The application provides a method for realizing
well logging lithology identification based on a convolutional recurrent
deep learning network of a self-attention mechanism, mainly comprising: (1)
data set construction, that is, using drilling core
lithology description results and
well logging data of a
coring well section to group samples; (2) model construction, that is, determining a sample input mode and a basic structure of the model; (3) model training, that is, removing null values and abnormal values, normalizing sample characteristic values, encoding
label values, and dividing the samples into a
training set, a
verification set and a
test set; (4) model evaluation, that is, realizing model construction, parameter optimization, model training and
verification based on PyTorch. The application has reasonable conception, and realizes
well logging lithology identification by constructing a core-well
logging mapping relationship.