Volcanosedimentary boron deposits are present within Tertiary lacustrine sediments and volcanic rocks in Xiongba, Tibet. Boron deposits are characterized by low density relative to country rocks; thus, it is possible ...Volcanosedimentary boron deposits are present within Tertiary lacustrine sediments and volcanic rocks in Xiongba, Tibet. Boron deposits are characterized by low density relative to country rocks; thus, it is possible to locate them by gravity measurements. We conducted a 1：50000 high-precision gravity survey in the Xiongba area, Tibet, and obtained the Bouguer and residual gravity anomalies. We analyzed fault systems and the distribution of sedimentary and volcanic rocks and their relation to the volcanosedimentary boron deposits. The processing of the gravity data revealed local gravity variations and fault structures. We applied preferential downward continuation and wavelet transform to the gravity data, and in conjunction with geological data, we predicted the distribution of volcanosedimentary boron deposits.展开更多
Remarkable progress has been achieved on microseismic signal denoising in recent years,which is the basic component for rock-burst detection.However,its denoising effectiveness remains unsatisfactory.To extract the ef...Remarkable progress has been achieved on microseismic signal denoising in recent years,which is the basic component for rock-burst detection.However,its denoising effectiveness remains unsatisfactory.To extract the effective microseismic signal from polluted noisy signals,a novel microseismic signal denoising method that combines the variational mode decomposition(VMD)and permutation entropy(PE),which we denote as VMD–PE,is proposed in this paper.VMD is a recently introduced technique for adaptive signal decomposition,where K is an important decomposing parameter that determines the number of modes.VMD provides a predictable eff ect on the nature of detected modes.In this work,we present a method that addresses the problem of selecting an appropriate K value by constructing a simulation signal whose spectrum is similar to that of a mine microseismic signal and apply this value to the VMD–PE method.In addition,PE is developed to identify the relevant effective microseismic signal modes,which are reconstructed to realize signal filtering.The experimental results show that the VMD–PE method remarkably outperforms the empirical mode decomposition(EMD)–VMD filtering and detrended fl uctuation analysis(DFA)–VMD denoising methods of the simulated and real microseismic signals.We expect that this novel method can inspire and help evaluate new ideas in this field.展开更多
基金supported by the National Science and Technology Major Project of China(No.2011CB403-005)the Tibet WangSheng Investment Co.,LTD
文摘Volcanosedimentary boron deposits are present within Tertiary lacustrine sediments and volcanic rocks in Xiongba, Tibet. Boron deposits are characterized by low density relative to country rocks; thus, it is possible to locate them by gravity measurements. We conducted a 1：50000 high-precision gravity survey in the Xiongba area, Tibet, and obtained the Bouguer and residual gravity anomalies. We analyzed fault systems and the distribution of sedimentary and volcanic rocks and their relation to the volcanosedimentary boron deposits. The processing of the gravity data revealed local gravity variations and fault structures. We applied preferential downward continuation and wavelet transform to the gravity data, and in conjunction with geological data, we predicted the distribution of volcanosedimentary boron deposits.
基金supported by the National Natural Science Foundation of China(No.51904173)Shandong Provincial Natural Science Foundation(No.ZR2018MEE008)the Project of Shandong Province Higher Educational Science and Technology Program(No.J18KA307).
文摘Remarkable progress has been achieved on microseismic signal denoising in recent years,which is the basic component for rock-burst detection.However,its denoising effectiveness remains unsatisfactory.To extract the effective microseismic signal from polluted noisy signals,a novel microseismic signal denoising method that combines the variational mode decomposition(VMD)and permutation entropy(PE),which we denote as VMD–PE,is proposed in this paper.VMD is a recently introduced technique for adaptive signal decomposition,where K is an important decomposing parameter that determines the number of modes.VMD provides a predictable eff ect on the nature of detected modes.In this work,we present a method that addresses the problem of selecting an appropriate K value by constructing a simulation signal whose spectrum is similar to that of a mine microseismic signal and apply this value to the VMD–PE method.In addition,PE is developed to identify the relevant effective microseismic signal modes,which are reconstructed to realize signal filtering.The experimental results show that the VMD–PE method remarkably outperforms the empirical mode decomposition(EMD)–VMD filtering and detrended fl uctuation analysis(DFA)–VMD denoising methods of the simulated and real microseismic signals.We expect that this novel method can inspire and help evaluate new ideas in this field.
