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姓名	李奕賢(I-hsien Lee)  查詢紙本館藏	畢業系所	應用地質研究所
論文名稱	三維離散裂隙網路水流與溶質傳輸模式發展 (Development of Flow and Transport Model for Three-dimensional Discrete Fracture Networks)
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摘要(中)	為瞭解裂隙岩層中的溶質傳輸行為，開發三維(3D)離散裂隙網路(DFN)水流與溶質傳輸模式是項重要任務。由於裂隙與母岩水流與傳輸能力差異較大，並且兩者在三度空間交互作用涉及複雜空間幾何，計算分析困難。因此，多數水流與傳輸研究僅考慮裂隙網路。因建構3D DFN，生成裂隙非結構化網格及模擬水流與傳輸是極具挑戰的任務，過去的裂隙網路水流及傳輸分析，通常針對二維或一維問題。本研究主要目的在開發、驗證與應用三維離散裂隙網路水流與傳輸模式，模式具備建構三維DFN、有效DFN網格生成以及DFN水流與傳輸數值模擬等功能。建構3D DFN模式首先必須分析現地調查資料，建立裂隙參數統計結構。為重現調查裂隙結構，本研究開發的DFN模式考慮裂隙中心位置符合Poisson分佈，其餘裂隙統計參數先考慮均勻分佈，未來將朝增加統計結構分析精進。DFN網格生成採用Delaunay三角網格演算法，並且透過邊界回復技術修正所有節點於裂隙面共線與共點位置為唯一，網格生成可自動轉換網格資訊，作為本研究開發的水流與傳輸模式，或者轉換為既有模式如TOUGH系列或HYDROGEOCHEM模式網格設定。不同於過去以質點追蹤分析，本研究中模擬3D DFN水流與傳輸，將透過裂隙方位逆轉流程，結合有限元素法直接求解移流延散偏微分控制方程式，因模式在生成網格時已經考慮回復裂隙共線內邊界節點，可確保每個網格求解結果連續，簡化3D DFN傳輸模擬時方程式的空間轉換。開發完成的DFN水流與傳輸模式與既有TOUGH系列模式與HYDROGEOCHEM模式進行驗證，藉由單一平板裂隙模擬進行穩態水流與傳輸模式分析比較。模式應用區分為兩部份，包括DFN網格資訊應用於TOUGH系列模式，模擬CO2地質封存與核種傳輸行為。以及利用蒙地卡羅法產生多組三維裂隙網路，裂隙頻率為1至6 m-1，討論依質量守恆原理計算的裂隙岩體等效水力傳導係數，分析裂隙頻率與等效水力傳導係數關係。此外，亦由多組3D DFN，分析不同觀測策略與位置條件下，濃度穿透曲線的差異與不確定性。研究結果顯示，在開發的DFN水流與傳輸模式中，若以單一水平裂隙進行模擬可重現TOUGH2與HYDROGEOCHEM結果。DFN水流模擬推估等效水力傳導係數結果發現，相似的等效水力傳導係數對應的二維裂隙頻率(P21)變化大於三維裂隙頻率(P32)變化，裂隙岩體等效水力傳導係數約低於裂隙水力傳導係數2至3個級數(order)。根據DFN傳輸分析結果顯示，不同觀測方式濃度穿透曲線差異較劇烈時刻，常發生於濃度團前緣通過觀測位置時。經由多組傳輸模擬結果發現，不同觀測方法觀測平均最大濃度，可能達不到裂隙岩層初始設定最大濃度值。相同的觀測位置，濃度標準偏差可超過一半的初始釋放濃度，隨著觀測位置遠離釋放源，不同觀測策略觀測濃度標準偏差無明顯變化。
摘要(英)	Development of flow and contaminant transport models for three-dimensional (3D) discrete fracture networks (DFNs) is critical to characterize flow and transport in fractured rocks. The fractures in a rock are relatively permeable as compared with the rock matrix. The difficulty in resolving complex fracture and matrix interactions in 3D domains has motivated investigators to focus mainly on fracture networks for characterizing flow and transport in fractured rocks. Because of the complex fracture geometry and connectivity, generations of fracture unstructured mesh and simulations of flow and transport in 3D DNF become challenging tasks. The objectives of this study are to develop, test, and implement numerical models for generation of 3D DFNs, generation of DFN meshes, and simulations of DFN flow and advection-dispersion transport. The developed DFN generator enables the Poisson and uniform distributions to be implemented for fracture locations and other fracture properties such as sizes, trend, and plunge. Other distributions of fracture properties can be employed in the developed DFN generation model. The DFN mesh generation model employed the Delaunay triangulation algorithm and applied a boundary recovery technique to resolve detailed fracture intersections and fracture concurrent points. This mesh generation model can automatically export mesh formats for other public domain models such as TOUGH series models and HYDROGEOCHEM model. Unlike previous investigations that focused on the particle tracking algorithm for DFN transport simulations, this study proposed a back rotation process (BRP) for fracture orientations and directly solved Eularian-based advection-dispersion equation for 3D fracture networks. The developed flow and transport model were validated with the TOUGH2 and HYDROGEOCHEM models using single porous fracture plate. The implementations of the developed models were simply divided into two different parts. The first part is implementations of DFN and DFN mesh generations for the TOUGH2 model and the associated equation of state (EOS) modules, including