Journal of Tropical Oceanography ›› 2012, Vol. 31 ›› Issue (5): 88-92.doi: 10.11978/j.issn.1009-5470.2012.05.013cstr: 32234.14.j.issn.1009-5470.2012.05.013

• Marine Mineral Resources and Their Development • Previous Articles     Next Articles

GIS assessment of potential gas hydrate mineral resources in the Gulf of Mexico based on Weights-of-Evidence modeling

WANG Chun-juan1, DU De-wen1, LIU Yong-gang2, ZHU Zhi-wei1, YAN Shi-juan1, YANG Gang1   

  1. 1. First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China; 2.Guangzhou Marine Geological Survey, Guangzhou 510760, China
  • Received:2011-09-01 Revised:2012-03-19 Online:2012-11-01 Published:2013-02-06

Abstract: By using the ArcGIS tool and the Weights-of-Evidence-Modeling, the discovered gas hydrate mineral points in the northern Gulf of Mexico are considered as a training area, and estimate the ore-controlling evidence weight coefficients, which include water depth, seabed faults, seabed physiognomy, seep, slope basins, seabed temperature, geothermal gradient, and organic carbon. Then, the coefficients are extended for the whole northern slope in the Gulf of Mexico to estimate the spatial distribution of gas hydrate resources in the area. Evidence weight coefficients show that the hydrate formation and occurrence are closely related to seep, seabed physiognomy and slope basins; and the coefficients are respectively 6.6250, 2.2726 and 2.0447 for seep, seabed physiognomy and slope basins. Prediction results indicate that the discovered gas hydrate mineralization is distributed in the posterior probability sections, which shows the Weights-of-Evidence can be applied to the prediction of gas hydrate resources. Advantaged posterior probabilities show that there are abundant gas hydrate resources in the northern slope Gulf of Mexico, especially in the Texas-Louisiana-Mississippi canyon that is the potential seabed area searching for gas hydrate resources.

Key words: Weights-of-Evidence modeling, gas hydrate, Gulf of Mexico, mineral resource prediction, GIS

CLC Number: 

  • P628