TY - GEN
T1 - Multi-domain surface multiple leakage extraction using local primary-and-multiple orthogonalization
AU - Zhang, Dong
AU - Verschuur, Eric
AU - Qu, Shan
AU - Chen, Yangkang
PY - 2020
Y1 - 2020
N2 - Surface-related multiple elimination (SRME) is a solid and effective approach for primary estimation. However, due to the imperfections in data and method multiple energy leakage is commonly seen in the results of SRME-predicted primaries. Assuming that the primaries and multiples do not correlate locally in the time-space domain, we are able to extract the leaked multiples from the initially estimated primaries using multi-domain local primary-and-multiple orthogonalization. The proposed framework consists of two steps: an initial primary/multiple estimation step and a multiple-leakage extraction step. The initial step corresponds to SRME, which produces the initial estimated primary and multiple models. The second step is based on multi-domain local primary-and-multiple orthogonalization to retrieve the leaked multiples. Multi-domain indicates that we first extract the leaked multiples in shot domain, and then the residual can be further extracted in common-offset domain. Thus, we can obtain a better primary output which has much less leaked multiple energy. We demonstrate a good performance of our proposed framework on both synthetic and field data, where it repairs the leakage of standard global adaptive subtraction.
AB - Surface-related multiple elimination (SRME) is a solid and effective approach for primary estimation. However, due to the imperfections in data and method multiple energy leakage is commonly seen in the results of SRME-predicted primaries. Assuming that the primaries and multiples do not correlate locally in the time-space domain, we are able to extract the leaked multiples from the initially estimated primaries using multi-domain local primary-and-multiple orthogonalization. The proposed framework consists of two steps: an initial primary/multiple estimation step and a multiple-leakage extraction step. The initial step corresponds to SRME, which produces the initial estimated primary and multiple models. The second step is based on multi-domain local primary-and-multiple orthogonalization to retrieve the leaked multiples. Multi-domain indicates that we first extract the leaked multiples in shot domain, and then the residual can be further extracted in common-offset domain. Thus, we can obtain a better primary output which has much less leaked multiple energy. We demonstrate a good performance of our proposed framework on both synthetic and field data, where it repairs the leakage of standard global adaptive subtraction.
UR - http://www.scopus.com/inward/record.url?scp=85079502566&partnerID=8YFLogxK
U2 - 10.1190/segam2019-3216199.1
DO - 10.1190/segam2019-3216199.1
M3 - Conference contribution
T3 - SEG Technical Program Expanded Abstracts
SP - 4585
EP - 4589
BT - SEG Technical Program Expanded Abstracts 2019
A2 - Winter, Glenn
A2 - Woller, Kevin
T2 - Society of Exploration Geophysicists International Exposition and Annual Meeting 2019, SEG 2019
Y2 - 15 September 2019 through 20 September 2019
ER -