Application of Multivariate Data Analysis to Determine Geochemical Hydrocarbon Anomaly in Yakela, China

Many statistical tools are useful in developing qualitative insights into a wide variety of natural phenomena; many others can be used to develop quantitative answers to specific questions. Unfortunately most classical statistical methods make no use of the spatial information in the earth science data. A large number of useful or potentially useful multivariate techniques are available, e.g., kriging, moving average, factor analysis, cluster analysis, and fourrier filtering as well as an increasingly large number of them are being applied in geologic and geochemical investigations. Yakla is a typical and important oil and gas region in north Tarim basin in China. Therefore, a lot of exploration work has been already carried out in this area. Samples collected from the area were analyzed for their hydrocarbon mass fractions and multivariate techniques combined with other data helped the authors to identify the hydrocarbon anomaly in Yakela.