Bibliography#
Antoine Collet. Assisted History Matching in Reactive Transport : Application to Uranium in Situ Recovery. PhD Manuscript, Université Paris sciences et lettres, December 2024.
Gene H. Golub and Charles F. Van Loan. Matrix Computations. Johns Hopkins Studies in the Mathematical Sciences. Johns Hopkins University Press, Baltimore, 3rd ed edition, 1996. ISBN 978-0-8018-5413-2 978-0-8018-5414-9.
Kaare Brandt Petersen and Michael Syskind Pedersen. The Matrix Cookbook. November 2008.
Peter K. Kitanidis. Quasi-Linear Geostatistical Theory for Inversing. Water Resources Research, 31(10):2411–2419, 1995. doi:10.1029/95WR01945.
O.J. Lepine, R.C. Bissell, S.I. Aanonsen, I.C. Pallister, and J.W. Barker. Uncertainty Analysis in Predictive Reservoir Simulation Using Gradient Information. SPE Journal, 4(03):251–259, September 1999. doi:10.2118/57594-PA.
Albert Tarantola. Inverse Problem Theory and Methods for Model Parameter Estimation. Other Titles in Applied Mathematics. Society for Industrial and Applied Mathematics, January 2005. ISBN 978-0-89871-572-9. doi:10.1137/1.9780898717921.
Arvind K. Saibaba and Peter K. Kitanidis. Fast computation of uncertainty quantification measures in the geostatistical approach to solve inverse problems. Advances in Water Resources, 82:124–138, August 2015. doi:10.1016/j.advwatres.2015.04.012.
Ge Ren-pu and M. J. D. Powell. The convergence of variable metric matrices in unconstrained optimization. Mathematical Programming, 27(2):123–143, October 1983. doi:10.1007/BF02591941.
L. Bonet-Cunha, D. S. Oliver, R. A. Redner, and A. C. Reynolds. A Hybrid Markov Chain Monte Carlo Method for Generating Permeability Fields Conditioned to Multiwell Pressure Data and Prior Information. In SPE Annual Technical Conference and Exhibition. OnePetro, October 1996. doi:10.2118/36566-MS.
Dean S. Oliver, Luciane B. Cunha, and Albert C. Reynolds. Markov chain Monte Carlo methods for conditioning a permeability field to pressure data. Mathematical Geology, 29(1):61–91, March 1997. doi:10.1007/BF02769620.
Alexandre A. Emerick and Albert C. Reynolds. Investigation of the sampling performance of ensemble-based methods with a simple reservoir model. Computational Geosciences, 17(2):325–350, April 2013. doi:10.1007/s10596-012-9333-z.
D. S. Oliver, N. He, and A. C. Reynolds. Conditioning Permeability Fields to Pressure Data. In ECMOR V - 5th European Conference on the Mathematics of Oil Recovery, cp. European Association of Geoscientists & Engineers, September 1996. doi:10.3997/2214-4609.201406884.
Geir Evensen, Patrick Raanes, Andreas Stordal, and Joakim Hove. Efficient Implementation of an Iterative Ensemble Smoother for Data Assimilation and Reservoir History Matching. Frontiers in Applied Mathematics and Statistics, 5:47, October 2019. doi:10.3389/fams.2019.00047.
R. E. Kalman. A New Approach to Linear Filtering and Prediction Problems. Journal of Basic Engineering, 82(1):35–45, March 1960. doi:10.1115/1.3662552.
STANLEY F. Schmidt. Application of State-Space Methods to Navigation Problems. In C. T. Leondes, editor, Advances in Control Systems, volume 3, pages 293–340. Elsevier, January 1966. doi:10.1016/B978-1-4831-6716-9.50011-4.
Geir Evensen. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research: Oceans, 99(C5):10143–10162, 1994. doi:10.1029/94JC00572.
Dean S. Oliver and Yan Chen. Recent progress on reservoir history matching: a review. Computational Geosciences, 15(1):185–221, January 2011. doi:10.1007/s10596-010-9194-2.
