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dc.contributor.authorZhang, Yanhui
dc.contributor.authorVossepoel, Femke C.
dc.contributor.authorHoteit, Ibrahim
dc.date.accessioned2021-07-12T13:37:47Z
dc.date.available2021-07-12T13:37:47Z
dc.date.issued2020
dc.identifier.issn1930-0220
dc.identifier.issn1086-055X
dc.identifier.urihttp://hdl.handle.net/10754/670158
dc.description.abstractAn ensemble-based history-matching framework is proposed to enhance the characterization of petroleum reservoirs through the assimilation of crosswell electromagnetic (EM) data. As an advanced technology in reservoir surveillance, crosswell EM tomography can be used to estimate a cross-sectional conductivity map and associated saturation profile at an interwell scale by exploiting the sharp contrast in conductivity between hydrocarbons and saline water. Incorporating this information into reservoir simulation in combination with other available observations is expected to enhance the forecasting capability of reservoir models and to lead to better quantification of uncertainty.
dc.description.sponsorshipSupport for authors Yanhui Zhang and Ibrahim Hoteit is provided by the research project “Efficient Integration of Electromagnetic Tomography into Reservoir History Matching,” which is funded by Saudi Aramco. The authors also thank Wim Mulder and Marwan Wirianto for providing the multigrid EM forward solver that formed the basis for our inversion.
dc.relation.urlhttps://watermark.silverchair.com/spe-193808-pa.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAuMwggLfBgkqhkiG9w0BBwagggLQMIICzAIBADCCAsUGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMPc6Ngtij3nkwDTnJAgEQgIIClh-iXG7ihOL7LSJ6rWMbXHyXv_RV6sY5w0RRJ0mskOGdilJLx_byezIH5n8AuZh3cPPCP0IrJUQH05cg_8AOvZ9OHmZrBUjeWNZo7QjVJBN6i37ujIUGe6SwekzM0Vg1lZLwgAbwtfbFMKoFsRFEjdkcESRnkakZK8tZXwKjMaNXEYzIZNSdpnMJQan5j6Oqakugq3G4_IKxQj5Ihj1QLWbFuKW-wFE6nPBoPb3yaghz5vuSHZTWU8G7u1WnODfEF-8HgcesctdRJfIiinmO3J4tb4KCOnXQjjq4sjr7E3BQMciQ-ZFijrXt5UX6N4USVKbE1Ue8jXxAOMcfLUivU58W5ARmvR8Q_NH0N9WZLYfLZCWmSxaNVepnaz3xpcCsgnk-P1AU7i5sGLsUipeiWbrSfzTYnVYlsZ3bfny9MLOqQzryWTHdRCn93-iSrgYALosUGXbAXqpYFdHbEdrIq4qDQ4k7nEuel1dKOFAlQK3g1oeU7MDXZZSgsqVo5DQKPwwkTQJQMaBTE-ynueyUzEERn1DStwNL-kaVqSHAyswuHz7_dgyw6yn1LYeaw7sMdJXsfOHcOzZ7oLR1MYd267JcSjkf6oREKBVgGBc7s0ZUUSzbsR4Y3p5JTFt6Ms2BSbX0KBZgYtjVYWMwprfpHO659HitFaerKG-e7fecrZLYee9i4s6I2O1uXYCXUq5Y6hHPpm15_Kbv98iYwSZRWHXcH8tDF4EEuoCyKAoJv0SuXPdDoAxe7QxdLoBhRdMWFo1HVIBpXP4lMOOIG95rknfL7YJ0hgddI0VjsL8UAesJ2SsdPVZF-DL4domkhSJyPsXENtdGezuCJwuNDQt5eJAvvub9E29AIAn0x_x0DeKf3mPSsy8n
dc.rightsArchived with thanks to SPE JOURNAL
dc.titleEfficient Assimilation of Crosswell Electromagnetic Data Using an Ensemble-Based History-Matching Framework
dc.typeArticle
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.contributor.departmentEarth Science and Engineering Program
dc.identifier.journalSPE JOURNAL
dc.identifier.wosutWOS:000576059800006
dc.eprint.versionPost-print
dc.contributor.institutionDelft University of Technology
dc.identifier.volume25
dc.identifier.issue1
dc.identifier.pages119-138
kaust.personZhang, Yanhui
kaust.personHoteit, Ibrahim


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