MRST - MATLAB Reservoir Simulation Toolbox

Journal papers using MRST
The following is a list of journal papers in which MRST is used as a key research tool. All papers are written by authors that are (or were) not part of the MRST development team at SINTEF.
Preprints
  1. G. A. Padmanabha and N. Zabaras. Solving inverse problems using conditional invertible neural networks. arXiv preprint arXiv:2007.15849, 2020.
  2. M. Elizarev, A. Mukhin, and A. Khlyupin. Objective-sensitive principal component analysis for high-dimensional inverse problems. arXiv preprint arXiv:2006.04527, 2020.
  3. H. Zalavadia and E. Gildin. Non-intrusive parametric model order reduction with error correction modeling for changing well locations using a machine learning framework. arXiv preprint arXiv:2001.05061, 2020.
  4. Adil Sbai and A. Larabi. On solving groundwater flow and transport models with algebraic multigrid preconditioning, preprint, ResearchGate.
  5. B. Wang. MRST-Shale: An open-source framework for generic numerical modeling of unconventional shale and tight gas reservoirs. Preprints 2020, 2020010080. DOI: 10.20944/preprints202001.0080.v1.
  6. D. Illiano, I. S. Pop, and F. A. Radu. An efficient numerical scheme for fully coupled flow and reactive transport in variably saturated porous media including dynamic capillary effects. arXiv preprint arXiv:1912.06731, 2019
  7. D. Illiano, I.S. Pop, F.A. Radu. Iterative schemes for surfactant transport in porous media. arXiv preprint arXiv:1906.00224, 2019
  8. L. Mosser, O. Dubrule, and M. J. Blunt. DeepFlow: History matching in the space of deep generative models. arXiv preprint arXiv:1905.05749, 2019.
  9. C. Xiao, O. Leeuwenburgh, H.X. Lin, A. Heemink. Subdomain POD-TPWL with local parameterization for large-scale reservoir history matching problems. arXiv preprint arXiv:1901.08059, 2019
  10. A. Capolei, L.H. Christiansen, and J.B. Jørgensen. Risk minimization in life-cycle oil production optimization. arXiv preprint arXiv:1801.00684, 2018
  11. M.M. Siraj, P.M.J. Van den Hof and J.D. Jansen. Asymmetric risk measures for optimizing economic performance of oil reservoirs. Submitted for publication in Journal of Process Control.
  12. M.M. Siraj, P.M.J. Van den Hof, and J.D. Jansen. Robust closed-loop reservoir management using residual analysis, Submitted for publication in Journal of Petroleum Science & Engineering, 2017.
  13. D. Stone, G. Lord. A positivity preserving convergent event based asynchronous PDE solver. arXiv preprint:1610.06800, 2016.
2020/electronic only
  1. A. Khanal and R. Weijermars. Comparison of flow solutions for naturally fractured reservoirs using complex analysis methods (CAM) and embedded discrete fracture models (EDFM): Fundamental design differences and improved scaling method. Geofluids, Vol. 2020, Article ID 8838540, 2020. DOI: 10.1155/2020/8838540.
  2. T. Chen. Equivalent permeability distribution for fractured porous rocks: correlating fracture aperture and length. Geofluids. 2020 |Article ID 8834666. DOI: 10.1155/2020/8834666.
  3. C. Xiao, O. Leeuwenburgh, H.X. Lin, and A. Heemink. Efficient estimation of space varying parameters in numerical models using non-intrusive subdomain reduced order modeling. Journal of Computational Physics, 2020. DOI: 10.1016/j.jcp.2020.109867.
  4. L. Deng and Y. Pan. Data-driven proxy model for waterflood performance prediction and optimization using Echo State Network with Teacher Forcing in mature fields. Journal of Petroleum Science and Engineering, 2020. DOI: 10.1016/j.petrol.2020.107981.
  5. D. Grana, M. Liu, and M. Ayani. Prediction of CO2 saturation spatial distribution using geostatistical inversion of time-lapse geophysical data. IEEE Transactions on Geoscience and Remote Sensing, 2020. DOI: 10.1109/TGRS.2020.3018910.
  6. M. Ashworth and F. Doster. Anisotropic dual-continuum representations for multiscale poroelastic materials: Development and numerical modelling. Numerical and Analytical Methods in Geomechanics, 2020. DOI: 10.1002/nag.3140, 2020.
  7. M. A. de Almeida, A. T. S. Souza, V. F. Dornelas, and A.P. Meneguelo. Analysis of the effectiveness of the alternating water and gas injection method (WAG). International Journal of Advanced Engineering Research and Science (IJAERS), Vol. 7, Issue 8, August 2020. DOI: 10.22161/ijaers.78.7
  8. X. Ning, Y. Feng, and B. Wang. Numerical simulation of channel fracturing technology in developing shale gas reservoirs. Journal of Natural Gas Science and Engineering, 2020, 103515. DOI: 10.1016/j.jngse.2020.103515.
