Characterise the non-uniqueness in full-waveform inversion by using the square-root variable metric based null-space shuttle
Type
Conference PaperAuthors
Liu, Q.Peter, Daniel

KAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionEarth Science and Engineering Program
Extreme Computing Research Center
King Abdullah University of Science and Technology
Physical Science and Engineering (PSE) Division
KAUST Grant Number
UAPN#2605-CRG4Date
2019-08-26Permanent link to this record
http://hdl.handle.net/10754/661840
Metadata
Show full item recordAbstract
Full-waveform inversion is an ill-posed inverse problem, with non-unique solutions. We examine its non-uniqueness by exploring the null-space shuttle, which can generate an ensemble of data-fitting solutions efficiently. We construct this shuttle based on a quasi-Newton method, the square-root variable-metric (SRVM) method. This method enables a retrieval of the inverse data-misfit Hessian after the SRVM-based elastic FWI converges. Combining SRVM with randomised singular value decomposition (SVD), we obtain the eigenvector subspaces of the inverse data-misfit Hessian. The first one among them is considered to determine the null space of the elastic FWI result. Using the SRVM-based null-space shuttle we can modify the inverted result a posteriori in a highly efficient manner without corrupting data misfit. Also, because the SRVM method is embedded through elastic FWI, our method can be extended to multi-parameter problems. We confirm and highlight our methods with the elastic Marmousi example.Citation
Liu, Q., & Peter, D. (2019). Characterise the Non-Uniqueness in Full-Waveform Inversion by Using the Square-Root Variable Metric Based Null-Space Shuttle. 81st EAGE Conference and Exhibition 2019. doi:10.3997/2214-4609.201901222Sponsors
This work was supported by the King Abdullah University of Science & Technology (KAUST) Office of Sponsored Research (OSR) under award No. UAPN#2605-CRG4. Computational resources were provided by the Information Technology Division and Extreme Computing Research Center (ECRC) at KAUST.Publisher
EAGE PublicationsConference/Event name
81st EAGE Conference and Exhibition 2019ae974a485f413a2113503eed53cd6c53
10.3997/2214-4609.201901222