Journal of Tropical Oceanography ›› 2011, Vol. 30 ›› Issue (5): 74-80.doi: 10.11978/j.issn.1009-5470.2011.05.074cstr: 32234.14.j.issn.1009-5470.2011.05.074

• Marine geomorphology • Previous Articles     Next Articles

Studying basement fault division in Southeast Hainan Basin of the South China Sea using gravity horizontal gradient vector method

LIU Bing1, 2, WU Shi-min1, 3, LONG Gen-yuan1, 2, GUO Xiang-yan1, 2, ZENG Guang-dong4   

  1. 1. Key Laboratory of Marginal Sea Geology , South China Sea Institute of Oceanology, CAS, Guangzhou 510301, China ; 2. Graduate University of CAS , Beijing 100039, China ; 3. Department of earth sciences, Sun Yat-Sen University , Guangzhou 510275 , China ; 4. Institute of SINOPEC Shanghai Offshore Oil and Gas Company, Shanghai 200120, China
  • Received:2011-11-01 Revised:2011-11-01 Online:2011-11-01 Published:2011-11-01
  • Contact: 吴世敏 E-mail:wushim@mail.sysu.edu.cn

Abstract: Basement fault is an associated structure with the basin. The deposition in a basin and the tectonic style as well as the distribution of resources are determined by basement faults. On the basis of 2-minute Free Air Gravity anomaly database in the Southeast Hainan Basin of the South China Sea , the Bouguer anomaly is obtained after topography correction and Bouguer correction. The gravity horizontal gradient vector data are obtained from the analysis of the Bouguer anomaly. We are able to find 48 basement faults in the basin using the gravity horizontal gradient vector data, which are divided into three ranks, including five first rank faults, eight second rank faults, and 35 third rank faults. Comparing these findings with the results using other geological and geophysical methods such as seismic profiles, we find all results are consistent in terms of the main tectonic structure. However, the gravity horizontal gradient vector method has the advantages of being inexpensive, easy, and intuitive.

Key words: gravity, horizontal gradient vector, Southeast Hainan Basin , basement fault, seismic profile

CLC Number: 

  • P736