  9. D.U. de Brito and L.J. Durlofsky. Field development optimization using a sequence of surrogate treatments. Computational Geosciences, 2020. DOI: 10.1007/s10596-020-09985-y.
  10. T. Chung, Y. Da Wang, R. T. Armstrong, and P. Mostaghimi. CNN-PFVS: Integrating neural network and finite volume models to accelerate flow simulation on pore space images. Transport in Porous Media, 2020. DOI: 10.1007/s11242-020-01466-1.
  11. M. Ahmadinia and S.M. Shariatipour. Analysing the role of caprock morphology on history matching of Sleipner CO2 plume using an optimisation method. Greenhouse Gases: Science and Technology, 2020. DOI: 10.1002/ghg.2027.
  12. H. Klie and H. Florez. Data-driven prediction of unconventional shale-reservoir dynamics. SPE Journal, 2020DOI: 10.2118/193904-PA.
  13. F. Hourfar, L. Khoshnevisan, B. Moshiri, K. Salahshoor, and A. Elkamel. Mixed H∞/passivity controller design through LMI approach applicable for waterflooding optimization in the presence of geological uncertainty. Computers & Chemical Engineering, Volume 142, 2020, 107055. DOI: 10.1016/j.compchemeng.2020.107055.
  14. A.V. Umanovsky. Adversarial convolutional neural networks as a heuristic model of the two-phase filtration process in a porous medium. Computational Continuum Mechanics, 2020. (In Russian). DOI: 10.7242/1999-6691/2020.13.2.18.
  15. M. Ghasemi, S. Tofigh, A. Parsa, A. Najafi-Marghmaleki. Numerical simulation of impact of biopolymer production and microbial competition between species on performance of MEOR process. Journal of Petroleum Science and Engineering, 2020, 107643. DOI: 10.1016/j.petrol.2020.107643.
  16. G.P. Oliveira, M.D. Santos, and E. Roemers-Oliveira. Well placement subclustering within partially oil-saturated flow units. Journal of Petroleum Science and Engineering, Volume 196, 2021, 107730. DOI: 10.1016/j.petrol.2020.107730.
  17. D.L.Y Wong, F. Doster, S. Geiger, E. Francot, and F. Gouth. Fluid flow characterization framework for naturally fractured reservoirs using small-scale fully explicit models. Transport in Porous Media, 2020 DOI: 10.1007/s11242-020-01451-8.
  18. O. Olorode. B. Wang. and H. U. Rashid. Three-dimensional projection-based embedded discrete-fracture model for compositional simulation of fractured reservoirs. SPE Journal, 2020. DOI: 10.2118/201243-PA.
  19. D. Landa-Marbán, G. Bødtker, B.F. Vik, P. Pettersson, I.S. Pop, K. Kumar, and F.A. Radu. Mathematical modeling, laboratory experiments, and sensitivity analysis of bioplug technology at Darcy scale. SPE Journal, 2020. DOI: 10.2118/201247-PA.
  20. C. Xiao and L. Tian. Surrogate‐based joint estimation of subsurface geological and relative permeability parameters for high‐dimensional inverse problem by use of smooth local parameterization. Water Resources Research, Vol. 56, Issue 7, 2020, e2019WR0253662020. DOI: 10.1029/2019WR025366.
  21. M. Ayani and D. Grana. Statistical rock physics inversion of elastic and electrical properties for CO2 sequestration studies. Geophysical Journal International, 2020. DOI: 10.1093/gji/ggaa346.
  22. A.M Kassa, K. Kumar, S.E. Gasda, and F.A. Radu. Implicit linearization method for non-standard two-phase flow in porous media. Numerical Methods in Fluids, 2020. DOI: 10.1002/fld.4891.
  23. C. Li, J. Ye, J. Yang, and J. Zhou. Performance evaluation of multiple fractured horizontal wells in shale gas reservoirs. Earth Science & Engineering, 2020. DOI: 10.1002/ese3.773.
  24. M. Ayani, D. Grana, and M. Liu. Stochastic inversion method of time-lapse controlled source electromagnetic data for CO2 plume monitoring. International Journal of Greenhouse Gas Control, Volume 100, September 2020, 103098. DOI: 10.1016/j.ijggc.2020.103098.
  25. B. Callow, I. Falcon-Suarez, H. Marin-Moreno, J.M. Bull, and S. Ahmed. Optimal X-ray micro-CT image based methods for porosity and permeability quantification in heterogeneous sandstones. Geophysical Journal International, ggaa321, 2020. DOI: 10.1093/gji/ggaa321.
