• Corpus ID: 4696289

A parameterization analysis for acoustic full-waveform inversion of sub-wavelength anomalies

  title={A parameterization analysis for acoustic full-waveform inversion of sub-wavelength anomalies},
  author={Pawan Bharadwaj and Wim A. Mulder and Guy Drijkoningen},
  journal={arXiv: Geophysics},
In the case of multi-parameter full-waveform inversion, the computation of the additional Hessian terms that contain derivatives with respect to more than one type of parameter is necessary. If a simple gradient-based minimization is used, different choices of parameterization can be interpreted as different preconditioners that change the condition number of the Hessian. If the non-linear inverse problem is well-posed, then the inversion should converge to a band-limited version of the true… 
1 Citations

From constant- to variable-density inverse extended Born modeling

For quantitative seismic imaging, iterative least-squares reverse time migration is the recommended approach. The existence of an inverse of the forward modelling operator would considerably reduce



Parametrization for 2-D SH Full Waveform Inversion

With single-parameter full waveform inversion, estimating the inverse of the Hessian matrix will accelerate the convergence, but is computationally expensive. Therefore, an approximate Hessian, which

Which parameterization is suitable for acoustic vertical transverse isotropic full waveform inversion? Part 1: Sensitivity and trade-off analysis

ABSTRACTIn most geologic environments, accounting for anisotropy is necessary to perform acoustic full waveform inversion (FWI) of wide-azimuth and wide-aperture seismic data because of the potential

An overview of full-waveform inversion in exploration geophysics

This review attempts to illuminate the state of the art of FWI by building accurate starting models with automatic procedures and/or recording low frequencies, and improving computational efficiency by data-compression techniquestomake3DelasticFWIfeasible.

A parametrization study for surface seismic full waveform inversion in an acoustic vertical transversely isotropic medium

SUMMARY Full waveform inversion (FWI) of surface seismic data requires low-frequency and long-offset data, namely diving waves or post-critical reflections, to update the long wavelength features of

A guided tour of multiparameter full-waveform inversion with multicomponent data: From theory to practice

Building high-resolution models of several physical properties of the subsurface by multiparameter full waveform inversion (FWI) of multicomponent data will be a challenge for seismic imaging for the

Multiparameter full waveform inversion of multicomponent ocean-bottom-cable data from the Valhall field. Part 1: imaging compressional wave speed, density and attenuation

Multiparameter full waveform inversion (FWI) is a challenging quantitative seismic imaging method for lithological characterization and reservoir monitoring. The difficulties in multiparameter FWI

Full waveform inversion and the truncated Newton method: quantitative imaging of complex subsurface structures

Full waveform inversion is a powerful tool for quantitative seismic imaging from wide‐azimuth seismic data. The method is based on the minimization of the misfit between observed and simulated data.

Inversion of seismic reflection data in the acoustic approximation

The nonlinear inverse problem for seismic reflection data is solved in the acoustic approximation. The method is based on the generalized least‐squares criterion, and it can handle errors in the data

A strategy for nonlinear elastic inversion of seismic reflection data

The problem of interpretation of seismic reflection data can be posed with sufficient generality using the concepts of inverse theory. In its roughest formulation, the inverse problem consists of

Gauss–Newton and full Newton methods in frequency–space seismic waveform inversion

SUMMARY By specifying a discrete matrix formulation for the frequency^space modelling problem for linear partial diierential equations (‘FDM’ methods), it is possible to derive a matrix formalism for