Seismic data multi-domain processing method and device based on machine learning

The invention provides a seismic data multi-domain processing method and device based on machine learning. The seismic data multi-domain processing method based on machine learning comprises the steps of obtaining seismic data of a target work area; and according to a pre-generated machine learning...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: ZENG TONGSHENG, CUI DONG, SHOU HAO, CAO HONG
Format: Patent
Sprache:chi ; eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator ZENG TONGSHENG
CUI DONG
SHOU HAO
CAO HONG
description The invention provides a seismic data multi-domain processing method and device based on machine learning. The seismic data multi-domain processing method based on machine learning comprises the steps of obtaining seismic data of a target work area; and according to a pre-generated machine learning model and the seismic data, determining a feature domain range in a plurality of domains of the seismic data. According to the seismic data multi-domain processing method and device based on machine learning provided by the invention, the dimension range of the machine learning model during seismic data processing can be expanded, and the characteristics of the seismic data can be judged more comprehensively, so that the precision of processing the seismic data by using the machine learning is improved. 本发明提供了一种基于机器学习的地震数据多域处理方法及装置,基于机器学习的地震数据多域处理方法包括:获取目标工区的地震数据;根据预生成的机器学习模型以及所述地震数据,确定所述地震数据多个域中的特征域范围。本发明所提供的基于机器学习的地震数据多域处理方法及装置,可以拓展地震数据处理时机器学习模型的维度范围,更加综合的判断地震数据的特征,从而提高使用机器学习处理地震数据的精度。
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN113971415A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN113971415A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN113971415A3</originalsourceid><addsrcrecordid>eNqNyjEKAjEQBdA0FqLeYTzAFmEVsZRFsRJB-2VMvrsDySRsoufXwgNYvebNzfUGKVEcea5M8RWqND5FFqU8JYdSRAeKqGPyxOrJ4y0O9OACT0kpshtFQQE86fcuzezJoWD1c2HWp-O9OzfIqUfJ7KCofXextt3v7MZuD-0_5wN9KzcQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Seismic data multi-domain processing method and device based on machine learning</title><source>esp@cenet</source><creator>ZENG TONGSHENG ; CUI DONG ; SHOU HAO ; CAO HONG</creator><creatorcontrib>ZENG TONGSHENG ; CUI DONG ; SHOU HAO ; CAO HONG</creatorcontrib><description>The invention provides a seismic data multi-domain processing method and device based on machine learning. The seismic data multi-domain processing method based on machine learning comprises the steps of obtaining seismic data of a target work area; and according to a pre-generated machine learning model and the seismic data, determining a feature domain range in a plurality of domains of the seismic data. According to the seismic data multi-domain processing method and device based on machine learning provided by the invention, the dimension range of the machine learning model during seismic data processing can be expanded, and the characteristics of the seismic data can be judged more comprehensively, so that the precision of processing the seismic data by using the machine learning is improved. 本发明提供了一种基于机器学习的地震数据多域处理方法及装置,基于机器学习的地震数据多域处理方法包括:获取目标工区的地震数据;根据预生成的机器学习模型以及所述地震数据,确定所述地震数据多个域中的特征域范围。本发明所提供的基于机器学习的地震数据多域处理方法及装置,可以拓展地震数据处理时机器学习模型的维度范围,更加综合的判断地震数据的特征,从而提高使用机器学习处理地震数据的精度。</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DETECTING MASSES OR OBJECTS ; GEOPHYSICS ; GRAVITATIONAL MEASUREMENTS ; HANDLING RECORD CARRIERS ; MEASURING ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS ; TESTING</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20220125&amp;DB=EPODOC&amp;CC=CN&amp;NR=113971415A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20220125&amp;DB=EPODOC&amp;CC=CN&amp;NR=113971415A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>ZENG TONGSHENG</creatorcontrib><creatorcontrib>CUI DONG</creatorcontrib><creatorcontrib>SHOU HAO</creatorcontrib><creatorcontrib>CAO HONG</creatorcontrib><title>Seismic data multi-domain processing method and device based on machine learning</title><description>The invention provides a seismic data multi-domain processing