Three-Dimensional Nonlinear Inversion of Electrical Conductivity

Electrical Engineering, Mathematics and Computer Scienc

A finite-difference contrast source inversion method

Electrical Engineering, Mathematics and Computer Scienc

Application of the finite-difference contrast-source inversion algorithm to seismic full-waveform data

We have applied the finite-difference contrast-source inversion (FDCSI) method to seismic full-waveform inversion problems. The FDCSI method is an iterative nonlinear inversion algorithm. However, unlike the nonlinear conjugate gradient method and the Gauss-Newton method, FDCSI does not solve any full forward problem explicitly in each iterative step of the inversion process. This feature makes the method very efficient in solving large-scale computational problems. It is shown that FDCSI, with a significant lower computation cost, can produce inversion results comparable in quality to those produced by the Gauss-Newton method and better than those produced by the nonlinear conjugate gradient method. Another attractive feature of the FDCSI method is that it is capable of employing an inhomogeneous background medium without any extra or special effort. This feature is useful when dealing with time-lapse inversion problems where the objective is to reconstruct changes between the baseline and the monitor model. By using the baseline model as the background medium in crosswell seismic monitoring problems, high quality time-lapse inversion results are obtained.IST/Imaging Science and TechnologyApplied Science

The diagonalized contrast source approach: An inversion method beyond the Born approximation

Applied Science

Structural similarity regularization scheme for multiparameter seismic full waveform inversion

We introduce a new regularization scheme for multiparameter seismic full-waveform inversion (FWI). Using this scheme, we can constrain spatial variations of parameters which are having a weak sensitivity with the one that having a good sensitivity to the measurement, assuming that these parameters have similarities in their structures. In seismic FWI, we apply this scheme when inverting the P-wave velocity and mass density simultaneously. Results from numerical tests show that this scheme may significantly improve the reconstruction of the mass density. Since we obtain an improved mass-density distribution, the inverted P-wave velocity is also enhanced. Hence, we also obtain a better data fit. As numerical examples we show inversions of both vertical seismic profiling (VSP) and surface seismic measurements.IST/Imaging Science and TechnologyApplied Science