Data‐driven time–frequency analysis of seismic data using non‐stationary Prony method

ABSTRACT Empirical mode decomposition aims to decompose the input signal into a small number of components named intrinsic mode functions with slowly varying amplitudes and frequencies. In spite of its simplicity and usefulness, however, empirical mode decomposition lacks solid mathematical foundati...

Full description

Saved in:
Bibliographic Details
Published in:Geophysical Prospecting 2018-01, Vol.66 (1), p.85-97
Main Authors: Wu, Guoning, Fomel, Sergey, Chen, Yangkang
Format: Article
Language:English
Subjects:
Bandwidths
Data analysis
Decomposition
Empirical analysis
Frequency analysis
Functions (mathematics)
Hilbert transform
Hilbert transformation
intrinsic mode function
non‐stationary Prony method
Philosophy
Prony's method
Seismic analysis
Seismic data
Time-frequency analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-a3790-8a6a7b930a33b6a5c023de7e77cf0c3d8c2abb27b61227a6525b7c953d5d1ffd3
cites cdi_FETCH-LOGICAL-a3790-8a6a7b930a33b6a5c023de7e77cf0c3d8c2abb27b61227a6525b7c953d5d1ffd3
container_end_page 97
container_issue 1
container_start_page 85
container_title Geophysical Prospecting
container_volume 66
creator Wu, Guoning
Fomel, Sergey
Chen, Yangkang
description ABSTRACT Empirical mode decomposition aims to decompose the input signal into a small number of components named intrinsic mode functions with slowly varying amplitudes and frequencies. In spite of its simplicity and usefulness, however, empirical mode decomposition lacks solid mathematical foundation. In this paper, we describe a method to extract the intrinsic mode functions of the input signal using non‐stationary Prony method. The proposed method captures the philosophy of the empirical mode decomposition but uses a different method to compute the intrinsic mode functions. Having the intrinsic mode functions obtained, we then compute the spectrum of the input signal using Hilbert transform. Synthetic and field data validate that the proposed method can correctly compute the spectrum of the input signal and could be used in seismic data analysis to facilitate interpretation.
doi_str_mv 10.1111/1365-2478.12530
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1978213963</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1978213963</sourcerecordid><originalsourceid>FETCH-LOGICAL-a3790-8a6a7b930a33b6a5c023de7e77cf0c3d8c2abb27b61227a6525b7c953d5d1ffd3</originalsourceid><addsrcrecordid>eNqFkM1KAzEURoMoWKtrtwHX0-anmcwspWoVChbRlYuQSTKa0klqMlVm10cQfMM-iakjbr2bC5fvXD4OAOcYjXCaMaY5y8iEFyNMGEUHYPB3OQQDhHCeFYiwY3AS4xIhihibDMDzlWzlbvupg303Dra2MbvtVx3M28Y41UHp5KqLNkJfw2hsbKyCOiFwE617gc67BMdWttY7GTq4CN51sDHtq9en4KiWq2jOfvcQPN1cP05vs_n97G56Oc8k5SXKCplLXpUUSUqrXDKFCNWGG85VjRTVhSKyqgivckwIlzkjrOKqZFQzjeta0yG46P-ug0-1YyuWfhNS8ShwyQuCaZnTlBr3KRV8jMHUYh1skzoLjMTeoNj7Entf4sdgIlhPfNiV6f6Li9nioee-AVt8doo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1978213963</pqid></control><display><type>article</type><title>Data‐driven time–frequency analysis of seismic data using non‐stationary Prony method</title><source>Wiley</source><creator>Wu, Guoning ; Fomel, Sergey ; Chen, Yangkang</creator><creatorcontrib>Wu, Guoning ; Fomel, Sergey ; Chen, Yangkang</creatorcontrib><description>ABSTRACT Empirical mode decomposition aims to decompose the input signal into a small number of components named intrinsic mode functions with slowly varying amplitudes and frequencies. In spite of its simplicity and usefulness, however, empirical mode decomposition lacks solid mathematical foundation. In this paper, we describe a method to extract the intrinsic mode functions of the input signal using non‐stationary Prony method. The proposed method captures the philosophy of the empirical mode decomposition but uses a different method to compute the intrinsic mode functions. Having the intrinsic mode functions obtained, we then compute the spectrum of the input signal using Hilbert transform. Synthetic and field data validate that the proposed method can correctly compute the spectrum of the input signal and could be used in seismic data analysis to facilitate interpretation.