Advances in asphaltene science and a new generation of downhole fluid analysis (DFA) technology have been integrated to yield powerful new insights to reservoir dynamics. The Yen-Mullins model of asphaltene nanoscience has enabled development of the industry’s first predictive equation of state (EOS) for asphaltene concentration gradients - the Flory-Huggins-Zuo (FHZ) EOS in oil reservoirs. The FHZ EOS along with DFA measurements has successfully addressed a variety of reservoir concerns including reservoir connectivity, viscosity gradients, and fluid disequilibrium. The model shows that asphaltene concentration gradients can be large owing to both the gravity term and gas/oil ratio (GOR) gradients. The FHZ EOS is reduced to a very simple form for low GOR black oils and heavy oils, and heavy oils are shown to exhibit enormous asphaltene concentration gradients compared to conventional black oil. In this paper, the FHZ EOS has been applied not only to calculate asphaltene concentration gradients but also to predict asphaltene phase instability in oil reservoirs and potential flow assurance issues. Two categories of tar mats are addressed, one with a large discontinuous increase in asphaltene concentration versus depth typically at the base of an oil column (corresponding to asphaltene phase transition); the second with a continuous increase in asphaltene content at the base of a mobile heavy oil column due to an exponential increase in viscosity with asphaltene content. The discontinuous type of tar mat is show to occur in two distinct setting, one more common tar mat at the base of the column and a second unusual tar mat that occurs upstructure and is permeable. The predictions are in good agreement with the laboratory and field data and the mechanisms of forming these two kinds of tar mats are also discussed. This methodology establishes a powerful new approach for conducting the analyses of asphaltene concentration grading, flow assurance and tar mat formation in oil reservoirs by integrating the Yen-Mullins model, and the FHZ EOS with DFA technology.


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