Abstract:Full waveform inversion (FWI) is a multi-parameter, strong nonlinear global minimum problem. Non-constrained iterative local optimization methods are usually used to solve this problem. In this paper, we propose a FWI method based on scalar wave equation. First we establish object functions using the least square, and then deduce gradient equations. For the iteration, we apply the limited-memory BFGS (L-BFGS) method and line search to the time domain FWI, which will migrate the inversion illness. A numeric test on a complex velocity model shows that the proposed method has higher inversion precision than the conventional gradient method, and can accelerate the convergence of the object function. On real data test, similar encouraging results are obtained.
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