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 (primarily) by authors who are not part of the MRST development team at SINTEF.
Preprints
  1. C.S. Lee, F.P. Hamon, N. Castelletto, P.S. Vassilevski, and J.A. White. An aggregation-based nonlinear multigrid solver for two-phase flow and transport in porous media. arXiv:2109.07546.
  2. M. Ashworth, A. Elsheikh, and F. Doster. Machine learning-based multiscale constitutive modelling: Development and application to dual-porosity mass transfer. arXiv:2108.08847.
  3. S. B. M. Bosma, F. P. Hamon, B. T. Mallison, and H. A. Tchelepi. Smooth implicit hybrid upwinding for compositional multiphase flow in porous media. ResearchGate, 2021.
  4. A. M. AlRassas, H. V. Thanh, S. Ren, R. Sun, N. L. N. Hai, and K.-K. Lee. Integrated static modelling and dynamic simulation framework for CO2 storage capacity in upper Qishn Clastics, S1A reservoir, Yemen. Research Square. DOI: 10.21203/rs.3.rs-503826/v1.
  5. D. Landa-Marbán, K. Kumar, S. Tveit, and S.E. Gasda. Numerical studies of CO2 leakage remediation by MICP-based plugging technology. arXiv preprint arXiv:2105.04382, 2021.
  6. M. HosseiniMehr, J.P. Tomala, C. Vuik, M. Al Kobaisi, and H. Hajibeygi. Projection-based embedded discrete fracture model (pEDFM) for flow and heat transfer in real-field geological formations with corner-point grid geometries, arXiv preprint arXiv:2105.05888.
  7. J.J. Hu, C. Siefert, and R.S. Tuminaro. Smooth Aggregation for Difficult Stretched Mesh and Coefficient Variation Problems. arXiv preprint arXiv:2103.10476, 2021.
  8. S. Dana, X. Zhao, and B. Jha. Two-grid method on unstructured tetrahedra: Applying computational geometry to staggered solution of coupled flow and mechanics problems. arXiv preprint arXiv:2102.04455, 2021
  9. D. Illiano, J.W. Both, I.S. Pop, and F.A. Radu. Efficient solvers for nonstandard models for flow and transport in unsaturated porous media. arXiv preprint arXiv:2012.14773, 2020.
  10. R. March, D. Egya, C. Maier, A. Busch, and F. Doster. Numerical computation of stress-permeability relationships of fracture networks in a shale rock. arXiv preprint arXiv:2012.02080, 2020.
  11. M. Elizarev, A. Mukhin, and A. Khlyupin. Objective-sensitive principal component analysis for high-dimensional inverse problems. arXiv preprint arXiv:2006.04527, 2020.
  12. 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.
  13. 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
  14. L. Mosser, O. Dubrule, and M. J. Blunt. DeepFlow: History matching in the space of deep generative models. arXiv preprint arXiv:1905.05749, 2019.
  15. 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
  16. A. Capolei, L.H. Christiansen, and J.B. Jørgensen. Risk minimization in life-cycle oil production optimization. arXiv preprint arXiv:1801.00684, 2018
  17. 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.
  18. 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.
  19. D. Stone, G. Lord. A positivity preserving convergent event based asynchronous PDE solver. arXiv preprint:1610.06800, 2016.
2022
  1. H. Liu, X. Liao, X. Zhao, L. Sun, X. Tang, L. Zhao. A high-resolution numerical well-test model for pressure transient analysis of multistage fractured horizontal wells in naturally fractured reservoirs. Journal of Petroleum Science and Engineering, Vol. 208, 2022. DOI: 10.1016/j.petrol.2021.109417.
2021
  1. M. Elizarev, A. Mukhin, and A. Khlyupin. Objective-sensitive principal component analysis for high-dimensional inverse problems. Computational Geosciences, 2021. DOI: 10.1007/s10596-021-10081-y.
  2. Q. Wang and R. Jiang. Comprehensive effects of polymer flooding on oil-water relative permeabilities. Journal of Energy Resources Technology, 2021. DOI: 10.1115/1.4052792.
  3. Y. Li, H. Yang, and S. Sun. Fully implicit two-phase VT-flash compositional flow simulation enhanced by multilayer nonlinear elimination. Journal of Computational Physics, 2021. DOI: 10.1016/j.jcp.2021.110790.
  4. H. Li, H. Yu, N. Cao, S. Cheng, H. Tian, and S. Di. Three-dimensional numerical simulation of multiscale fractures and multiphase flow in heterogeneous unconventional reservoirs with coupled fractal characteristics. Geofluids, 2021. DOI: 10.1155/2021/8265962
  5. A. Jiang and B. Jafarpour. Deep convolutional autoencoders for robust flow model calibration under uncertainty in geologic continuity. Water Resources Research, 2021. DOI: https://doi.org/10.1029/2021WR029754.
  6. C. Park, J. Oh, S. Jo,I. Jang, and K. S. Lee. Multi-objective optimization of CO2 sequestration in heterogeneous saline aquifers under geological uncertainty. Applied Sciences. 2021, 11(20), 9759. DOI: 10.3390/app11209759.
