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    Efficient Assimilation of Crosswell Electromagnetic Data Using Ensemble-Based History-Matching Framework

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    SPE-193808-MS.pdf
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    Type
    Conference Paper
    Authors
    Zhang, Yanhui
    Hoteit, Ibrahim cc
    KAUST Department
    Earth Fluid Modeling and Prediction Group
    Earth Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2019-03-29
    Online Publication Date
    2019-03-29
    Print Publication Date
    2019
    Permanent link to this record
    http://hdl.handle.net/10754/631803
    
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    Abstract
    An ensemble-based history-matching framework is proposed to enhance the characterization of petroleum reservoirs through the assimilation of crosswell electromagnetic (EM) data. As one of advanced technologies in reservoir surveillance, crosswell EM tomography can provide a cross-sectional conductivity map and hence saturation profile at an interwell scale by exploiting the sharp contrast in conductivity between hydrocarbons and saline water. Incorporating this new information into reservoir simulation in combination with other available observations is therefore expected to enhance the forecasting capability of reservoir models and to lead to better quantification of uncertainty. The proposed approach applies ensemble-based data-assimilation methods to build a robust and flexible framework under which various sources of available measurements can be readily integrated. Because the assimilation of crosswell EM data can be implemented in different ways (e.g., components of EM fields or inverted conductivity), a comparative study is conducted. The first approach integrates crosswell EM data in its original form which entails establishing a forward model simulating observed EM responses. In this work, the forward model is based on Archie's law that provides a link between fluid properties and formation conductivity, and Maxwell’s equations that describe how EM fields behave given the spatial distribution of conductivity. Alternatively, formation conductivity can be used for history matching, which is obtained from the original EM data through inversion using an adjoint gradient-based optimization method. Because the inverted conductivity is usually of high dimension and very noisy, an image-oriented distance parameterization utilizing fluid front information is applied aiming to assimilate the conductivity field efficiently and robustly. Numerical experiments for different test cases with increasing complexity are carried out to examine the performance of the proposed integration schemes and potential of crosswell EM data for improving the estimation of relevant model parameters. The results demonstrate the efficiency of the developed history-matching workflow and added value of crosswell EM data in enhancing the characterization of reservoir models and reliability of model forecasts.
    Citation
    Zhang Y, Hoteit I (2019) Efficient Assimilation of Crosswell Electromagnetic Data Using Ensemble-Based History-Matching Framework. SPE Reservoir Simulation Conference. Available: http://dx.doi.org/10.2118/193808-ms.
    Sponsors
    Support for the authors 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 Femke C. Vossepoel, Wim Mulder, and Marwan Wirianto for providing the multigrid EM forward solver which formed the basis for our inversion.
    Publisher
    Society of Petroleum Engineers (SPE)
    Journal
    SPE Reservoir Simulation Conference
    DOI
    10.2118/193808-ms
    10.2118/193808-pa
    Additional Links
    https://www.onepetro.org/conference-paper/SPE-193808-MS
    ae974a485f413a2113503eed53cd6c53
    10.2118/193808-ms
    Scopus Count
    Collections
    Conference Papers; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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