A pattern recognition and its application to stratum contrast
Xu Shao · 2002
In this paper we propose a pattern recognition method for the oil field stratum contrast problems of complicated geological condition and varying parameters. First, we use rule set's least decision\|making algorithm in rough set theory, get rid of redundancy and incompatible characteristics in pattern set. Second, we change digital well\|logging curves and stratum parameters into two\|value lattice image pattern by pretreatment, distill and memory stratum pattern characters that the curves expressed by compress lattice data code. Lastly, we use multi\|layer neural networks to train mapping relation between condition property and pattern sort. The neural network obtained has strong memory ability and extension ability and better adaptability to solve stratum contrast problem.