Field development optimization of waterflooding process using data assimilation methods
The application of data assimilation methods for field development optimization has been the subject of intense investigation during the past 10 years. Lately has seen remarkable progress in the ability of data assimilation approach in reservoir characterization and based on this, improvements of fi...
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| Published in | IOP conference series. Materials Science and Engineering Vol. 700; no. 1; pp. 12054 - 12061 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Bristol
IOP Publishing
01.11.2019
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1757-8981 1757-899X 1757-899X |
| DOI | 10.1088/1757-899X/700/1/012054 |
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| Abstract | The application of data assimilation methods for field development optimization has been the subject of intense investigation during the past 10 years. Lately has seen remarkable progress in the ability of data assimilation approach in reservoir characterization and based on this, improvements of field development optimization. In this review paper, we have summarized key achievements in field development optimization of waterflooding process with data assimilation approach and review many of the achievements of the past time, including developments in the field of search for modifications of Ensemble Kalman Filter (EnKF) and Ensemble Smoothers (ES). An attempt has been made to discuss different data assimilation methods and to identify possible limitations of each. Current challenges and future research opportunities for improved data assimilation methods for field development optimization of waterflooding process are also discussed. |
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| AbstractList | The application of data assimilation methods for field development optimization has been the subject of intense investigation during the past 10 years. Lately has seen remarkable progress in the ability of data assimilation approach in reservoir characterization and based on this, improvements of field development optimization. In this review paper, we have summarized key achievements in field development optimization of waterflooding process with data assimilation approach and review many of the achievements of the past time, including developments in the field of search for modifications of Ensemble Kalman Filter (EnKF) and Ensemble Smoothers (ES). An attempt has been made to discuss different data assimilation methods and to identify possible limitations of each. Current challenges and future research opportunities for improved data assimilation methods for field development optimization of waterflooding process are also discussed. |
| Author | Zolotukhin, A Guliev, R |
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| References | Haugen (MSE_700_1_012054bib9) 2008; 13 Nævdal (MSE_700_1_012054bib4) 2006; 10 Aman (MSE_700_1_012054bib15) 2012 Barros E (MSE_700_1_012054bib7) 2016; 20 Khrulenko (MSE_700_1_012054bib13) 2018 Bianco (MSE_700_1_012054bib10) 2007 Peters (MSE_700_1_012054bib2) 2010 Chen (MSE_700_1_012054bib5) 2009; 14 Skjervheim (MSE_700_1_012054bib11) 2007; 12 Kalman (MSE_700_1_012054bib8) 1960; 82 Jansen (MSE_700_1_012054bib3) 2009 Brouwer (MSE_700_1_012054bib1) 2004; 9 Chen (MSE_700_1_012054bib12) 2008 Gordon (MSE_700_1_012054bib14) 1993; 140 van Essen (MSE_700_1_012054bib6) 2009; 14 |
| References_xml | – volume: 13 start-page: 382 year: 2008 ident: MSE_700_1_012054bib9 article-title: History Matching Using the Ensemble Kalman Filter on a North Sea Field Case publication-title: SPE J. doi: 10.2118/102430-PA – volume: 14 start-page: 202 year: 2009 ident: MSE_700_1_012054bib6 article-title: Robust Waterflooding Optimization of Multiple Geological Scenarios publication-title: SPE J. doi: 10.2118/102913-PA – volume: 14 start-page: 634 year: 2009 ident: MSE_700_1_012054bib5 article-title: Efficient Ensemble-Based Closed-Loop Production Optimization publication-title: SPE J. doi: 10.2118/112873-PA – year: 2009 ident: MSE_700_1_012054bib3 – volume: 140 start-page: 107 year: 1993 ident: MSE_700_1_012054bib14 article-title: Novel approach to nonlinear/non-Gaussian Bayesian state estimation publication-title: IEE Proc. F - Radar Signal Process doi: 10.1049/ip-f-2.1993.0015 – volume: 12 start-page: 282 year: 2007 ident: MSE_700_1_012054bib11 article-title: Incorporating 4D Seismic Data in Reservoir Simulation Models Using Ensemble Kalman Filter publication-title: SPE J. doi: 10.2118/95789-PA – year: 2012 ident: MSE_700_1_012054bib15 – start-page: 19 year: 2008 ident: MSE_700_1_012054bib12 – volume: 20 start-page: 737 year: 2016 ident: MSE_700_1_012054bib7 article-title: Value of information in closed-loop reservoir management publication-title: Comput. Geosci. doi: 10.1007/s10596-015-9509-4 – start-page: 10 year: 2007 ident: MSE_700_1_012054bib10 article-title: History Matching and Production Forecast Uncertainty by Means of the Ensemble Kalman Filter: A Real Field Application – volume: 82 start-page: 35 year: 1960 ident: MSE_700_1_012054bib8 article-title: A New Approach to Linear Filtering and Prediction Problems publication-title: J. Basic Eng. doi: 10.1115/1.3662552 – year: 2018 ident: MSE_700_1_012054bib13 – volume: 10 start-page: 37 year: 2006 ident: MSE_700_1_012054bib4 article-title: Waterflooding using closed-loop control publication-title: Comput. Geosci. doi: 10.1007/s10596-005-9010-6 – volume: 9 start-page: 391 year: 2004 ident: MSE_700_1_012054bib1 article-title: Dynamic Optimization of Waterflooding With Smart Wells Using Optimal Control Theory publication-title: SPE J. doi: 10.2118/78278-PA – year: 2010 ident: MSE_700_1_012054bib2 |
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| Title | Field development optimization of waterflooding process using data assimilation methods |
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