  26. X. Ma, K. Zhang, C. Yao, L. Zhang, J. Wang, Y. Yang, and J. Yao. Multiscale-network structure inversion of fractured media based on a hierarchical-parameterization and data-driven evolutionary-optimization method. SPE Journal, 2020. DOi: 10.2118/201237-PA
  27. L. Pasquinelli, M. Felder, M.L. Gulbrandsen, T.M. Hansen, J.-S. Jeon, N. Molenaar, K. Mosegaard, and I.L. Fabricius. The feasibility of high-temperature aquifer thermal energy storage in Denmark: the Gassum Formation in the Stenlille structure. Bulletin of the Geological Society of Denmark, Vol. 68, pp. 133–154, 2020. DOI: 10.37570/bgsd-2020-68-06.
  28. S. Parvin, M. Masoudi, A. Sundal, and R. Miri. Continuum scale modelling of salt precipitation in the context of CO2 storage in saline aquifers with MRST compositional. International Journal of Greenhouse Gas Control 99:103075. DOI: 10.1016/j.ijggc.2020.103075.
  29. M. Liu and D. Grana. Petrophysical characterization of deep saline aquifers for CO2 storage using ensemble smoother and deep convolutional autoencoder, Advances in Water Resources, 2020, 103634. DOI: 10.1016/j.advwatres.2020.103634.
  30. T Bai and P Tahmasebi. Hybrid geological modeling: Combining machine learning and multiple-point statistics. Computers & Geosciences, 2020. DOI: 10.1016/j.cageo.2020.104519.
  31. Z. Wang, X. Liu, H. Tang, Z. Lv, and Q. Liu. Reservoir inverse modeling by ensemble smoother with multiple data assimilation for seismic and production data. Computer Modeling in Engineering & Sciences CMES, vol.123, no.2, pp.873-893, 2020 CMES. DOI: 10.32604/cmes.2020.08993.
  32. M. H. Rammay, A. H. Elsheikh, and Y. Chen. Robust algorithms for history matching of imperfect subsurface models. SPE Journal, 2020 DOI: 10.2118/193838-PA
  33. A. S Grema, A. S Kolo, U. H. Taura, and M. B Grema. Evaluation of intelligent wells performance in a five-spot arrangement. FUOYE Journal of Engineering and Technology, Volume 5, Issue 1, March 2020.
  34. H. Liu, X. Zhao, X. Tang, B. Peng, J. Zou, and X. Zhang. A discrete fracture–matrix model for pressure transient analysis in multistage fractured horizontal wells with discretely distributed natural fractures. Journal of Petroleum Science and Engineering, Volume 192, 2020, 107275. DOI: 10.1016/j.petrol.2020.107275.
  35. N. Salmani, R. Fatehi and R. Azin. On the liquid condensate vertical migration near the production wells of gas-condensate reser-voirs. Engineering Science and Technology, an International Journal, 2020. DOI: 10.1016/j.jestch.2020.03.006.
  36. K. Zhang, F. Du, and B. Nojabaei. Effect of pore size heterogeneity on hydrocarbon fluid distribution, transport, and primary and secondary recovery in nano-porous media. Energies 2020, 13, 1680. DOI: 10.3390/en13071680.
  37. Y. Sun, Z. Liu, and Y. Hu. Adjoint based state estimation of compressible flow in porous media. Petroleum, 2020. DOI: 10.1016/j.petlm.2020.03.004.
  38. D. Wong, F. Doster, S. Geiger, and A. Kamp. Partitioning thresholds in hybrid implicit‐explicit representations of naturally fractured reservoirs. Water Resources Research, 56, 2020. DOI: 10.1029/2019WR025774
  39. S. Sanguinito, H. Singh, E. M. Myshakin, et al. Methodology for estimating the prospective CO2 storage resource of residual oil zones at the national and regional scale, International Journal of Greenhouse Gas Control, Volume 96, 2020, 103006. DOI: 10.1016/j.ijggc.2020.103006
  40. A.A. Lukyanov and K. Vuik. A stable SPH discretization of the elliptic operator with heterogeneous coefficients. Journal of Computational and Applied Mathematics Volume 374, 15 August 2020, 112745. DOI: 10.1016/j.cam.2020.112745.
  41. A. D. Obembe. A fractional diffusion model for single-well simulation in geological media. Journal of Petroleum Science and Engineering,10 March 2020, 107162. DOI: 10.1016/j.petrol.2020.107162
  42. E. I. Epelle and D. I.Gerogiorgis. Adjoint-based well placement optimisation for enhanced oil recovery (EOR) under geological uncertainty: From seismic to production. Journal of Petroleum Science and Engineering, 20 February 2020, 107091 DOI: 10.1016/j.petrol.2020.107091
  43. L. Luo, L. Liu, X.-C. Cai, and D. E.Keyes. Fully implicit hybrid two-level domain decomposition algorithms for two-phase flows in porous media on 3D unstructured grids. Journal of Computational Physics, 2020, 109312. DOI: 10.1016/j.jcp.2020.109312.
  44. E.L.F. Fortaleza, E.P.B Neto, and M.E.R. Miranda. Production optimization using a modified net present value. Computational Geosciences, 2020. DOI: 10.1007/s10596-019-09927-3.
