groups according to the approach used to represent the molecular composition: approach by model molecule, deterministic molecular reconstruction approach, and stochastic molecular reconstruction approach.…”