Asphaltene precipitation is a challenging and complex problem in all sections of the oil industry including oil production, transportation and processing. Asphaltenes can plug pumps, valves, tubing and flow lines, cause fouling in surface handling facilities and even act as coke precursors and catalyst poisons. For these reasons, the occurrence of asphaltene deposits may result in productivity losses and sometimes even production shutdowns. For many years, much effort has been done on modelling asphaltene precipitation because experimental investigation is a hard task. Thermodynamic models based on Flory-Huggins theory have been used by several oil companies to predict the asphaltene onset conditions due to the depletion or gas injection. However, the main requirement to accomplish a successful calculation of asphaltene precipitation is an accurate solubility parameter. A variety of models to calculate asphaltene precipitation based on the solubility parameter is available in literature but most of them are complex due to inherent assumptions that are built-in. In this work, a new simple and accurate method to calculate the asphaltene solubility parameter is proposed, which requires only SARA (saturate, aromatic, resin, and asphaltene) analysis, the oil composition and the reservoir temperature. Once it is sufficient to know up to C7+ fraction, a much detailed analysis of the oil composition is unnecessary. Soave-Redlich-Kwong (SRK) (Prausnitz et al. 1999) equation of state (EOS) and Pedersen's characterization method (Pedersen et al. 1984) were used to calculate the liquid phase molar volume and SARA analysis was employed to determine the number of fractions that correspond to the amount of asphaltene in the oil. Five oils were selected from literature and calculation of their asphaltene solubility parameter was performed without needing their composition in details. Just one fraction was sufficient to include the amount of asphaltene indicated in SARA analysis for all oils tested. Each oil was considered as a mixture of 26 components. The values of asphaltene solubility parameters calculated by a simple method based on SRK EOS were comparable to those given by perturbed-chain statistical associating fluid theory (PC SAFT) EOS available in literature (Punnapala and Vargas 2013), which requires an extremely detailed characterization of the oil. Therefore, the proposed simple method is preferred because it is much more useful to the oil industry.

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