ECO2N and EOS7R. The second part focuses on implementations of the developed DFN flow and advection-dispersion models for issues of equivalent hydraulic conductivity in DFN upscaling and for analysis of transport uncertainty based on different monitoring strategies. The results of model validations showed that our DFN flow and transport models can reproduce identically the solutions of flow and concentration obtained from TOUGH2 and HYDROGEOCHEM models. The estimations of equivalent hydraulic conductivity based on multiple DFN realizations showed that different fracture intensities can lead to variations of equivalent hydraulic conductivity values in 2 to 3 orders of magnitude lower than the value of the fracture hydraulic conductivity. The comparisons of 2D fracture intensity (P21) and 3D fracture intensity (P32) indicate that the variations of P21 values are relatively high as compared with a specified range of P32. High variations of concentration breakthrough curves were obtained when fronts of plumes passing the observed locations. The maximal mean concentration breakthrough curves for different averaging strategies might not reach the maximal concentration value released at continuous sources. The standard deviations of concentration at different times can be higher than half of the source concentration at different monitoring locations. Additionally, the values of concentration standard deviations are similar for different monitoring points and monitoring (averaging) strategies.
關鍵字(中)	★ 離散裂隙網路 ★ 濃度穿透曲線 ★ 裂隙方位逆轉流程 ★ 蒙地卡羅模擬 ★ 等效水力傳導係數	關鍵字(英)	★ Discrete fracture network ★ Breakthrough curve ★ Back rotation process ★ Monte Carlo simulation ★ Equivalent hydraulic conductivity
論文目次	目錄 摘要 i Abstract iii 表目錄 viii 圖目錄 ix 1 前言 1 1.1 研究背景與目的 1 1.2 研究流程 4 1.3 論文架構 6 2 文獻回顧 8 2.1.1 裂隙母岩特徵總攬 8 2.1.2 裂隙幾何參數 15 2.1.3 裂隙網格生成 20 2.1.4 裂隙水流與傳輸模擬 23 3 研究方法 27 3.1 建構有效離散裂隙網路 29 3.2 DFNe網格生成 29 3.3 TOUGH系列模式網格資訊匯出 32 3.4 離散裂隙網路水流與溶質傳輸有限元素模式開發 34 3.4.1 水流與傳輸模擬控制方程式 34 3.4.2 裂隙方位逆轉流程(BRP) 36 3.4.3 有限元素方法求解方位逆轉DFN水流與傳輸模擬 40 3.5 裂隙母岩等效水力傳導係數 42 4 模式驗證 44 4.1 水平裂隙穩態水流模擬 44 4.2 水平裂隙溶質傳輸模擬 48 5 模式應用 51 5.1 TOUGH系列模式相關應用 51 5.1.1 水平裂隙CO2注儲 51 5.1.2 複雜離散裂隙網路CO2遷移模擬 56 5.1.3 DFNe核種模擬傳輸 61 5.2 三維離散裂隙網路水流與溶質傳輸模式應用 68 5.2.1 連體模式等效水力傳導係數 71 5.2.2 DFN質點追蹤分析模式 73 5.2.3 三維DFNe溶質傳輸不確定性分析 76 6 結論與建議 83 6.1 結論 83 6.2 建議 84 參考文獻 86 簡歷 98
參考文獻	[1] Castelletto, N., Teatini, P., Gambolati, G., Bossie-Codreanu, D., Vincké, O., Daniel, J.-M., Battistelli, A., Marcolini, M., Donda, F., Volpi, V., 2013. Multiphysics modeling of CO2 sequestration in a faulted saline formation in Italy. Advances in Water Resources 62, Part C, 570-587. [2] Bodin, J., Porel, G., Delay, F., 2003. Simulation of solute transport in discrete fracture networks using the time domain random walk method. Earth and Planetary Science Letters 208, 297-304. [3] Dverstorp, B., Andersson, J., Nordqvist, W., 1992. Discrete fracture network interpretation of field tracer migration in sparsely fractured rock. Water Resources Research 28, 2327-2343. [4] Long, J.C.S., Remer, J.S., Wilson, C.R., Witherspoon, P.A., 1982. Porous media equivalents for networks of discontinuous fractures. Water Resources Research 18, 645-658. [5] Wang L, Cardenas MB., 2015. An efficient quasi-3D particle tracking-based approach for transport through fractures with application to dynamic dispersion calculation. Journal of Contaminant Hydrology 179, 47-54. [6] Hyman JD, Karra S, Makedonska N, Gable CW, Painter SL, Viswanathan HS., 2015. DFNWORKS: A discrete fracture network framework for modeling