摘要
Yakla area is a very important and typical region in North Tarim, because it is the region that leads to a breakthrough in North Tarim oil/gas exploring. Therefore, a lot of exploration work has been already carried out in the area aiming at assessing the hydrocarbon anomaly and some techniques for anomaly delineation are being suggested. Yakla covers about 312 km 2 and lies 20 km south to Luntai Kuche road and displays as a long rectangular, with the length of 24 km in ENE and the width of 13 km in WSW. The surface is desert covered with saline akali, sand ribbon and sand dune. Samples collected from Yakla were analyzed for their hydrocarbon mass fractions and the spatial distribution of the concentrations of selected hydrocarbons C 1, C 2, C 3, i C 4, n C 4, i C 5, n C 5 and UF365 were estimated from these data sets. Multivariate statistical techniques including Kriging, moving average, factor analyses, cluster analyses and furrier filtering are used. The statistical techniques, spatial data analysis and transformation capabilities of geographic information systems, combined with geophysical and geological data, helped the authors to identify the hydrocarbon anomaly in Yakla.
Yakla area is a very important and typical region in North Tarim, because it is the region that leads to a breakthrough in North Tarim oil/gas exploring. Therefore, a lot of exploration work has been already carried out in the area aiming at assessing the hydrocarbon anomaly and some techniques for anomaly delineation are being suggested. Yakla covers about 312 km 2 and lies 20 km south to Luntai Kuche road and displays as a long rectangular, with the length of 24 km in ENE and the width of 13 km in WSW. The surface is desert covered with saline akali, sand ribbon and sand dune. Samples collected from Yakla were analyzed for their hydrocarbon mass fractions and the spatial distribution of the concentrations of selected hydrocarbons C 1, C 2, C 3, i C 4, n C 4, i C 5, n C 5 and UF365 were estimated from these data sets. Multivariate statistical techniques including Kriging, moving average, factor analyses, cluster analyses and furrier filtering are used. The statistical techniques, spatial data analysis and transformation capabilities of geographic information systems, combined with geophysical and geological data, helped the authors to identify the hydrocarbon anomaly in Yakla.
