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Journal papers using MRST
The following list comprises journal papers that extensively utilize MRST as a research tool. Notably, all papers are authored primarily by researchers not affiliated with the MRST development team at SINTEF.
2024
  1. Z. Safari, R. Fatehi, and R. Azin. Developing a numerical model for microbial methanation in a depleted hydrocarbon reservoir. Renewable Energy, 2024. DOI: 10.1016/j.renene.2024.120426.
  2. Q. Wang, Y. Wang, K. Wang, J. Zhao, Y. Hu, and Y. Li. Evolution law of stress induced by pressure depletion in fractured shale reservoirs: Implications for subsequent refracturing and infill well development. Petroleum, 2024. DOI: 10.1016/j.petlm.2024.04.001.
  3. B. Zhou, Z. Chen, X. Zhao, B. Wang, H. Wang, and K. Sepehrnoori. A three-dimensional numerical well-test model for pressure transient analysis in fractured horizontal wells with secondary fractures. Physics of Fluids, Volume 227, June 2024, 120426. DOI: 10.1063/5.0203853.
  4. M. Petrosyants, V. Trifonov, E. Illarionov, and D. Koroteev. Speeding up the reservoir simulation by real time prediction of the initial guess for the Newton-Raphson's iterations. Computational Geosciences, 2024. DOI: 10.1007/s10596-024-10284-z.
  5. M.K. Marvin, A.B. Ngulde, and Z.M. Sarkinbaka. Optimal control of multilateral waterflooding wells in carbonate reservoirs with uncertainty consideration. Petroleum Science and Technology, 2024. DOI: 10.1080/10916466.2024.2326174.
  6. A.K.L. Limaluka, Y. Elakneswaran, and N. Hiroyoshi. Macroscale modeling of geochemistry influence on polymer and low-salinity waterflooding in carbonate oil reservoirs. ACS Omega, 2024. DOI: 10.1021/acsomega.3c10022 .
  7. Y. Liu, S. Yang, N. Zhang, J. Cao, and C. Guo. Simulation enhancement GAN for efficient reservoir simulation at fine scales. Mathematical Geosciences, 2024. DOI 10.1007/s11004-024-10136-7.
  8. H.U. Rashid and O. Olorode. Use of controlled fractures in enhanced geothermal systems. Advances in Geo-Energy Research, Vol. 12, No. 1, 2024. DOI: 10.46690/ager.2024.04.04.
  9. R. E. Rizzo, N. F. Inskip, H. Fazeli, P. Betlem, K. Bisdom, N. Kampman, J. Snippe, K. Senger, F. Doster, and A. Busch. Modelling geological CO2 leakage: Integrating fracture permeability and fault zone outcrop analysis, International Journal of Greenhouse Gas Control, Volume 133, 2024, 104105. DOI: 10.1016/j.ijggc.2024.104105.
  10. Q. Wang, D. Zhang, Y. Li, C. Li, and H. Tang. Numerical simulation study of CO2 storage capacity in deep saline aquifers. Science and Technology for Energy Transition, 2024. DOI: 10.2516/stet/2024005.
  11. X. Ma, J. Zhao, D. Zhou, K. Zhang, and Y. Tian. Deep graph learning-based surrogate model for inverse modeling of fractured reservoirs. Mathematics, 2024. DOI: 10.3390/math12050754.
  12. M.K. Marvin, A.B. Ngulde, and Z.M. Sarkinbaka. Comparative study on the optimal control of smart well in oil reservoir waterflooding with uncertainty. Geosystem Engineering, 2024. DOI: 10.1080/12269328.2024.2314767.
  13. J. Jiang. Simulating multiphase flow in fractured media with graph neural networks. Physics of Fluids 36, 023115 (2024). DOI: 10.1063/5.0189174.
  14. Y.Z. Wang, R.Y. Cao, Z.H. Jia, B.Y. Wang, M. Ma, and L.S. Cheng. A multi-mechanism numerical simulation model for CO2-EOR and storage in fractured shale oil reservoirs. Petroleum Science, 2024. DOI: 10.1016/j.petsci.2024.02.006.