  45. D. Wong, F. Doster, S. Geiger, and A. Kamp. Partitioning thresholds in hybrid implicit‐explicit representations of naturally fractured reservoirs. Water Resources Research, 2020. DOI: 10.1029/2019WR025774.
  46. L. Liu, Z. Huang, J. Yao, Y. Di, and Y.S. Wu. An efficient hybrid model for 3D complex fractured vuggy reservoir simulation. SPE Journal, 2020 DOI: 10.2118/199899-PA.
  47. Q. Liao, G. Lei, Z. Wei, D. Zhang, and S. Patil. Efficient analytical upscaling method for elliptic equations in three-dimensional heterogeneous anisotropic media. Journal of Hydrology, 2020 DOI: 10.1016/j.jhydrol.2020.124560.
  48. B. Guo J. Zeng, and M. L. Brusseau. A mathematical model for the release, transport, and retention of per‐ and polyfluoroalkyl substances (PFAS) in the vadose zone. Water Resources Research, 2020. DOI: 10.1029/2019WR026667.
  49. A. Jahandideh and B. Jafarpour. Closed-loop stochastic oilfield optimization for hedging against geologic, development, and operation uncertainty. Computational Geosciences, 2020. DOI: 10.1007/s10596-019-09902-y.
  50. R. Weijermars, A. Khanal, and L. Zuo. Fast models of hydrocarbon migration paths and pressure depletion based on complex analysis methods (CAM): Mini-review and verification. Fluids, 5, 7, 2020. DOI: 10.3390/fluids5010007.
  51. S. Ayirala, A. Alghamdi, A. Gmira, D. K. Cha, M. A. Alsaud, and A. Yousef. Linking pore scale mechanisms with macroscopic to core scale effects in controlled ionic composition low salinity waterflooding processes. Fuel, Volume 264, 15 March 2020, 116798, DOI: 10.1016/j.fuel.2019.116798.
2019/electronic only
  1. K. Zhang, B. Nojabaei, K. Ahmadi, and R. T. Johns. Effect of gas/oil capillary pressure on minimum miscibility pressure for tight reservoirs. SPE Journal, 2019. DOI: 10.2118/199354-PA.
  2. D. Pedretti and M. Bianchi. Preliminary results from the use of entrograms to describe transport in fractured media. Acque Sotterranee-Italian Journal of Groundwater, AS31-421: 07 - 11, 2019. DOI: 10.7343/as-2019-421.
  3. U. Hassan, J.A. Ajienka, and A.D.I. Sulaiman. Evaluating the performance of ultrasound energy on improved oil recovery using MATLAB reservoir simulation toolbox (MRST). Journal of Petroleum and Gas Engineering. Vol.10(4), pp. 85-100, July 2019. DOI: 10.5897/JPGE2019.0311.
  4. E. Ahmed, S. A. Hassan, C. Japhet, M. Kern, M. Vohralik. A posteriori error estimates and stopping criteria for space-time domain decomposition for two-phase flow between different rock types. SMAI journal of computational mathematics, Volume 5 (2019), p. 195-227. DOI : 10.5802/smai-jcm.47.
  5. Q. Wang, R. Jiang, Y. Cui, and J. Yuan. Pre-Darcy flow behavior of CO2 Huff-n-Puff development in Fuyu tight formation: Experiment and numerical evaluation. Journal of Petroleum Science and Engineering 186 (2020) 106773. DOI: 10.1016/j.petrol.2019.106773 .
  6. C. Xiao, L. Tian, L. Zhang, G. Wang, and Y. Deng. Distributed Gauss-Newton optimization with smooth local parameterization for large-scale history-matching problems. SPE Journal, 2019. DOI: 10.2118/198913-PA.
  7. D. Lauzon and D. Marcotte. Calibration of random fields by a sequential spectral turning bands method. Computers & Geosciences, 2019. DOI: 10.1016/j.cageo.2019.104390.
  8. G.P. Oliveira, M.D. Santos, and W.L. Roque. Constrained clustering approaches to identify hydraulic flow units in petroleum reservoirs. Journal of Petroleum Science and Engineering, 2019. DOI: 10.1016/j.petrol.2019.106732.
  9. H.R.N.B. Mfoubat, and E.I. Zaky. Optimization of waterflooding performance by using finite volume-based flow diagnostics simulation. Journal of Petroleum Exploration and Production Technology DOI: 10.1007/s13202-019-00803-5.
  10. A. Nissan and B. Berkowitz. Reactive transport in heterogeneous porous media under different Péclet numbers. Water Resources Research, 2019. DOI: 10.1029/2019WR025585
  11. G.P. Oliveira, E.A. Araújo, M.D. Santos, and W.L.Roque. Non-uniform injector/producer well pattern designs induced by morphology and anisotropy of flow units. Journal of Petroleum Science and Engineering, 2019. DOI: 10.1016/j.petrol.2019.106680
  12. M Liu, and D Grana. Time-lapse seismic history matching with iterative ensemble smoother and deep convolutional autoencoder. Geophysics, 2019. DOI: 10.1190/geo2019-0019.1
  13. E. Ahmed. Splitting-based domain decomposition methods for two-phase flow with different rock types. Advances in Water Resources, 2019. DOI: 10.1016/j.advwatres.2019.103431
  14. M. Rongved and P. Cerasi. Simulation of stress hysteresis effect on permeability increase risk along a fault. Energies 2019, 12(18), 3458. DOI: 10.3390/en12183458.
