Full waveform inversion(FWI)is a data-fitting inverse problem aiming to delineate high-resolution quantitative images of the Earth.While its basic principle has been proposed in the eighties,the approach has been sign...Full waveform inversion(FWI)is a data-fitting inverse problem aiming to delineate high-resolution quantitative images of the Earth.While its basic principle has been proposed in the eighties,the approach has been significantly developed and applied to2Dand 3Dproblems at various scales for the last fifteen years.Despite these successes,FWI is still facing some issues for applications in complex geological setups because of some lack of robustness and automatic workflow,while being computationally intensive.In this paper,after a short review of the basic FWI formulation and analysis of the FWI gradient,three recent methodological developments performed in the frame of the SEISCOPE project are presented.First,an algorithmic development is presented as a low-memory and computationally efficient approach for building the time-domain FWI gradient in 3Dviscous media.Second,a reformulation of FWI is performed to handle reflections in their tomography regime while still using the diving waves,leading to the joint full waveform inversion(JFWI)approach.Finally,an optimal transport approach is proposed as an alternative to the classical difference-based misfit for mitigating the cycle-skipping issue.展开更多
基金funded by the SEISCOPE consortium(http:∥seiscope2.osug.fr)sponsored by CGG,CHEVRON,EXXON-MOBIL,JGI,SHELL,SINOPEC,STATOIL,TOTAL and WOODSIDEgranted access to the HPC resources of the Froggy platform of the CIMENT infrastructure(https:∥ciment.ujf-grenoble.fr),which is supported by the Rh8ne-Alpes region(GRANT CPER07_13 CIRA)+2 种基金the OSUG@2020 labex(reference ANR10LABX56)the Equip @ Meso project(reference ANR-10-EQPX-29-01)of the programme Investissements d'Avenir supervised by the Agence Nationale pour la Recherchethe HPC resources of CINES/IDRIS under the allocation 046091made by GENCI
文摘Full waveform inversion(FWI)is a data-fitting inverse problem aiming to delineate high-resolution quantitative images of the Earth.While its basic principle has been proposed in the eighties,the approach has been significantly developed and applied to2Dand 3Dproblems at various scales for the last fifteen years.Despite these successes,FWI is still facing some issues for applications in complex geological setups because of some lack of robustness and automatic workflow,while being computationally intensive.In this paper,after a short review of the basic FWI formulation and analysis of the FWI gradient,three recent methodological developments performed in the frame of the SEISCOPE project are presented.First,an algorithmic development is presented as a low-memory and computationally efficient approach for building the time-domain FWI gradient in 3Dviscous media.Second,a reformulation of FWI is performed to handle reflections in their tomography regime while still using the diving waves,leading to the joint full waveform inversion(JFWI)approach.Finally,an optimal transport approach is proposed as an alternative to the classical difference-based misfit for mitigating the cycle-skipping issue.