  15. S. Anyosa, J. Eidsvik, and D. Grana. Evaluating geophysical monitoring strategies for a CO2 storage project. Computers & Geosciences, 2024. DOI: 10.1016/j.cageo.2024.105561
  16. H. Yang, R. Li, and C. Yang. Nonlinearly constrained pressure residual (NCPR) algorithms for fractured reservoir simulation. SIAM Journal on Scientific Computing, Vol. 46, Iss. 1, 2024. DOI: 10.1137/22M1516294.
  17. D. Cao, S. Ayirala, M. Han, and S. Salah. Simulation of hybrid Microsphere-SmartWater recovery process for permeable carbonates. Geoenergy Science and Engineering, 2024. DOI: 10.1016/j.geoen.2024.212696.
  18. F.V. Donzé, L. Bourdet, L. Truche, C. Dusséaux, P. Huyghe, Modeling deep control pulsing flux of native H2 throughout tectonic fault-valve systems, International Journal of Hydrogen Energy, Volume 58, pp. 1443-1456, 2024. DOI: 10.1016/j.ijhydene.2024.01.178.
  19. J. Wu, L. Zhang, Y. Liu, K. Ma, and X. Luo. Effect of displacement pressure gradient on oil–water relative permeability: experiment, correction method, and numerical simulation. Processes, 2024. DOI: 10.3390/pr12020330.
  20. B. Yan, Z. Zhong, and B. Bai. A convolutional neural network-based proxy model for field production prediction and history matching. Gas Science and Engineering, 2024. DOI: 10.1016/j.jgsce.2024.205219.
  21. M. Haugen, L. Salo-Salgado, K. Eikehaug, B. Benali, J. W. Both, E. Storvik, O. Folkvord, R. Juanes, J. M. Nordbotten, and M. A. Ferno. Physical variability in meter-scale laboratory CO2 injections in faulted geometries. Transport in Porous Media, 2024. DOI: 10.1007/s11242-023-02047-8.
  22. A. Rovelli, J. Brodie, B. Rashid, W.J. Tay, and R. Pini. Effects of core size and surfactant choice on fluid saturation development in surfactant/polymer corefloods. Energy & Fuels, 2024. DOI: 10.1021/acs.energyfuels.3c04313.
  23. Z. X. Leong, T. Zhu., and A. Y. Sun. Time-lapse seismic inversion for CO2 saturation with SeisCO2Net: An application to Frio-II site. International Journal of Greenhouse Gas Control Volume 132, February 2024, 104058. DOI: 10.1016/j.ijggc.2024.104058.
  24. Q. Zhang, H. Li, Y. Li, H. Wang, and K. Lu. A dynamic permeability model in shale matrix after hydraulic fracturing: considering mineral and pore size distribution, dynamic gas entrapment and variation in poromechanics. Processes, 2024, 12(1), 117. DOI: 10.3390/pr12010117.
  25. J. Dai, K. Tian, Z. Xue, S. Ren, T. Wang, J. Li, and S. Tian. CO2-enhanced radial borehole development of shale oil: production simulation and parameter analysis Processes, 2024, 12(1), 116. DOI: 10.3390/pr12010116.
  26. T. Esfandi, S. Sadeghnejad, and A. Jafari. Effect of reservoir heterogeneity on well placement prediction in CO2-EOR projects using machine learning surrogate models: Benchmarking of boosting-based algorithms. Geoenergy Science and Engineering, Volume 233, February 2024, 212564. DOI: 10.1016/j.geoen.2023.212564.
  27. E Sarı, and E Çiftçi. Underground hydrogen storage in a depleted gas field for seasonal storage: A numerical case study of the Tekirdağ gas field. Fuel, Volume 358, Part B, 15 February 2024, 130310. DOI: 10.1016/j.fuel.2023.130310.
