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Intelligent velocity picking and uncertainty analysis based on the Gaussian mixture model

Wang Xiaowei, Gao Yang, Chen Chang, Yuan Huan, Yuan Sanyi

Acta Geophysica

2022

Vol. 70, no 6

2659--2673

The stacking velocity is often obtained manually. However, manually picking is inefficient and is easily affected by subjective factors such as the priori information and the experience of different processors. To enhance its objectivity, efficiency and consistency, we investigated an unsupervised clustering intelligent velocity picking method based on the Gaussian mixture model (GMM). This method can automatically pick the stacking velocity fast, and provide uncertainty analysis as a quality control. Combined with the geometry feature of energy clusters in velocity spectra, taking advantages of the geometric diversity of energy clusters, GMM can ft the energy clusters with different distributions more appropriately. Then, mean values of the final several submodels are located as the optimal velocity, and the multiples are avoided under the expert knowledge and geological rules. In addition, according to the covariance of submodels, we can derive the uncertainty analysis of the final time-velocity pairs, so as to indicate the reliability of picking velocity at different depths. Moreover, the automated interpreted velocity field is used for both normal moveout (NMO) correction and stacking. The comparison with the manual references is adopted to evaluate the quality of the unsupervised clustering intelligent velocity picking method. Both synthetic data and 3D field data have shown that the proposed unsupervised intelligent velocity picking method can not only achieve similar accuracy with manual results, but also get rid of multiples. Furthermore, compared with manual picking, it can significantly improve the efficiency and accuracy in identifying pore and cave structures, as well as indicating the uncertainty of time-velocity pairs by variance.

Study on leaching kinetics of laterite ore using hydrochloric acid

Li Jinhui, Xu Zhifeng, Wang Ruixiang, Gao Yang, Yang Yang

Physicochemical Problems of Mineral Processing

2019

Vol. 55, iss. 3

711--720

The process of atmosphere-pressure acid leaching of laterites has attracted considerable attention in the nickel industry in recent years. However, the leaching kinetics of laterite using hydrochloride acid has not yet been fully researched. In this paper, the mineral analysis of the ore was carried out, and the leaching mechanism of different minerals at different time was studied comprehensively. The kinetics analysis of the leaching process of nickel, cobalt and manganese showed that the kinetics model of diffusion controlling was suitable and could be described by the linear equation, 1-3(1-a)2/3+2(1-a)=k2t. Based on the linear equation and the Arrhenius equation, the values of activation energy of metal leaching can be deduced (11.56 kJ/mol for nickel, 11.26 kJ/mol for cobalt and 10.77 kJ/mol for manganese). Study of leaching mechanism shows that the order of these minerals dissolution is: goethite, lizardite, magnetite and hematite. Due to the original or product of silica, magnetite, hematite and talc, they can form the solid film which hinders the leaching of valuable metals. Thus, the diffusion controlling step is inner diffusion, namely solid film diffusion controlling.