- Geir Evensen, Analysis of iterative ensemble smoothers for solving inverse problems, Computational Geosciences, 2018, vol 22, issue 3, pp 885–908
- Geir Evensen and Kjersti S. Eikrem, Conditioning reservoir models on rate data using ensemble smoothers, Computational Geosciences, 2018, vol 22, issue 5, pp 1251-1270
- Luo, X., Lorentzen, R. J., Valestrand, R., & Evensen, G. (2018, October 1). Correlation-Based Adaptive Localization for Ensemble-Based History Matching: Applied To the Norne Field Case Study. Society of Petroleum Engineers. doi:10.2118/191305-PA
- Alyaev, Hong and Bratvold, Are you Myopic, Naïve or Farsighted About your Geosteering Decisions?, European Association of Geoscientists & Engineers, Conference Proceedings, Second EAGE/SPE Geosteering and Well Placement Workshop, Nov 2018, Volume 2018, p.1 - 5
- Geir Evensen, Accounting for model errors in iterative ensemble smoothers, Comput Geosci (2019) vol 23: 761-775.
- Aanonsen, S. I., Tveit, S., & Alerini, M. (2019, March 1). Using Bayesian Model Probability for Ranking Different Prior Scenarios in Reservoir History Matching. Society of Petroleum Engineers. SPE 194505-PA
- Ricardo Soares, Xiaodong Luo, and Geir Evensen, Sparse Representation of 4D Seismic Signal Based on Dictionary Learning, SPE 195599-MS (2019). https://doi.org/10.2118/195599-MS
- Lingya Wang and Dean S. Oliver, Efficient Optimization of Well Drilling Sequence with Learned Heuristics, SPE-195640. SPE Journal, 24 (5), 2111-2134, (2019). 195640-PA.
- Patrick N. Raanes, Geir Evensen, and Andreas S. Stordal, Revising the stochastic, iterative ensemble smoother, Nonlin. Processes Geophys., 26, 325–338, (2019)
- Geir Evensen, Patrick N. Raanes, Andreas S. Stordal, and Joakim Hove, Efficient Implementation of an Iterative Ensemble Smoother for Data Assimilation and Reservoir History Matching, Frontiers in Applied Mathematics and Statistics, (2019).
- Xiaodong Luo and Tuhin Bhakta, Automatic and adaptive localization for ensemble-based history matching, Journal of Petroleum Science and Engineering, 184 (2019), https://doi.org/10.1016/j.petrol.2019.106559
- Xiaodong Luo, Ensemble-based kernel learning for a class of data assimilation problems with imperfect forward simulators. PLoS ONE, 2019, 14(7): e0219247. https://doi.org/10.1371/journal.pone.0219247
- Ricardo Soares, Xiaodong Luo, Tuhin Bhakta, and Geir Evensen, 4D seismic history matching: Assessing the use of a dictionary learning based sparse representation method. Journal of Petroleum Science and Engineering, 195 (2020) 107763. https://doi.org/10.1016/j.petrol.2020.107763
- Ricardo Soares, Xiaodong Luo, Geir Evensen and Tuhin Bhakta, Handling Big Models and Big Data Sets in History-Matching Problems through an Adaptive Local Analysis Scheme, SPE journal, 2020, https://doi.org/10.2118/204221-PA.
- Xiaodong Luo, R. J. Lorentzen, and T. Bhakta, Accounting for model errors of rock physics models in 4d seismic history matching problems: A perspective of machine learning, Journal of Petroleum Science and Engineering, 196, 107,961, (2021).
- Lingya Wang and Dean S. Oliver, Fast robust optimization using bias correction applied to the mean model, Comput Geosci (2020). https://doi.org/10.1007/s10596-020-10017-y
- Xiaodong Luo, Novel Ensemble Data Assimilation Algorithms Derived from A Class of Generalized Cost Functions, Conference Proceedings, ECMOR XVII, (2020), Volume 2020, p.1 - 32, DOI: https://doi.org/10.3997/2214-4609.202035044
- Bratvold, R. B. and Mohus, E. and Petutschnig, D. and Bickel, E., Production Forecasting: Optimistic and Overconfident-Over and Over Again, SPE Res Eval & Eng 23 (03): 0799–0810, SPE-195914-PA2020. https://doi.org/10.2118/195914-PA
- Geir Evensen, Formulating the history matching problem with consistent error statistics. Comput Geosci (2021). https://doi.org/10.1007/s10596-021-10032-7
- Gilson Neto, Ricardo Soares, Geir Evensen et al, Subspace Ensemble Randomized Maximum Likelihood with Local Analysis for Time-Lapse-Seismic-Data Assimilation, SPE-205029-PA (2021). https://doi.org/10.2118/205029-PA
- Xiaodong Luo, Novel iterative ensemble smoothers derived from a class of generalized cost functions. Comput Geosci (2021). https://doi.org/10.1007/s10596-021-10046-1
- Andreas S. Stordal, Rafael J. Moraes, Patrick Raanes and Geir Evensen, p-Kernel Stein Variational Gradient Descent for Data Assimilation and History Matching, Math. Geosci. 53, pp 375–393, (2021), https://doi.org/10.1007/s11004-021-09937-x
- Xiaodong Luo et al, Data assimilation with multiple types of observation boreholes via the ensemble Kalman filter embedded within stochastic moment equations, Hydrology and Earth System Sciences, 25, (2021). https://doi.org/10.5194/hess-25-1689-2021
- Lingya Wang and Dean Oliver, Improving Sequential Decisions – Efficiently Accounting for Future Learning, Journal of Petroleum Science and Engineering, (2021). https://doi.org/10.1016/j.petrol.2021.108770
- Amine Tadjer, Aojie Hong and Reidar B. Bratvold, Machine Learning based Decline Curve Analysis for Short-Term Oil Production Forecast.
Energy Exploration & Exploitation (2021). https://doi.org/10.1177/01445987211011784
- Amine Tadjer and Reidar B. Bratvold, Managing Uncertainty in Geological CO2 Storage using Bayesian Evidential Learning, Energies 14, p1557, (2021), https://doi.org/10.3390/en14061557
- Amine Tadjer, Reidar B. Bratvold and Remus Hanea, Efficient Dimensionality Reduction Methods in Reservoir History Matching, Energies 2021,14, p3137, (2021), https://doi.org/10.3390/en14113137
- Amine Tadjer, Aojie Hong, Reidar B. Bratvold and Remus Hanea, Application of Machine Learning to Assess the Value of Information in Polymer Flooding, Petroleum Research (2021). https://doi.org/10.1016/j.ptlrs.2021.05.006