Large-scale subsurface injection of CO_2 has the potential to reduce emissions of atmospheric CO_2 and improve oil recovery. Studying the effects of injected CO_2 on the elastic properties of the saturated reservoir rock can help to improve long-term monitoring effectiveness and accuracy at locations undergoing CO_2 injection. We used two vintages of existing 3D surface seismic data and well logs to probabilistically invert for the CO_2 saturation and porosity at the Cranfield reservoir using a double-difference approach. The first step of this work was to calibrate the rock-physics model to the well-log data. Next, the baseline and time-lapse seismic data sets were inverted for acoustic impedance Ip using a high-resolution basis pursuit inversion technique. The reservoir porosity was derived statistically from the rock-physics model based on the Ip estimates inverted from the baseline survey. The porosity estimates were used in the double-difference routine as the fixed initial model from which CO_2 saturation was then estimated from the time-lapse Ip data. Porosity was assumed to remain constant between survey vintages; therefore, the changes between the baseline and time-lapse Ip data may be inverted for CO_2 saturation from the injection activities using the calibrated rock-physics model. Comparisons of inverted and measured porosity from well logs indicated quite accurate results. Estimates of CO_2 saturation found less accuracy than the porosity estimates.
展开▼
