1-D ELASTIC WAVE-FORM INVERSION - A DIVIDE-AND-CONQUER APPROACH

Subsurface rock properties are manifested in seismic records as variat ions in traveltimes, amplitudes, and waveforms. It is commonly acknowl edged that traveltimes are sensitive to the long wavelength part of th e velocity, whereas amplitudes are sensitive to the short wavelength p art of the velocity. The inherent sensitivity of seismic velocity at d ifferent wavelengths suggests an approach that decomposes the waveform data into traveltime and amplitude components. Therefore we propose a divide-and-conquer approach to the elastic wave form inversion proble m. We first estimate the smoothly varying background velocity from the traveltime and the rapidly changing perturbations from the amplitude by amplitude variation with offset (AVO) inversion based on linearized reflection coefficient, Then we combine the perturbation with the bac kground to obtain a starting model to be used in the final waveform in version that models all converted waves and internal multiples assumin g a 1-D earth model. For estimating the background velocity, we use th e flatness of events as the objective criterion, and simulated anneali ng as a search tool. Three different model parameterization schemes (c onstant velocity blocks, splines, and arctangent models) are compared, with the arctangent having the most flexibility and least artifacts. Having obtained the background velocities, we analyze the AVO effects to estimate the perturbations to the background, for which we use a li nearized inversion method. The combination of the perturbation and bac kground should be sufficiently close to the true model so that the inv erse problem becomes quasi-linear. A full elastic waveform inversion i s used to fine-tune the combined model to obtain P-wave and S-wave vel ocity and density, again using either a nonlinear optimization method or an iterative linearized solution. Application of the inversion algo rithm to synthetic data from an 84-layer model was able to predict the full reflectivity data and recover the true model parameters. Applica tion to one seismic line in the Carolina Trough area found a thin gas zone which produces strong Bottom Simulating Reflectors (BSRs).