  15. Y.D. Wang, T. Chung, R.T. Armstrong, J. McClure, T. Ramstad, and P. Mostaghimi. Accelerated computation of relative permeability by coupled morphological and direct multiphase flow simulation. Journal of Computational Physics, 18 October 2019, 108966. DOI: 10.1016/j.jcp.2019.108966.
  16. T. Chung, Y.D. Wang, R.T. Armstrong, and P.Mostaghimi. Voxels agglomeration for fast estimation of permeability of micro-CT images. Journal of Petroleum Science and Engineering, October 2019. DOI: 10.1016/j.petrol.2019.106577.
  17. D. Batista. Mesh-independent streamline tracing. Journal of Computational Physics, 2019. DOI: 10.1016/j.jcp.2019.108967.
  18. L. Zhao, H. Jiang, H. Wang, H.Yang, F. Sun, and J. Li. Representation of a new physics-based non-Darcy equation for low-velocity flow in tight reservoirs. Journal of Petroleum Science and Engineering, 2019. DOI: 10.1016/j.petrol.2019.106518.
  19. K. Nunna and M. J. King. Dynamic diffuse-source upscaling in high-contrast systems. SPE Journal, 2019. DOI: 10.2118/182689-PA.
  20. L.-M. Zhang. J. Qi, K. Zhang, L.-X. Li, X.-M. Zhang, H.-Y. Wu, M. T. Chipecane, and J. Yao. Calibrate complex fracture model for subsurface flow based on Bayesian formulation. Petroleum Science, 2019. DOI: 10.1007/s12182-019-00357-5.
  21. A. S. Grema and Y. Cao. Dynamic self-optimizing control for uncertain oil reservoir waterflooding processes. IEEE Transactions on Control Systems Technology, 2019. DOI: 10.1109/TCST.2019.2934072.
  22. M. Jesmani, B. Jafarpour, M. C. Bellout, B. Foss. A reduced random sampling strategy for fast robust well placement optimization, Journal of Petroleum Science and Engineering, 2019, 106414. DOI: 10.1016/j.petrol.2019.106414.
  23. Y. Sun, Z. Liu, and X. Dong. Rate optimization of fractional flow reservoir model based on the continuous adjoint method. Journal of Petroleum Science and Engineering, 2019. DOI: 10.1016/j.petrol.2019.106346.
  24. K. Nunna, C.-H. Liu, and M. J. King. Application of diffuse source functions for improved flow upscaling. Computational Geosciences, 2019. DOI: 10.1007/s10596-019-09868-x.
  25. G. Dutta, T. Mukerji, and J. Eidsvik. Value of information of time-lapse seismic data by simulation-regression: comparison with double-loop Monte Carlo. Computational Geosciences, 2019. DOI: 10.1007/s10596-019-09864-1.
  26. H. Yang, S. Sun, Y., and C. Yang. Parallel reservoir simulators for fully implicit complementarity formulation of multicomponent compressible flows. Computer Physics Communications, 2019. DOI: 10.1016/j.cpc.2019.07.011.
  27. Y. Hu, R. T. Armstrong, I.Shikhov, T. T. Hung, B. Lee, and P. Mostaghimi. Unsteady-state coreflooding monitored by positron emission tomography and X-ray computed tomography. SPE Journal, 2019. DOI: 10.2118/195701-PA.
  28. H. Singh. Machine learning for surveillance of fluid leakage from reservoir using only injection rates and bottomhole pressures. Journal of Natural Gas Science and Engineering, Vol. 69, September 2019, 102933. DOI: 10.1016/j.jngse.2019.102933.
  29. H. Yang, S. Sun, Y. Li, and C. Yang. A fully implicit constraint-preserving simulator for the black oil model of petroleum reservoirs. Journal of Computational Physics, Vol. 396, pp. 347-363, 2019. DOI: 10.1016/j.jcp.2019.05.038
  30. W. Zhang and M. Al Kobaisi. Cell-centered nonlinear finite-volume methods with improved robustness. SPE Journal, 2019. DOI: 10.2118/195694-PA
  31. V. Spooner, S. Geiger, and D. Arnold. Flow diagnostics for naturally fractured reservoirs. Petroleum Geoscience, 1 July 2019. DOI: 10.1144/petgeo2018-136
  32. H. Florez and E. Gildin. Global/local model order reduction in coupled flow and linear thermal-poroelasticity. Computational Geosciences, June 2019. DOI: 10.1007/s10596-019-09834-7
  33. M. A. Abdullah, A. Panda, S. Gupta, S. Joshi, A. Singh, and N. Rao. Multi-scale method for modelling and simulation of two-phase flow in reservoir using MRST. Petroleum & Coal, Vol. 61 Issue 3, pp. 546-558, 2019.
