The invention discloses a geothermal
resource assessment method and
system based on
machine learning, and relates to the technical field of
resource development, and the method comprises the following steps: S1, obtaining, preprocessing and uploading multi-
source data; s2, constructing a
machine learning model containing a geologic feature
branch, a dynamic change
branch and an attention fusion layer, and obtaining a geothermal resource evaluation model through hierarchical training and multi-dimensional
verification; s3, inputting real-
time data to evaluate reserves, and sequencing and positioning the maximum reserve position; and S4, the development value is analyzed based on the whole-cycle cost income measurement and calculation and the return on investment rate. The method correspondingly comprises a
data acquisition module, a model construction module, a preliminary evaluation module and a value evaluation module, solves the problems of erroneous judgment and resource waste caused by dependence on empirical formulas, incapability of capturing complex features and lack of economic association analysis in a traditional method, realizes accurate evaluation through a multi-
branch attention fusion model, and improves the evaluation accuracy. The
economic evaluation closed loop is combined to ensure the development feasibility, reduce the investment risk and improve the project success rate.