Carbon dioxide injection, which is widely used as an enhanced oil recovery (EOR) method, has the potential of being coupled with CO2 sequestration and reducing the emission of greenhouse gas. Hence, knowing the compressibility factor of carbon dioxide is of a vital significance. Compressibility factor (Z-factor) is traditionally measured through time consuming, expensive and cumbersome experiments. Hence, developing a fast, robust and accurate model for its estimation is necessary. In this study, a new reliable model on the basis of feed forward artificial neural networks is presented to predict CO2 compressibility factor. Reduced temperature and pressure were selected as the input parameters of the proposed model. To evaluate and compare the results of the developed model with pre-existing models, both statistical and graphical error analyses were employed. The results indicated that the proposed model is more reliable and accurate compared to pre-existing models in a wide range of temperature (up to 1,273.15 K) and pressure (up to 140MPa). Furthermore, by employing the relevancy factor, the effect of pressure and temprature on the Z-factor of CO2 was compared for below and above the critical pressure of CO2, and the physcially expected trends were observed. Finally, to identify the probable outliers and applicability domain of the proposed ANN model, both numerical and graphical techniques based on Leverage approach were performed. The results illustrated that only 1.75% of the experimental data points were located out of the applicability domain of the proposed model. As a result, the developed model is reliable for the prediction of CO2 compressibility factor.
Bahadori A, Vuthaluru H, Rapid estimation of carbon dioxide compressibility factor using simple predictive tool, in: SPE Asia Pacific Oil and Gas Conference and Exhibition, Society of Petroleum Engineers (2010).
Ahmed T, Reservoir engineering handbook, Gulf Professional Publishing (2006).
Ahmed TH, Ahmed TH, Ahmed TH, Hydrocarbon phase behavior, Gulf Publishing Company (1989).
Heidaryan E, Moghadasi J, Rahimi M, J. Petroleum Sci. Eng., 73, 67, 2010
Lawal A, Van der Laan E, Thambynayagam R, Four-parameter modification of the Lawal-Lake-Silberberg equation of state for calculating gas-condensate phase equilibria, in: SPE Annual Technical Conference and Exhibition, Society of Petroleum Engineers (1985).