Journal of Tropical Oceanography ›› 2012, Vol. 31 ›› Issue (1): 55-61.doi: 10.11978/j.issn.1009-5470.2012.01.055cstr: 32234.14.j.issn.1009-5470.2012.01.055

• Marine Geology • Previous Articles     Next Articles

Multiples suppression using combination method in Chaoshan Depression of the South China Sea

LIN Qiu-jin1,2, YAN Pin1, YU Hong3, ZHENG Hong-bo1, TANG Qun-shu1, WANG Yan-lin1   

  1. 1. CAS Key Laboratory of Marginal Sea Geology, South China Sea Institute of Oceanology , CAS , Guangzhou 510301, China ; 2. Graduate University of CAS , Beijing 100049, China ; 3. Deep Energy Technology Limited Company, Zhanjiang 524000, China
  • Received:2010-07-08 Revised:2010-09-03 Online:2012-03-10 Published:2012-03-13

Abstract: The Chaoshan Depression, where the Mesozoic strata well developed, is an important mothball area for gas and oil exploration in the South China Sea. Identification and suppression of seismic multiples are especially difficult and are the keys to this area. In order to obtain high-quality seismic profiles, combining methods for multiples suppression is critical. According to the original seismic data with abnormal development and various multiples in two dimensions, This paper analysises the types and properties of the multiples, trying to suppress multiples using combination method with predictive deconvolution in τ-p domain, Surface Related Multiples Elimination (SRME) and Hyperbolic Radon transform. Short-period reverberation and peg-leg multiples are effectively attenuated by predictive deconvolution; SRME method is used for suppressing surface-relat ed multiples well, especially in the near-offset range; and hyperbolic radon transform is a good choice to attenuate long-period and surface-related multiples that are not sufficiently suppressed. As we expected, the quality of seismic profile improves significantly after suppress multiples using combination method .

Key words: Chaoshan Depression;predictive deconvolution, Surface-RelatedMultipleElimination , Hyperbolic Radon transform

CLC Number: 

  • P733.23