  34. X. Zhao and B. Jha. Role of well operations and multiphase geomechanics in controlling fault stability during CO2 storage and enhanced oil recovery. JGR Solid Earth, June 2019. 10.1029/2019JB017298
  35. S. Xu, Q. Feng, S. Wang, and Y. Li. A 3D multi-mechanistic model for predicting shale gas permeability. Journal of Natural Gas Science and Engineering, Vol. 68, 2019. DOI: 10.1016/j.jngse.2019.102913
  36. Y. Zhao, H. Jiang, S. Rahman, Y. Yuan, L. Zhao, J. Li, J. Ge, J. Li. Three-dimensional representation of discrete fracture matrix model for fractured reservoirs. Journal of Petroleum Science and Engineering, Vol. 180, pp. 886-900, 2019. DOI: 10.1016/j.petrol.2019.06.015
  37. A. Jahandideh and B. Jafarpour. Stochastic oilfield optimization under uncertain future development plans. SPE Journal, 2019. DOI: 10.2118/190139-PA
  38. Y. Mehmani and H.A. Tchelepi. Multiscale formulation of two-phase flow at the pore scale. Journal of Computational Physics. Volume 389, pp. 164-188, 2019. DOI: 10.1016/j.jcp.2019.03.035
  39. X. Lang and D. Grana. Rock physics modelling and inversion for saturation‐pressure changes in time‐lapse seismic studies. Geophysical Prospecting, Vol. 67, Issue 7, pp. 1912-1928, 2019. DOI: 10.1111/1365-2478.12797
  40. L. Zhang, C. Cui, Y. Wang, K. Zhang, Z. Sun, and J. Yao. Reducing fracture prediction uncertainty based on time-lapse seismic (4D) and deterministic inversion algorithm. International Journal for Uncertainty Quantification, Vol. 9, No. 2, pp. 187-204, 2019. DOI: 10.1615/Int.J.UncertaintyQuantification.2019027680
  41. L. Zhang, C. Cui, X. Ma, Z. Sun, F. Liu, K. Zhang. A fractal discrete fracture network model for history matching of naturally fractured reservoirs. Fractals, Vol. 27, No. 01, 1940008, 2019. DOI: 10.1142/S0218348X19400085
  42. Q. Liao, G. Lei, D. Zhang, and S. Patil. Analytical solution for upscaling hydraulic conductivity in anisotropic heterogeneous formations. Advances in Water Resources, Volume 128, pp. 97-116, 2019. DOI: 10.1016/j.advwatres.2019.04.011
  43. B. Sousedík. On adaptive BDDC for the flow in heterogeneous porous media. Applications of Mathematics, Vol. 64, No. 3, pp. 309-334, 2019. DOI: 10.21136/AM.2019.0222-18
  44. M. Hosseini and M. A. Riahi. Using input-adaptive dictionaries trained by the method of optimal directions to estimate the permeability model of a reservoir. Journal of Applied Geophysics, Volume 165, pp. 16-28, 2019. DOI: 10.1016/j.jappgeo.2019.04.006
  45. Y. D. Wang, T. Chung, R. T. Armstrong, J. E. McClure, and P. Mostaghimi. Computations of permeability of large rock images by dual grid domain decomposition. Advances in Water Resources, Volume 126, pp. 1-14, 2019. DOI: 10.1016/j.advwatres.2019.02.002
  46. E.G.D. Barros, P.M.J. Van den Hof, and J.D. Jansen. Informed production optimization in hydrocarbon reservoirs. Optimization and Engineering, 2019. DOI: 10.1007/s11081-019-09432-7
  47. C. S. Hemmingsen. S. L. Glimberg, N. Quadrio, C. Völcker, K. K. Nielsen, J. H. Walther, M. lByrne, and A. P.Engsig-Karup. Multiphase coupling of a reservoir simulator and computational fluid dynamics for accurate near-well flow. J. Petrol. Sci. Eng.,  Vol. 178, pp. 517-527, 2019. DOI: 10.1016/j.petrol.2019.03.063
  48. T. Chung, Y. D. Wang, R. T. Armstrong, and P. Mostaghimi. Approximating permeability of microcomputed-tomography images using elliptic flow equations. SPE Journal, Vol. 24, Issue 3, pp. 1154-1163, 2019. DOI: 10.2118/191379-PA
  49. T. L. Silva, A. Codas, M. Stanko, E. Camponogara, and B. Foss. Network-constrained production optimization by means of multiple shooting. SPE Reservoir Evaluation & Engineering, Vol. 22, Issue 2, pp. 709-733, 2019. DOI: 10.2118/194504-PA
  50. M. H. Rammay, A. H. Elsheikh, and Y. Chen. Quantification of prediction uncertainty using imperfect subsurface models with model error estimation. J. Hydrol., Vol. 576, pp. 764-783, 2019. DOI: 10.1016/j.jhydrol.2019.02.056
  51. D. Egya, S. Geiger, and P.W.M. Corbett. Pressure-transient responses of fractures with variable conductivity and asymmetric well location. SPE Reservoir Evaluation & Engineering, Vol. 22, Issue 2, pp. 745-755, 2019. DOI: 10.2118/190884-PA
