| 研究生: |
林怡君 Yi-Chun Lin |
|---|---|
| 論文名稱: |
水力內寬不確定性:影響因子與現地資料分析方法之探討 |
| 指導教授: |
董家鈞
Jia-Jyug Dong |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
地球科學學院 - 應用地質研究所 Graduate Institute of Applied Geology |
| 論文出版年: | 2020 |
| 畢業學年度: | 108 |
| 語文別: | 中文 |
| 論文頁數: | 139 |
| 中文關鍵詞: | 人工合成水力內寬 、現地水力內寬量測 、不確定性 、統計分析 、Barton-Bandis 模式 、深度 、岩性 、位態 、不連續面粗糙係數 、不連續面壁面強度 |
| 外文關鍵詞: | synthetic hydraulic aperture, in-situ measurement, uncertainty, statistical analysis, Barton-Bandis model, depth, lithology, orientation, JRC, JCS |
| 相關次數: | 點閱:18 下載:0 |
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不連續面水力內寬為評估岩盤中流體傳輸能力的重要參數,然而工程實務中對於現地不連續面水力內寬的量測值卻不多,因此,放射性廢棄物最終處置安全評估之地下水流場分析即具有不確定性。為了解不同資料統計分析方法對水力內寬不確定性之影響,本研究根據特定場址(砂岩與硬頁岩出露地區)蒐集所得資料,假設岩盤不連續面之合理參數統計分布條件,隨機生成不同岩性不連續面的位態、不連續面粗糙係數(Joint Roughness Coefficient, JRC)及不連續面壁面強度(Joint Compressive Strength, JCS),並採Barton-Bandis模式,在合理現地應力條件下,生成力學內寬資料組後,再藉由經驗式將力學內寬轉換成水力內寬,進而完成人工合成案例之水力內寬資料生成;本研究亦蒐集一現地案例之水力內寬量測資料進行不確定性分析研究。
根據人工合成案例及現地案例測試結果,水力內寬之機率密度分布符合對數常態分布,工程實務不宜直接假設水力內寬為常態分布進行資料統計。分析資料時若不考慮影響因子(如:深度、岩性、裂隙特性…),水力內寬的標準差最大,隨著考慮不同岩性分開統計、水力內寬隨深度減小,統計所得標準差也逐漸下降,而多變量分析中,同時考慮岩性、深度、不連續面之傾角、JRC與JCS時,統計所得標準差會降至最小,根據立方律,其導水係數標準差為不考慮任何影響因子標準差的0.56%。在現地案例的分析結果中,當考慮水力內寬隨著深度變深而減小的趨勢時,同樣顯示出不確定性的顯著降低。
Hydraulic aperture of joints is an important parameter for estimating the fluid flow capability of rock mass. However, the measurements of hydraulic apertures are not common and uncertainty encountered accordingly in the groundwater flow modelling for safety assessment of the radioactive waste final disposal. A synthetic hydraulic aperture dataset was used to evaluate the statistical characteristics of hydraulic apertures via different analysis methods. First of all, reasonable statistical distributions of different parameters of joints (joint roughness coefficient JRC, joint compressive strength JCS, and joint orientation) are assumed according to the data collected from specific sites where the sandstone and argillite outcropped. Secondly, the joints with different orientation, JRC and JCS are randomly generated on the basis of different lithology (sandstone and argillite) at different depth. Thirdly, the Barton-Bandis model was used to calculate the mechanical apertures of each joint under assigned in-situ stresses. Finally, synthetic hydraulic aperture dataset can be obtained according to the mechanical aperture and empirical function described the relation between hydraulic and mechanical apertures. In addition to the synthetic case, we collected a real case where the hydraulic apertures at different depth are available.