  7. Q. Guo. Evaluation of oil wells performance ranking in high water cut stage. Computational Geosciences, Vol. 25, pp. 1821–1835, 2021. DOI: 10.1007/s10596-021-10071-0
  8. N. Salmani, R. Fatehi, and R. Azin. A double-scale method for near-well flow in reservoir simulation. Journal of Petroleum Science and Engineering, 2021. DOI: 10.1016/j.petrol.2021.109487
  9. F. Bakharev, A. Enin, A. Groman, A. Kalyuzhnuk, S. Matveenko, Yu. Petrova, I.Starkov, and S. Tikhomirov. Velocity of viscous fingers in miscible displacement. Journal of Computational and Applied Mathematics, 2021. DOI: 10.1016/j.cam.2021.113808.
  10. D. Egya, P.W.M. Corbett, S. Geiger, J.P. Norgard, and S. Hegndal-Andersen. Calibration of naturally fractured reservoir models using integrated well-test analysis – an illustration with field data from the Barents Sea. Petroleum Geoscience, 2021. DOI: 10.1144/petgeo2020-042.
  11. H. Zhang and J.J. Sheng. Complex fracture network simulation and optimization in naturally fractured shale reservoir based on modified neural network algorithm. Journal of Natural Gas Science and Engineering, 2021. DOI: 10.1016/j.jngse.2021.104232
  12. A.V. Umavovskiy. Data-driven simulation of a two-phase flow in heterogenous porous media (in Russian). Computer Research and Modeling, 2021, vol. 13, no. 4, pp. 779-792. DOI: 10.20537/2076-7633-2021-13-4-779-792
  13. Y. Han and K. Liu. Integrated digital rock construction workflow for chemical enhanced oil recovery numerical simulation. Energy & Fuels, 2021. DOI: 10.1021/acs.energyfuels.1c02301.
  14. J. Xu, W. Wang, B. Ma, Y. Su, H. Wang, and S. Zhan. Stochastic-based liquid apparent permeability model of shale oil reservoir considering geological control. Journal of Petroleum Exploration and Production Technology, 2021. DOI: 10.1007/s13202-021-01273-4.
  15. L. Zhang, L. Xue, C. Cui, J. Qi, J. Sun, X. Zhou, Q. Dai, and K. Zhang. Monitoring the geometry morphology of complex hydraulic fracture network by using a multiobjective inversion algorithm based on decomposition. Energies,2021, 14(16), 5216. DOI: 10.3390/en14165216.
  16. J. Zeng and B. Guo. Multidimensional simulation of PFAS transport and leaching in the vadose zone: impact of surfactant-induced flow and soil heterogeneities. Advances in Water Resources, Volume 155, September 2021, 104015. DOI: 10.1016/j.advwatres.2021.104015
  17. D. Zeqiraj. Fully coupled stochastic geomechanical-geochemical-Reservoir modeling for fracture reservoirs. Results in Engineering, 2021. DOI: 10.1016/j.rineng.2021.100242
  18. M. Dugstad, K. Kumar, and Ø. Pettersen. Dimensional reduction of a fractured medium for a polymer EOR model. Computational Geosciences, 2021. DOI: 10.1007/s10596-021-10075-w.
  19. P.R. Punnam, B. Krishnamurthy, and V.K. Surasani. Investigations of structural and residual trapping phenomena during CO2 sequestration in Deccan volcanic province of the Saurashtra region, Gujarat. International Journal of Chemcial Engineering, 2021. DOI: 10.1155/2021/7762127.
  20. J. Jiang, P. Tomin, and Y. Zhou. Inexact methods for sequential fully implicit (SFI) reservoir simulation. Computational Geosciences, 2021. DOI: 10.1007/s10596-021-10072-z.
  21. G. M. S. Neto, A. Davolio, and D. J. Schiozer. Assimilating time-lapse seismic data in the presence of significant spatially correlated model errors. Journal of Petroleum Science and Engineering, 2021, 109127. DOI: 10.1016/j.petrol.2021.109127.
  22. M. M. Kida, Z. M. Sarkinbaka, A. M. Abubakar, and A. Z. Abdul. Neural network based performance evaluation of a waterflooded oil reservoir. International Journal of Recent Engineering Science, Vol. 8, Issue 3, 2021. DOI: 10.14445/23497157/IJRES-V8I3P101.
  23. L. Li, X. Guo, M. Zhou, Z. Chen, L. Zhao, and S. Wang. Numerical modeling of fluid flow in tight oil reservoirs considering complex fracturing networks and Pre-Darcy flow, Journal of Petroleum Science and Engineering, Volume 207, 2021, 109050. DOI: 10.1016/j.petrol.2021.109050.
