Abstract
Numerical methods are often used to simulate and analyze flow and transport in heterogeneous reservoirs. However, they are limited by computational restrictions including small time steps and fine grid size to avoid numerical dispersion. The ability to perform efficient coarse-scale simulations that capture the uncertainties in reservoir attributes and transport parameters introduced by scale-up remains challenging. A novel method is formulated to properly represent sub-grid variability in coarse-scale models. First, multiple sub-grid realizations depicting detailed fine-scale heterogeneities and of the same physical sizes as the transport modeling grid block are subjected to random walk particle tracking (RWPT) simulation, which is not prone to numerical dispersion. To capture additional unresolved heterogeneities occurring below even the fine scale, the transition time is sampled stochastically in a fashion similar to the continuous time random walk (CTRW) formulation. Coarse-scale effective dispersivities and transition time are estimated by matching the corresponding effluent history for each realization with an equivalent medium consisting of averaged homogeneous rock properties. Probability distributions of scale-up effective parameters conditional to particular averaged rock properties are established by aggregating results from all realizations. Next, to scale-up porosity and permeability, volume variance at the transport modeling scale is computed corresponding to a given spatial correlation model; numerous sets of “conditioning data” are sampled from probability distributions whose mean is the block average of the actual measured values and the variance is the variance of block mean. Multiple realizations at the transport modeling scale are subsequently constructed via stochastic simulations. The method is applied to model the tracer injection process. Results obtained from coarse-scale models where properties are populated with the proposed approach are in good agreement with those obtained from detailed fine-scale models. With the advances in nanoparticle technology and its increasing application in unconventional reservoirs, the method presented in this study has significant potential in analyzing tracer tests for characterization of complex reservoirs and reliable assessment of fluid distribution. The approach can also be employed to study scale-dependent dispersivity and its impacts in miscible displacement processes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Bibliography
Berkowitz B, Klafter J, Metzler R, Scher H (2002) Physical pictures of transport in heterogeneous media: advection-dispersion, random-walk, and fractional derivative formulations. Water Resour Res 38(10):W1191
Berkowitz B, Cortis A, Dentz M, Scher H (2006) Modeling non-Fickian transport in geological formations as a continuous time random walk. Rev Geophys 44(2)
Cortis A, Berkowitz B (2005) Computing “anomalous” contaminant transport in porous media: the CTRW MATLAB toolbox. Ground Water 43(6):947–950
Cortis A, Gallo C, Scher H, Berkowitz B (2004) Numerical simulation of non-Fickian transport in geological formations with multiple-scale heterogeneities. Water Resour Res 40(4)
Delay F, Ackerer P, Danquigny C (2005) Simulating solute transport in porous or fractured formations using random walk particle tracking. Vadose Zone J 4(2):360–379
Dentz M, Cortis A, Scher H, Berkowitz B (2004) Time behavior of solute transport in heterogeneous media: transition from anomalous to normal transport. Adv Water Resour 27(2):155–173
Gao G, Zhan H, Feng S, Huang G, Mao X (2009) Comparison of alternative models for simulating anomalous solute transport in a large heterogeneous soil column. J Hydrol 377(3):391–404
John AK (2008) Dispersion in large scale permeable media (Dissertation)
Journel AG, Huijbregts CJ (1978) Mining geostatistics. Academic, London
Kinzelbach W (1986) Groundwater modelling: an introduction with sample programs in BASIC, vol 25. Elsevier, Amsterdam
Kreft A, Zuber A (1978) On the physical meaning of the dispersion equation and its solutions for different initial and boundary conditions. Chem Eng Sci 33(11):1471–1480
LaBolle EM, Fogg GE, Tompson AF (1996) Random-walk simulation of transport in heterogeneous porous media: local mass-conservation problem and implementation methods. Water Resour Res 32(3):583–593
Lake LW, Srinivasan S (2004) Statistical scale-up of reservoir properties: concepts and applications. J Pet Sci Eng 1-2:27–39
Leung JY, Srinivasan S (2011) Analysis of uncertainty introduced by scaleup of reservoir attributes and flow response in heterogeneous reservoirs. SPE J 16(3):713–724
Li L, Zhou H, Gómez-Hernández JJ (2011) A comparative study of three-dimensional hydraulic conductivity upscaling at the macro-dispersion experiment (MADE) site, Columbus Air Force Base, Mississippi (USA). J Hydrol 404(3):278–293
Margolin G, Dentz M, Berkowitz B (2003) Continuous time random walk and multirate mass transfer modeling of sorption. Chem Phys 295(1):71–80
Rhodes M, Bijeljic B, Blunt MJ (2009) A rigorous pore-to-field-scale simulation method for single-phase flow based on continuous-time random walks. SPE J 14(01):88–94
Salamon P, Fernàndez-Garcia D, Gómez-Hernández JJ (2006) A review and numerical assessment of the random walk particle tracking method. A review and numerical assessment of the random walk particle tracking method. J Contam Hydrol 87(3):277–305
Salamon P, Fernandez-Garcia D, Gómez-Hernández JJ (2007) Modeling tracer transport at the MADE site: the importance of heterogeneity. Water Resour Res 43(8)
Srinivasan G, Tartakovsky DM, Dentz M, Viswanathan H, Berkowitz B, Robinson BA (2010) Random walk particle tracking simulations of non-Fickian transport in heterogeneous media. J Comput Phys 229(11):4304–4314
Tompson AF, Gelhar LW (1990) Numerical simulation of solute transport in three-dimensional, randomly heterogeneous porous media. Water Resour Res 26(10):2541–2562
Vishal V, Leung JY (2015) Modeling impacts of subscale heterogeneities on dispersive solute transport in subsurface systems. J Contam Hydrol 182:63–77
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Vishal, V., Leung, J.Y. (2017). Statistical Scale-Up of Dispersive Transport in Heterogeneous Reservoir. In: Gómez-Hernández, J., Rodrigo-Ilarri, J., Rodrigo-Clavero, M., Cassiraga, E., Vargas-Guzmán, J. (eds) Geostatistics Valencia 2016. Quantitative Geology and Geostatistics, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-46819-8_50
Download citation
DOI: https://doi.org/10.1007/978-3-319-46819-8_50
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-46818-1
Online ISBN: 978-3-319-46819-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)