Shale oil soluble hydrocarbon prediction method

The invention belongs to the technical field of unconventional and new energy, and discloses a shale oil soluble hydrocarbon prediction method, which comprises the following steps: S1, analyzing to obtain a total organic carbon content sensitive logging curve, and establishing a calculation model of the soluble hydrocarbon and total organic carbon content sensitive logging curve in combination with actually measured geochemical data; s2, extracting logging data in a production work area, and importing the logging data into the calculation model to calculate soluble hydrocarbon single well data; s3, establishing a data set of seismic attributes and soluble hydrocarbon single well data, taking soluble hydrocarbon as target data, optimizing sensitive seismic attributes through intersection of the target data and the seismic attributes, and performing machine learning by applying a probabilistic neural network method to establish a mapping relation between the target data and the sensitive seismic attributes, and