  24. L. Luo, X.-C. Cai, and D. E. Keyes. (2021). Nonlinear preconditioning strategies for two-phase flows in porous media discretized by a fully implicit discontinuous Galerkin method. SIAM Journal on Scientific Computing, S317–S344, 2021. DOI: 10.1137/20m1344652
  25. G. B. Diaz Cortés, C. Vuik, and J.-D. Jansen. Accelerating the solution of linear systems appearing in two-phase reservoir simulation by the use of POD-based deflation methods. Computational Geosciences, 2021. DOI: 10.1007/s10596-021-10041-6.
  26. D. Hien, P.H. Giao, P.Q. Ngoc, N.M Quy, B.V. Dung, D.D. Huy, P.T Giang, and H. Long. Numerical simulation of low salinity water flooding on core samples for an oil reservoir in the Nam Con Son Basin, Vietnam. Energies, Vol. 14, 2021. 2658. DOI: 10.3390/en14092658.
  27. G. A. Padmanabha and N. Zabaras. Solving inverse problems using conditional invertible neural networks. Journal of Computational Physics, Volume 433, 15 May 2021, 110194. DOI: 10.1016/j.jcp.2021.110194.
  28. A. Ali and L. Guo. Data-driven based investigation of pressure dynamics in underground hydrocarbon reservoirs. Energy Reports, Volume 7, Supplement 2, pp. 104-110, 2021. DOI: 10.1016/j.egyr.2021.02.036
  29. B. Pouladi, N. Linde, L. Longuevergne, and O. Bour. Individual and joint inversion of head and flux data by geostatistical hydraulic tomography. Advances in Water Resources, 2021, 103960. DOI: 10.1016/j.advwatres.2021.103960
  30. V. E. Spooner, S. Geiger, and D. Arnold. Dual-porosity flow diagnostics for spontaneous imbibition in naturally fractured reservoirs. Water Resources Research. DOI: 10.1029/2020WR027775.
  31. R. March, S. Zhang, and H.H. Liu. Direct numerical simulation of density driven fingering flow: towards a model to predict the spacing between halite fingers in hydrocarbon reservoirs Journal of Petroleum Science and Engineering, 2021. DOI: 10.1016/j.petrol.2021.108929.
  32. P. Huang, L. Shen, Y. Gan, Y. Shen, D. Du, B. Yu, F. Maggi, and A. El‐Zein. Measurements of the relative permeability to CO2‐and‐brine multiphase fluid of Paaratte formation at near‐reservoir conditions. Greenhouse Gas: Science and Technology. DOI: 10.1002/ghg.2074.
  33. N. Suciu, D. Illiano, A. Prechtel, F.A. Radu. Global random walk solvers for fully coupled flow and transport in saturated/unsaturated porous media. Advances in Water Resources, 202110.1016/j.advwatres.2021.103935
  34. F. Meng, J. Li, H. Jiang, L. Zhao, L. Li, Y. Qiao, Y. Zhou, and F. Xu. Study on characteristics of waterflooding in fractured reservoirs based on discrete fracture model. Arabian Journal of Geosciences, Volume 14, 772, 2021. DOI: 10.1007/s12517-021-07102-6.
  35. M. Conjard and D. Grana. Ensemble-based seismic and production data assimilation using selection Kalman model. Mathematical Geosciences, 2021. DOI: 10.1007/s11004-021-09940-2.
  36. A. Koochakzadeh, H. Younesian-Farid, and S. Sadeghnejad . Acid pre-flushing evaluation before pH-sensitive microgel treatment in carbonate reservoirs: Experimental and numerical approach. Fuel, Volume 297, 2021, 120670. DOI: 10.1016/j.fuel.2021.120670.
  37. O. Khebzegga, A. Iranshahr, and H. Tchelepi. A nonlinear solver with phase boundary detection for compositional reservoir simulation. Transport in Porous Media, 2021. DOI: 10.1007/s11242-021-01584-4.
  38. H. Zalavadia and E. Gildin. Two-step predict and correct non-intrusive parametric model order reduction for changing well locations using a machine learning framework. Energies, 14(6), 1765, 2021. DOI: 10.3390/en14061765.
  39. P. Leary and P. Malin. Crustal reservoir flow simulation for long-range spatially-correlated random poroperm media. Journal of Energy and Power Technology, volume 3, issue 1, 2021. DOI: 10.21926/jept.2101013.
  40. A. Semnani, M. Ostadhassan, Y. Xu, M. Sharifi, and B. Liu. Joint optimization of constrained well placement and control parameters using teaching-learning based optimization and an inter-distance algorithm. Journal of Petroleum Science and Engineering, 2021. DOI: 10.1016/j.petrol.2021.108652.
  41. L. Li, X. Guo, M. Zhou, G. Xiang, N. Zhang, Y. Wang, S. Wang, A. Landjobo Pagou. The investigation of fracture networks on heat extraction performance for an enhanced geothermal system. Energies. 2021; 14(6):1635. DOI: 10.3390/en14061635.
  42. A. Tadjer and R.B. Bratvold. Managing uncertainty in geological CO2 storage using Bayesian evidential learning. Energies, 14(6):1667, 2021. DOI: 10.3390/en14061557.
