The invention relates to a
logging interpretation method related to
lithology identification, in particular to a formation
lithology identification method based on a
deep belief network. The
logging lithology identification method based on the
deep belief network is mainly completed through a computer, and equipment needed for achieving the method comprises a
logging instrument, a data
communication interface and a computer. The method comprises the following steps: identifying lithology around a
wellhead by utilizing logging data; preprocessing the logging data: performing normalization
processing; digitalizing the lithology classification; calculating the correlation degree between the logging curve and the lithology; presetting the structure of the
deep belief network; determining the number of restricted Boltzmann machines; determining a lithology classification boundary; training the deep belief network used for identifying formation lithology; and inputting the
well logging dataof the well to be interpreted into the network, and carrying out lithology identification work. The identification method provided by the invention is simple in prediction, high in identification accuracy, good in effect, practical and reliable for regions lacking stratum element logging and imaging logging data.