Geostatistical facies simulation with geometric patterns of a petroleum reservoir
During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple...
Gespeichert in:
Veröffentlicht in: | Stochastic environmental research and risk assessment 2017-09, Vol.31 (7), p.1805-1822 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1822 |
---|---|
container_issue | 7 |
container_start_page | 1805 |
container_title | Stochastic environmental research and risk assessment |
container_volume | 31 |
creator | de Carvalho, Paulo Roberto Moura da Costa, João Felipe Coimbra Leite Rasera, Luiz Gustavo Varella, Luiz Eduardo Seabra |
description | During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations. |
doi_str_mv | 10.1007/s00477-016-1243-5 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1948056770</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1948056770</sourcerecordid><originalsourceid>FETCH-LOGICAL-c316t-a88e0b47c6ee53c378cf5f63685181de91caaaf7b992652292266981d39245a23</originalsourceid><addsrcrecordid>eNp1kE9LxDAQxYMouKz7AbwFPFfzp0maoyy6Cgsi6Dlk43SNtE1NUsVvb5aKePE0w5v33sAPoXNKLikh6ioRUitVESorympeiSO0oDWXFWdCH__uNTlFq5T8rmQE15qSBXrcQEjZZp-yd7bDrXUeEk6-n7qihgF_-vyK9xB6yNE7PNqcIQ4JhxZbPBYxdDD1OEKC-BF8PEMnre0SrH7mEj3f3jyt76rtw-Z-fb2tHKcyV7ZpgOxq5SSA4I6rxrWilVw2gjb0BTR11tpW7bRmUjCmGZNSlwvXrBaW8SW6mHvHGN4nSNm8hSkO5aWhum6IkEqR4qKzy8WQUoTWjNH3Nn4ZSswBnpnhmQLPHOAZUTJszqTiHfYQ_zT_G_oGcohx6A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1948056770</pqid></control><display><type>article</type><title>Geostatistical facies simulation with geometric patterns of a petroleum reservoir</title><source>Springer Journals</source><creator>de Carvalho, Paulo Roberto Moura ; da Costa, João Felipe Coimbra Leite ; Rasera, Luiz Gustavo ; Varella, Luiz Eduardo Seabra</creator><creatorcontrib>de Carvalho, Paulo Roberto Moura ; da Costa, João Felipe Coimbra Leite ; Rasera, Luiz Gustavo ; Varella, Luiz Eduardo Seabra</creatorcontrib><description>During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.</description><identifier>ISSN: 1436-3240</identifier><identifier>EISSN: 1436-3259</identifier><identifier>DOI: 10.1007/s00477-016-1243-5</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aquatic Pollution ; Chemistry and Earth Sciences ; Computational Intelligence ; Computer Science ; Computer simulation ; Corridors ; Decision analysis ; Decision making ; Earth and Environmental Science ; Earth Sciences ; Environment ; Feasibility studies ; Geostatistics ; Math. Appl. in Environmental Science ; Oil exploration ; Original Paper ; Petroleum ; Physics ; Probability Theory and Stochastic Processes ; Reservoirs ; Service life assessment ; Shale ; Simulation ; Statistics for Engineering ; Waste Water Technology ; Water Management ; Water Pollution Control ; Workflow</subject><ispartof>Stochastic environmental research and risk assessment, 2017-09, Vol.31 (7), p.1805-1822</ispartof><rights>Springer-Verlag Berlin Heidelberg 2016</rights><rights>Stochastic Environmental Research and Risk Assessment is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-a88e0b47c6ee53c378cf5f63685181de91caaaf7b992652292266981d39245a23</citedby><cites>FETCH-LOGICAL-c316t-a88e0b47c6ee53c378cf5f63685181de91caaaf7b992652292266981d39245a23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00477-016-1243-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00477-016-1243-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27926,27927,41490,42559,51321</link.rule.ids></links><search><creatorcontrib>de Carvalho, Paulo Roberto Moura</creatorcontrib><creatorcontrib>da Costa, João Felipe Coimbra Leite</creatorcontrib><creatorcontrib>Rasera, Luiz Gustavo</creatorcontrib><creatorcontrib>Varella, Luiz Eduardo Seabra</creatorcontrib><title>Geostatistical facies simulation with geometric patterns of a petroleum reservoir</title><title>Stochastic environmental research and risk assessment</title><addtitle>Stoch Environ Res Risk Assess</addtitle><description>During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.</description><subject>Aquatic Pollution</subject><subject>Chemistry and Earth Sciences</subject><subject>Computational Intelligence</subject><subject>Computer Science</subject><subject>Computer simulation</subject><subject>Corridors</subject><subject>Decision analysis</subject><subject>Decision making</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environment</subject><subject>Feasibility studies</subject><subject>Geostatistics</subject><subject>Math. Appl. in Environmental Science</subject><subject>Oil exploration</subject><subject>Original Paper</subject><subject>Petroleum</subject><subject>Physics</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Reservoirs</subject><subject>Service life assessment</subject><subject>Shale</subject><subject>Simulation</subject><subject>Statistics for