Abstract: Studying the nanoscale pore characteristics of common rock minerals in reservoirs, as well as the thermal maturity, content, and occurrence state of organic matter, can help evaluate the unconventional oil and gas storage performance and hydrocarbon generation potential. This also serves as the foundation for unconventional oil and gas reservoir evaluation. However, in practical applications, the selection of single minerals is often prone to confusion due to similar morphology and optical properties, while thin-section identification faces challenges in accurately recognizing components due to the fine-grained minerals in shale. Traditional methods for detecting organic matter maturity also have many limitations. To address these issues, this study employs laser Raman spectroscopy rapid imaging as the basis. Using the point, line, and area scanning modes of this method, data were collected from several common single minerals and black shale in the reservoir. By processing the characteristic Raman spectra and final imaging, rapid identification and analysis of typical mineral components, spatial distribution, and organic matter were achieved. A multimodal scanning technique for the rapid identification of mineral components was proposed, and the practical application effects of this method in samples of different forms were investigated. Experimental results demonstrate that this method can effectively identify the presence of quartz, feldspar, and biotite in single minerals with a 100% recognition rate. Based on the 474cm⁻¹ and 513cm⁻¹ peaks of feldspar, the feldspar in the sample was preliminarily identified as adularia, a type of alkali feldspar. In shale thin sections, the recognition rate was 99%–100%, with calculated mineral contents of approximately 18% quartz, 27% calcite, 5% dolomite, and 50% carbonaceous material, which closely matches the mineral information obtained from thin-section analysis (discrepancy of 1%–5%). Furthermore, by analyzing the Raman spectra (1335–1348cm⁻¹, 1597–1605cm⁻¹) and Raman characteristic parameters of carbonaceous matter, it was determined that at least two different types of organic matter exist in the rock. The calculated Raman reflectance (_RmcRo%) of the organic matter in the sample ranged from 2.46% to 2.95%, with TypeⅠ between 2.56%–2.95% (accounting for ～72% of the organic matter in the scanned area) and TypeⅡ between 2.48%–2.81% (～28%). These results indicate that this technique performs well in practical applications across different sample forms, enabling intuitive determination of mineral components, content, organic matter composition, abundance, and thermal maturity within the scanned area. It provides a more accurate, intuitive, and convenient analytical method for unconventional oil and gas reservoir research.