  43. Y. D. Wang, T. Chung, A. Rabbani, R. T. Armstrong, and P. Mostaghimi. Fast direct flow simulation in porous media by coupling with pore network and Laplace models. Advances in Water Resources. DOI: 10.1016/j.advwatres.2021.103883.
  44. A. Farasat, H. Younesian-Farid, S. Sadeghnejad. Conformance control study of preformed particle gels (PPGs) in mature waterflooded reservoirs: numerical and experimental investigations. Journal of Petroleum Science and Engineering, 2021. DOI: 10.1016/j.petrol.2021.108575.
  45. B. Wang and C. Fidelibus. An open-source code for fluid flow simulations in unconventional fractured reservoirs. Geosciences, 2021. DOI: 10.3390/geosciences11020106.
  46. C. Xiao, Y. Deng, and G. Wang. Deep‐learning‐based adjoint state method: methodology and preliminary application to inverse modeling. Water Resources Research. Volume 57, Issue 2, February 2021. DOI: 10.1029/2020WR027400.
  47. K. Zhang, J. Zhang, Xi. Ma, C. Yao, L. Zhang, Y. Yang, J. Wang, J. Yao, and H. Zhao. History matching of naturally fractured reservoirs using a deep sparse autoencoder. SPE Journal, 2021. DOI: 10.2118/205340-PA.
  48. Z. Jiang, P. Tahmasebi, and Z. Mao. Deep residual U-net convolution neural networks with autoregressive strategy for fluid flow predictions in large-scale geosystems. Advances in Water Resources, 2021. DOI: 10.1016/j.advwatres.2021.103878.
  49. J. Zhang, S. Cheng, S. Di, Z. Gao, R. Yang, and P. Cao. A two-phase numerical model of well test analysis to characterize formation damage in near-well regions of injection wells. Geofluids, 2021. DOI: https://doi.org/10.1155/2021/6693965.
  50. G. M. Silva Neto, R. V. Soares, G. Evensen, A. Davolio, and D. J. Schiozer. Subspace ensemble randomized maximum likelihood with local analysis for time-lapse-seismic-data assimilation. SPE Journal, 2021. DOI: 10.2118/205029-PA .
  51. D. Landa-Marbán, S. Tveit, K. Kumar, and S.E. Gasda. Practical approaches to study microbially induced calcite precipitation at the field scale. International Journal of Greenhouse Gas Control, Volume 106, March 2021, 103256. DOI: https://doi.org/10.1016/j.ijggc.2021.103256
  52. M. K. Loe, D. Grana, and H. Tjelmeland. Geophysics-based fluid-facies predictions using ensemble updating of binary state vectors. Mathematical Geosciences, 2021. DOI: 10.1007/s11004-021-09922-4.
  53. J. C. Teixeira, L. J. N. Guimarães, and D. K. E. Carvalho. Streamline-based simulation in highly heterogeneous and anisotropic petroleum reservoirs using a non-orthodox MPFA method and an adaptive timestep strategy with unstructured meshes. Journal of Petroleum Science and Engineering, 2021,108369, DOI: 10.1016/j.petrol.2021.108369.
  54. S. Anyosa, S. Bunting, J. Eidsvik, A. Romdhane, and P. Bergmo. Assessing the value of seismic monitoring of CO2 storage using simulations and statistical analysis. International Journal of Greenhouse Gas Control, Volume 105, February 2021, 103219. DOI: 10.1016/j.ijggc.2020.103219.
2020
  1. A. Jiang and B. Jafarpour. Inverting subsurface flow data for geologic scenarios selection with convolutional neural networks. Advances in Water Resources, 2020, 103840. DOI: 10.1016/j.advwatres.2020.103840.
  2. J. Abbasi, M. Ghaedi, and M. Riazi. A multiscale study on the effects of dynamic capillary pressure in two-phase flow in porous media. Korean Journal of Chemical Engineering, vol. 37, pp. 2122-2135, 2020 DOI: 10.1007/s11814-020-0645-8.
  3. M.H .Rammay, A.H. Elsheikh, and Y. Chen. Flexible iterative ensemble smoother for calibration of perfect and imperfect models. Computational Geosciences, 2020, DOI: 10.1007/s10596-020-10008-z.
  4. T Chen. Equivalent permeability distribution for fractured porous rocks: the influence of fracture network properties. Geofluids, 6751349, 2020. DOI: 10.1155/2020/6751349.
  5. H. Zhang and J.J. Sheng. An efficient embedded discrete fracture model based on the unstructured quadrangular grid. Journal of Natural Gas Science and Engineering, 2020DOI: 10.1016/j.jngse.2020.103710.
  6. N. Andrianov and H.M. Nick. Machine learning of dual porosity model closures from discrete fracture simulations. Advances in Water Resources, 2020. DOI: 10.1016/j.advwatres.2020.103810.
