Pore-scale simulation of gas-water flow in low permeability gas reservoirs

Abstract

A novel method was developed to establish a realistic three dimensional (3D) network model representing pore space in low permeability sandstone. Digital core of rock sample was established by the combination of micro-CT scanning and image processing, then 3D pore-throat network model was extracted from the digital core through analyzing pore space topology, calculating pore-throat parameters and simplifying the shapes of pores and throats. The good agreements between predicted and measured porosity and absolute permeability verified the validity of this new network model. Gas-water flow mechanism was studied by using pore-scale simulations, and the influence of pore structure parameters, including coordination number, aspect ratio and shape factor, on gas-water flow, was investigated. The present simulation results show that with the increment of coordination number, gas flow ability in network improves and the effect of invading water on blocking gas flow weakens. The smaller the aspect ratio is, the stronger the anisotropy of the network is, resulting in the increase of seepage resistance. It is found that the shape factor mainly affects the end points in relative permeability curves, and for a highly irregular pore or throat with a small shape factor, the irreducible water saturation (S_wi) and residual gas saturation (S_gr) are relatively high.

Keywords

low permeability sandstone / X-ray computed tomography / pore-scale modeling / pore structure / gas-water flow

References

[1] XuZ-y, ZhangX-y, WuS-h, ZhaoYan. Genesis of the low-permeability reservoir bed of upper Triassic Xujiahe Formation in Xinchang gas field, western Sichuan Depression [J]. Petroleum Science, 2008, 5(3): 230-237

[2] BluntM J, BijeljicB, HuD, GharbiO, IglauerS, MostaghimiP, PalusznyA, PentlandC. Pore-scale imaging and modeling [J]. Advances in Water Resources, 2013, 51: 197-216

[3] BakkeS, ØrenP E. 3-D pore-scale modeling of sandstones and flow simulations in the pore networks [J]. SPE Journal, 1997, 2(2): 136-149

[4] ØrenP E, BakkeS. Reconstruction of Berea sandstone and pore-scale modeling of wettability effects [J]. Journal of Petroleum Science and Engineering, 2003, 39(3): 177-199

[5] ZhangT, LiD-l, LuD-t, YangJ-qing. Research on the reconstruction method of porous media using multiple-point geostatistics [J]. Science China Physics, Mechanics and Astronomy, 2010, 53(1): 122-134

[6] LuD-t, ZhangT, YangJ-q, LiD-l, KongX-yan. A reconstruction method of porous media integrating soft data with hard data [J]. Chinese Science Bulletin, 2009, 54(11): 1876-1885

[7] HajizadehA, SafekordiA, FarhadpourF A. A multiple-point statistics algorithm for 3D pore space reconstruction from 2D images [J]. Advances in Water Resources, 2011, 34(10): 1256-1267

[8] Moreno-AtanasioR, WilliamsR A, JiaX. Combining X-ray microtomography with computer simulation for analysis of granular and porous materials [J]. Particuology, 2010, 8(2): 81-99

[9] BauerD, YoussefS, FleuryM, BekriS, RosenbergE, VizikaO. Improving the estimations of petrophysical transport behavior of carbonate rocks using a dual pore network approach combined with computed microtomography [J]. Transport in Porous Media, 2012, 94(2): 505-524

[10] YangB-h, WuA-x, YinS-hua. Simulation of pore scale fluid flow of granular ore media in heap leaching based on realistic model [J]. Journal Central South University of Technology, 2011, 18(3): 848-853

[11] BaldwinC A, SedermanA J, MantleM D, AlexanderP, GladdenL F. Determination and characterization of the structure of a pore space from 3D volume images [J]. Journal of Colloid and Interface Science, 1996, 181(1): 79-92

[12] HuD, BluntM J. Pore-network extraction from micro-computerized-tomography images [J]. Physical Review E, 2009, 80(3): 036307

[13] BryantS L, BluntM J. Prediction of relative permeability in simple porous media [J]. Physical Review A, 1992, 46(4): 2004-2012

[14] WangJ-x, WuX-d, PanX-wei. The influence of aqueous phase trapping on gas flow by pore scale network model [J]. Petroleum Exploration and Development, 2003, 30(5): 113-115

[15] LiD-w, ZhangL-h, ZhouK-m, GuoL-ping. Gas-water two-phase flow mechanism in visual microscopic pore model [J]. Journal of China University of Petroleum (Natural Science Edition), 2008, 32(3): 80-83

[16] ShaoC-j, YangZ-q, ZhouG-g, LuG-wu. Pore network modeling of water block in low permeability reservoirs [J]. Petroleum Science, 2010, 7(3): 362-366

[17] MousaviM A, BryabtS L. Connectivity of pore space as a control on two-phase flow properties of tight-gas sandstones [J]. Transport in Porous Media, 2012, 94(2): 537-554

[18] ØrenP E, BakkeS. Reconstruction of Berea sandstone and pore-scale modeling of wettability effects [J]. Journal of Petroleum Science and Engineering, 2003, 39(3): 177-199

[19] IdowuN A, BluntM J. Pore-scale modeling of rate effects in water flooding [J]. Transport in Porous Media, 2010, 83(1): 151-169

[20] BolandtabaS F, SkaugeA. Network modeling of EOR processes: A combined invasion percolation and dynamic model for mobilization of trapped oil [J]. Transport in Porous Media, 2011, 89(3): 357-382

[21] SuicmezV S, PiriM, BluntM J. Pore-scale simulation of water alternate gas injection [J]. Transport in Porous Media, 2007, 66(3): 259-286

[22] ValvatneP H, BluntM J. Predictive pore-scale modeling of two-phase flow in mixed wet media [J]. Water Resources Research, 2004, 40(7): W07406

[23] HouJ, LiZ-q, ZhangS-k, CaoX-l, SongX-w, GaoD-bo. Experiment and simulation study on construction of three-dimensional network model [J]. Science in China Series G: Physics, Mechanics & Astronomy, 2008, 51(11): 1761-1774

[24] PatzekT W, KristensenJ G. Shape factor correlations of hydraulic conductance in noncircular capillaries II. Two-phase creeping flow [J]. Journal of Colloid and Interface Science, 2001, 236(2): 305-317