Based on seismic attenuation theory in a fluid-filled porous medium, we improve conventional methods of low-frequency shadow analysis （LFSA） and energy absorption analysis （EAA） and propose a high-precision freque...Based on seismic attenuation theory in a fluid-filled porous medium, we improve conventional methods of low-frequency shadow analysis （LFSA） and energy absorption analysis （EAA） and propose a high-precision frequency attenuation analysis technology. First, we introduce the method of three-parameter wavelet transform and the time-frequency focused criterion and develop a high-precision time-frequency analysis method based on an adaptive three-parameter wavelet transform, which has high time-frequency resolution with benefit to LFSA and can obtain a single-peaked spectrum with narrow side-lobes with benefit to EAA. Second, we correctly compute absorption coefficient by curve fitting based on the nonlinear Nelder-Mead algorithm and effectively improve EAA precision. Practical application results show that the proposed frequency attenuation analysis technology integrated with LFSA and EAA can effectively predict favorable zones of carbonate oolitic reservoir. Furthermore, reservoir prediction results based on LFSA correspond with EAA. The new technology can effectively improve reservoir prediction reliability and reduce exploration risk.展开更多
This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the ps...This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.展开更多
The ocean’s thermal inertia is a major contributor to irreversible ocean changes exceeding time scales that matter to human society.This fact is a challenge to societies as they prepare for the consequences of climat...The ocean’s thermal inertia is a major contributor to irreversible ocean changes exceeding time scales that matter to human society.This fact is a challenge to societies as they prepare for the consequences of climate change,especially with respect to the ocean.Here the authors review the requirements for human actions from the ocean’s perspective.In the near term(∼2030),goals such as the United Nations Sustainable Development Goals(SDGs)will be critical.Over longer times(∼2050–2060 and beyond),global carbon neutrality targets may be met as countries continue to work toward reducing emissions.Both adaptation and mitigation plans need to be fully implemented in the interim,and the Global Ocean Observation System should be sustained so that changes can be continuously monitored.In the longer-term(after∼2060),slow emerging changes such as deep ocean warming and sea level rise are committed to continue even in the scenario where net zero emissions are reached.Thus,climate actions have to extend to time scales of hundreds of years.At these time scales,preparation for“high impact,low probability”risks—such as an abrupt showdown of Atlantic Meridional Overturning Circulation,ecosystem change,or irreversible ice sheet loss—should be fully integrated into long-term planning.展开更多
基金sponsored by the National Natural Science Foundation of China (Grant No.40904035)
文摘Based on seismic attenuation theory in a fluid-filled porous medium, we improve conventional methods of low-frequency shadow analysis （LFSA） and energy absorption analysis （EAA） and propose a high-precision frequency attenuation analysis technology. First, we introduce the method of three-parameter wavelet transform and the time-frequency focused criterion and develop a high-precision time-frequency analysis method based on an adaptive three-parameter wavelet transform, which has high time-frequency resolution with benefit to LFSA and can obtain a single-peaked spectrum with narrow side-lobes with benefit to EAA. Second, we correctly compute absorption coefficient by curve fitting based on the nonlinear Nelder-Mead algorithm and effectively improve EAA precision. Practical application results show that the proposed frequency attenuation analysis technology integrated with LFSA and EAA can effectively predict favorable zones of carbonate oolitic reservoir. Furthermore, reservoir prediction results based on LFSA correspond with EAA. The new technology can effectively improve reservoir prediction reliability and reduce exploration risk.
基金partially supported by the National Natural Science Foundation of China (Nos.11590772, 11590770)the Pre-research Project for Equipment of General Information System (No.JZX2017-0994/Y306)
文摘This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.
基金L.Cheng acknowledges financial supports from the Strategic Priority Research Program of the Chinese Academy of Sciences[grant munber XDB42040402]the National Natural Science Foundation of China[grant numbers 42122046 and 42076202]The National Center for Atmospheric Research is sponsored by the National Science Foundation.
文摘The ocean’s thermal inertia is a major contributor to irreversible ocean changes exceeding time scales that matter to human society.This fact is a challenge to societies as they prepare for the consequences of climate change,especially with respect to the ocean.Here the authors review the requirements for human actions from the ocean’s perspective.In the near term(∼2030),goals such as the United Nations Sustainable Development Goals(SDGs)will be critical.Over longer times(∼2050–2060 and beyond),global carbon neutrality targets may be met as countries continue to work toward reducing emissions.Both adaptation and mitigation plans need to be fully implemented in the interim,and the Global Ocean Observation System should be sustained so that changes can be continuously monitored.In the longer-term(after∼2060),slow emerging changes such as deep ocean warming and sea level rise are committed to continue even in the scenario where net zero emissions are reached.Thus,climate actions have to extend to time scales of hundreds of years.At these time scales,preparation for“high impact,low probability”risks—such as an abrupt showdown of Atlantic Meridional Overturning Circulation,ecosystem change,or irreversible ice sheet loss—should be fully integrated into long-term planning.