  7. H. Liu, X. Liao, X. Tang, Z. Chen, X. Zhao, and J. Zou. A well test model based on embedded discrete-fracture method for pressure-transient analysis of fractured wells with complex fracture networks. Journal of Petroleum Science and Engineering, 2020. 10.1016/j.petrol.2020.108042.
  8. M. Ahmadinia, S.M. Shariatipour, O. Andersen, B. Nobakht. Quantitative evaluation of the joint effect of uncertain parameters in CO2 storage in the Sleipner project, using data-driven models. International Journal of Greenhouse Gas Control Volume 103, December 2020, 103180. DOI: 10.1016/j.ijggc.2020.103180.
  9. 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.
  10. D. Illiano, I.S. Pop, F.A. Radu. Iterative schemes for surfactant transport in porous media. Computational Geosciences, 2020. DOI: 10.1007/s10596-020-09949-2.
  11. Adil Sbai and A. Larabi. On solving groundwater flow and transport models with algebraic multigrid preconditioning. Groundwater, 2020. DOI: 10.1111/gwat.13016.
  12. T. Chen. Equivalent permeability distribution for fractured porous rocks: correlating fracture aperture and length. Geofluids. 2020 |Article ID 8834666. DOI: 10.1155/2020/8834666.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. H. Klie and H. Florez. Data-driven prediction of unconventional shale-reservoir dynamics. SPE Journal, 2020DOI: 10.2118/193904-PA.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. 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
  37. 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.
  38. 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.
  39. 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.
  40. 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.
  41. 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.
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  24. G.B. Diaz Cortes, C.Vuik, and J.D.Jansen. On POD-based deflation vectors for DPCG applied to porous media problems. Journal of Computational and Applied Mathematics. Volume 330, pp. 193-213, 2018. DOI: 10.1016/j.cam.2017.06.032
  25. H Singh, J Cai. Screening improved recovery methods in tight-oil formations by injecting and producing through fractures. International Journal of Heat and Mass Transfer, Vol. 116, pp. 977-993, 2018. DOI: 10.1016/j.ijheatmasstransfer.2017.09.071
  26. J. Abbasi, M. Ghaedi, and M. Riazi. A new numerical approach for investigation of the effects of dynamic capillary pressure in imbibition process. Journal of Petroleum Science and Engineering, Volume 162, Pages 44-54, March 2018. DOI: 10.1016/j.petrol.2017.12.035
2017
  1. A.D. Obembe, M.E. Hossain, K. Mustapha, and S.A. Abu-Khamsin. A modified memory-based mathematical model describing fluid flow in porous media. Computers & Mathematics with Applications, Volume 73, Number 6, pp. 1385-1402, 2017. DOI: 10.1016/j.camwa.2016.11.022
  2. A.D. Obembe, M.E. Hossain, and S.A. Abu-Khamsin. Variable-order derivative time fractional diffusion model for heterogeneous porous media. Journal of Petroleum Science and Engineering 152, 391-405, 2017. DOI: 10.1016/j.petrol.2017.03.015
  3. E. Ucar, I. Berre, and E. Keilegavlen. Post-injection normal closure of fractures as a mechanism for induced seismicity. Geophysical Research Letters, Volume 44, Issue 19, pp. 9598-9606, 2017. DOI: 10.1002/2017GL074282
  4. A. Capolei, L. H. Christiansen, and J. B. Jørgensen. A novel approach for risk minimization in life-cycle oil production optimization. Computer Aided Chemical Engineering. Volume 40, pp. 157-162, 2017. DOI: 10.1016/B978-0-444-63965-3.50028-3
  5. A. S. Grema, D. Baba, U. H. Taura, M. B. Grema, and L. T. Popoola. Optimization and non-linear identification of reservoir water flooding process. Arid Zone Journal of Engineering, Technology and Environment, [S.l.], Volume 13, Number 5, pp. 610-619, 2017.
  6. H. Singh and N. J. Huerta. Detecting subsurface fluid leaks in real-time using injection and production rates. Advances in Water Resources, Volume 110, pp. 147-165, 2017. DOI: 10.1016/j.advwatres.2017.10.012
  7. L Agélas, G Enchéry, B Flemisch, M Schneider. Convergence of nonlinear finite volume schemes for heterogeneous anisotropic diffusion on general meshes. Journal of Computational Physics, Volume 351, pp. 80-107, December 2017. DOI: 10.1016/j.jcp.2017.09.003
  8. E. Insuasty, P. M. J. Van den Hof, S. Weiland, and J.-D. Jansen. Flow-based dissimilarity measures for reservoir models: a spatial-temporal tensor approach. Computational Geosciences, Volume 21, Issue 4, pp 645 -663, 2017. DOI: 10.1007/s10596-017-9641-4
  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
  10. L. Li, H. Jiang, J. Li, K. Wu, F. Meng, and Z. Chen, Modeling tracer flowback in tight oil reservoirs with complex fracture networks, Journal of Petroleum Science and Engineering, Volume 157, pp. 1007-1020, 2017. DOI: 10.1016/j.petrol.2017.08.022.