</description><identifier>ISSN: 0016-8025</identifier><identifier>EISSN: 1365-2478</identifier><identifier>DOI: 10.1111/1365-2478.12530</identifier><language>eng</language><publisher>Houten: Wiley Subscription Services, Inc</publisher><subject>Bandwidths ; Data analysis ; Decomposition ; Empirical analysis ; Frequency analysis ; Functions (mathematics) ; Hilbert transform ; Hilbert transformation ; intrinsic mode function ; non‐stationary Prony method ; Philosophy ; Prony's method ; Seismic analysis ; Seismic data ; Time-frequency analysis</subject><ispartof>Geophysical Prospecting, 2018-01, Vol.66 (1), p.85-97</ispartof><rights>2017 European Association of Geoscientists &amp; Engineers</rights><rights>2018 European Association of Geoscientists &amp; Engineers</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3790-8a6a7b930a33b6a5c023de7e77cf0c3d8c2abb27b61227a6525b7c953d5d1ffd3</citedby><cites>FETCH-LOGICAL-a3790-8a6a7b930a33b6a5c023de7e77cf0c3d8c2abb27b61227a6525b7c953d5d1ffd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Wu, Guoning</creatorcontrib><creatorcontrib>Fomel, Sergey</creatorcontrib><creatorcontrib>Chen, Yangkang</creatorcontrib><title>Data‐driven time–frequency analysis of seismic data using non‐stationary Prony method</title><title>Geophysical Prospecting</title><description>ABSTRACT Empirical mode decomposition aims to decompose the input signal into a small number of components named intrinsic mode functions with slowly varying amplitudes and frequencies. In spite of its simplicity and usefulness, however, empirical mode decomposition lacks solid mathematical foundation. In this paper, we describe a method to extract the intrinsic mode functions of the input signal using non‐stationary Prony method. The proposed method captures the philosophy of the empirical mode decomposition but uses a different method to compute the intrinsic mode functions. Having the intrinsic mode functions obtained, we then compute the spectrum of the input signal using Hilbert transform. Synthetic and field data validate that the proposed method can correctly compute the spectrum of the input signal and could be used in seismic data analysis to facilitate interpretation.</description><subject>Bandwidths</subject><subject>Data analysis</subject><subject>Decomposition</subject><subject>Empirical analysis</subject><subject>Frequency analysis</subject><subject>Functions (mathematics)</subject><subject>Hilbert transform</subject><subject>Hilbert transformation</subject><subject>intrinsic mode function</subject><subject>non‐stationary Prony method</subject><subject>Philosophy</subject><subject>Prony's method</subject><subject>Seismic analysis</subject><subject>Seismic data</subject><subject>Time-frequency analysis</subject><issn>0016-8025</issn><issn>1365-2478</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFkM1KAzEURoMoWKtrtwHX0-anmcwspWoVChbRlYuQSTKa0klqMlVm10cQfMM-iakjbr2bC5fvXD4OAOcYjXCaMaY5y8iEFyNMGEUHYPB3OQQDhHCeFYiwY3AS4xIhihibDMDzlWzlbvupg303Dra2MbvtVx3M28Y41UHp5KqLNkJfw2hsbKyCOiFwE617gc67BMdWttY7GTq4CN51sDHtq9en4KiWq2jOfvcQPN1cP05vs_n97G56Oc8k5SXKCplLXpUUSUqrXDKFCNWGG85VjRTVhSKyqgivckwIlzkjrOKqZFQzjeta0yG46P-ug0-1YyuWfhNS8ShwyQuCaZnTlBr3KRV8jMHUYh1skzoLjMTeoNj7Entf4sdgIlhPfNiV6f6Li9nioee-AVt8doo</recordid><startdate>201801</startdate><enddate>201801</enddate><creator>Wu, Guoning</creator><creator>Fomel, Sergey</creator><creator>Chen, Yangkang</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope></search><sort><creationdate>201801</creationdate><title>Data‐driven