  52. E.L.F. Fortaleza, J.O.A. Limaverde Filho, G.S.V. Gontijo, É. L. Albuquerque, R.D.P. Simões, M.M. Soares, M.E.R. Miranda, and G.C. Abade. Analytical, numerical and experimental study of gas coning on horizontal wells. J Braz. Soc. Mech. Sci. Eng. (2019) 41: 141. DOI: 10.1007/s40430-019-1643-9
  53. Y. Zhang, Z. Xue, H. Park, J. Shi, T. Kiyama, X. Lei, and Y. Liang. Tracking CO2 plumes in clay‐rich rock by distributed fiber optic strain sensing (DFOSS): a laboratory demonstration. Water Resources Research, Vol. 55, Issue 1, pp. 856-767, 2019. DOI: 10.1029/2018WR023415
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2018
  1. E. Ucar, I. Berre, E. Keilegavlen, and J.M. Nordbotten. A finite-volume discretization for deformation of fractured media. Computational Geosciences, Volume 22, Issue 4, pp. 993 -1007, 2018. DOI: 10.1007/s10596-018-9734-8
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    Volume 123, Issue 5, pp. 3891-3908, 2018. DOI: 10.1029/2017JB015241
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2017
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  9. K. Zhang, X. Zhang, L. Zhang, L. Li, H. Sun, Z. Huang, and J Yao. Assisted history matching for the inversion of fractures based on discrete fracture-matrix model with different combinations of inversion parameters. Computational Geosciences, Volume 21, Issue 5 -6, pp 1365 -1383, December 2017. DOI: 10.1007/s10596-017-9690-8
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2016
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2015
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  10. T. Chen, C. Clauser, G. Marquart, K. Willbrand, and D. Mottaghy. A new upscaling method for fractured porous media. Advances in Water Resources, Vol. 80, pp. 60-68, 2015. DOI: 10.1016/j.advwatres.2015.03.009
  11. X. Lu, H. Jiang, J. Li, L. Zhao, Y. Pei, Y. Zhao, G. Liu, and W. Fang. Polymer thermal degradation in high-temperature reservoirs. Petroleum Science and Technology, Volume 33, Issue 17-18, pp. 1571-1579, 2015. DOI: 10.1080/10916466.2015.1072561
  12. K. Katterbauer, I. Hoteit, S. Sun. History matching of electromagnetically heated reservoirs incorporating full-wavefield seismic and electromagnetic imaging. SPE Journal, Volume 20, No 5, pp. 923 - 941, 2015. DOI: 10.2118/173896-PA
  13. F. Lindner, C. Munz, and M. Pfitzner. Fluid flow and heat transfer with phase change and local thermal non-equilibrium in vertical porous channels. Transport in Porous Media, Volume 106, Issue 1, pp 201 -220, 2015. DOI: 10.1007/s11242-014-0396-2.
  14. A. Capolei, E. Suwartadi, B. Foss, J. B. Jørgensen. A mean-variance objective for robust production optimization in uncertain geological scenarios. J. Petroleum Science and Engineering, Volume 125, pp. 23-37 2014, DOI: 10.1016/j.petrol.2014.11.015.
2014
  1. J. D. Jansen, R.M. Fonseca, S. Kahrobaei, M.M. Siraj, G.M. Van Essen, and P.M.J. Van den Hof. The egg model - A geological ensemble for reservoir simulation. Geoscience Data Journal, Volume 1 (2), pp. 192-195, 2014. DOI: 10.1002/gdj3.21
  2. O. Leeuwenburgh and R. Arts. Distance parameterization for efficient seismic history matching with the ensemble Kalman Filter. Computational Geosciences. Volume, 18, Issue: 3-4, pp. 535-548. 2014. DOI: 10.1007/s10596-014-9434-y
  3. K. Fossum and T. Mannseth. Parameter sampling capabilities of sequential and simultaneous data assimilation: II. Statistical analysis of numerical results. Inverse Problems, Volume 30, Number 11, 114002, 2014. DOI: 10.1088/0266-5611/30/11/114003
  4. T. D. Humphries, R. D. Haynes, and L. A. James. Simultaneous and sequential approaches to joint optimization of well placement and control. Computational Geosciences, Volume 18, Issue 3-4, pp 433-448, 2014. DOI: 10.1007/s10596-013-9375-x
  5. J. Rezaie and J. Eidsvik. Kalman Filter variants in the closed skew normal setting. Computational Statistics & Data Analysis, Volume 75, pp. 1 -14, 2014. DOI: 10.1016/j.csda.2014.01.014
  6. J. Rezaie, J. Eidsvig, and T. Mukerji. Value of information analysis and Bayesian inversion for closed skew-normal distributions: Applications to seismic amplitude variation with offset data. Geophysics, Volume 79, Issue 4, pp. R151-R163, 2014. DOI: 10.1190/geo2013-0048.1
  7. K. Katterbauer, I. Hoteit, and S. Sun. EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs. J. Petrol. Sci. Eng., 2014, DOI: 10.1016/j.petrol.2014.07.039.
