The XWITM optimisation toolbox powering Full Waveform Inversion now integrates the AWI and RWI 2.0 cost functions. This introduces increased sensitivity to the deepest and most subtle reflection moveout invisible to standard FWI formulations.
AWI redefines the cost function with filter coefficients penalised away from zero lag. RWI redefines the cost function with a virtual-source generated scattered wavefield. AWI avoids cycle-skipped solutions. RWI increases the penetration depth of macro-model updates.
In this demonstration (SEG14 blind synthetic) we generate a superior fit between predicted and observed data by using AWI and RWI to update the macro model below the diving wave zone.
Original Starting Model
Simplified Starting Model
No AWI. No RWI.
X-Wave + AWI
Deeper penetrating update
X-Wave + AWI + RWI 2.0
Deepest penetrating update
Turning the remaining residual into macromodel updates
Enhanced convergence from fitting moveout curvature - deep reflected events in the predicted data shifting into position through the inversion.
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