Alexandre A. Emerick and Albert C. Reynolds. Ensemble smoother with multiple data assimilation. Computers & Geosciences, 55:3–15, June 2013. doi:10.1016/j.cageo.2012.03.011.
Geir Evensen. Data Assimilation - The Ensemble Kalman Filter. Springer Berlin Heidelberg, 2007. ISBN 978-3-642-03710-8. doi:10.1007/978-3-642-03711-5.
Shuaitao Wang, Nicolas Flipo, and Thomas Romary. Which filter for data assimilation in water quality models? Focus on oxygen reaeration and heterotrophic bacteria activity. Journal of Hydrology, 620:129423, March 2023. doi:10.1016/j.jhydrol.2023.129423.
Albert Reynolds. Assisted History Matching. March 2017.
Peter Jan van Leeuwen and Geir Evensen. Data Assimilation and Inverse Methods in Terms of a Probabilistic Formulation. Monthly Weather Review, 124(12):2898–2913, December 1996. doi:10.1175/1520-0493(1996)124<2898:DAAIMI>2.0.CO;2.
Sigurd Aanonsen, Geir Nævdal, Dean Oliver, Albert Reynolds, and Brice Vallès. The Ensemble Kalman Filter in Reservoir Engineering–a Review. SPE Journal - SPE J, 14:393–412, September 2009. doi:10.2118/117274-PA.
J.-a.-A. Skjervheim, G. Evensen, J. Hove, and J. G. Vabø. An Ensemble Smoother for assisted History Matching. In SPE Reservoir Simulation Symposium. OnePetro, February 2011. doi:10.2118/141929-MS.
A. C. Reynolds, M. Zafari, and G. Li. Iterative Forms of the Ensemble Kalman Filter. In ECMOR X - 10th European Conference on the Mathematics of Oil Recovery, cp. European Association of Geoscientists & Engineers, September 2006. doi:10.3997/2214-4609.201402496.
Jifu Yin, Xiwu Zhan, Youfei Zheng, Christopher R. Hain, Jicheng Liu, and Li Fang. Optimal ensemble size of ensemble Kalman filter in sequential soil moisture data assimilation. Geophysical Research Letters, 42(16):6710–6715, 2015. doi:10.1002/2015GL063366.
Martin Leutbecher. Ensemble size: How suboptimal is less than infinity? Quarterly Journal of the Royal Meteorological Society, 145(S1):107–128, 2019. doi:10.1002/qj.3387.
Sebastian Milinski, Nicola Maher, and Dirk Olonscheck. How large does a large ensemble need to be? Earth System Dynamics, 11(4):885–901, October 2020. doi:10.5194/esd-11-885-2020.
Geir Evensen. The Ensemble Kalman Filter: theoretical formulation and practical implementation. Ocean Dynamics, 53(4):343–367, November 2003. doi:10.1007/s10236-003-0036-9.
Geir Evensen, Femke C. Vossepoel, and Peter Jan van Leeuwen. Localization and Inflation. In Geir Evensen, Femke C. Vossepoel, and Peter Jan van Leeuwen, editors, Data Assimilation Fundamentals: A Unified Formulation of the State and Parameter Estimation Problem, Springer Textbooks in Earth Sciences, Geography and Environment, pages 111–122. Springer International Publishing, Cham, 2022. doi:10.1007/978-3-030-96709-3_10.
P. L. Houtekamer and Herschel L. Mitchell. A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation. Monthly Weather Review, 129(1):123–137, January 2001. doi:10.1175/1520-0493(2001)129<0123:ASEKFF>2.0.CO;2.
Gregory Gaspari and Stephen E. Cohn. Construction of correlation functions in two and three dimensions. Quarterly Journal of the Royal Meteorological Society, 125(554):723–757, 1999. doi:10.1002/qj.49712555417.
Jeffrey L. Anderson. Exploring the need for localization in ensemble data assimilation using a hierarchical ensemble filter. Physica D: Nonlinear Phenomena, 230(1):99–111, June 2007. doi:10.1016/j.physd.2006.02.011.
Craig H. Bishop and Daniel Hodyss. Flow-adaptive moderation of spurious ensemble correlations and its use in ensemble-based data assimilation. Quarterly Journal of the Royal Meteorological Society, 133(629):2029–2044, 2007. doi:10.1002/qj.169.
