Method for identifying stratum lithology parameters based on multi-kernel ensemble learning
An integrated learning and stratum lithology technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of low judgment accuracy and low logging data utilization, and achieve high judgment accuracy and improve The effect of utilization
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[0042] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.
[0043] Such as figure 1 As shown, the embodiment of the present invention provides a method for identifying formation lithology parameters based on multi-core integrated learning, which specifically includes:
[0044] Step S1, dividing M different sample sets according to the characteristics of logging parameters,
[0045] S 1 ={(x 11 ,y 11 ),(x 12 ,y 12 ),…,(x 1n ,y 1n )};
[0046] S 2 ={(x 21 ,y 21 ),(x 22 ,y 22 ),…,(x 2n ,y 2n )};...;
[0047] S m ={(x m1 ,y m1 ),(x m2 ,y m2 ),…,(x mn ,y mn )}
[0048] in
[0049] Step S2, according to the predicted lithological parameter characteristics, in the case of maintaining the same ratio, each sample set is divided into the training sample set S according to a certain ratio mtrain and test sample set S mtest , the number of samples in the training sample set is n mtrain , the ...
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