  28. H.U. Rashid and O. Olorode. A continuous projection-based EDFM model for flow in fractured reservoirs. SPE Journal, 29 (01): 476–492, 2024. DOI: 10.2118/217469-PA.
2023
  1. K. Jiao, D. Han, Y. Chen, B. Bai, B. Yu, and S. Wang, The enriched-embedded discrete fracture model (nEDFM) for fluid flow in fractured porous media, Advances in Water Resources, Volume 184, 2024, 104610, DOI: 10.1016/j.advwatres.2023.104610.
  2. X. Liu, S. Geng, P. Hu, Y. Li, R. Zhu, S. Liu, Q. Ma, C. Li. Blasingame production decline curve analysis for fractured tight sand gas wells based on embedded discrete fracture model. Gas Science and Engineering, 2023. DOI: 10.1016/j.jgsce.2023.205195.
  3. V. Putra and K. Furui. Phase-field modeling of coupled thermo-hydromechanical processes for hydraulic fracturing analysis in enhanced geothermal systems. Energies, 2023. 16(24), 7942; DOI: 10.3390/en16247942.
  4. G. Cao, M. Lin, L. Zhang, L. Ji, and W. Jiang. Numerical simulation of the dynamic migration mechanism and prediction of saturation of tight sandstone oil. Science China Earth Sciences, 67, 2023. DOI: 10.1007/s11430-023-1202-1.
  5. J.O. Helland, H.A. Friis, M. Assadi, Ł. Klimkowski, and S. Nagy. Prediction of optimal production time during underground CH4 storage with cushion CO2 using reservoir simulations and artificial neural networks. Energy & Fuels, 2023
  6. E. Sarı and E Çiftçi. A numerical investigation on the utilization of a depleted natural gas field for seasonal hydrogen storage: A case study for Değirmenköy gas field. International Journal of Hydrogen Energy, 2023. DOI: 10.1016/j.ijhydene.2023.11.090
  7. D. Han, W. Zhang, K. Jiao, B. Yu, T. Li, L. Gong, S. Wang. Thermal‒hydraulic‒mechanical‒chemical coupling analysis of enhanced geothermal systems based on an embedded discrete fracture model. Natural Gas Industry B, 2023. DOI: 10.1016/j.ngib.2023.10.001.
  8. Y. Ma, Z. Kang, X. Lei, X. Chen, C. Gou, Z. Kang, and S. Wang. Coupling effect of critical properties shift and capillary pressure on confined fluids: A simulation study in tight reservoirs. Heliyon 9 (2023) e15675. DOI: 10.1016/j.heliyon.2023.e15675.
  9. A. Shojaee, S. Kord, R. Miri, and O. Mohammadzadeh. Reactive transport modeling of scale precipitation and deposition during incompatible water injection in carbonate reservoirs. Journal of Petroleum Exploration and Production Technology, 2023. DOI: 10.1007/s13202-023-01715-1.
  10. Y. Zhang, Y. Wang, J. Gao, Y. Cui, and S. Wang. Study of the influence of dynamic and static capillary forces on production in low-permeability reservoirs. Energies 2023, 16(3), 1554. DOI: 10.3390/en16031554.
  11. M. J. Dall’Aqua, E. J. R. Coutinho, E. Gildin, Z. Guo, H. Zalavadia, and S. Sankaran. Guided deep learning manifold linearization of porous media flow equations. SPE Journal, 2023. DOI: 10.2118/212204-PA.
  12. F. Meng, Y. Wang, X. Song, M. Hao, G. Qin, Y. Qi, Z. Ma, and D. Wang. Numerical simulation of fracture flow interaction based on discrete fracture model. Processes 2023, 11, 3013. DOI: 10.3390/pr11103013.
  13. S. Jia. An integrated machining learning-based workflow for CO2 sequestration optimization under geological uncertainty. International Journal of Engineering Technology and Construction, 2023, 4(2). DOI: 10.38007/IJETC.2023.040204.
