(101d) Prediction of Heavy Oil Viscosity at Elevated Temperature

prediction of heavy oil viscosity is important for calculations of cold oil production rate and planning for thermal means of oil recovery.

Several correlations, corresponding state models, and equation of state based models are used to calculate heavy oil viscosity when experimental data are unavailable or at temperatures higher than the formation temperature. These methods have serious limitations and have poor accuracy to predict heavy oil viscosity.

Rarely heavy oil viscosity is measured at temperature higher than the formation temperature. Thus productivity and recovery estimates are based on predictive tools that have poor accuracy of heavy oil viscosity. The prediction capability of these methods have never been tested at elevated temperature simply because of lacking the experimental data.

I this study viscosity data for several heavy oil samples having API gravity from 10 to 15 degree are measured at original formation temperature and at elevated temperature encountered in hot water, steam cycling and steam flooding. The measured data and other data collected from literatures are used to assess the accuracy of the existing methods used to predict heavy oil viscosity. The assessment indicate that the available model have serious accuracy problems. The data was used to develop a new compositional model to predict viscosity of heavy oil at formation temperature and at elevated temperature. The new model uses compositional data of crude oil (saturated, aromatic, asphaltenes, resins, and molecular weight), pressure and temperature to predict heavy oil viscosity. The proposed model was tested against unbiased experimental data. The comparison shows that the new model has better accuracy and valid to be used to predict heavy oil viscosity at elevated temperature in case these measurements are unavailable.