Full Waveform Inversion (FWI) is a nonlinear optimization problem aimed to estimating subsurface parameters by minimizing the misfit between modeled and recorded seismic data using gradient descent methods, which are the only practical choice because of the size of the problem. Due to the high nonlinearity of the problem, gradient methods will converge to a local minimum if the starting model is not close to the true one. The accuracy of the longwavelength components of the initial model controls the level of nonlinearity of the inversion. In order for FWI to converge to the global minimum, we have to obtain the long wavelength components of the model before inverting for the short wavelengths. Ultralow temporal frequencies are sensitive to the smooth (long wavelength) part of the model, and can be utilized by waveform inversion to resolve that part. Unfortunately, frequencies in this range are normally missing in field data due to data acquisition limitations. The lack of low frequencies can be compensated for by utilizing wideaperture data, as they include arrivals that are especially sensitive to the long wavelength components of the model. The higher the scattering angle of a 5 recorded event, the higher the model wavelength it can resolve. Based on this property, a scatteringangle filtering algorithm is proposed to start the inversion process with events corresponding to the highest scattering angle available in the data, and then include lower scattering angles progressively. The large scattering angles will resolve the smooth part of the model and reduce the nonlinearity of the problem, then the lower ones will enhance the resolution of the model. Recorded data is first migrated using Prestack Exploding Reflector Migration (PERM), then the resulting prestack image is transformed into angle gathers to which an angle filtering process is applied to remove events below a certain cutoff angle. The filtered prestack image cube is then demigrated (forward modeled) to produce filtered surface data that can be used in waveform inversion. Numerical tests confirm the feasibility of the proposed filtering algorithm. However, the accuracy of the filtered section is limited by PERMâ€™s singularity for horizontallytraveling waves, which in turn is dependent on the velocity model used for migration and demigration
Date of Award  Sep 2014 

Original language  English (US) 

Awarding Institution   Physical Sciences and Engineering


Supervisor  Tariq Ali Alkhalifah (Supervisor) 

 PERM
 Exploring Reflector
 Angel Filtering
 FWI
 Seismic Inversion