subsurface flow and transport. Computers & Geosciences 84, 10-9. [7] Hyman JD, Gable CW, Painter SL, Makedonska N., 2014. Conforming delaunay triangulation of stochastically generated three dimensional discrete fracture networks: A feature rejection algorithm for meshing strategy. SIAM Journal on Scientific Computing 36, A1871-A94. [8] Kalbacher T, Wang W, McDermott C, Kolditz O, Taniguchi T., 2005. Development and application of a CAD interface for fractured rock. Environmental Geology 47, 1017-27. [9] Zhang Q-H., 2015. Finite element generation of arbitrary 3-D fracture networks for flow analysis in complicated discrete fracture networks. Journal of Hydrology 529, Part 3, 890-908. [10] Makedonska N, Painter S, Bui Q, Gable C, Karra S., 2015. Particle tracking approach for transport in three-dimensional discrete fracture networks. Computational Geosciences 19, 1123-1137. [11] Neuman S., 2005. Trends, prospects and challenges in quantifying flow and transport through fractured rocks. Hydrogeology Journal 13, 124-47. [12] Berrone, S., Pieraccini, S., Scialò, S., 2014. An optimization approach for large scale simulations of discrete fracture network flows. Journal of Computational Physics 256, 838-853. [13] Berrone, S., Pieraccini, S., Scialò, S., 2013. A PDE-constrained optimization formulation for discrete fracture network flows. SIAM Journal on Scientific Computing 35, B487-B510. [14] Peratta, A., Popov, V., 2006. A new scheme for numerical modelling of flow and transport processes in 3D fractured porous media. Advances in Water Resources 29, 42-61. [15] Maryška, J., Severýn, O., Vohralík, M., 2005. Numerical simulation of fracture flow with a mixed-hybrid FEM stochastic discrete fracture network model. Computational Geosciences 8, 217-234. [16] Lee, I.-H., Ni, C.-F., 2015. Fracture-based modeling of complex flow and CO2 migration in three-dimensional fractured rocks. Computers & Geosciences 81, 64-77. [17] La Pointe, P.R., 1988. A method to characterize fracture density and connectivity through fractal geometry. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 25, 421-429. [18] Okubo, P.G., Aki, K., 1987. Fractal geometry in the San Andreas Fault System. Journal of Geophysical Research: Solid Earth 92, 345-355. [19] Scholz, C.H., Cowie, P.A., 1990. Determination of total strain from faulting using slip measurements. Nature 346, 837-839. [20] Segall, P., Pollard, D.D., 1983. Joint formation in granitic rock of the Sierra Nevada. Geological Society of America Bulletin 94, 563-575. [21] Hestir, K., Long, J.C.S., 1990. Analytical expressions for the permeability of random two-dimensional Poisson fracture networks based on regular lattice percolation and equivalent media theories. Journal of Geophysical Research: Solid Earth 95, 21565-21581. [22] Khamforoush, M., Shams, K., 2007. Percolation thresholds of a group of anisotropic three-dimensional fracture networks. Physica A: Statistical Mechanics and its Applications 385, 407-420. [23] Davy P, Bour O, de Dreuzy JR, Darcel C., 2006. Flow in multiscale fractal fracture networks. Geological Society Special Publication,pp. 31-45. [24] Stephens, M.B., Follin, S., Petersson, J., Isaksson, H., Juhlin, C., Simeonov, A., 2015. Review of the deterministic modelling of deformation zones and fracture domains at the site proposed for a spent nuclear fuel repository, Sweden, and consequences of structural anisotropy. Tectonophysics 653, 68-94. [25] Hartley, L., Joyce, S., 2013. Approaches and algorithms for groundwater flow modeling in support of