  14. A. M. Hassan, E. W. Al-Shalabi, W. AlAmeri, M. S. Kamal, S. Patil, and S. M. Shakil Hussain. New insights into hybrid low salinity polymer (LSP) flooding through a coupled geochemical-based modeling approach. SPE Resevoir Evaluation & Engineering, 2023. DOI: 10.2118/210120-PA.
  15. P. Cornelissen, and J.D. Jansen. Steady-state flow through a subsurface reservoir with a displaced fault and its poro-elastic effects on fault stresses. Transport in Porous Media, 2023. DOI: 10.1007/s11242-023-02029-w.
  16. F. Nazari, S.A. Nafchi, E.V. Asbaghi, R. Farajzadeh, and V. J. Viasar. Impact of capillary pressure hysteresis and injection-withdrawal schemes on performance of underground hydrogen storage. International Journal of Hydrogen Energy. DOI: 10.1016/j.ijhydene.2023.09.136.
  17. T. Cheng, H. Yang, J. Huang, and C. Yang. Nonlinear parallel-in-time sim. ulations of multiphase flow in porous media Journal of Computational Physics, 2023. DOI: 10.1016/j.jcp.2023.112515.
  18. N. Wang, Q. Liao, H. Chang, and D. Zhang. Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network.. Computational Geosciences. DOI: 10.1007/s10596-023-10233-2.
  19. S. M. Mousavi, P. Bakhtiarimanesh, F. Enzmann, M. Kersten, and S. Sadeghnejad. Machine-learned surrogate models for efficient oil well placement under operational reservoir constraints. SPE Journal. DOI: 10.2118/217467-PA.
  20. Z. Xu, J.Chen, and J. Y. Leung. An improved dual-porosity dual-permeability modeling workflow for representing nonplanar hydraulic fractures. Gas Science and Engineering Volume 118, October 2023, 205108. DOI: 10.1016/j.jgsce.2023.205108.
  21. S. Fu, E. Chung, and L. Zhao. An efficient multiscale preconditioner for large-scale highly heterogeneous flow. SIAM Journal on Scientific Computing, 2023. DOI: https://doi.org/10.1137/22M1502859.
  22. Z. Xiang, R. Zhen, Y. Xu, S. Wang, X. Ao, Z. Chen, and J. Hu. A numerical pressure transient model of fractured well with complex fractures of tight gas reservoirs considering gas-water two phase by EDFM. Geoenergy Science and Engineering. DOI: 10.1016/j.geoen.2023.212286.
  23. J.S. Azevedo and J.A. Fernandes. The parameter inversion in coupled geomechanics and flow simulations using Bayesian inference. Journal of Computational Mathematics and Data Science. DOI: 10.1016/j.jcmds.2023.100083.
  24. L. Saló-Salgado, M. Haugen, K. Eikehaug, M. Fernø, J. M. Nordbotten, and R. Juanes. Direct comparison of numerical simulations and experiments of CO2 injection and migration in geologic media: Value of local data and forecasting capability. Transport in Porous Media. DOI: 10.1007/s11242-023-01972-y.
  25. B. Flemisch, J. M. Nordbotten, M. Fernø et al. The FluidFlower validation benchmark study for the storage of CO2. Transport in Porous Media. DOI: 10.1007/s11242-023-01977-7.
  26. T. Alyousuf, Y. Li, R. Krahenbuhl, and D. Grana. Three-axis borehole gravity monitoring for CO2 storage using machine learning coupled to fluid flow simulator. Geophysical Prospecting. DOI: 10.1111/1365-2478.13413.
  27. X Fang, Y Lv, C Yuan, X Zhu, J Guo, W Liu, and H Li. Effects of reservoir heterogeneity on CO2 dissolution efficiency in randomly multilayered formations. Energies. Vol. 16(13). DOI: 10.3390/en16135219.
  28. D. Lauzon and D. Marcotte. Joint hydrofacies-hydraulic conductivity modeling based on a constructive spectral algorithm constrained by transient head data. Hydrogeology Journal, 2023. DOI: 10.1007/s10040-023-02638-1.
