Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province

This paper deals with the study of multi-channel adaptive noise cancellation with a focus on its application in electromagnetic (EM) telemetry. We presented new variable step-size least mean square (LMS) techniques: regularized variable step-size LMS and regularized sigmoid variable size LMS, for el...

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Main Authors: Olalekan Fayemi, Qingyun Di, Qihui Zhen, Yu L. Wang
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/13/22/5873
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spelling doaj-394a1766c08d4f5db4427a4f573586f12020-11-25T04:02:17ZengMDPI AGEnergies1996-10732020-11-01135873587310.3390/en13225873Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan ProvinceOlalekan Fayemi0Qingyun Di1Qihui Zhen2Yu L. Wang3Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, ChinaKey Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, ChinaKey Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, ChinaKey Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, ChinaThis paper deals with the study of multi-channel adaptive noise cancellation with a focus on its application in electromagnetic (EM) telemetry. We presented new variable step-size least mean square (LMS) techniques: regularized variable step-size LMS and regularized sigmoid variable size LMS, for electromagnetic telemetry data processing. Considering the complexity and spatial distribution of environmental noise, algorithms with multiple reference signals were used to retrieve transmitted EM signals. The feasibility of the regularized variable step size LMS algorithms with numerical simulation was analyzed and presented. The adaptive processing techniques were applied in the recovery of frequency and binary phase shift key modulated signal. The proposed multi-channel adaptive technique achieves fast convergence speed, low mean squared error and is shown to have good convergence characteristics compared to conventional methods. In addition to attaining good results from the multi-channel adaptive filter and performing the signal analysis in real-time, we implemented combined fast effective impulse noise removal techniques. The combination of median and mean filters was effective in removing a wide range of impulsive noises without distorting any other data points. Further, electromagnetic telemetry data were acquired during a drilling operation in Sichuan province, China, for real field application. Data processing workflow was designed for EM telemetry data processing based on the noise characteristics, simulation results and expected result for demodulation. To establish a comprehensive overview, a performance comparison of the acquisition array system is also provided. Conclusively, the introduced multichannel adaptive noise canceling techniques are very effective in recovering transmitted EM telemetry signals.https://www.mdpi.com/1996-1073/13/22/5873adaptive filteringcomplex noise cancelingelectromagnetic telemetry
collection DOAJ
language English
format Article
sources DOAJ
author Olalekan Fayemi
Qingyun Di
Qihui Zhen
Yu L. Wang
spellingShingle Olalekan Fayemi
Qingyun Di
Qihui Zhen
Yu L. Wang
Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province
Energies
adaptive filtering
complex noise canceling
electromagnetic telemetry
author_facet Olalekan Fayemi
Qingyun Di
Qihui Zhen
Yu L. Wang
author_sort Olalekan Fayemi
title Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province
title_short Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province
title_full Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province
title_fullStr Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province
title_full_unstemmed Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province
title_sort adaptive processing for em telemetry signal recovery: field data from sichuan province
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-11-01
description This paper deals with the study of multi-channel adaptive noise cancellation with a focus on its application in electromagnetic (EM) telemetry. We presented new variable step-size least mean square (LMS) techniques: regularized variable step-size LMS and regularized sigmoid variable size LMS, for electromagnetic telemetry data processing. Considering the complexity and spatial distribution of environmental noise, algorithms with multiple reference signals were used to retrieve transmitted EM signals. The feasibility of the regularized variable step size LMS algorithms with numerical simulation was analyzed and presented. The adaptive processing techniques were applied in the recovery of frequency and binary phase shift key modulated signal. The proposed multi-channel adaptive technique achieves fast convergence speed, low mean squared error and is shown to have good convergence characteristics compared to conventional methods. In addition to attaining good results from the multi-channel adaptive filter and performing the signal analysis in real-time, we implemented combined fast effective impulse noise removal techniques. The combination of median and mean filters was effective in removing a wide range of impulsive noises without distorting any other data points. Further, electromagnetic telemetry data were acquired during a drilling operation in Sichuan province, China, for real field application. Data processing workflow was designed for EM telemetry data processing based on the noise characteristics, simulation results and expected result for demodulation. To establish a comprehensive overview, a performance comparison of the acquisition array system is also provided. Conclusively, the introduced multichannel adaptive noise canceling techniques are very effective in recovering transmitted EM telemetry signals.
topic adaptive filtering
complex noise canceling
electromagnetic telemetry
url https://www.mdpi.com/1996-1073/13/22/5873
work_keys_str_mv AT olalekanfayemi adaptiveprocessingforemtelemetrysignalrecoveryfielddatafromsichuanprovince
AT qingyundi adaptiveprocessingforemtelemetrysignalrecoveryfielddatafromsichuanprovince
AT qihuizhen adaptiveprocessingforemtelemetrysignalrecoveryfielddatafromsichuanprovince
AT yulwang adaptiveprocessingforemtelemetrysignalrecoveryfielddatafromsichuanprovince
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