  8. C. Lieberman and K. Willcox. Nonlinear goal-oriented Bayesian inference: Application to carbon capture and storage. SIAM Journal on Scientific Computing 36, no. 3, B427 -B449, 2014. DOI: 10.1137/130928315.
  9. A. Butler, R.D. Haynes, T.D. Humphries, and P. Ranjan. Efficient optimization of the likelihood function in Gaussian process modelling, Computational Statistics & Data Analysis, Volume 73, May 2014, Pages 40-52, ISSN 0167-9473, Doi: 10.1016/j.csda.2013.11.017.
  10. T. H. Sandve, E. Keilegavlen and J. M. Nordbotten. Physics-based preconditioners for flow in fractured porous media. Water Resources Research, Volume 50, Issue 2, pages 1357 -1373, February 2014. DOI: 10.1002/2012WR013034
2013
  1. Y. Efendiev, O. Iliev, and C. Kronsbein. Multilevel Monte Carlo methods using ensemble level mixed MsFEM for two-phase flow and transport simulations. Computational Geosciences, Volume 17, Issue 5, pp 833-850, 2013. DOI: 10.1007/s10596-013-9358-y
  2. A. Rotevatn, T. H. Sandve, E. Keilegavlen, D. Kolyukhin and H. Fossen. Deformation bands and their impact on fluid flow in sandstone reservoirs: the role of natural thickness variations. Geofluids, Volume 13, Issue 3, pages 359 -371, 2013. DOI: 10.1111/gfl.12030
  3. A. Capolei, E. Suwartadi, B. Foss, J. B. Jørgensen. Waterflooding optimization in uncertain geological scenarios. Computational Geosciences, Volume 17, Issue 6, pp 991-1013, 2013. DOI: 10.1007/s10596-013-9371-1
  4. A. Tambue. Efficient numerical simulation of incompressible two-phase flow in heterogeneous porous media based on exponential Rosenbrock−Euler method and lower-order Rosenbrock-type method. Journal of Porous Media, Volume 16, Issue 5, pp. 381-393, 2013. DOI: 10.1615/JPorMedia.v16.i5.10
  5. A. Tambue, I. Berre, J.M. Nordbotten. Efficient simulation of geothermal processes in heterogeneous porous media based on the exponential Rosenbrock-Euler and Rosenbrock-type methods. Advances in Water Resources, Volume 53, pp. 250 -262, 2013. DOI: 10.1016/j.advwatres.2012.12.004
2012
  1. Lijian Jiang, J. David Moulton, Daniil Svyatskiy, Analysis of stochastic mimetic finite difference methods and their applications in single-phase stochastic flows, Computer Methods in Applied Mechanics and Engineering, Volumes 217 -220, 1 April 2012, Pages 58-76, ISSN 0045-7825, doi: 10.1016/j.cma.2011.12.007.
  2. J. Rezaie and J. Eidsvig. Shrinked (1 − α) ensemble Kalman filter and α Gaussian mixture filter. Comput. Geosci., Vol. 16, No.3, pp. 837-852, 2012. DOI: 10.1007/s10596-012-9291-5.
  3. T. H. Sandve, I. Berre, J. M. Nordbotten. An efficient multi-point flux approximation method for Discrete Fracture-Matrix simulations. J. Comp. Phys., Vol. 231, Issue 9, pp. 3784 -3800, 2012. DOI: 10.1016/j.jcp.2012.01.023
  4. E. Keilegavlen, J. M. Nordbotten, A. F. Stephansen. Tensor relative permeabilities: origins, modeling and numerical discretization. Int. J Numer. Anal. Mod. (Special issue in memory of Magne Espedal), Vol. 9, No. 3, pp. 701-724, 2012.
  5. E. Suwartadi, S. Krogstad, and B. Foss. Nonlinear output constraints handling for production optimization of oil reservoirs. Comput. Geosci., Vol. No. 2, pp. 499-517, 2012. DOI: 10.1007/s10596-011-9253-3.
2011
  1. E. W. Bhark, B. Jafarpour, and A. Datta-Gupta. A generalized grid connectivity -based parameterization for subsurface flow model calibration, Water Resour. Res., 47, W06517, 2011. DOI: 10.1029/2010WR009982.

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Published February 18, 2017

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