Engineering</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><subject>Workflow</subject><issn>1436-3240</issn><issn>1436-3259</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kE9LxDAQxYMouKz7AbwFPFfzp0maoyy6Cgsi6Dlk43SNtE1NUsVvb5aKePE0w5v33sAPoXNKLikh6ioRUitVESorympeiSO0oDWXFWdCH__uNTlFq5T8rmQE15qSBXrcQEjZZp-yd7bDrXUeEk6-n7qihgF_-vyK9xB6yNE7PNqcIQ4JhxZbPBYxdDD1OEKC-BF8PEMnre0SrH7mEj3f3jyt76rtw-Z-fb2tHKcyV7ZpgOxq5SSA4I6rxrWilVw2gjb0BTR11tpW7bRmUjCmGZNSlwvXrBaW8SW6mHvHGN4nSNm8hSkO5aWhum6IkEqR4qKzy8WQUoTWjNH3Nn4ZSswBnpnhmQLPHOAZUTJszqTiHfYQ_zT_G_oGcohx6A</recordid><startdate>20170901</startdate><enddate>20170901</enddate><creator>de Carvalho, Paulo Roberto Moura</creator><creator>da Costa, João Felipe Coimbra Leite</creator><creator>Rasera, Luiz Gustavo</creator><creator>Varella, Luiz Eduardo Seabra</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7XB</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L6V</scope><scope>M2P</scope><scope>M7S</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0W</scope><scope>SOI</scope></search><sort><creationdate>20170901</creationdate><title>Geostatistical facies simulation with geometric patterns of a petroleum reservoir</title><author>de Carvalho, Paulo Roberto Moura ; da Costa, João Felipe Coimbra Leite ; Rasera, Luiz Gustavo ; Varella, Luiz Eduardo Seabra</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-a88e0b47c6ee53c378cf5f63685181de91caaaf7b992652292266981d39245a23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Aquatic Pollution</topic><topic>Chemistry and Earth Sciences</topic><topic>Computational Intelligence</topic><topic>Computer Science</topic><topic>Computer simulation</topic><topic>Corridors</topic><topic>Decision analysis</topic><topic>Decision making</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Environment</topic><topic>Feasibility studies</topic><topic>Geostatistics</topic><topic>Math. Appl. in Environmental Science</topic><topic>Oil exploration</topic><topic>Original Paper</topic><topic>Petroleum</topic><topic>Physics</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Reservoirs</topic><topic>Service life assessment</topic><topic>Shale</topic><topic>Simulation</topic><topic>Statistics for Engineering</topic><topic>Waste Water Technology</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><topic>Workflow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Carvalho, Paulo Roberto Moura</creatorcontrib><creatorcontrib>da Costa, João Felipe Coimbra Leite</creatorcontrib><creatorcontrib>Rasera, Luiz Gustavo</creatorcontrib><creatorcontrib>Varella, Luiz Eduardo Seabra</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Science Journals</collection><collection>Engineering Database</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering & Technology Collection</collection><collection>Environment Abstracts</collection><jtitle>Stochastic environmental research and risk assessment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Carvalho, Paulo Roberto Moura</au><au>da Costa, João Felipe Coimbra Leite</au><au>Rasera, Luiz Gustavo</au><au>Varella, Luiz Eduardo Seabra</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geostatistical facies simulation with geometric patterns of a petroleum reservoir</atitle><jtitle>Stochastic environmental research and risk assessment</jtitle><stitle>Stoch Environ Res Risk Assess</stitle><date>2017-09-01</date><risdate>2017</risdate><volume>31</volume><issue>7</issue><spage>1805</spage><epage>1822</epage><pages>1805-1822</pages><issn>1436-3240</issn><eissn>1436-3259</eissn><abstract>During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00477-016-1243-5</doi><tpages>18</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1436-3240 |
ispartof | Stochastic environmental research and risk assessment, 2017-09, Vol.31 (7), p.1805-1822 |
issn | 1436-3240 1436-3259 |
language | eng |
recordid | cdi_proquest_journals_1948056770 |
source | Springer Journals |
subjects | Aquatic Pollution Chemistry and Earth Sciences Computational Intelligence Computer Science Computer simulation Corridors Decision analysis Decision making Earth and Environmental Science Earth Sciences Environment Feasibility studies Geostatistics Math. Appl. in Environmental Science Oil exploration Original Paper Petroleum Physics Probability Theory and Stochastic Processes Reservoirs Service life assessment Shale Simulation Statistics for Engineering Waste Water Technology Water Management Water Pollution Control Workflow |
title | Geostatistical facies simulation with geometric patterns of a petroleum reservoir |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-17T18%3A22%3A13IST&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=Geostatistical%20facies%20simulation%20with%20geometric%20patterns%20of%20a%20petroleum%20reservoir&rft.jtitle=Stochastic%20environmental%20research%20and%20risk%20assessment&rft.au=de%20Carvalho,%20Paulo%20Roberto%20Moura&rft.date=2017-09-01&rft.volume=31&rft.issue=7&rft.spage=1805&rft.epage=1822&rft.pages=1805-1822&rft.issn=1436-3240&rft.eissn=1436-3259&rft_id=info:doi/10.1007/s00477-016-1243-5&rft_dat=%3Cproquest_cross%3E1948056770%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1948056770&rft_id=info:pmid/&rfr_iscdi=true |