Mr. Ling Zhu Profile

Ling Zhu

at Beijing Research Institute of Uranium Geology

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Proceedings Article | 21 March 2023 Paper

Spectral characteristics analysis of different minerals impregnated by crude oil fractions

Xin Cui, Kai Qin, Yuechao Yang, Ling Zhu

Proceedings Volume 12595, 125950S (2023) https://doi.org/10.1117/12.2667158

KEYWORDS: Minerals, Absorption, Contamination, Diagnostics, Analytical research, Calcite, Matrices, Fluorite, Spectroscopy

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One of the key fundamental scientific issues in the study of hyperspectral detection of oil and gas seepage is to determine the diagnostic spectral characteristics of surface soils and altered minerals during oil and gas seepage. In this study, various crude oil fractions were used to contaminate different minerals. The same crude oil was fractionated according to four temperature ranges: 0-120°C, 120-200°C, 200-275°C and 275-350°C. Subsequently, fractions from these four temperature ranges were used to contaminate four mineral powders (limonite, illite, calcite and fluorite) at doses of 1 ml to 10 ml. The spectral measurements and processing of the mixed matrices were carried out, the spectral characteristics and variation patterns were analyzed, and the spectral libraries of the four mineral mixed matrices were constructed for different crude oil fractions and different contaminated dose. The results show that all contaminated minerals have distinct hydrocarbon characteristic absorption peaks near the 1730 nm and 2300 nm positions. However, the hydrocarbon diagnostic feature peaks of the mixed matrix contaminated with crude oil are influenced by the original spectral characteristics of the minerals: the simpler the spectral characteristics of the mineral itself, the more positions of hydrocarbon absorption peak the mixed matrix spectrum exhibits, and the more obvious and prominent the characteristics. Meanwhile, the characteristic absorption peak of hydrocarbon is controlled by the type of crude oil fraction and the contamination dose. The heavier the crude oil fraction, the higher the contamination dose, the greater the absorption depth and area of the hydrocarbon diagnostic absorption peak.

Proceedings Article | 12 March 2021 Paper

Depth feature extraction for mineral mixed spectrum analysis based hyperspectral data

Kai Qin, Yingjun Zhao, Ling Zhu, Yuechao Yang, Xin Cui

Proceedings Volume 11763, 1176322 (2021) https://doi.org/10.1117/12.2586320

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Rocks in nature are mostly aggregates of various minerals. Because of the intimate mixing of minerals, the rock spectrum measured by hyperspectral sensors is generally the mixing spectrum of mineral components. Influenced by the noise of measuring equipment, non-linear mixing of mineral spectra, rock structure and mineral cleavage, determining and quantifying the abundances of minerals is still an open problem. In this paper, a method based on depth feature extraction for spectral unmixing of minerals is proposed to solve the problems of estimating the number of mineral endmembers, extracting the endmembers spectrum and calculating the abundance of mineral. Firstly, hyperspectral signal subspace minimum error identification (HySIME) algorithm is used to calculate the number of mineral endmembers. Secondly, the depth neural network is constructed to extract the dimension reduction feature of hyperspectral data, and obtain the mineral endmembers spectrum. Finally, the single scattering albedo of the spectrum is calculated by the Hapke model, and the abundance is estimated according to the number of endmembers and the endmembers spectrum. Aiming at the common rock forming minerals and altered minerals, the spectral data measured in the laboratory are tested. The results show that the method and technical process proposed in this paper are superior to the commonly used spectral mixed analysis method.

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