Elana J. Fertig, Brian R. Hunt, Edward Ott, and Istvan Szunyogh. Assimilating non-local observations with a local ensemble Kalman filter. Tellus, 59(5):719–730, January 2007. doi:10.1111/j.1600-0870.2007.00260.x.
Xiaodong Luo, Rolf J. Lorentzen, Randi Valestrand, and Geir Evensen. Correlation-Based Adaptive Localization for Ensemble-Based History Matching: Applied To the Norne Field Case Study. SPE Reservoir Evaluation & Engineering, 22(03):1084–1109, October 2018. doi:10.2118/191305-PA.
Xiaodong Luo and Tuhin Bhakta. Automatic and adaptive localization for ensemble-based history matching. Journal of Petroleum Science and Engineering, 184:106559, January 2020. doi:10.1016/j.petrol.2019.106559.
Xiaodong Luo and Chuan-An Xia. Continuous Hyper-parameter OPtimization (CHOP) in an ensemble Kalman filter. Frontiers in Applied Mathematics and Statistics, 2022.
Geir Evensen. Spurious correlations, localization, and inflation. In Geir Evensen, editor, Data Assimilation: The Ensemble Kalman Filter, pages 237–253. Springer, Berlin, Heidelberg, 2009. doi:10.1007/978-3-642-03711-5_15.
Alexandre A. Emerick and Albert C. Reynolds. History matching time-lapse seismic data using the ensemble Kalman filter with multiple data assimilations. Computational Geosciences, 16(3):639–659, June 2012. doi:10.1007/s10596-012-9275-5.
Ruijian Li, A. C. Reynolds, and D. S. Oliver. History Matching of Three-Phase Flow Production Data. SPE Journal, 8(04):328–340, December 2003. doi:10.2118/87336-PA.
Guohua Gao and Albert C. Reynolds. An Improved Implementation of the LBFGS Algorithm for Automatic History Matching. SPE Journal, 11(01):5–17, March 2006. doi:10.2118/90058-PA.
Duc Le, Alexandre Emerick, and Albert Reynolds. An Adaptive Ensemble Smoother With Multiple Data Assimilation for Assisted History Matching. SPE Journal, June 2016. doi:10.2118/173214-PA.
Marco Iglesias and Yuchen Yang. Adaptive regularisation for ensemble Kalman inversion. Inverse Problems, 37(2):025008, January 2021. doi:10.1088/1361-6420/abd29b.
Paulo Henrique Ranazzi and Marcio Augusto Sampaio. Ensemble size investigation in adaptive ES-MDA reservoir history matching. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(10):413, September 2019. doi:10.1007/s40430-019-1935-0.
Alexandre Emerick and Albert Reynolds. History-Matching Production and Seismic Data in a Real Field Case Using the Ensemble Smoother With Multiple Data Assimilation. In SPE Reservoir Simulation Symposium, volume 2. The Woodlands, Texas, USA, February 2013. doi:10.2118/163675-MS.
Geir Evensen. Sampling strategies and square root analysis schemes for the EnKF. Ocean Dynamics, 54(6):539–560, December 2004. doi:10.1007/s10236-004-0099-2.
Geir Evensen. Correlation-Based Localization. January 2023.
Javad Rafiee and Albert C. Reynolds. Theoretical and efficient practical procedures for the generation of inflation factors for ES-MDA. Inverse Problems, 33(11):115003, October 2017. doi:10.1088/1361-6420/aa8cb2.
Valeria Todaro. Advanced techniques for solving groundwater and surface water problems in the context of inverse methods and climate change. Tesis doctoral, Universitat Politècnica de València, May 2021. doi:10.4995/Thesis/10251/166439.
Valeria Todaro, Marco D'Oria, Maria Giovanna Tanda, and J. Jaime Gómez-Hernández. genES-MDA: A generic open-source software package to solve inverse problems via the Ensemble Smoother with Multiple Data Assimilation. Computers & Geosciences, 167:105210, October 2022. doi:10.1016/j.cageo.2022.105210.