An exploratory multi-scale framework to reservoir digital twin

Tao Zhang, Shuyu Sun

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In order to make full use of the information provided in the physical reservoirs, including the production history and environmental conditions, the whole life cycle of reservoir discovery and recovery should be considered when mapping in the virtual space. A new concept of reservoir digital twin and the exploratory multi-scale framework is proposed in this paper, covering a wide range of engineering processes related with the reservoirs, including the drainage, sorption and phase change in the reservoirs, as well as extended processes like injection, transportation and on-field processing. The mathematical tool package for constructing the numerical description in the digital space for various engineering processes in the physical space is equipped with certain advanced models and algorithms developed by ourselves. For a macroscopic flow problem, we can model it either in the Navier-Stokes scheme, suitable for the injection, transportation and oil-water separation processes, or in the Darcy scheme, suitable for the drainage and sorption processes. Lattice Boltzmann method can also be developed as a special discretization of the Navier-Stokes scheme, which is easy to be coupled with multiple distributions, for example, temperature field, and a rigorous Chapman-Enskog expansion is performed to show the equivalence between the lattice Bhatnagar-Gross-Krook formulation and the corresponding Navier-Stokes equations and other macroscopic models. Based on the mathematical toolpackage, for various practical applications in petroleum engineering related with reservoirs, we can always find the suitable numerical tools to construct a digital twin to simulate the operations, design the facilities and optimize the processes.

Cited as: Zhang, T., Sun, S. An exploratory multi-scale framework to reservoir digital twin. Advances in Geo-Energy Research, 2021, 5(3): 239-251, doi: 10.46690/ager.2021.03.02


Digital twin, reservoir simulation, multi-scale framework, oil-water separation

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Abe, T. Derivation of the lattice Boltzmann method by means of the discrete ordinate method for the Boltzmann equation. Journal of Computational Physics, 1997, 131(1): 241-246.

Boschert, S., Rosen, R. Mechatronic Futures, in Digital Twin—the Simulation Aspect, edited by H. Peter and B. David, Springer, Cham, pp. 59-74, 2016.

Chen, H., Kou, J., Sun, S., et al. Fully mass-conservative IMPES schemes for incompressible two-phase flow in porous media. Computer Methods in Applied Mechanics and Engineering, 2019, 350: 641-663.

Chorin, A. J. Numerical solution of the Navier-Stokes equations. Mathematics of Computation, 1968, 22(104): 745-762.

Guermond, J. L., Minev, P., Shen, J. An overview of projection methods for incompressible flows. Computer Methods in Applied Mechanics and Engineering, 2006, 195(44-47): 6011-6045.

He, B., Bai, K. -J. Digital twin-based sustainable intelligent manufacturing: A review. Advances in Manufacturing, 2021, 9(1): 1-21.

Khasanov, M., Krasnov, F. Digital twin of a research organization: Approaches and methods. Paper SPE 198372 Presented at SPE Annual Caspian Technical Conference, Baku, Azerbaijan, 16-18 October, 2019.

Kou, J., Sun, S. A new treatment of capillarity to improve the stability of IMPES two-phase flow formulation. Computers and Fluids, 2010, 39(10): 1923-1931.

Kritzinger, W., Karner, M., Traar, G., et al. Digital Twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine, 2018, 51(11): 1016-1022.

Mayani, M. G., Baybolov, T., Rommetveit, R., et al. Optimizing drilling wells and increasing the operation efficiency using digital twin technology. Paper SPE 199566 Presented at IADC/SPE International Drilling Conference and Exhibition, Galveston, Texas, 3-5 March, 2020.

Qi, Q., Tao, F. Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison. IEEE Access, 2018, 6: 3585-3593.

Qian, Y., d’Humières, D., Lallemand, P. Lattice BGK models for Navier-Stokes equation. Europhysics Letters, 1992, 17(6): 479-484.

Rao, S. V. Using a digital twin in predictive maintenance. Journal of Petroleum Technology, 2020, 72(8): 42-44.

Shao, G., Helu, M. Framework for a digital twin in manufacturing: Scope and requirements. Manufacturing Letters, 2020, 24: 105-107.

Spiegel, E. A., Veronis, G. On the Boussinesq approximation for a compressible fluid. The Astrophysical Journal, 1960, 131: 442-447.

Sun, S., Zhang, T. A 6M digital twin for modeling and simulation in subsurface reservoirs. Advances in Geo-Energy Research, 2020, 4(4): 349-351.

Tao, F., Cheng, J., Qi, Q., et al. Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Manufacturing Technology, 2018, 94(9): 3563-3576.

Thoresen, K. E., Kyllingstad, Å., Hovland, S., et al. Using an advanced digital twin to improve downhole pressure control. Paper SPE 194088 Presented at SPE/IADC International Drilling Conference and Exhibition, The Hague, The Netherlands, 5-7 March, 2019.

Wanasinghe, T. R., Wroblewski, L., Petersen, B. K., et al. Digital twin for the oil and gas industry: Overview, research trends, opportunities, and challenges. IEEE Access, 2020, 8: 104175-104197.

Zhang, T., Salama, A., Sun, S., et al. A compact numerical implementation for solving Stokes equations using matrix-vector operations. Procedia Computer Science, 2015, 51: 1208-1218.

Zhang, T., Sun, S. A Compact and Efficient Lattice Boltzmann Scheme to Simulate Complex Thermal Fluid Flows, in Computational Science-ICCS 2018, edited by Y. Shi, H. Fu, Y. Tian, et al., Springer, Cham, pp. 149-162, 2018.

Zhou, G., Zhang, C., Li, Z., et al. Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing. International Journal of Production Research, 2020, 58(4): 1034-1051.

Zhuang, C., Gong, J., Liu, J. Digital twin-based assembly data management and process traceability for complex products. Journal of Manufacturing Systems, 2021, 58: 118-131.


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