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Automatic channel detection Using DNN on 2D Seismic Data

Computer Systems Science & Engineering 2021年第1期36卷 57-67页

作者： Fahd A.Alhaidari Saleh A.Al-Dossary Ilyas A.Salih Abdlrhman M.Salem Ahmed S.Bokir Mahmoud O.Fares Mohammed I.Ahmed Mohammed S.Ahmed Imam Abdulrahman Bin Faisal University College of Computer Science and Information TechnologyDammam34212Saudi Arabia Saudi Aramco Oil Company EXPEC-IIDhahranSaudi Arabia

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon *** are among the most important geological features interpreters analyze to locate petroleum ***,manual channel picking is both time consuming and ***,similar to any other process dependent on human intervention,manual channel picking is error prone and *** address these issues,automatic channel detection is both necessary and important for efficient and accurate seismic *** systems make use of real-time image processing techniques for different *** channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil *** this paper,we propose an innovative automatic channel detection algorithm based on machine learning *** new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation *** algorithm uses deep neural network to train the classifier with both the channel and non-channel *** provide a field data example to demonstrate the performance of the new *** training phase gave a maximum accuracy of 84.6%for the classifier and it performed even better in the testing phase,giving a maximum accuracy of 90%.

关键词： Deep neural networks deep learning channel detection image processing two-dimensional seismic data

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AN IMPROVED channel detection METHOD FOR IEEE 802.11N MIMO SYSTEM

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Journal of Electronics(China) 2011年第4期28卷 658-663页

作者： Yao Xiaocheng Jian Haifang Fang Zhi Shi Yin Institute of Semiconductors Chinese Academy of Science Beijing 100083 China

Coexistence and interoperability between 20 MHz and 40 MHz device and modes of op-erations are stressed in standard IEEE 802.11n *** is mandate to report the both sub-channels states to Medium Access Control(MAC) at receiver,since for 40 MHz device,it should serve not only 20 MHz but also 40 MHz signals *** energy detection and carrier sense are employed to detect channel *** the case of 20/40 M mode,the power difference between the two sub-channels is also detected in order to report the channel state *** simulation results demonstrate that the performance of the proposed methods are much better than the methods which just employ energy ***,the simulation results show that the proposed methods ensure that the channel sensing is not a roadblock of IEEE 802.11n system design.

关键词： MIMO-OFDM channel detection Carrier sense Energy detection

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A Novel channel Sensing Method for IEEE802.11n MIMO System

A Novel Channel Sensing Method for IEEE802.11n MIMO System

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2012年计算机应用与系统建模国际会议

作者： Yao Xiaocheng Fang Zhi Jian Haifang Shi Yin Institute of Semiconductors Chinese Academy of Science Department of Electronic Engineering Tsinghua University

Coexistence and interoperability between 20MHz and 40MHz device and modes of operation are addressed in standard IEEE802.11n system. It is mandate to give the channel state in receiving processing, since for 40MHz device and modes for it should not only fulfill the single 20MHz signal but also 40MHz signal receiver requirement. Both energy detection and carrier sense are employed to detecting channel state. In the case of 20/40M mode, the power difference between the two sub-channels is also detected in order to indicate the channel state accurately. The simulation results demonstrate that the performance of the proposed methods is much better than the methods which just taking the first step above.

关键词： MIMO-OFDM channel detection IEEE802.11n Carrier Sense Energy detection

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