Abstract
To obtain the real physical model characterizing the pore structure of coal rocks and further explore the rules governing the flow of coalbed methane (CBM) using numerical simulation, we proposed a sequential method from real coal model to computer-aided designed (CAD) coal model to finite element coal model. First, six different coal samples were scanned using \(\upmu \)CT225kVFCB CT system. The obtained CT data were subject to threshold segmentation using the compensated digital terrain model and a coal model in STL format was established. Then, we elaborated a reverse engineering method to convert the coal model into a CAD coal model. Lastly, we obtained the finite element coal model after setting the boundary conditions with CFX software, numerically simulated CBM flow at 30 different pressure gradients based on the finite element coal model and analyzed the impacts of effective porosity on permeability and seepage velocity of CBM. The results showed that (1) at the microscale (\({<}100\,\upmu \hbox {m}\)), the seepage velocity and pressure gradient were in agreement with the Forchheimer law of high-speed nonlinear seepage; (2) permeability of CBM shows a fluctuating, but not absolute increase with effective porosity increasing; (3) at the same pressure gradient, the overall seepage velocity of CBM increases with the effective porosity increasing, but declines with non-Darcy flow coefficient increasing; (4) the non-Darcy flow coefficient reduces with both effective porosity and permeability increasing. Fitting to power function analysis shows that compared with permeability, the effective porosity has more significant impact on the non-Darcy flow coefficient.
Similar content being viewed by others
References
Van Geet, M.; Swennen, R.; David, P.: Quantitative coal characterisation by means of microfocus X-ray computer tomography, colour image analysis and back-scattered scanning electron microscopy. Int. J. Coal Geol. (2001). doi:10.1016/S0166-5162(01)00006-4
Nie, B.; He, X.; Li, X.; Chen, W.; Hu, S.: Meso-structures evolution rules of coal fracture with the computerized tomography scanning method. Eng. Fail. Anal. (2014). doi:10.1016/j.engfailanal.2013.10.007
Li, S.; Tang, D.Z.; Xu, H.; Yang, Z.: Advanced characterization of physical properties of coals with different coal structures by nuclear magnetic resonance and X-ray computed tomography. Comput. Geosci. (2012). doi:10.1016/j.cageo.2012.01.004
Forchheimer, P.: Wasserbewegung durch Boden. Z. Ver. Dtsch. Ing. 45, 1781–1788 (1901)
Guo, X.; Fu, Y.; Du, Z.M.; Shu, Z.Z.: Coupled flow simulation in coalbed methane reservoirs. SPE 91397. (2004). doi:10.2118/91397-MS
Wang, J.G.; Liu, J.; Kabir, A.: Combined effects of directional compaction, non-Darcy flow and anisotropic swelling on coal seam gas extraction. Int. J. Coal Geol. (2013). doi:10.1016/j.coal.2013.01.009
Ye, Z.H.; Chen, D.; Wang, J.G.: Evaluation of the non-Darcy effect in coalbed methane production. Fuel (2014). doi:10.1016/j.fuel.2013.12.019
Wang, X.Q.; Wang, Z.M.; Zeng, Q.S.; Yang, G.; Chen, T.; Guo, X.: Non-Darcy effect on fracture parameters optimization in fractured CBM horizontal well. J. Nat. Gas Sci. Eng. (2015). doi:10.1016/j.jngse.2015.10.010
Jeong, N.; Choi, D.H.; Lin, C.L.: Prediction of Darcy–Forchheimer drag for micro-porous structures of complex geometry using the lattice Boltzmann method. J. Micromech. Microeng. (2006). doi:10.1088/0960-1317/16/10/042
Chai, Z.; Shi, B.; Lu, J.; Guo, Z.: Non-Darcy flow in disordered porous media: a lattice Boltzmann study. Comput. Fluids (2010). doi:10.1016/j.compfluid.2010.07.012