  29. J Wang, J Dai, B Xie, J Du, J Li, H Liu, T Wang, Z Mu, and S Tian. Gas injection capacity of slotted liner and perforation completion in underground natural gas storage reservoirs. Processes. 11(5):1471. DOI: 10.3390/pr11051471.
  30. Y Yao, L Wang, K Wang, CD Adenutsi, Y Wang, and D Feng. A novel high-dimension shale gas reservoir hydraulic fracture network parameters optimization framework. Geoenergy Science and Engineering, Volume 229, October 2023, 212155. DOI: 10.1016/j.geoen.2023.212155.
  31. Q. Liao, G. Li, S. Tian, X. Song, G. Lei, X. Liu, W. Chen, and S. Patil. An efficient analytical approach for steady-state upscaling of relative permeability and capillary pressure. Energy, Volume 282, 1 November 2023, 128426. DOI: 10.1016/j.energy.2023.128426.
  32. H.M. Naghneh, M. Amani, A. Farhadi, and M.T. Isaai. Application of the closed loop industrial internet of things (IIoT)‐based control system in enhancing the oil recovery factor and the oil production. IET Cyber‐Physical Systems: Theory & Applications, 2023. DOI: 10.1049/cps2.12068.
  33. L. Xie, G. Li, Z. Wang, L. Cui, and M. Gong. Surrogate-assisted evolutionary algorithm with model and onfill criterion auto-configuration. IEEE Transactions on Evolutionary Computation, 2023. DOI: 10.1109/TEVC.2023.3291614.
  34. A. Kubeyev. Enhancing multi-physics modelling with deep learning: Predicting permeability through structural discontinuities. Engineering Applications of Artificial Intelligence, Volume 124, September 2023, 106562. DOI: 10.1016/j.engappai.2023.106562.
  35. W. Zhang, D. Han, B. Wang, Y. Chen, K. Jiao, L. Gong, and B. Yu. Thermal-hydraulic-mechanical-chemical modeling and simulation of an enhanced geothermal system based on the framework of extended finite element methods - Embedded discrete fracture model. Journal of Cleaner Production, June 2023, 137630. DOI: 10.1016/j.jclepro.2023.137630.
  36. X. Zhao, Z. Chen, B. Zhou, X. Liao, H. Wang, and B. Wang. Multiple flow mechanism-based numerical model for CO2 huff-n-puff in shale gas reservoirs with complex fractures. Energy & Fuels, 2023. DOI: 10.1021/acs.energyfuels.3c00931.
  37. J.A. Silva, L. Saló-Salgado, J. Patterson, G.R. Dasari, and R. Juanes. Assessing the viability of CO2 storage in offshore formations of the Gulf of Mexico at a scale relevant for climate-change mitigation. International Journal of Greenhouse Gas Control, Volume 126, June 2023, 103884. DOI: 10.1016/j.ijggc.2023.103884.
  38. N. Wang, H. Chang, X. Kong, M.O. Saar, and D. Zhang. Deep learning based closed-loop optimization of geothermal reservoir production. Renewable Energy, 2023. DOI: 10.1016/j.renene.2023.04.088.
  39. Z. Chen, B. Zhou, S. Zhang, D. Li, and K. Sepehrnoori. Pressure transient behaviors for horizontal wells with well interferences, complex fractures and two-phase flow. Geoenergy Science and Engineering, 2023. DOI: 10.1016/j.geoen.2023.211845.
  40. J. Cornelio, S. M. Razak, Y. Cho, H.-H. Liu, R. Vaidya, and B. Jafarpour. Transfer learning with prior data-driven models from multiple unconventional fields. SPE JournaD Cao, S Ayirala, M Han, S Salah - Geoenergy Science and Engineering, 2024l, 2023. DOI: 10.2118/214312-PA.
