The application discloses a
coal seam
lithium-rich layer detection method based on
well logging curves and
statistical analysis, and belongs to the technical field of mineral resource exploration. The method comprises the following steps: selecting a series of representative
coal seam positions for systematic sampling, and preparing the samples into
piston samples and
powder samples; determining the
kaolinite and
lithium content of the
powder samples, and distinguishing
lithium-rich and ordinary
coal samples; systematically determining various geophysical
response parameters of the
piston samples, such as density, resistivity and
wave velocity, and screening out sensitive discrimination indexes for lithium enrichment; setting a window size, calculating the moving statistical value curves of the density, resistivity,
wave velocity and other
well logging curves sensitive to the lithium-rich layer, calculating principal components, and using the selected principal components and a support micro
machine to
train a prediction model, so as to predict the lithium-rich layer in the coal seam. The application combines geophysical
logging,
statistical analysis,
principal component analysis and a
support vector machine, and provides a fast, economical and non-destructive means for lithium resource exploration in coal.