Sukop, M.C.; Huang, H.; Alvarez, P.F.; Variano, E.A.; Cunningham, K.J.: Evaluation of permeability and nonc-Darcy flow in vuggy macroporous limestone aquifer samples with lattice Boltzmann methods. Water Resour. Res. (2013). doi:10.1029/2011WR011788
Sheikholeslami, M.: Lattice Boltzmann method simulation for MHD non-Darcy nanofluid free convection. Physica B (2017). doi:10.1016/j.physb.2017.04.029
Yoo, D.J.: Three-dimensional surface reconstruction of human bone using a B-spline based interpolation approach. Comput. Aided Des. (2011). doi:10.1016/j.cad.2011.03.002
Zhu, X.L.; Ai, S.G.; Lu, X.F.; Cheng, K.; Ling, X.; Zhu, L.X.; Liu, B.: Collapse models of aluminum foam sandwiches under static three-point bending based on 3D geometrical reconstruction. Comput. Mater. Sci. (2014). doi:10.1016/j.commatsci.2013.12.055
He, X.M.: Coal Chemistry. Metallurgical Industry Press, Beijing (2010)
Razak, K.A.; Santangelo, M.; Van Westen, C.J.; Straatsma, M.W.; De Jon, S.M.: Generating an optimal DTM from airborne laser scanning data for landslide mapping in a tropical forest environment. Geomorphology (2013). doi:10.1016/j.geomorph.2013.02.021
Bonetto, S.; Facello, A.; Ferrero, A.M.; Umili, G.: A tool for semi-automatic linear feature detection based on DTM. Comput. Geosci. (2015). doi:10.1016/j.cageo.2014.10.005
Maguya, A.S.; Junttila, V.; Kauranne, T.: Adaptive algorithm for large scale DTM interpolation from lidar data for forestry applications in steep forested terrain. ISPRS J. Photogramm. (2013). doi:10.1016/j.isprsjprs.2013.08.005
Polat, N.; Uysal, M.: Investigating performance of Airborne LiDAR data filtering algorithms for DTM generation. Measurement. (2015). doi:10.1016/j.measurement.2014.12.017
Taud, H.; Martinez-Angeles, R.; Parrot, J.F.; Hernandez-Escobedo, L.: Porosity estimation method by X-ray computed tomography. J. Petrol. Sci. Eng. (2005). doi:10.1016/j.petrol.2005.03.009
Bazilevs, Y.; Calo, V.M.; Cottrell, J.A.; Evans, J.A.; Hughes, T.J.R.; Lipton Scott, M.A.; Sederberg, T.W.: Isogeometric analysis using T-splines. Comput. Method Appl. Mech. Eng. (2010). doi:10.1016/j.cma.2009.02.036
Li, Q.; Gao, S.S.; Liu, H.X.; Ye, L.Y.; Gai, Z.H.: Core permeability calculation methods and application scopes. Nat. Gas Ind. 35(3), 68–73 (2015). doi:10.3787/j.issn.1000-0976.2015.03.010
Ji, W.D.; Yang, C.H.; Liu, W.; Li, M.M.: Experimental investigation on meso-pore structure properties of bedded salt rock. Chin. J. Rock Mech. Eng. 32(10), 2036–2044 (2013)
Li, M.L.; Li, W.Q.: Geological Foundation of Oil and Gas Field Development. Petroleum Industry Press, Beijing (1981)
Li, S.C.; Miao, X.X.; Chen, Z.Q.; Mao, X.B.: Experimental study on seepage properties of non-Darcy flow in confined broken rocks. Eng. Mech. 25(4), 85–92 (2008)
Huang, X.W.; Tang, P.; Miao, X.X.; Chen, Z.Q.: Testing study on seepage properties of broken sandstone. Rock Soil Mech. 26(9), 1385–1388 (2005)
Johnson, T.W.; Taliaferro, D.B.: Flow of Air and Natural Gas Through Porous Media. Bureau of Mines, Bartlesville (1938)
Straughan, B.: Structure of the dependence of Darcy and Forchheimer coefficients on porosity. Int. J. Eng Sci. (2010). doi:10.1016/j.ijengsci.2010.04.012
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Wang, G., Yang, X., Chu, X. et al. Microscale Numerical Simulation of Non-Darcy Flow of Coalbed Methane. Arab J Sci Eng 43, 2547–2561 (2018). https://doi.org/10.1007/s13369-017-2802-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13369-017-2802-x