  41. P. Hu, S. Geng, X. Liu, C. Li, R. Zhu, and X. He. A three-dimensional numerical pressure transient analysis model for fractured horizontal wells in shale gas reservoirs. Journal of Hydrology, 2023. DOI: 10.1016/j.jhydrol.2023.129545
  42. J.G. Souza Debossam, G. de Souza, H.P. Amaral Souto, and A. P. Pires. Numerical simulation of single-phase two-component non-Darcy flow in naturally fractured reservoirs for enhanced gas recovery and carbon dioxide storage. Brazilian Journal of Chemical Engineering, 2023. DOI: 10.1007/s43153-023-00318-x.
  43. W. Xiong, L.H. Zhang, Y. Tian, L.X. Li, Y.L. Zhao, and Z.X. Chen. Phase equilibrium modeling for carbon dioxide capture and storage (CCS) fluids in brine using an electrolyte association equation of state. Chemical Engineering Science. April 2023, 118723. DOI: 10.1016/j.ces.2023.118723.
  44. G. Li, L. Xie, Z. Wang, H. Wang, and M. Gong. Evolutionary algorithm with individual-distribution search strategy and regression-classification surrogates for expensive optimization. Information Sciences, Volume 634, 2023. DOI: 10.1016/j.ins.2023.03.101.
  45. X. Zhao, Z. Chen, B. Wang, X. Liao, D. Li, and B. Zhou. A multi-medium and multi-mechanism model for CO2 injection and storage in fractured shale gas reservoirs. Fuel, Volume 345, 2023, 128167. DOI: 10.1016/j.fuel.2023.128167.
  46. L. Xin, X. Rao, X. Peng, Y. Xu, and J. Chen. Production dynamic prediction method of waterflooding reservoir based on deep convolution generative adversarial network (DC-GAN). Energy Engineering 2022, 119(5), 1905-1922. DOI: 10.32604/ee.2022.019556.
  47. C. Xiao, S. Zhang, X. Ma, T. Zhou, T. Hou, and F. Chen. Deep-learning-generalized data-space inversion and uncertainty quantification framework for accelerating geological CO2 plume migration monitoring, Geoenergy Science and Engineering, 2023, 211627. DOI: 10.1016/j.geoen.2023.211627.
  48. P.K. Gupta, B. Gharedaghloo, and J.S. Price. Multiphase flow behavior of diesel in bog, fen, and swamp peats. Journal of Contaminant Hydrology, 2023, 104162. DOI: 10.1016/j.jconhyd.2023.104162.
  49. D. Wang, F. Liu, G. Li, S. He, K. Song, and J. Zhang. Characterization and dynamic adjustment of the flow field during the late stage of waterflooding in strongly heterogeneous reservoirs. Energies 2023, 16, 831. DOI: 10.3390/en16020831.
  50. F. Jiang, Y. Guo, T. Tsuji, Y. Kato, M. Shimokawara, L. Esteban, M. Seyyedi, M. Pervukhina, M. Lebedev, and R. Kitamura. Upscaling permeability using multiscale X‐ray‐CT images with digital rock modeling and deep learning techniques. Water Resources Research, 2023. DOI: 10.1029/2022WR033267-
  51. A. Alqahtani, X. He, B. Yan, and H. Hoteit. Uncertainty analysis of CO2 storage in deep saline aquifers using machine learning and bayesian optimization. Energies, 16(4), 1684, 2023. DOI: 10.3390/en16041684
  52. M. Zeynalli, E. W. Al-Shalabi, and W. AlAmeri. An extended unified viscoelastic model for predicting polymer apparent viscosity at different shear rates. SPE Reservoir Evaluation & Engineering, 26 (01): 99–121, 2023. DOI: 10.2118/206010-PA.
  53. Z. Guo, S. Sankaran, and W. Sun. Reservoir modeling, history matching, and characterization with a reservoir graph network model. SPE Reservoir Evaluation & Engineering, 2023. DOI: 10.2118/209337-PA.
  54. M. Ahmadinia, M. Sadri, B. Nobakht, and S.M. Shariatipour. Uncertainty quantification of the CO2 storage process in the Bunter Closure 36 model. Sustainability, 2023, , 15(3), 2004. DOI: 10.3390/su15032004.