time–frequency analysis of seismic data using non‐stationary Prony method</title><author>Wu, Guoning ; Fomel, Sergey ; Chen, Yangkang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3790-8a6a7b930a33b6a5c023de7e77cf0c3d8c2abb27b61227a6525b7c953d5d1ffd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Bandwidths</topic><topic>Data analysis</topic><topic>Decomposition</topic><topic>Empirical analysis</topic><topic>Frequency analysis</topic><topic>Functions (mathematics)</topic><topic>Hilbert transform</topic><topic>Hilbert transformation</topic><topic>intrinsic mode function</topic><topic>non‐stationary Prony method</topic><topic>Philosophy</topic><topic>Prony's method</topic><topic>Seismic analysis</topic><topic>Seismic data</topic><topic>Time-frequency analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Guoning</creatorcontrib><creatorcontrib>Fomel, Sergey</creatorcontrib><creatorcontrib>Chen, Yangkang</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><jtitle>Geophysical Prospecting</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Guoning</au><au>Fomel, Sergey</au><au>Chen, Yangkang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data‐driven time–frequency analysis of seismic data using non‐stationary Prony method</atitle><jtitle>Geophysical Prospecting</jtitle><date>2018-01</date><risdate>2018</risdate><volume>66</volume><issue>1</issue><spage>85</spage><epage>97</epage><pages>85-97</pages><issn>0016-8025</issn><eissn>1365-2478</eissn><abstract>ABSTRACT Empirical mode decomposition aims to decompose the input signal into a small number of components named intrinsic mode functions with slowly varying amplitudes and frequencies. In spite of its simplicity and usefulness, however, empirical mode decomposition lacks solid mathematical foundation. In this paper, we describe a method to extract the intrinsic mode functions of the input signal using non‐stationary Prony method. The proposed method captures the philosophy of the empirical mode decomposition but uses a different method to compute the intrinsic mode functions. Having the intrinsic mode functions obtained, we then compute the spectrum of the input signal using Hilbert transform. Synthetic and field data validate that the proposed method can correctly compute the spectrum of the input signal and could be used in seismic data analysis to facilitate interpretation.</abstract><cop>Houten</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/1365-2478.12530</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0016-8025
ispartof Geophysical Prospecting, 2018-01, Vol.66 (1), p.85-97
issn 0016-8025
1365-2478
language eng
recordid cdi_proquest_journals_1978213963
source Wiley
subjects Bandwidths
Data analysis
Decomposition
Empirical analysis
Frequency analysis
Functions (mathematics)
Hilbert transform
Hilbert transformation
intrinsic mode function
non‐stationary Prony method
Philosophy
Prony's method
Seismic analysis
Seismic data
Time-frequency analysis
title Data‐driven time–frequency analysis of seismic data using non‐stationary Prony method
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-21T02%3A23%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Data%E2%80%90driven%20time%E2%80%93frequency%20analysis%20of%20seismic%20data%20using%20non%E2%80%90stationary%20Prony%20method&rft.jtitle=Geophysical%20Prospecting&rft.au=Wu,%20Guoning&rft.date=2018-01&rft.volume=66&rft.issue=1&rft.spage=85&rft.epage=97&rft.pages=85-97&rft.issn=0016-8025&rft.eissn=1365-2478&rft_id=info:doi/10.1111/1365-2478.12530&rft_dat=%3Cproquest_cross%3E1978213963%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a3790-8a6a7b930a33b6a5c023de7e77cf0c3d8c2abb27b61227a6525b7c953d5d1ffd3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1978213963&rft_id=info:pmid/&rfr_iscdi=true