Article
Computer Science, Interdisciplinary Applications
Detao Wang, Guoxiong Chen
Summary: Deep learning has greatly improved the processing and interpretation of seismic big data in oil and gas exploration. A novel scheme based on temporal convolution network (TCN) is proposed for intelligent seismic stratigraphic interpretation, which can accurately build a 3-D subsurface stratigraphic model using a small amount of well log labels or geological profiles. The proposed TCN algorithm outperforms traditional methods in terms of training time, model size, and prediction accuracy.
COMPUTERS & GEOSCIENCES
(2023)
Article
Engineering, Geological
Danqing Song, Xiaoli Liu, Jin Huang, Jianmin Zhang
Summary: An energy-based method for identifying the seismic failure mechanism of landslides with discontinuities was proposed and verified through experimental tests. The concentration of earthquake energy in low-frequency and high-frequency components, as well as the analysis of marginal spectrum, can help clarify the dynamic damage process of the slope.
Article
Optics
Zhang Zhang, Xinyue Guo, Maosheng Yang, Qili Yang, Xin Yan, Lanju Liang, Longhai Liu, Jianquan Yao
Summary: This article introduces a more comprehensive algorithm, continuous wavelet transform (CWT), for processing THz time-domain spectroscopy signals, achieving label-free recognition and concentration detection of biological cells, and revealing that the absorption of THz radiation by biological cells can be effectively controlled through the design of metasurfaces.
Article
Engineering, Electrical & Electronic
F. Villa-Gonzalez, R. Bhattacharyya, T. Athauda, S. E. Sarma, N. C. Karmakar
Summary: This article presents a low-cost and food-safe chipless RFID time-temperature sensor that operates in the 3-5 GHz UWB band. The sensor can detect three types of temperature exposure events in cold chain operations by analyzing the phase change of cooking oils. Logistic providers can use the data obtained from the sensor to infer temperature exposure at key steps in the cold chain. The article also discusses planned sensor improvements and future research directions.
IEEE SENSORS JOURNAL
(2022)
Article
Multidisciplinary Sciences
Kanchan Aggarwal, Siddhartha Mukhopadhya, Arun K. Tangirala
Summary: The proposed novel real-time automatic P-wave detector and picker in the prediction framework with a time-frequency localization feature enhances the effectiveness of P-wave onset detection, especially in low signal-to-noise ratio conditions. The method monitors the difference in squared magnitudes of predictions and measurements in the time-frequency bands with a statistically determined threshold, demonstrating significantly improved detection rate, accuracy, and robustness compared to existing methods.
Article
Geosciences, Multidisciplinary
Mahmoud Shirazi, Amin Roshandel Kahoo, Mohammad Radad, Gang Yu
Summary: The presence of natural gas reserves is often associated with the observation of a low-frequency shadow phenomenon in seismic signals. A high-resolution time-frequency transform called multi-synchrosqueezing transform (MSST) is introduced in this research to accurately recover the non-stationary signal and identify low-frequency shadows. Synthetic seismic data and real 3D seismic data from the North Sea were used to demonstrate the effectiveness of the proposed method in locating shallow gas reservoirs accurately.
NATURAL RESOURCES RESEARCH
(2023)
Article
Environmental Sciences
Laura Crocetti, Matthias Schartner, Benedikt Soja
Summary: This study investigates the use of machine learning algorithms to detect discontinuities caused by earthquakes in GNSS time series, and finds that Random Forest algorithm performs the best. Splitting the time series into chunks of 21 days, combining the components into one sample, and adding value range as an additional feature improve the detection results.
Article
Astronomy & Astrophysics
C. Munteanu, D. C. Turicu, O. Cret, M. Echim
Summary: Real-time analysis of variability in space data is crucial for scientists and space mission controllers. This paper presents the design and implementation of an automated system for detecting directional discontinuities in physical quantities using Field-Programmable Gate Array (FPGA). The system has been successfully applied to detect directional discontinuities in solar wind and terrestrial magnetosheath magnetic fields.
EARTH AND SPACE SCIENCE
(2022)
Article
Optics
Yanhao Chu, Xingjian Xiao, Xin Ye, Chen Chen, Shining Zhu, Tao Li
Summary: In this study, a design method is proposed to achieve large scale achromatic hybrid lens with no residual dispersion by considering the refraction element and metasurface together as a whole. The tradeoff between the meta-unit library and the characteristics of resulting hybrid lenses is also discussed in detail, and a centimeter scale achromatic hybrid lens is realized to demonstrate the effectiveness of the method.
Article
Computer Science, Information Systems
Pingping Bing, Wei Liu, Yang Liu
Summary: The proposed seismic time-frequency analysis method TSST, which reassigns time-frequency coefficients in the time direction rather than in the frequency direction, is more effective in extracting seismic time-frequency features and identifying thin layers compared to the traditional method FSST.
Article
Geochemistry & Geophysics
Xiaofeng Gu, Wenkai Lu, Yile Ao, Yinshuo Li, Cao Song
Summary: In this article, a deep active learning (AL)-based method is proposed to improve seismic stratigraphic interpretation by reducing labeling effort through prediction uncertainty. The uncertainty is easily obtained by measuring the similarity of predictions of adjacent seismic images. The method effectively improves the performance of the learned seismic interpretation network with limited labeled samples.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Multidisciplinary Sciences
Julian Karst, Moritz Floess, Monika Ubl, Carsten Dingler, Claudia Malacrida, Tobias Steinle, Sabine Ludwigs, Mario Hentschel, Harald Giessen
Summary: The study presents plasmonic nanoantennas made from metallic polymers and demonstrates an optically driven metal-to-insulator transition, enabling electrically switchable plasmonic resonances. Using this concept, electrically switchable beam-steering metasurfaces with high efficiency were successfully realized, showing potential for integrated active optical devices based on plasmonics.
Article
Chemistry, Multidisciplinary
Abd Al-Salam Al-Masgari, Mohamed Elsaadany, Abdul Halim Abdul Latiff, Maman Hermana, Umar Bin Hamzah, IsmailAlwali Babikir, Teslim Adeleke, Qazi Sohail Imran, Mohammed Ali Mohammed Al-Bared
Summary: This study focused on sequence stratigraphy and seismic facies in the Central Taranaki basin, identifying four regional seismic sequences and boundaries representing unconformities. Analysis indicated a new perspective surface between the upper and lower Giant formation due to seawater encroachment. The study proposed a new sequence stratigraphy framework and discussed potential hydrocarbon accumulations, suggesting the SA-Middle Giant Formation (SEQ3) as a potential trap.
APPLIED SCIENCES-BASEL
(2021)
Article
Geochemistry & Geophysics
Andrey Bakulin, Dmitry Neklyudov, Ilya Silvestrov
Summary: Seismic speckle noise is a major factor causing reflection distortions in seismic data, and traditional processing techniques struggle to handle multiplicative noise. Researchers have developed a time-frequency masking technique based on a mathematical model to suppress speckle noise, significantly improving the coherence and signal-to-noise ratio of seismic data, making it processable by conventional techniques subsequently.
Article
Multidisciplinary Sciences
Julian Karst, Yohan Lee, Moritz Floess, Monika Ubl, Sabine Ludwigs, Mario Hentschel, Harald Giessen
Summary: This study demonstrates electrically switchable metallic polymer metalenses, whose optical states and focal length can be adjusted via CMOS compatible voltages, opening up new possibilities for ultra-compact photonic integration.
NATURE COMMUNICATIONS
(2022)