  55. Y. Wang, D. Fernàndez-Garcia, and M. W.Saaltink. Modeling reactive multi-component multi-phase flow for Geological Carbon Sequestration (GCS) with Matlab. Computers & Geosciences, Volume 172, March 2023, 105300. DOI: 10.1016/j.cageo.2023.105300.
  56. J. Zhou, H. Wang, C. Xiao, and S. Zhang. Hierarchical surrogate-assisted evolutionary algorithm for integrated multi-objective optimization of well placement and hydraulic fracture parameters in unconventional shale gas reservoir. Energies 2023, 16(1), 303. DOI: 10.3390/en16010303.
  57. C. Xiao, S. Zhang, X. Ma, T. Zhou, T. Hou, and F. Chen. Data-driven model predictive control for closed-loop refracturing design and optimization in naturally fractured shale gas reservoir under geological uncertainty. Computers & Chemical Engineering, Volume 169, January 2023, 108096. DOI: 10.1016/j.compchemeng.2022.108096.
  58. D. Losapio and A. Scotti. Local embedded discrete fracture model (LEDFM). Advances in Water Resources, Volume 171, January 2023, 104361. DOI: 10.1016/j.advwatres.2022.104361
  59. A. Dell'Oca, A. Manzoni, M. Siena, N.G. Bona, L. Moghadasi, M. Miarelli, D. Renna, and A. Guadagnini. Stochastic inverse modeling of transient laboratory-scale three-dimensional two-phase core flooding scenarios. International Journal of Heat and Mass Transfer, vol. 202, 2023, 123716. DOI: 10.1016/j.ijheatmasstransfer.2022.123716.
2022
  1. C. Li, C. Fang, Y. Huang, H. Zuo, Z. Zhang, and S. Wang. Infill well placement optimization for secondary development of waterflooding oilfields with SPSA algorithm. Frontiers in Energy Research, 2022. DOI: 10.3389/fenrg.2022.1005749.
  2. L. Saló-Salgado, J.S. Davis, and R. Juanes. Fault permeability from stochastic modeling of clay smears. Geology, 2022. DOI: 10.1130/G50739.1.
  3. J.J. Hu, C. Siefert, and R.S. Tuminaro. Smoothed aggregation for difficult stretched mesh and coefficient variation problems. Numerical Linear Algebra with Applications 10.1002/nla.2442.
  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. Geomech. Geophys. Geo-Energy Geo-Resour. 2022, 8 (1), 2, DOI: 10.1007/s40948-021-00305-x.
  5. Q. Hu, D. Grana, and KA Innanen. Feasibility of seismic time-lapse monitoring of CO2 with rock physics parameterized full waveform inversion. Geophysical Journal International, 2022. DOI: 10.1093/gji/ggac462.
  6. H. Xiao, S. Geng, H. Luo, L. Song, H. Wang, and X. He. Numerical simulation of fractured horizontal well considering threshold pressure gradient, non‐darcy flow, and stress sensitivity. Energy Science & Engineering, 2022. DOI: 10.1002/ese3.1365.
  7. R. J. N. C. Junior, J. D. L. Silva, G. E. S. D. Castro, A. C. M. Almeida. Análise da eficiência no uso de software de simulação de reservatórios para a determinação da permeabilidade na produção de petróleo. Open Science Research VIII, Chapter 82, pp. 1111-1127, 2022, Editora Científica Digital. DOI: 10.37885/221211198.
  8. Y. Wang, S.F. Estefen, and M.I. Lourenço. A fully integrated reservoir/pipeline network model and its application on the evaluation of subsea water separation performance. Journal of Petroleum Science and Engineering, 2022. DOI: 10.1016/j.petrol.2022.111140.
  9. E. M. Ramos, M. R. Borges, G. A. Giraldi, B. Schulze, and F. Bernardo. Prediction of permeability of porous media using optimized convolutional neural networks. Computational Geosciences, 2022. DOI: 10.1007/s10596-022-10177-z.
