Model training method and stratigraphic division conclusion extraction method

A model training apparatus, comprising:

• a processor and a memory in communication connection with the processor;
• wherein
• the memory stores computer-executable instructions;
• and
• the processor executes the computer-executable instructions stored in the memory, so as to implement the following steps:
• obtaining a plurality of first logging curves of a target logging well, wherein a plurality of the first logging curves are respectively used to indicate depth, gamma ray, spontaneous potential, acoustic velocity and dual laterolog resistivity;
• pre-processing a plurality of the first logging curves to obtain a second logging curve corresponding to each of the first logging curves;
• performing a multi-scale wavelet decomposition on target segment lengths of a plurality of the second logging curves to obtain a multi-scale component corresponding to each of the second logging curves;
• and
• inputting sample point data of the target segment length of each of the second logging curves and the multi-scale component corresponding to each of the second logging curves into a pre-constructed multi-level bidirectional long short-term memory network so as to train the multi-level bidirectional long short-term memory network;
• wherein the multi-level bidirectional long short-term memory network is constructed by a plurality of bidirectional long short-term memory networks with different network parameters;
• and the multi-level bidirectional long short-term memory network after completion of training is configured to output a first stratigraphic division conclusion corresponding to each of the second logging curves.