  11. R. V. Ponce, F.V. Alvarado, and M.S. Carvalho. Water-alternating-macroemulsion reservoir simulation through capillary number-dependent modeling. Journal of the Brazilian Society of Mechanical Sciences and Engineering, Volume 39, Issue 10, pp. 4135 -4145, October 2017. DOI: 10.1007/s40430-017-0885-7
  12. M. M. Siraj, P.M.J Van den Hof, and J.-D. Jansen. Handling geological and economic uncertainties in balancing short-term and long-term objectives in waterflooding optimization. SPE Journal, Vol. 22, No. 4, pp. 1313-1325, 2017. DOI: 10.2118/185954-PA
  13. W. Zhang and M. Al Kobaisi. A two-step finite volume method for the simulation of multiphase fluid flow in heterogeneous and anisotropic reservoirs. Journal of Petroleum Science and Engineering, Volume 156, pp. 282-298, 2017 DOI: 10.1016/j.petrol.2017.06.003
  14. D. Stone, S. Geiger, G. Lord. Asynchronous discrete event schemes for PDEs. Journal of Computational Physics, Volume 342, pp. 161-176, August 2017,. DOI: 10.1016/j.jcp.2017.04.026
  15. L. Zhang, X. Zhang, K. Zhang, H. Zhang, J. Yao. Inversion of fractures with combination of production performance and in-situ stress analysis data. Journal of Natural Gas Science and Engineering, Volume 42, pp. 232-242, 2017. DOI: 10.1016/j.jngse.2017.03.002
  16. E. Ahmed, J. Jaffré, J.E. Roberts, A reduced fracture model for two-phase flow with different rock types, Mathematics and Computers in Simulation, Volume 137, pp. 49-70, 2017. DOI: 10.1016/j.matcom.2016.10.005.
  17. A. Benali, A. Bacetti, A. Belkherroubi, H. Harhad, and S. Fasla-Louhibi, S. Fluid flow simulation through a naturally fractured reservoir with Matlab & Eclipse software. Nature & Technology, Vol. 16, pp. 21-29, 2017.
  18. K.G. Hanssen, A. Codas, and B. Foss. Closed-loop predictions in reservoir management under uncertainty. SPE Journal, Volume 22, Issue 05, pp. 1585-1595, 2017. DOI: 10.2118/185956-PA
  19. A. Singh, N.M. Reddy, and P. Tiwari. Petroleum Reservoir Simulation of Two-Phase Flow. In: Saha A., Das D., Srivastava R., Panigrahi P., Muralidhar K. (eds) Fluid Mechanics and Fluid Power - Contemporary Research. Lecture Notes in Mechanical Engineering. Springer, New Delhi. DOI: 10.1007/978-81-322-2743-4_89
  20. F. Hourfar, B. Moshiri, K. Salahshoor, A. Elkamel, Real-time management of the waterflooding process using proxy reservoir modeling and data fusion theory. Computers & Chemical Engineering, Volume 106, pp. 339-354, 2017, DOI: 10.1016/j.compchemeng.2017.06.018.
  21. G.J. Lord and D. Stone. New efficient substepping methods for exponential timestepping. Applied Mathematics and Computation, Volume 307, pp. 342 -365, August 2017. DOI: 10.1016/j.amc.2017.02.052
  22. W. Zhang, M. Al Kobaisi. A simplified enhanced MPFA formulation for the elliptic equation on general grids. Computational Geosciences. Volume 21, Issue 4, pp 621 -643, 2017. DOI: 10.1007/s10596-017-9638-z
  23. A. A. Shamsuddeen, H. Ismail, and Z. Z. Ibrahim. Well trajectory optimization of homogeneous and heterogeneous reservoirs by the use of adjoint-based optimization technique. International Research Journal of Advanced Engineering and Science, Volume 2, Issue 2, pp. 36-50, 2017.
  24. A. Codas, K.G. Hanssen, B. Foss, A. Capolei, J. B. Jørgensen. Multiple shooting applied to robust reservoir control optimization including output constraints on coherent risk measures. Computational Geosciences, Volume 21, Issue 3, pp 479 -497, June 2017. DOI: 10.1007/s10596-017-9625-4
  25. L. H. Christiansen, A. Capolei, J. B. Jørgensen. A least squares approach for efficient and reliable short-term versus long-term optimization. Computational Geosciences, Volume 21, Issue 3, pp. 411 -426, June 2017. DOI: 10.1007/s10596-017-9620-9.
  26. W. Zhang, M. Al Kobaisi. A globally coupled pressure method for the discretization of the tensor-pressure equation on non-K-orthogonal grids. SPE Journal, Vol. 22, Issue 2, pp. 679 - 698, 2017. DOI: 10.2118/184405-PA.