  10. E. Ranaee, F. Inzoli, M. Riva, and A. Guadagnini. Sensitivity-based parameter calibration of single- and dual-continuum coreflooding simulation models Transport in Porous Media, 2022. DOI: 10.1007/s11242-022-01854-9.
  11. J.Chen, Z. Xu, and J. Y. Leung. Analysis of fracture interference – Coupling of flow and geomechanical computations with discrete fracture modeling using MRST. Journal of Petroleum Science and Engineering, October 2022, 111134. DOI: 10.1016/j.petrol.2022.111134.
  12. O. Amrollahinasab, S. Azizmohammadi, and H. Ott. Simultaneous interpretation of SCAL data with different degrees of freedom and uncertainty analysis. Computers and Geotechnics, October 2022. DOI: 10.1016/j.compgeo.2022.105074.
  13. D. Yang and C. V. Deutsch. Managing risk in well placement optimization within an expected utility framework. SPE Reservoir Evaluation & Engineering, 2022. DOI: 10.2118/212305-PA.
  14. M. K. Marvin, A. B. Ngulde, and A. M. Abubakar. Pattern effect for oil reservoir waterflooding using smart well. Applied Engineering, pp 50-56, October 2022. DOI: 10.11648.j.ae.20220602.13.
  15. L. Gutierrez-Sosa, S. Geiger, and F. Doster. Poro-mechanical coupling for flow diagnostics. Transport in Porous Media, 2022. DOI: 10.1007/s11242-022-01857-6.
  16. X. Cui,C. Jiang, B. Nassichuk, and J. Wilson. Characteristics of canister core desorption gas from unconventional reservoirs and applications to improve assessment of hydrocarbons-in-place. Minerals 2022, 12(10), 1226. DOI: 10.3390/min12101226.
  17. R. Alguliyev, R. Aliguliyev, Y. Imamverdiyev, L. Sukhostat. History matching of petroleum reservoirs using deep neural networks. Intelligent Systems with Applications, 2022, 200128. DOI: 10.1016/j.iswa.2022.200128.
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2021
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2020
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2018
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  4. A. D. Obembe, S. A. Abu-Khamsin, M. E. Hossain, K. Mustapha. Analysis of subdiffusion in disordered and fractured media using a Grünwald-Letnikov fractional calculus model. Computational Geosciences, Volume 22, Issue 5, pp. 1231 -1250, 2018. DOI: 10.1007/s10596-018-9749-1
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  9. S. Trehan and L.J. Durlofsky. Machine-learning-based estimation of upscaling error, with application to uncertainty quantification. Computational Geosciences, Volume 22, Issue 4, pp. 1093 -1113, 2018. DOI: 10.1007/s10596-018-9740-x
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  12. M. Schneider, B. Flemisch, R. Helmig, K. Terekhov, and H. Tchelepi. Monotone nonlinear finite-volume method for challenging grids. Computational Geosciences, Volume 22, Issue 2, pp. 565 -586, April 2018,. DOI: 10.1007/s10596-017-9710-8
  13. K. Zhang, X. Ma, Y. Lie, H. Wu, C. Cui, X. Zhang, H. Zhang, and J. Yao. Parameter prediction of hydraulic fracture for tight reservoir based on micro-seismic and history matching. Fractals, Volume 26, Number 2, 1840009, 2018. DOI: 10.1142/S0218348X18400091
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  18. H.Zanbouri and K.Salahshoor. Development of robust surrogate model for economic performance prediction of oil reservoir production under waterflooding process. Journal of Petroleum Science and Engineering. Volume 165, pp. 496-504, 2018. DOI: 10.1016/j.petrol.2018.01.065
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2017
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  10. 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
  11. 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.
  12. 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
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2016
  1. L. Zhao, H. Jiang, J. Li, X. Lu, Z. Zhang, J. Li, and Y. Pei. Numerical simulation study of thermal degradation in polymer flooding based on streamlines. Petroleum Geology and Recovery Efficiency, 2016, 23(6):76-81.
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2015
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  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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