site investigations and safety assessment of the Forsmark site, Sweden. Journal of Hydrology 500, 200-216. [26] Dershowitz, W.S., Fidelibus, C., 1999. Derivation of equivalent pipe network analogues for three-dimensional discrete fracture networks by the boundary element method. Water Resources Research 35, 2685-2691. [27] Cacas, M.C., Ledoux, E., de Marsily, G., Tillie, B., Barbreau, A., Durand, E., Feuga, B., Peaudecerf, P., 1990b. Modeling fracture flow with a stochastic discrete fracture network: calibration and validation: 1. The flow model. Water Resources Research 26, 479-489. [28] Painter, S., Cvetkovic, V., Selroos, J.-O., 2002. Power-law velocity distributions in fracture networks: Numerical evidence and implications for tracer transport. Geophysical Research Letters 29, 20-21-20-24. [29] Li, S.C., Xu, Z.H., Ma, G.W., 2014. A Graph-theoretic Pipe Network Method for water flow simulation in discrete fracture networks: GPNM. Tunnelling and Underground Space Technology 42, 247-263. [30] Li, S.C., Xu, Z.H., Ma, G.W., Yang, W.M., 2014. An adaptive mesh refinement method for a medium with discrete fracture network: The enriched Persson’s method. Finite Elements in Analysis and Design 86, 41-50. [31] Ahmed, R., Edwards, M.G., Lamine, S., Huisman, B.A.H., Pal, M., 2015. Control-volume distributed multi-point flux approximation coupled with a lower-dimensional fracture model. Journal of Computational Physics 284, 462-489. [32] Johnson, J., Brown, S., Stockman, H., 2006. Fluid flow and mixing in rough-walled fracture intersections. Journal of Geophysical Research: Solid Earth 111, B12206. [33] Botros, F.E., Hassan, A.E., Reeves, D.M., Pohll, G., 2008. On mapping fracture networks onto continuum. Water Resources Research 44, W08435. [34] Hyman, J.D., Painter, S.L., Viswanathan, H., Makedonska, N., Karra, S., 2015b. Influence of injection mode on transport properties in kilometer-scale three-dimensional discrete fracture networks. Water Resources Research, 7289- 7308. [35] Bogdanov, I.I., Mourzenko, V.V., Thovert, J.F., Adler, P.M., 2003. Effective permeability of fractured porous media in steady state flow. Water Resources Research 39, 1023. [36] Mourzenko, V.V., Bogdanov, I.I., Thovert, J.F., Adler, P.M., 2011. Three-dimensional numerical simulation of single-phase transient compressible flows and well-tests in fractured formations. Mathematics and Computers in Simulation 81, 2270-2281. [37] 趙奕然，2014。利用LiDAR點雲及影像資料決定露頭節理結合面之研究。國立中央大學碩士論文。 [38] Long, J.C.S., Gilmour, P., Witherspoon, P.A., 1985. A model for steady fluid flow in random three-dimensional networks of disc-shaped fractures. Water Resources Research 21, 1105-1115. [39] Lee, C.-H., 1990. Flow in fractured rock. The University of Arizona, p. 311. [40] Long, J.C.S., Gilmour, P., Witherspoon, P.A., 1985. A model for steady fluid flow in random three-dimensional networks of disc-shaped fractures. Water Resources Research 21, 1105-1115. [41] Baecher, G., 1983. Statistical analysis of rock mass fracturing. Journal of the International Association for Mathematical Geology 15, 329-348. [42] Baecher, G.B., Lanney, N.A., Einstein, H.H., 1977. Statistical description of rock properties and sampling, The 18th U.S. Symposium on Rock Mechanics (USRMS). American Rock Mechanics Association. [43] Dershowitz, W.S., Einstein, H.H., 1988. Characterizing rock joint geometry with joint system models. Rock Mechanics and Rock Engineering 21, 21-51. [44] 林宏奕，2009。裂隙岩體優勢水流路徑之研究。國立成功大學博士論文。 [45] Parsons, R.W., 1966. Permeability of idealized fractured rock 6 th, Society of Petroleum Engineers, 126-136. [46] Wilson, C.R., Witherspoon, P.A., 1976. Flow interference effects at fracture intersections. Water Resources Research 12, 102-104. [47] Schwartz, F.W., Smith, L., Crowe, A.S., 1983. A stochastic analysis of macroscopic dispersion in fractured media. Water Resources Research 19, 1253-1265. [48] Smith, L., Schwartz, F.W., 1984. An analysis of the influence of fracture geometry on mass transport in fractured media. Water Resources Research 20, 1241-1252. [49] Andersson, J., Shapiro, A.M., Bear, J., 1984. A stochastic model of a fractured rock conditioned by measured information. Water Resources Research 20, 79-88. [50] Andersson, J., Thunvik, R., 1986. Predicting mass transport in discrete fracture networks with the aid of geometrical field data. Water Resources Research 22, 1941-1950. [51] Wei, Z.Q., Egger, P., Descoeudres, F., 1995. Permeability predictions for jointed rock masses. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 32, 251-261. [52] Gómez-Hernández, J.J., Franssen, H.J.H., Cassiraga, E.F., 2001. Stochastic analysis of flow response in a three-dimensional fractured rock mass block. International Journal of Rock Mechanics and Mining Sciences 38, 31-44. [53] Rejeb, A., Bruel, D., 2001. Hydromechanical effects of shaft sinking at the Sellafield site. International Journal of Rock Mechanics and Mining Sciences 38, 17-29. [54] de Dreuzy, J.-R., Davy, P., Bour, O., 2001. Hydraulic properties of two-dimensional random fracture networks following a power law length distribution: 1. Effective connectivity. Water Resources Research 37, 2065-2078. [55] Park, Y.-J., Lee, K.-K., Kosakowski, G., Berkowitz, B., 2003. Transport behavior in three-dimensional fracture intersections. Water Resources Research 39, 1215. [56] 葉振峰，2012。低放射性廢棄物場址核種傳輸之研究-以台東達仁場址為例，國立成功大學碩士論文。 [57] Barenblatt, G.I., Zheltov, I.P., Kochina, I.N., 1960. Basic concepts in the theory of seepage of homogeneous liquids in fissured rocks [strata]. Journal of Applied Mathematics and Mechanics 24, 1286-1303. [58] Warren, J.E., Root, P.J., 1963. The behavior of naturally fractured reservoirs. Society of Petroleum Engineers 3, 245-255. [59] Zimmerman, R.W., Chen, G., Hadgu, T., Bodvarsson, G.S., 1993. A numerical dual-porosity model with semianalytical treatment of fracture/matrix flow. Water Resources Research 29, 2127-2137. [60] Huyakorn, P.S., Lester, B.H., Faust, C.R., 1983. Finite element techniques for modeling groundwater flow in fractured aquifers. Water Resources Research 19, 1019-1035. [61] Snow, D.T., 1965. A parallel plate model of fractured permeable media. University of California, Berkeley. [62] Weiss, L.E., 1972. The Minor Structures of Deformed Rocks: A Photographic Atlas. Springer Berlin Heidelberg. [63] Oda, M., 1985. Permeability tensor for discontinuous rock masses. Géotechnique 35, 483-495. [64] Rouleau, A., Gale, J.E., 1987. Stochastic discrete fracture simulation of groundwater flow into an underground excavation in granite. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 24, 99-112. [65] Neuman, S.P., Depner, J.S., 1988. Use of variable-scale pressure test data to estimate the log hydraulic conductivity covariance and dispersivity of fractured granites near Oracle, Arizona. Journal of Hydrology 102, 475-501. [66] Larocque, M., Banton, O., Ackerer, P., Razack, M., 1999. Determining Karst Transmissivities with Inverse Modeling and an Equivalent Porous Media. Ground Water 37, 897-903. [67] Bernabé, Y., Bruderer-Weng, C., Maineult, A., 2003. Permeability fluctuations in heterogeneous networks with different dimensionality and topology. Journal of Geophysical Research: Solid Earth 108, 2351. [68] Ripley, B.D., 1981. Spatial statistics. John Wiley & Sons. [69] Priest, S.D., Hudson, J.A., 1976. Discontinuity spacings in rock. