caa a22 4500 605538921 CHVBK 20210128100904.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s11053-014-9233-0 doi (NATIONALLICENCE)springer-10.1007/s11053-014-9233-0 Estimation of Facies Boundaries Using Categorical Indicators with P-Field Simulation and Ensemble Kalman Filter (EnKF) [Elektronische Daten] [Siavash Nejadi, Japan Trivedi, Juliana Leung] The Ensemble Kalman Filter (EnKF) often fails to reproduce realistic facies distribution and proportion corresponding to the prior spatial distribution. In this paper, a new step is proposed for inclusion in the history matching of multiple facies reservoir models using EnKF. The new step consists of constructing a facies probability map and application of probability field (P-Field) simulation to re-sample a new ensemble. After certain number of assimilation steps in EnKF, the updated ensemble members are used to propose a probability map for facies distribution. P-Field simulation is performed subsequently using the facies probability map to generate a new ensemble, which honors the static geologic data and is more consistent with the early production data. After the re-sampling step, the forecast model is applied to the new ensemble from the beginning. EnKF is again applied on the ensemble members to assimilate the remaining production history. Two case studies with different facies distribution and well configurations were conducted. Initial ensemble was created using known facies classification at the well locations and populating binary facies data throughout the reservoir using prior information of spatial facies distribution and facies proportions. The qualities of the history-matched models were assessed by comparing the spatial facies distribution and proportions of the updated ensemble, in addition to the root mean square error of the predicted data mismatch. Implementation of EnKF together with re-sampling of the new realizations using probability maps demonstrates reasonable improvement in the history matching and uncertainty assessment of multiple facies reservoir models. International Association for Mathematical Geosciences, 2014 History matching nationallicence Ensemble Kalman Filter nationallicence probability field simulation nationallicence discrete cosine transform nationallicence facies modeling nationallicence variogram nationallicence Nejadi Siavash Department of Civil & Environmental Engineering, School of Mining and Petroleum Engineering, University of Alberta, 3-122 Markin/CNRL Natural Resources Engineering Facility, T6G 2W2, Edmonton, AB, Canada aut Trivedi Japan Department of Civil & Environmental Engineering, School of Mining and Petroleum Engineering, University of Alberta, 3-122 Markin/CNRL Natural Resources Engineering Facility, T6G 2W2, Edmonton, AB, Canada aut Leung Juliana Department of Civil & Environmental Engineering, School of Mining and Petroleum Engineering, University of Alberta, 3-122 Markin/CNRL Natural Resources Engineering Facility, T6G 2W2, Edmonton, AB, Canada aut Natural Resources Research Springer US; http://www.springer-ny.com 24/2(2015-06-01), 121-138 1520-7439 24:2<121 2015 24 11053 https://doi.org/10.1007/s11053-014-9233-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11053-014-9233-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Nejadi Siavash Department of Civil & Environmental Engineering, School of Mining and Petroleum Engineering, University of Alberta, 3-122 Markin/CNRL Natural Resources Engineering Facility, T6G 2W2, Edmonton, AB, Canada aut NATIONALLICENCE 700 1- Trivedi Japan Department of Civil & Environmental Engineering, School of Mining and Petroleum Engineering, University of Alberta, 3-122 Markin/CNRL Natural Resources Engineering Facility, T6G 2W2, Edmonton, AB, Canada aut NATIONALLICENCE 700 1- Leung Juliana Department of Civil & Environmental Engineering, School of Mining and Petroleum Engineering, University of Alberta, 3-122 Markin/CNRL Natural Resources Engineering Facility, T6G 2W2, Edmonton, AB, Canada aut NATIONALLICENCE 773 0- Natural Resources Research Springer US; http://www.springer-ny.com 24/2(2015-06-01), 121-138 1520-7439 24:2<121 2015 24 11053