According to the testing results of synthetic case and real case, the probability density distribution of the hydraulic aperture conforms to the lognormal distribution. In engineering practice, a normal distribution assumption of hydraulic apertures could be problematic. The standard deviations of the hydraulic apertures are largest when the influence of depth, lithology, and joint characteristics (joint orientation, JRC and JCS) is neglected. When the hydraulic apertures of different lithology were separately analyzed, the uncertainty dropped. If the decreasing trend of hydraulic apertures with depth was considered, the uncertainty dropped further. When the multivariate regression analysis model considering the depth and joint characteristics was used to analysis the synthetic hydraulic apertures of sandstone and argillite separately, the standard deviation is the lowest among others. According to the cubic law, the standard deviation of the joint transmissivity can be reduced to 0.56% of the one where neglecting all of the influential factors when making statistical analysis of the synthetic hydraulic fracture. The analysis result of real case also shows a significant reduced uncertainty when the decreasing trend of hydraulic apertures with increasing depth was considered.
[1]台灣電力公司,2016,「低放射性廢棄物最終處置技術評估報告」(編號: LLWD1-SC-2016-02-V08)。
[2]中央地質調查所工程地質探勘資料庫。台9線安朔至草埔段初步路線規劃及地質探查委託服務作業之地質鑽探工作。檢自https://geotech.moeacgs.gov.tw/imoeagis/Home/Map#
[3]呂玉菀,2004,「使用震源機制逆推台灣地區應力分區狀況」,國立中央大學應用地質研究所,碩士論文。
[4]Bandis, S.C., Lumsden, A.C., Barton, N.R., 1983. Fundamentals of rock joint deformation. International Journal of Rock Mechanics and Mining Science and Geomechanics Abstracts, 20(6), 249-268.
[5]Barton, N., Bandis, S., Bakhtar, K., 1985. Strength, deformation and conductivity coupling of rock joints. International Journal of Rock Mechanics and Mining Sciences and Geomechanics Abstracts, 22(3), 121-140.
[6]Barton, N., Choubey, V., 1977. The shear strength of rock joints in theory and practice. Rock Mechanics, 10(1-2), 1-54.
[7]Bianch, L., Snow, D.T., 1968. Permeability of crystalline rock interpreted from measured orientations and apertures of fractures. Analysis of Acid Zone, 8(2), 231-245.
[8]Brady, B. H., Brown, E. T., 2004. Rock Mechanics: for Underground Mining. Dordrecht, Netherlands: Kluwer Academic Publishers.
[9]Bremer, M., 2012. Polynomial regression models. Math 261A- Spring. Retrieved from http://mezeylab.cb.bscb.cornell.edu/
labmembers/documents/supplement%205%20-%20multiple%20
regression.pdf
[10]Butler, R. F., 1998. Paleomagnetism: Magnetic Domains to Geologic Terranes. Boston: Blackwell Scientific Publications.
[11]Clarke, J. R., Ferris, V., 2012. The Use of One-Sample Prediction Intervals for Estimating CO2 Scrubber Canister Durations (No. NEDU-TR-12-03).
[12]Fisher, R. A., 1953. Dispersion on a sphere. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 217(1130), 295-305.
[13]Freeze, R. A., Cherry, J. A., 1979. Groundwater. Englewood Cliffs: Prentice Hall.
[14]Ghoochaninejad, H. Z., Asef, M. R., Moallemi, S. A., 2018. Estimation of fracture aperture from petrophysical logs using teaching–learning-based optimization algorithm into a fuzzy inference system. Journal of Petroleum Exploration and Production Technology, 8(1), 143-154.
[15]Guerriero, V., Mazzoli, S., Iannace, A., Vitale, S., Carravetta, A., Strauss, C., 2013. A permeability model for naturally fractured carbonate reservoirs. Marine and Petroleum Geology, 40, 115-134.
[16]Hamm, S. Y., Kim, M., Cheong, J. Y., Kim, J. Y., Son, M., Kim, T. W., 2007. Relationship between hydraulic conductivity and fracture properties estimated from packer tests and borehole data in a fractured granite. Engineering Geology, 92(1-2), 73-87.
[17]Jaeger, J. C., 1960. Shear failure of anisotropic rocks. Geological Magazine, 97(1), 65-72.
[18]Jäntschi, L., Bolboacă, S. D., 2018. Computation of probability associated with Anderson–Darling statistic. Mathematics, 6(6), 88.
