Interference in the data of geochemical hydrocarbon exploration is a large obstacle for anomaly recognition. The multiresolution analysis of wavelet analysis can extract the information at different scales so as to pr...Interference in the data of geochemical hydrocarbon exploration is a large obstacle for anomaly recognition. The multiresolution analysis of wavelet analysis can extract the information at different scales so as to provide a powerful tool for information analysis and processing. Based on the analysis of the geometric nature of hydrocarbon anomalies and background, Mallat wavelet and symmetric border treatment are selected and data pre-processing (logarithm-normalization) is established. This approach provide good results in Shandong and Inner Mongolia, China. It is demonstrated that this approach overcome the disadvantage of backgound variation in the window (interference in window), used in moving average, frame filtering and spatial and scaling modeling methods.展开更多
文摘Interference in the data of geochemical hydrocarbon exploration is a large obstacle for anomaly recognition. The multiresolution analysis of wavelet analysis can extract the information at different scales so as to provide a powerful tool for information analysis and processing. Based on the analysis of the geometric nature of hydrocarbon anomalies and background, Mallat wavelet and symmetric border treatment are selected and data pre-processing (logarithm-normalization) is established. This approach provide good results in Shandong and Inner Mongolia, China. It is demonstrated that this approach overcome the disadvantage of backgound variation in the window (interference in window), used in moving average, frame filtering and spatial and scaling modeling methods.
