A method to compute composite distance matrix from a multitude of data attributes

摘要: Example implementations described herein create a rich feature set based on observed/recorded attributes as well derived from those, and models each data vector in this multi-dimensional attribute space. then compute composite similarity between wells which provides better insights into their behavior. This can be calculated along all dimensions or subsets of dimensions, serve input to any clustering algorithm for further analysis. Finally, the incrementally computed by incorporating more required. Such used provide behavior oil wells, especially horizontal integrating features multiple upstream processes.