Research Methods and Prospects of Oil and Gas Reservoir Numerical Simulation
DOI:
https://doi.org/10.54097/ije.v3i2.009Keywords:
Hydrocarbon Reservoir Numerical Simulation, Numerical Simulation Method, Numerical Simulation ApplicationAbstract
This paper briefly describes the development process of oil and gas reservoir numerical simulation, introduces the method and application of oil and gas reservoir numerical simulation, and predicts the future development trend of oil and gas reservoir numerical simulation on this basis, To help extract oil better and more efficiently.
Downloads
References
Tagliazucchi M, Szleifer I. Transport mechanisms in nanopores and nanochannels: Can we mimic nature? Mater Today, 2015, 18: 131–142.
Yao J, Zhao X C. Digital Core and Pore Scale Simulation Theory (in Chinese). Beijing: Petroleum Industry Press, 2010.
Wenlong Wang, Yanshu Yin. Research progress and development trend of reservoir modeling [J]. Journal of Geology, 2017, 41(01):97-102.
Xiangyang Hu, Qihua Xiong, Shenghe Wu. Advances in reservoir modeling methods [J]. Journal of the University of Petroleum (Natural Science Edition),2001(01):107-112+0.
Ma G D. Numerical study of multiphase flow in porous media based on lattice Boltzmann method [D]. China university of petroleum (east China), 2019.
Mingchuan Li, Shuanshi Fan, Mingjing Lu. One-dimensional mass transfer mathematical model of hot water decomposition front of natural gas hydrate [J]. Journal of Chemical Engineering of Universities,2014,28(02):223-228.
Opral 1 and Zahradnik J.Elasastic Finite-difference method for irregular grids. Geophysics, 1999, 64 (1): 240-250 finite difference Method.
Crouch S L, Starfield A M. Crouch S L, Starfield A M. Boundary element methods in solid mechanics [M]. London: Goerge Allen and Unwin Publishers, 1983. Boundary element methods in solid mechanics.
Chao Tang, Xiaofan Chen, Zhimin Du et al. Two-phase flow model in fractured reservoir based on finite volume method [J]. Acta Petrolei Sinica,2018,39(08):924-936.
Shaohua Li, Changmin Zhang, Kexiang Lin et al. Establishment of several prototype models in reservoir modeling [J]. Sedimentary & Tethys Geology,2004(03):102-107.
Qiang Zhang, Ling Zhang, Wei Wang et al. Uncertainty analysis method in geological reserves evaluation of overseas oilfields: A case study of Oilfield A [J]. Contemporary Chemical Industry Research,2022, No.110(09):72-74.
Iglesias M A, Dawson C.The representer method for state and parameter estimation in single-phase Darcy flow[J].Computer Methods in Applied Mechanics and Engineering 2007,196(45-48):4577-4596.
Baird J. Dawson C. A posteriori error estimation of the representer method for single-phase Darcy flow[J]. Computer Methods in Applied Mechanics & Engineering, 2007.196 (9/12): 1623-1632.
Przybysz-Jarnut J K. Hanea R G, Jansen J D, et al. Application of the representer method for parameter estimation in numerical reservoir models[J].Computational Geosciences, 2007, 11(1):73-85.
Yanbin Sun. Based on the adjoint method of water flooding reservoir production optimization and parameter estimation [D]. Southwest petroleum university, 2020. The DOI: 10.27420 /, dc nki. Gxsyc. 2020.000004.
Jianmin Yang, Bo Quan, Wentong Zhang et al. Uncertainty analysis of 3D geological model based on Monte Carlo simulation [J]. Fault-block Oil & Gas Field,20,27(03):309-312.
Wang Lin, Hongfu Fan, Lin Yan et al. Optimization simulation of injection huff and puff parameters in tight reservoirs: A case study of Fuyu Reservoir in Jilin Province [J]. Chinese Science and Technology Papers,2019,14(09):937-942.
Yu Long, Dehua Liu, Bo Hu. Strong heterogeneity sandstone reservoir waterflood parameters optimization analysis [J]. Journal of modern chemical industry, 2019 (04): 13. 782-786.
Jianjian Liu. Research on production performance prediction and dynamic parameter optimization of similar reservoirs based on Machine learning [D]. China university of petroleum (Beijing), 2021. DOI: 10.27643 /, dc nki. Gsybu. 2021.001033.
Merdeka, M.G.; Ridha, S.; Negash, B.M.; Ilyas, S.U. Reservoir Performance Prediction in Steam Huff and Puff Injection Using Proxy Modelling. [J] Applied Sciences. Volume 12, Issue 6 . 2022. PP 3169-3169.
Hailin Fu. Application analysis of reservoir management Technology in petroleum extraction Technology [J]. China Petroleum and Chemical Industry Standards and Quality,2018, 38 (15):153-154.
Yufeng Yuan, Kaixuan Rong, Jie Gao et al. Study on multi-component hot fluid huff and water channeling in heavy oil reservoirs with edge and bottom water [J]. Petrochemical Applications,2022,41(08):24-28.
NAGEL T, SHAO H, SINGH A K, et al. Non-equilibrium Thermochemical Heat Storage in Porous Media: Part 1 – Conceptual Model [J]. Energy, 2013, 60: 254–270.
SEITZ G, HELMIG R, CLASS H. A Numerical Modeling Study on the Influence of Porosity Changes During Thermochemical Heat Storage [J]. Applied Energy, 2020, 259: 114152.
Huihuang Fang, Shuxun Sang, Shiqi Liu. Numerical simulation of enhancing coalbed methane recovery by injecting CO2 with heat injection [J]. Petroleum Science, 2019,16 (1): 32-43.
CONNELL L Luke. Coupled flow and geomechanical processes during gas production from coal seams [J]. International Journal of Coal Geology, 2009,79 (1-2) : 18-28.
Xiaolan Li, Xiankui Zeng, Dong Wang et al. Uncertainty analysis of groundwater simulation parameters based on optimization-adaptive sparse grid replacement model [J]. Journal of jilin university (earth sciences), 2022,52 (4): 1234-1243. The DOI: 10.13278 / j. carol carroll nki jjuese. 20210067.
Youxi Le, Banke Sun. A hybrid genetic algorithm for automatic identification of reservoir permeability distribution [J]. Natural Gas Exploration and Development,2006(03):58-61+65+73.
SHI Y H, EBERHART R C. Parameter selection in particle swarm optimization[C]//Proceedings of sixth International Symposium on Micro Machine and Human Science. Nagoya, Japan: [s. n.], 1995: 66-73.
PU Z q, YI J q, LIU Z, et al. A review of collaborative knowledge and Data driven swarm intelligent decision making[J]. Acta Automatica Sinica, 2022, 48(3): 1-17.
Gang Mei. Design and application of 3D visualization Technology in oil-gas field joint station [J]. Petrochemical Automation,2021,57(S1):120-122.
Jinning Zhang, Energy Energy, Ma Xiao et al. Practice teaching, the application of virtual reality technology in geology [J]. Journal of education, 2022, 11 (25): September 11 + 18. DOI: 10.16070 / j.carol carroll nki cn45-1388 / g4s 2022. 25. 002.
Xinle Fu. Research on interactive Visualization of Fine 3D Spatial Data [D]. Beijing University of Civil Engineering and Architecture, 2014.