  27. N. Sorek, E. Gildin, F. Boukouvala, B. Beykal, C. A. Floudas. Dimensionality reduction for production optimization using polynomial approximations. Computational Geosciences. Volume 21, Issue 2, pp. 247 -266, 2017. DOI: 10.1007/s10596-016-9610-3
  28. L. Perozzi, B. Giroux, D.R. Schmitt, and E. Gloaguen. Sensitivity of seismic response for monitoring CO2 storage in a low porosity reservoir of the St Lawrence Lowlands, Québec, Canada: Part 2 - Synthetic modeling. Greenhouse Gases Science and Technology, Volume 7, pp. 613 -623, 2017. DOI: 10.1002/ghg.1670
  29. K. Katterbauer, S. Arango, S. Sun, I. Hoteit. Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs. Geophysical Prospecting. Volume 65, No 1, January 2017 pp. 337 - 364. DOI: 10.1111/1365-2478.12371.
  30. S. Le Clainche, F. Varas, J.M. Vega. Accelerating oil reservoir simulations using POD on the fly. International Journal for Numerical Methods in Engineering, Volume 110, Issue 1, pp. 79-100, April 2017. DOI: 10.1002/nme.5356
  31. S.Navabi, R. Khaninezhad, B. Jafarpour. A unified formulation for generalized oilfield development optimization. Computational Geosciences, Volume 21, Issue 1, pp. 47 -74, 2017. DOI: 10.1007/s10596-016-9594-z
2016
  1. L. Perozzi, E. Gloaguen, B. Giroux, K. Holliger. A stochastic inversion workflow for monitoring the distribution of CO2 injected into deep saline aquifers. Computational Geosciences, Volume 20, Issue 6, pp 1287 -1300, December 2016. DOI: 10.1007/s10596-016-9590-3
  2. A. Alyoubi, M. Ganesh. Parallel mixed FEM simulation of a class of single-phase models with non-local operators, Journal of Computational and Applied Mathematics, Volume 307, pp.106-118, December 2016. DOI: 10.1016/j.cam.2016.03.007.
  3. M. Jesmani, M.C. Bellout, R. Hanea, B. Foss. Well placement optimization subject to realistic field development constraints. Computational Geosciences. Volume 20, Issue 6, pp. 1185 -1209, December 2016. DOI: 10.1007/s10596-016-9584-1
  4. K.G. Hanssen, B. Foss. On selection of controlled variables for robust reservoir management. Journal of Petroleum Science and Engineering, Volume 147, pp. 504 -514, 2016. DOI: 10.1016/j.petrol.2016.08.027
  5. H. Yang, C. Yang, and S. Sun. Active-set reduced-space methods with nonlinear elimination for two-phase flow problems in porous media. SIAM Journal on Scientific Computing, Vol. 38, Number 4, pp. B593-B618, 2016. DOI: 10.1137/15M1041882
  6. J. S. Pau, W. Pao, and S.P. Yong. CO2 flow in saline aquifer with salt precipitation. International Journal of Numerical Methods for Heat & Fluid Flow, Vol. 26, Issue 1, pp. 122-145, 2016. DOI: 10.1108/HFF-02-2015-0051
  7. H. Sharma and M. Pandey. Two phase flow in three dimensional multigrid model. International Journal of Innovative Research in Science, Engineering and Technology, Vol. 5, Issue 10, October 2016. DOI: 10.15680/IJIRSET.2016.0510039
  8. A. Codas, B. Foss, E. Camponogara, S. Krogstad, Black-oil minimal fluid state parametrization for constrained reservoir control optimization, Journal of Petroleum Science and Engineering, Volume 143, July 2016, Pages 35-43. DOI: 10.1016/j.petrol.2016.01.034
  9. E. G. D. Barros, P. M. J. Van den Hof, J. D. Jansen. Value of information in closed-loop reservoir management. Computational Geosciences. Volume 20, Issue 3, pp. 737 -749, 2016. DOI: 10.1007/s10596-015-9509-4
  10. M. Hosseini and M. A. Riahi. Sparsity-based compressive reservoir characterization and modeling by applying ILS-DLA sparse approximation with LARS on DisPat-generated MPS models using seismic, well log, and reservoir data. Nonlinear Processes in Geophysics Discuss., 2016. DOI: 10.5194/npg-2016-46.
  11. L. H. Christiansen, A. Capolei, J. Bagterp Jørgensen, Time-explicit methods for joint economical and geological risk mitigation in production optimization. Journal of Petroleum Science and Engineering, Volume 146, October 2016, pp. 158-169. DOI: 10.1016/j.petrol.2016.04.018.
  12. F. Hourfar, B. Moshiri, K. Salahshoor, M. Zaare-Mehrjerdi, and P. Pourafshary. Adaptive modeling of waterflooding process in oil reservoirs. Journal of Petroleum Science and Engineering, Vol. 146, pp. 702-713, 2016. DOI: 10.1016/j.petrol.2016.06.038
  13. F. Lindner, M. Pfitzner, C. Mundt. Multiphase, multicomponent flow in porous media with local thermal non-equilibrium in a multiphase mixture model. Transport in Porous Media, March 2016, Volume 112, Issue 2, pp 313 -332. DOI: 10.1007/s11242-016-0646-6
  14. M. Babaei and I. Pan. Performance comparison of several response surface surrogate models and ensemble methods for water injection optimization under uncertainty, Computers & Geosciences, Vol. 91, pp. 9-32, 2016. DOI: 10.1016/j.cageo.2016.02.022.