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 13, 135-148. [70] Priest, D.S., 2004. Determination of discontinuity size distributions from scanline data. Rock Mechanics and Rock Engineering 37, 347-368. [71] Priest, D.S., 1993. Discontinuity analysis for rock engineering. Chapman and Hall. [72] Xu, C., Dowd, P., 2010. A new computer code for discrete fracture network modelling. Computers & Geosciences 36, 292-301. [73] Min, K.-B., Jing, L., Stephansson, O., 2004a. Determining the equivalent permeability tensor for fractured rock masses using a stochastic REV approach: Method and application to the field data from Sellafield, UK. Hydrogeology Journal 12, 497-510. [74] Min, K.-B., Rutqvist, J., Tsang, C.-F., Jing, L., 2004b. Stress-dependent permeability of fractured rock masses: a numerical study. International Journal of Rock Mechanics and Mining Sciences 41, 1191-1210. [75] Pichot, G., Erhel, J., de Dreuzy, J., 2012. A generalized mixed hybrid mortar method for solving flow in stochastic discrete fracture networks. SIAM Journal on Scientific Computing 34, B86-B105. [76] Cruden, D.M., 1977. Describing the size of discontinuities. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 14, 133-137. [77] Pahl, P.J., 1981. Estimating the mean length of discontinuity traces. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 18, 221-228. [78] Chilès, J.P., Fractal and geostatistical methods for modeling of a fracture network. Journal of the International Association for Mathematical Geology 20, 631-654. [79] Bour, O., Davy, P., Darcel, C., Odling, N., 2002. A statistical scaling model for fracture network geometry, with validation on a multiscale mapping of a joint network (Hornelen Basin, Norway). Journal of Geophysical Research: Solid Earth 107, ETG 4-1-ETG 4-12. [80] Chellappa, V., Chiou, Z.W., Jang, B.Z., Electromechanical and electrothermal behaviours of carbon whisker reinforced elastomer composites. Journal of Materials Science 30, 4263-4272. [81] Villaescusa, E., Brown, E.T., 1990. Characterizing joint spatial correlations using geostatistical methods. Barton and Stephansson, Balkema, 115-122. [82] Fisher, R., 1953. Dispersion on a sphere. Proceedings of the Royal Society 217, 295-305. [83] Herget, G., 1970. Shear strength anisotropy in a bedded pyritic shale and a siliceous dolomite. Rock mechanics 2, 93-100. [84] Bridges, M.C., 1975. Presentation of fracture data for rock mechanics, 2nd Australian-New Zealand Com. on Geomech. Brisbane, pp. 144-148. [85] Einstein, H.H., Baecher, G.B., 1983. Probabilistic and statistical methods in engineering geology. Rock Mechanics and Rock Engineering 16, 39-72. [86] Kulatilake, P.H.S.W., State-of-The-Art In Stochastic Joint Geometry Modeling. American Rock Mechanics Association. [87] Ross, S.M., 1997. Introduction to Probability Models 6th Edn. Academic press, 669. [88] La Pointe, P.R., Wallmann, P.C., Dershowitz, W.S., 1993. Stochastic estimation of fracture size through simulated sampling. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 30, 1611-1617. [89] Dershowitz, W.S., Herda, H.H., 1992. Interpretation of fracture spacing and intensity, The 33th US Symposium on Rock Mechanics (USRMS). American Rock Mechanics Association. [90] Pruess, K., Tsang, Y.W., 1990. On two-phase relative permeability and capillary pressure of rough-walled rock fractures. Water Resources Research 26, 1915-1926. [91] Kwicklis, E.M., Healy, R.W., 1993. Numerical investigation of steady liquid water flow in a variably saturated fracture network. Water Resources Research 29, 4091-4102. [92] Liu, H.H., Bodvarsson, G.S., Finsterle, S., 2002. A note on unsaturated flow in two-dimensional fracture networks. Water Resources Research 38, 1176. [93] Cacas, M.C., Ledoux, E., de Marsily, G., Barbreau, A., Calmels, P., Gaillard, B., Margritta, R., 1990a. Modeling fracture flow with a stochastic discrete fracture network: Calibration and validation: 2. The transport model. Water Resources Research 26, 491-500. [94] Dershowitz, W., Miller, I., 1995. Dual porosity fracture flow and transport. Geophysical Research Letters 22, 1441-1444. [95] Frampton, A., Cvetkovic, V., 2009. Significance of injection modes and heterogeneity on spatial and temporal dispersion of advecting particles in two-dimensional discrete fracture networks. Advances in Water Resources 32, 649-658. [96] Zafarani, A., Detwiler, R.L., 2013. An efficient time-domain approach for simulating Pe-dependent transport through fracture intersections. Advances in Water Resources 53, 198-207. [97] Ivanova, V.M., Sousa, R., Murrihy, B., Einstein, H.H., 2014. Mathematical algorithm development and parametric studies with the GEOFRAC three-dimensional stochastic model of natural rock fracture systems. Computers & Geosciences 67, 100-109. [98] Mustapha, H., Mustapha, K., 2007. A new approach to simulating flow in discrete fracture networks with an optimized mesh. SIAM Journal on Scientific Computing 29, 1439-1459. [99] Sun, S., Sui, J., Chen, B., Yuan, M., 2013. An efficient mesh generation method for fractured network system based on dynamic grid deformation. Mathematical Problems in Engineering 2013, 9. [100] Karimi-Fard, M., Gong, B., Durlofsky, L.J., 2006. Generation of coarse-scale continuum flow models from detailed fracture characterizations. Water Resources Research 42, W10423. [101] Erhel, J., de Dreuzy, J.R., Beaudoin, A., Bresciani, E., Tromeur-Dervout, D., 2009. A parallel scientific software for heterogeneous hydrogeoloy, Parallel Computational Fluid Dynamics 2007, 39-48. [102] Rutqvist, J., Leung, C., Hoch, A., Wang, Y., Wang, Z., 2013. Linked multicontinuum and crack tensor approach for modeling of coupled geomechanics, fluid flow and transport in fractured rock. Journal of Rock Mechanics and Geotechnical Engineering 5, 18-31. [103] Reeves, D.M., Benson, D.A., Meerschaert, M.M., 2008. Transport of conservative solutes in simulated fracture networks: 1. Synthetic data generation. Water Resources Research 44, W05404. [104] de Dreuzy, J.-R., Pichot, G., Poirriez, B., Erhel, J., 2013. Synthetic benchmark for modeling flow in 3D fractured media. Computers & Geosciences 50, 59-71. [105] Pan, J.-B., Lee, C.-C., Lee, C.-H., Yeh, H.-F., Lin, H.-I., 2010. Application of fracture network model with crack permeability tensor on flow and transport in fractured rock. Engineering Geology 116, 166-177. [106] Finsterle, S., Sonnenthal, E.L., Spycher, N., 2014. Advances in subsurface modeling using the TOUGH suite of simulators. Computers & Geosciences 65, 2-12. [107] Pruess, K., Spycher, N., 2007. ECO2N – A fluid property module for the TOUGH2 code for studies of CO2 storage in saline aquifers. Energy Conversion and Management 48, 1761-1767. [108] Kiryukhin, A., Xu, T., Pruess, K., Apps, J., Slovtsov, I., 2004. Thermal–hydrodynamic–chemical (THC) modeling based on geothermal field data. Geothermics 33, 349-381. [109] Itälä, A., Olin, M., Lehikoinen, J., 2011. Lot A2 test, THC modelling of the bentonite buffer. Physics and Chemistry of the Earth, Parts A/B/C 36, 1830-1837. [110] Aradóttir, E.S.P., Sonnenthal, E.L., Jónsson, H., 2012. Development and evaluation of a thermodynamic dataset for phases of interest in CO2 mineral sequestration in basaltic rocks. Chemical Geology 304–305, 26-38. [111] Zhang, K., Wu, Y.S., Bodvarsson, G.S., Liu, H.H., 2004. Flow focusing in unsaturated fracture networks: A numerical investigation. Vadose Zone Journal 3, 624-633. [112] Finsterle, S., Ahlers, C.F., Trautz, R.C., Cook, P.J., 2003. Inverse and predictive modeling of seepage into underground openings. Journal of Contaminant Hydrology 62–63, 89-109. [113] Mukhopadhyay, S., Tsang, Y.W., 2003. Uncertainties in coupled thermal–hydrological processes associated with the Drift Scale Test at Yucca Mountain, Nevada. Journal of Contaminant Hydrology 62–63, 595-612. [114] Zhang, K., Wu, Y.-S., Bodvarsson, G.S., 2003. Parallel computing simulation of fluid flow in the unsaturated zone of Yucca Mountain, Nevada. Journal of Contaminant Hydrology 62–63, 381-399. [115] Pan, P.-Z., Rutqvist, J., Feng, X.-T., Yan, F., 2014. TOUGH–RDCA modeling of multiple fracture interactions in caprock during CO2 injection into a deep brine aquifer. Computers & Geosciences 65, 24-36. [116] Yeh, G.-T., 1981. On the computation of Darcian velocity and mass balance in the finite element modeling of groundwater flow. Water Resources Research 17, 1529-1534. [117] Dagan, G., 1989. Flow and transport in porous formations. Springer-Verlag GmbH & Co. KG. [118] Zheng, C., Bennett, G.D., 2002. Applied contaminant transport modeling. Wiley-Interscience New York. [119] De Marsily, G., 1986. Quantitative hydrogeology. Academic Press. [120] Altman, S.J., Arnold, B., Barnard, R., Barr, G., Ho, C., McKenna, S., Eaton, R., 1996. Flow calculations for Yucca Mountain groundwater travel time (GWTT-95). Sandia National Labs., Albuquerque, N.M. SAND96-0819. [121] van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil science society of America journal 44, 892-898. [122] Corey, A.T., 1954. The interrelation between gas and oil relative permeabilities. Producers monthly 19, 38-41. [123] Vujević, K., Graf, T., Simmons, C.T., Werner, A.D., 2014. Impact of fracture network geometry on free convective flow patterns. Advances in Water Resources 71, 65-80. [124] Ben Abdelghani, F., Aubertin, M., Simon, R., Therrien, R., 2015. Numerical simulations of water flow and contaminants transport near mining wastes disposed in a fractured rock mass. International Journal of Mining Science and Technology 25, 37-45. [125] Mo, H., Bai, M., Lin, D., Roegiers, J.-C., 1998. Study of flow and transport in fracture network using percolation theory. Applied Mathematical Modelling 22, 277-291. [126] Graf, T., Therrien, R., 2007. Variable-density groundwater flow and solute transport in irregular 2D fracture networks. Advances in Water Resources 30, 455-468. [127] Cacace, M., Blöcher, G., 2015. MeshIt—a software for three dimensional volumetric meshing of complex faulted reservoirs. Environmental Earth Sciences, 1-19. [128] Painter, S., Cvetkovic, V., Mancillas, J., Pensado, O., 2008. Time domain particle tracking methods for simulating transport with retention and first-order transformation. Water Resources Research 44, W01406.
指導教授	倪春發(Chuen-fa Ni)	審核日期	2016-1-20
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