Rock slice intelligent identification device and method

Abstract

The invention discloses an intelligent identification device and method for a rock slice, and the device comprises microscopic image collection equipment which collects a rock microscopic image of the rock slice; mineral measurement imaging equipment which is used for acquiring a mineral fingerprint image of the rock slice; and an image processing system which is connected with the microscopic image acquisition equipment and the mineral measurement imaging equipment, and is used for identifying the rock slice based on the rock microscopic image and the mineral fingerprint image. According to the intelligent identification device for the rock slice, the method comprises the steps: acquiring the rock microscopic image through the microscopic image acquisition equipment, acquiring the mineral fingerprint image through the mineral measurement imaging equipment, digitally synthesizing the rock microscopic image and the mineral fingerprint image through the image processing system, and identifying the rock slice; and finally, outputting a rock slice identification report, so that intelligent and automatic identification of the rock slice is realized, the influence of subjective factors of manual identification is avoided, the identification accuracy is high, and the identification speed is high.

Description

technical field [0001] The invention belongs to the fields of geology, petroleum geology and rock and mine experiment research, and in particular relates to an intelligent identification device and method for rock thin section samples. Background technique [0002] Rock (mineral) identification is the precursor and foundation of all research in the geological and energy mineral industries. Since 1827, the Scottish geologist William Nickell invented the polarizing microscope and the thin-section method, and the British geologist Clifton Soapy applied it to rock research, grinding the rock into a thin slice with a thickness of 30 μ, Observing the optical properties of minerals with transmitted light under a polarizing microscope and accurately identifying them has become a basic means of rock (mineral) identification. In the past 200 years, with the continuous advancement of science and technology, although various new testing techniques and research methods have been continu...

AI Technical Summary

Problems solved by technology

[0006] The shortcomings of the above-mentioned technologies: only proposed to process a certain type of special rock thin section images through image segmentation, BP neural network and other technical methods, and to identify some characteristic parameters such as particle size, boundary, particle size or type, the obtained The rock characteristics are not comprehensive, and the accurate identification of minerals is lacking, and the complete rock thin section identification process is not involved

[0008] Disadvantages of this device: it is forced to define that the composition and physical properties of the rock matrix and the particles are different, which violates the objective composition characteristics of the rock. A complex mixture with very strong heterogeneity, its composition includes not only transparent minerals but also opaque minerals such as metals, the identification of rock sections cannot be solved by light transmission alone

[0009] In summary, the existing intelligent identification methods cannot accurately identify minerals in rocks, let alone complete identification of rock thin sections

Images