  15. M.N. Najafi, M. Ghaedi, and S. Moghimi-Araghi. Water propagation in two-dimensional petroleum reservoirs. Physica A: Statistical Mechanics and its Applications, Vol. 445, pp. 102-111, 2016. DOI: 10.1016/j.physa.2015.10.100
  16. R. March, F. Doster and S. Geiger. Accurate early-time and late-time modeling of countercurrent spontaneous imbibition. Water Resources Research, Vol. 52, Issue 8, pp. 6263 -6276, August 2016. DOI: 10.1002/2015WR018456.
  17. F. Sana, K. Katterbauer, T. Y. Al-Naffouri, and I. Hoteit. Orthogonal matching pursuit for enhanced recovery of sparse geological structures with the Ensemble Kalman filter. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume 9, Issue 4, pp. 1710-1724, 2016. DOI: 10.1109/JSTARS.2016.2518119
  18. A. S. Grema, Y. Cao. Optimal feedback control of oil reservoir waterflooding processes. International Journal of Automation and Computing, February 2016, Volume 13, Issue 1, pp. 73 -80. DOI: 10.1007/s11633-015-0909-7
  19. A. Alkhatib and M. Babaei. Applying the multilevel Monte Carlo method for heterogeneity-induced uncertainty quantification of surfactant/polymer flooding. SPE Journal, Volume 21, Issue 04, pp. 1192-1203, 2016. DOI: 10.2118/172635-PA
  20. H. Jeong and S. Srinivasan. Fast assessment of CO2 plume characteristics using a connectivity based proxy. International Journal of Greenhouse Gas Control, Volume 49, 387-412, 2016. DOI: 10.1016/j.ijggc.2016.03.001.
  21. F. Sana, F. Ravanelli, T. Y. Al-Naffouri and I. Hoteit. A sparse Bayesian imaging technique for efficient recovery of reservoir channels with time-lapse seismic measurements. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 6, pp. 2242-2254, June 2016. DOI: 10.1109/JSTARS.2016.2563163.
  22. H. Shahandeh, S. Rahim, and Z. Li. Strategic optimization of the oil sands development with SAGD: Drainage area arrangement and development planning. Journal of Petroleum Science and Engineering, Volume 137, 172 -184, 2016. DOI: 10.1016/j.petrol.2015.11.023
2015
  1. J. Zhang, and A. Revil. Cross-well 4-D resistivity tomography localizes the oil -water encroachment front during water flooding. Geophysical Journal International, Volume 201, Issue 1, pp. 343-354, 2015. DOI: 10.1093/gji/ggv028
  2. A. Codas, B. Foss, E. Camponogara. Output-constraint handling and parallelization for oil-reservoir control optimization by means of multiple shooting. SPE Journal, Volume 20, Issue 4, pp. 856-871, 2015. DOI: 10.2118/174094-PA
  3. K. Fossum and T. Mannseth. Assessment of ordered sequential data assimilation. Computational Geosciences, Volume 19, Issue 4, pp. 821-844, 2015. DOI: 10.1007/s10596-015-9492-9
  4. S. Rahim, Z. Li, J. Trivedi. Reservoir geological uncertainty reduction: an optimization-based method using multiple static measures. Mathematical Geosciences, May 2015, Volume 47, Issue 4, pp 373 -396. DOI: 10.1007/s11004-014-9575-5
  5. K. Katterbauer, S. Arango, S. Sun, S., and I. Hoteit. Multi-data reservoir history matching for enhanced reservoir forecasting and uncertainty quantification. Journal of Petroleum Science and Engineering, Volume 128, 160-176, 2015. DOI: 10.1016/j.petrol.2015.02.016
  6. M.N. Najafi, M. Ghaedi, Geometrical clusters of Darcy's reservoir model and Ising universality class, Physica A: Statistical Mechanics and its Applications, Volume 427, pp. 82-91, 2015. DOI: 10.1016/j.physa.2015.01.061.
  7. A. Hasan and B. Foss. Optimal switching time control of petroleum reservoirs. Journal of Petroleum Science and Engineering, Volume 131, pp. 131-137, 2015. DOI: 10.1016/j.petrol.2015.04.027
  8. J. Li, Z. Lei, G. Qin, B. Gong. Effective local-global upscaling of fractured reservoirs under discrete fractured discretization. Energies, Volume 8, number 9, pp. 10178-10197, 2015. DOI:10.3390/en80910178
  9. M. Babaei , A, Alkhatib, I. Pan. Robust optimization of subsurface flow using polynomial chaos and response surface surrogates. Computational Geosciences, Volume 19, Number 5, pp. 979 -998, 2015. DOI: 10.1007/s10596-015-9516-5
  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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