EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

Handle URI:
http://hdl.handle.net/10754/563782
Title:
EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs
Authors:
Katterbauer, Klemens; Hoteit, Ibrahim ( 0000-0002-3751-4393 ) ; Sun, Shuyu ( 0000-0002-3078-864X )
Abstract:
New developments of electromagnetic and seismic techniques have recently revolutionized the oil and gas industry. Time-lapse seismic data is providing engineers with tools to more accurately track the dynamics of multi-phase reservoir fluid flows. With the challenges faced in distinguishing between hydrocarbons and water via seismic methods, the industry has been looking at electromagnetic techniques in order to exploit the strong contrast in conductivity between hydrocarbons and water. Incorporating this information into reservoir simulation is expected to considerably enhance the forecasting of the reservoir, hence optimizing production and reducing costs. Conventional approaches typically invert the seismic and electromagnetic data in order to transform them into production parameters, before incorporating them as constraints in the history matching process and reservoir simulations. This makes automatization difficult and computationally expensive due to the necessity of manual processing, besides the potential artifacts. Here we introduce a new approach to incorporate seismic and electromagnetic data attributes directly into the history matching process. To avoid solving inverse problems and exploit information in the dynamics of the flow, we exploit petrophysical transformations to simultaneously incorporate time lapse seismic and electromagnetic data attributes using different ensemble Kalman-based history matching techniques. Our simulation results show enhanced predictability of the critical reservoir parameters and reduce uncertainties in model simulations, outperforming with only production data or the inclusion of either seismic or electromagnetic data. A statistical test is performed to confirm the significance of the results. © 2014 Elsevier B.V. All rights reserved.
KAUST Department:
Earth Science and Engineering Program; Physical Sciences and Engineering (PSE) Division; Environmental Science and Engineering Program; Earth Fluid Modeling and Prediction Group; Computational Transport Phenomena Lab
Publisher:
Elsevier BV
Journal:
Journal of Petroleum Science and Engineering
Issue Date:
Oct-2014
DOI:
10.1016/j.petrol.2014.07.039
Type:
Article
ISSN:
09204105
Sponsors:
We acknowledge the support of Olwijn Leeuwenburgh and Fabio Ravanelli in stimulating the idea for the integration of the history matching methods into the MRST Sintef framework. The work presented in this paper has been supported in part by the project entitled Simulation of Subsurface Geochemical Transport and Carbon Sequestration, funded by the GRP-AEA Program at King Abdullah University of Science and Technology (KAUST).
Appears in Collections:
Articles; Environmental Science and Engineering Program; Physical Sciences and Engineering (PSE) Division; Earth Science and Engineering Program; Computational Transport Phenomena Lab

Full metadata record

DC FieldValue Language
dc.contributor.authorKatterbauer, Klemensen
dc.contributor.authorHoteit, Ibrahimen
dc.contributor.authorSun, Shuyuen
dc.date.accessioned2015-08-03T12:09:54Zen
dc.date.available2015-08-03T12:09:54Zen
dc.date.issued2014-10en
dc.identifier.issn09204105en
dc.identifier.doi10.1016/j.petrol.2014.07.039en
dc.identifier.urihttp://hdl.handle.net/10754/563782en
dc.description.abstractNew developments of electromagnetic and seismic techniques have recently revolutionized the oil and gas industry. Time-lapse seismic data is providing engineers with tools to more accurately track the dynamics of multi-phase reservoir fluid flows. With the challenges faced in distinguishing between hydrocarbons and water via seismic methods, the industry has been looking at electromagnetic techniques in order to exploit the strong contrast in conductivity between hydrocarbons and water. Incorporating this information into reservoir simulation is expected to considerably enhance the forecasting of the reservoir, hence optimizing production and reducing costs. Conventional approaches typically invert the seismic and electromagnetic data in order to transform them into production parameters, before incorporating them as constraints in the history matching process and reservoir simulations. This makes automatization difficult and computationally expensive due to the necessity of manual processing, besides the potential artifacts. Here we introduce a new approach to incorporate seismic and electromagnetic data attributes directly into the history matching process. To avoid solving inverse problems and exploit information in the dynamics of the flow, we exploit petrophysical transformations to simultaneously incorporate time lapse seismic and electromagnetic data attributes using different ensemble Kalman-based history matching techniques. Our simulation results show enhanced predictability of the critical reservoir parameters and reduce uncertainties in model simulations, outperforming with only production data or the inclusion of either seismic or electromagnetic data. A statistical test is performed to confirm the significance of the results. © 2014 Elsevier B.V. All rights reserved.en
dc.description.sponsorshipWe acknowledge the support of Olwijn Leeuwenburgh and Fabio Ravanelli in stimulating the idea for the integration of the history matching methods into the MRST Sintef framework. The work presented in this paper has been supported in part by the project entitled Simulation of Subsurface Geochemical Transport and Carbon Sequestration, funded by the GRP-AEA Program at King Abdullah University of Science and Technology (KAUST).en
dc.publisherElsevier BVen
dc.subjectelectromagnetic tomographyen
dc.subjectEnKFen
dc.subjectEnRMLen
dc.subjectiterative EnKFen
dc.subjectreservoir history matchingen
dc.subjectseismic imagingen
dc.titleEMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirsen
dc.typeArticleen
dc.contributor.departmentEarth Science and Engineering Programen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.contributor.departmentEnvironmental Science and Engineering Programen
dc.contributor.departmentEarth Fluid Modeling and Prediction Groupen
dc.contributor.departmentComputational Transport Phenomena Laben
dc.identifier.journalJournal of Petroleum Science and Engineeringen
kaust.authorKatterbauer, Klemensen
kaust.authorHoteit, Ibrahimen
kaust.authorSun, Shuyuen
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