3-DIMENSIONAL, NONLINEAR, ASYMPTOTIC SEISMIC INVERSION

One of the difficulties associated with three-dimensional (3D) nonline ar seismic inverse problems is the huge computational size. A pragmati c way to reduce the computational effort is to first estimate a backgr ound model and subsequently linearize the problem around this backgrou nd model. This approach is taken in seismic imaging methods (such as B orn inversion). These methods are efficient but are, in general, not a ccurate for those cases where the estimate of the background model is inaccurate and for 3D data that are measured using an acquisition geom etry with large gaps. Nonlinear iterative inverse scattering methods c an be used to resolve this kind of problem but are extremely computer intensive. We propose an iterative scheme consisting of two alternate loops for an alternate estimation of background and contrast parameter s. For the inner loop for determining the contrast, high-frequency asy mptotic methods are used for both computing the data misfit function a nd accelerating the rate of convergence by means of preconditioning. A s a preconditioner, the Born inversion operator is used. We have appli ed the method to simulated data for a typical 3D acquisition geometry. On the one hand, the iterative method employed in the inner loop is s hown to be less sensitive to sampling problems (due to gaps in acquisi tion) than Born inversion. On the other hand, the rate of convergence of the iterative preconditioned Krylov (PK) scheme, important for the total computational effort, is accelerated significantly when compared to conjugate-gradient and other well established iterative methods. W e have found that the nonlinear iterative method, with our PK. scheme as inner loop, appears to be capable of resolving both background and contrast parameters after only a few iterations.