WINDOW STATISTICAL ANALYSIS FOR DETECTING ANOMALIES IN GEOPHYSICAL DATA SETS

摘要

1. A method for identifying geological features in one or more discretized sets of geophysical data or data attributes representing an underground region, each such data set being called a “source data set”, comprising the following steps, at least one of which is performed using a computer: (a) select the shape and size of the data window; (b) move the window to many positions and form a data window vector for each window position, whose components consist of voxel values from of the second window, for each initial data array; (c) a statistical analysis of the vectors of the data window is performed, the statistical analysis being performed simultaneously in the case of a plurality of initial data arrays; (d) using statistical analysis to identify outliers or anomalies in the data; and (e) use outliers or anomalies to predict the geological features of the underground area. 2. The method according to claim 1, wherein the statistical analysis is performed using one of the group of statistical analysis methods consisting of: (i) calculating the matrix of mean values and the covariance matrix of all vectors of the data window; (ii) analyzing the independent components; (iii) using the method groupings for combining data; (iv) diffusion mapping; and (v) another method of statistical analysis. 3. The method of claim 2, wherein the statistical analysis is performed using (i) further comprising using principal component analysis. The method according to claim 2, in which the statistical analysis is performed using (i), and the calculation of the covariance matrix is performed by calculating