[19]Kim, D. H., Gratchev, I., Balasubramaniam, A., 2013. Determination of joint roughness coefficient (JRC) for slope stability analysis: a case study from the gold coast area, Australia. Landslides, 10(5), 657-664.
[20]Laubach, S. E., 2003. Practical approaches to identifying sealed and open fractures. AAPG Bulletin, 87(4), 561-579.
[21]Lee, C. H., Farmer, I. W., 1993. Fluid Flow in Discontinuous Rocks. London: Chapman and Hall.
[22]Novakowski, K., 2000. Fate and Transport in Fractured Rock. Standard Handbook of Environmental Science, Health, and Technology, McGraw-Hill Inc.
[23]Olsson, R., Barton, N., 2001. An improved model for hydromechanical coupling during shearing of rock joints. International Journal of Rock Mechanics and Mining Sciences, 38(3), 317-329.
[24]Quinn, P. M., Parker, B. L., Cherry, J. A., 2011. Using constant head step tests to determine hydraulic apertures in fractured rock. Journal of Contaminant Hydrology, 126(1-2), 85-99.
[25]Rutqvist, J., 2015. Fractured rock stress‐permeability relationships from in situ data and effects of temperature and chemical‐mechanical couplings. Geofluids, 15(1-2), 48-66.
[26]Rutqvist, J., Tsang, C. F.,2003. Analysis of thermal-hydrologic- mechanical behavior near an emplacement drift at yucca mountain. Journal of Contaminant Hydrology, 62, 637-652.
[27]Sahimi, M., 1995. Flow and Transport in Porous Media and Fractured Rock. Weinheim, Germany: Wiley-VCH.
[28]SKB, 2004a, Forsmark Site Investigation: Addendum to Difference Flow Logging in Borehole KFM01A (No. P-04-193).
[29]SKB, 2004b, Forsmark Site Investigation: Difference Flow Logging in Borehole KFM02A (No. P-04-188).
[30]SKB, 2004c, Forsmark Site Investigation: Difference Flow Logging in Borehole KFM03A (No. P-04-189).
[31]SKB, 2004d, Forsmark Site Investigation: Difference Flow Logging in Borehole KFM04A (No. P-04-190).
[32]SKB, 2004e, Forsmark Site Investigation: Difference Flow Logging in Borehole KFM05A (No. P-04-191).
[33]SKB, 2007, Forsmark Site Investigation: Difference Flow Logging in Borehole KFM06A (No. P-05-15).
[34]SKB, 2010, Compilation and Analyses of Results from Cross-Hole Tracer Tests with Conservative Tracers (No. R-09-28).
[35]SKB, 2014, Long Term Stability of Rock Caverns BMA and BLA of SFR, Forsmark (No. R-13-53).
[36]Snow, D.T., 1965. A Parallel Plate Model of Fractured Permeable Media. University of California, PhD Thesis.
[37]Snow, D. T., 1968. Rock fracture spacings, openings, and porosities. Journal of Soil Mechanics and Foundations Division, 94(1), 73-91.
[38]Thiem, G., 1906. Hydrologische Methoden. Leipzig: Gebhardt.
[39]Tsang, Y. W., Tsang, C. F., 1987. Channel model of flow through fractured media. Water Resources Research, 23(3), 467-479.
[40]Witherspoon, P. A., Wang, J. S., Iwai, K., Gale, J. E., 1980. Validity of cubic law for fluid flow in a deformable rock fracture. Water Resources Research, 16(6), 1016-1024.
[41]Wu, H., Pollard, D. D., 2002. Imaging 3-d fracture networks around boreholes. AAPG bulletin, 86(4), 593-604.
[42]Zangar, C. N., 1953. Theory and Problems of Water Percolation (No. 8). Denver, Colorado: US Bureau of Reclamation.
[43]Zimmerman, R. W., Bodvarsson, G. S., 1996. Hydraulic conductivity of rock fractures. Transport in Porous Media, 23(1), 1-30.