method and device based on machine learning. The seismic data multi-domain processing method based on machine learning comprises the steps of obtaining seismic data of a target work area; and according to a pre-generated machine learning model and the seismic data, determining a feature domain range in a plurality of domains of the seismic data. According to the seismic data multi-domain processing method and device based on machine learning provided by the invention, the dimension range of the machine learning model during seismic data processing can be expanded, and the characteristics of the seismic data can be judged more comprehensively, so that the precision of processing the seismic data by using the machine learning is improved. 本发明提供了一种基于机器学习的地震数据多域处理方法及装置,基于机器学习的地震数据多域处理方法包括:获取目标工区的地震数据;根据预生成的机器学习模型以及所述地震数据,确定所述地震数据多个域中的特征域范围。本发明所提供的基于机器学习的地震数据多域处理方法及装置,可以拓展地震数据处理时机器学习模型的维度范围,更加综合的判断地震数据的特征,从而提高使用机器学习处理地震数据的精度。</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DETECTING MASSES OR OBJECTS</subject><subject>GEOPHYSICS</subject><subject>GRAVITATIONAL MEASUREMENTS</subject><subject>HANDLING RECORD CARRIERS</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyjEKAjEQBdA0FqLeYTzAFmEVsZRFsRJB-2VMvrsDySRsoufXwgNYvebNzfUGKVEcea5M8RWqND5FFqU8JYdSRAeKqGPyxOrJ4y0O9OACT0kpshtFQQE86fcuzezJoWD1c2HWp-O9OzfIqUfJ7KCofXextt3v7MZuD-0_5wN9KzcQ</recordid><startdate>20220125</startdate><enddate>20220125</enddate><creator>ZENG TONGSHENG</creator><creator>CUI DONG</creator><creator>SHOU HAO</creator><creator>CAO HONG</creator><scope>EVB</scope></search><sort><creationdate>20220125</creationdate><title>Seismic data multi-domain processing method and device based on machine learning</title><author>ZENG TONGSHENG ; CUI DONG ; SHOU HAO ; CAO HONG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN113971415A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DETECTING MASSES OR OBJECTS</topic><topic>GEOPHYSICS</topic><topic>GRAVITATIONAL MEASUREMENTS</topic><topic>HANDLING RECORD CARRIERS</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>ZENG TONGSHENG</creatorcontrib><creatorcontrib>CUI DONG</creatorcontrib><creatorcontrib>SHOU HAO</creatorcontrib><creatorcontrib>CAO HONG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ZENG TONGSHENG</au><au>CUI DONG</au><au>SHOU HAO</au><au>CAO HONG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Seismic data multi-domain processing method and device based on machine learning</title><date>2022-01-25</date><risdate>2022</risdate><abstract>The invention provides a seismic data multi-domain processing method and device based on machine learning. The seismic data multi-domain processing method based on machine learning comprises the steps of obtaining seismic data of a target work area; and according to a pre-generated machine learning model and the seismic data, determining a feature domain range in a plurality of domains of the seismic data. According to the seismic data multi-domain processing method and device based on machine learning provided by the invention, the dimension range of the machine learning model during seismic data processing can be expanded, and the characteristics of the seismic data can be judged more comprehensively, so that the precision of processing the seismic data by using the machine learning is improved. 本发明提供了一种基于机器学习的地震数据多域处理方法及装置,基于机器学习的地震数据多域处理方法包括:获取目标工区的地震数据;根据预生成的机器学习模型以及所述地震数据,确定所述地震数据多个域中的特征域范围。本发明所提供的基于机器学习的地震数据多域处理方法及装置,可以拓展地震数据处理时机器学习模型的维度范围,更加综合的判断地震数据的特征,从而提高使用机器学习处理地震数据的精度。</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN113971415A
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DETECTING MASSES OR OBJECTS
GEOPHYSICS
GRAVITATIONAL MEASUREMENTS
HANDLING RECORD CARRIERS
MEASURING
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
TESTING
title Seismic data multi-domain processing method and device based on machine learning
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T09%3A18%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=ZENG%20TONGSHENG&rft.date=2022-01-25&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN113971415A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true