A Jurrasic oilfield in Saudi Arabia is characterized by black oil in the crest and with mobile heavy oil underneath and all underlain by a tar mat at the oil-water contact. The viscosities in the black oil section of the column are fairly similar and are quite manageable from a production standpoint. In contrast, the mobile heavy oil section of the column contains a large continuous increase in asphaltene content with increasing depth extending to the tar mat. The tar shows very high asphaltene content but not monotonically increasing with depth. Because viscosity depends exponentially on asphaltene content in these oils, the observed viscosity varies from several to ~ 1000 centipoise in the mobile heavy oil and increases to far greater viscosities in the tar mat. Both the excessive viscosity of the heavy oil and the existence of the tar mat represent major, distinct challenges in oil production. Conventional PVT modeling of this oil column grossly fails to account for these observations. Indeed, the very large height in this oil column represents a stringent challenge for any corresponding fluid model. A simple new formalism to characterize the asphaltene nanoscience in crude oils, the Yen-Mullins model, has enabled the industry's first predictive equation of state (EoS) for asphaltene gradients, the Flory-Huggins-Zuo (FHZ) EoS. For low GOR oils such as those in this field, the FHZ EoS reduces to the simple gravity term. Robust application of the FHZ EoS employing the Yen-Mullins model accounts for the major property variations in the oil column and by extension the tar mat as well. Moreover, as these crude oils are largely equilibrated throughout the field, reservoir connectivity is indicated in this field. This novel asphaltene science is dramatically improving understanding of important constraints on oil production in oil reservoirs.