The invention belongs to the technical field of evaluation of components in mud shale, and discloses a method of evaluating volumes of components in mud shale by means of a conventional
logging curve. The method includes the steps of: 1) on the basis of organic carbon analysis,
porosity test and total rock inspection test of the mud shale after extraction, with combination of densities of the components in the mud shale, calibrating the volumes of the components in the mud shale and establishing a component volume model of the mud shale; 2) on the basis of evaluation of
total organic carbon content with a [
delta]logR method, with combination of a relationship of organic carbon before and after the extraction, calculating volume of
kerogen, and performing optimizing calculation to obtain a BP neural
network model of mineral components and pore volumes in a
cross validation manner. The method, on the basis of ensuring that the sum of the volumes of the components in mud shale is 1, achieves the advantages of multiple inputs and multiple outputs of the BP neural network and solves a complex nonlinear problem between the components in mud shale and
logging response.