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.
  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/
  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.
  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.
  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/
  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:
  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/
  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/
  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:
  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:
  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.
  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/
  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.
  42. 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
  43. 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.
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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
  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.
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  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
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  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.
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  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
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