Riazi, N., Lines, L. and Russell, B., 2015. Monitoring heavy oil recovery by time-lapse EEI inversion. Journal of Seismic Exploration, 24: 343-364. The application of time-lapse (4D) seismology in the monitoring and development of different oilfields has proven to be valuable in reservoir characterization. Time-lapse seismology utilizes successive seismic surveys acquired during the production of a reservoir in order to monitor production related changes by measuring the difference in elastic properties of subsurface. To monitor the reservoir related changes, rather than seismic processing and acquisition changes, a calibration process should be implemented to optimize and improve the repeatability of non-reservoir zones and consequently enhance the production-related anomalies in the reservoir. We can use two different approaches in our analysis, one based on seismic horizon changes and the other based on seismic volume changes. In time-lapse seismic horizon interpretation we measure the time-shift and amplitude differences along the seismic horizons both in the base and monitor surveys. In volume interpretation, we use seismic inversion, which incorporates time and amplitude changes in the reservoir, to derive impedance volumes and thus infer both pressure and fluid saturation changes. The elastic impedance (EI) inversion method proposed by Connolly (1999) is a technique used to extract elastic impedance volumes from partial angle-stack data, where elastic impedance is defined as the impedance that would be found by inverting linearized equation formulated by Aki and Richards (1980). Due to the variable scaling found at different incidence ray angles in the elastic impedance method, Whitcombe et al. (2002) normalized the technique and introduced a new technique called extended elastic impedance, or EEI. which uses the intercept and gradient volumes of standard AVO analysis as its seismic input rather than the angle-stack data, transformed using an angle (called chi) which correlates best with an elastic parameter of interest. Here. we apply both elastic impedance (EI) inversion and extended elastic impedance (EED inversion to time-lapse data acquired over a cold production heavy oilfield. We show which chi angles correlate best with our petrophysical attributes of interest. Furthermore, we illustrate how time-lapse EEI inversion results