Asymptotic methods provide an efficient means by which to infer reservoir flow properties, such as permeability, from timelapse seismic data. A trajectorybased methodology, similar to raybased methods for medical and seismic imaging, is the basis for an iterative inversion of timelapse amplitude changes. In this approach, a single reservoir simulation is required for each iteration of the algorithm. A comparison between purely numerical and the trajectorybased sensitivities demonstrates their accuracy. Analysis of a set of synthetic amplitude changes indicates that we are able to recover largescale reservoir permeability variations from timelapse amplitude data. In an application to actual timelapse amplitude changes from the Bay Marchand field in the Gulf of Mexico, we are able to reduce the misfit by 81% in 12 iterations. The timelapse observations indicate lower permeabilities are required in the central portion of thereservoir.
