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2D Time-lapse Seismic Tomography Using An Active Time Constraint (ATC) Approach
Citation:
Karaoulis, M., D Werkema, AND A. Revil. 2D Time-lapse Seismic Tomography Using An Active Time Constraint (ATC) Approach. Journal of Geophysics. Springer, New York, NY, 34(2):206-212, (2015).
Impact/Purpose:
Time-lapse seismic tomography is an important geophysical approach used to monitor the depletion of oil and gas reservoirs during their production (Vesnaver et al., 2003; Ayeni and Biondi, 2010), to monitor the sequestration of CO2 (e.g., Lazaratos and Marion, 1997; Ajo-Franklin et al., 2007a), to monitor geothermal fields, active volcanoes, or the remediation of contaminant plumes (e.g., McKenna et al, 2001). Several different time-lapse seismic tomography algorithms have been proposed in the literature, most of them based on travel time tomography rather than based on full waveform inversion (e.g., Ayeni and Biondi, 2010). Classical methods comprise sequential inversion with model-based regularization similar to the DC resistivity problem (Oldenburg et al., 2007 and Miller et al., 2008), travel time differences (Spetzler et al., 2007; Ajo-Franklin et al., 2007b), differential-wave-equation velocity analysis (Albertin et al., 2006), and the use of various regularization tools like compactness in the inverse problem (Ajo-Franklin et al., 2007b). Other approaches rely on time-lapse migration based on adjoint methods (Zhu et al., 2009).
Description:
We propose a 2D seismic time-lapse inversion approach to image the evolution of seismic velocities over time and space. The forward modeling is based on solving the eikonal equation using a second-order fast marching method. The wave-paths are represented by Fresnel volumes rather than by conventional rays. This approach accounts for complex velocity models and has the advantage of considering the effects of the wave frequency on the velocity resolution. The aim of time-lapse inversion is to find changes in velocities of each cell in the model as a function of time. Each model along the time axis is called a reference space model. This approach can be simplified into an inverse problem that seeks the optimum of several reference space models taken together using the approximation that the change in the seismic velocity varies linearly in time between two subsequent reference models. We demonstrate on a synthetic example that includes the regularization in time in the cost function and reduces inversion artifacts associated with noise in the data by comparison with independent inversions at each time.