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系統識別號 U0026-0107201914073600
論文名稱(中文) 應用貝氏同化技術結合電阻率測錄與岩性紀錄於水力傳導係數更新
論文名稱(英文) Bayesian assimilation of resistivity and lithologic logs for updating hydraulic conductivity
校院名稱 成功大學
系所名稱(中) 資源工程學系
系所名稱(英) Department of Resources Engineering
學年度 107
學期 2
出版年 108
研究生(中文) 鄭士揚
研究生(英文) Shih-Yang Cheng
學號 N46061046
學位類別 碩士
語文別 英文
論文頁數 76頁
口試委員 口試委員-李振誥
口試委員-倪春發
口試委員-余化龍
口試委員-蔡瑞彬
口試委員-李國榮
指導教授-徐國錦
中文關鍵字 資料融合  貝氏  水力傳導係數  電阻率測錄  岩性紀錄  多尺度  濁水溪沖積扇 
英文關鍵字 Assimilation  Bayesian  Hydraulic Conductivity  Resistivity Logs  Lithology Description  Multi-Scale  Choushui River Alluvial Fan 
學科別分類
中文摘要 推估異質性水力傳導係數在地下水資源管理與地下污染整治上十分重要,但是直接觀測的水力傳導係數資料十分稀少,因此推估結果存在不確定性。本研究使用貝氏統計方法同化次要資料以降低推估不確定性。不同於傳統地質統計方法,貝氏統計方法可以考慮資料的非線性關係。本研究利用假設案例驗證此方法的可行性。結果顯示,當主要資料與次要資料間存在高相關性,增加次要資料的數量可以有效率的改善水力傳導係數的估計結果。然而,資料的型態對於估計結果的影響不大。另外,本研究利用此方法探討電阻率測錄和岩性紀錄在推估濁水溪沖積扇水力傳導係數分布的有效性。結果顯示,同時使用兩種次要資料可以得到最精準的估測結果。相對於普通克利金的結果,含水層一不確定性下降達37.3 %,含水層二不確定性下降達9.6 %。此外,含水層一的水力傳導係數推估結果與先前研究推估的岩相分布具有相似的空間分布。
英文摘要 Characterizing spatially heterogeneous hydraulic conductivity (K) plays a crucial role in groundwater resources management and subsurface contaminant remediation. Since the direct measurements of K are sparse, the uncertainty is inherent in the estimated parameters. We propose to decrease the uncertainty by assimilating secondary data (related with K to some degree) with the primary data (K) using Bayesian statistical method. Different from classical geostatistical methods, both linear and nonlinear relations between the primary and secondary data can be considered in Bayesian statistical method. A synthetic example is designed to evaluate the method. Results show that increasing numbers of secondary data improves K estimates efficiently if higher correlation exists for primary and secondary data. However, the relation type has little influence on the accuracy and uncertainty. Also, we explore the use of resistivity logs and lithologic description for K estimation at Choushui River alluvial fan using the method. Results indicate jointly assimilating both types of secondary data can obtain the most accurate and least uncertain estimates. By combining both types of data with K data, a less uncertain K distribution of Choushui River alluvial fan is obtained. The K distribution of aquifer 1 has similar spatial variation with the result of facies distribution from previous study. The reduction efficiency of uncertainty is 37.3 % for aquifer 1 and 9.6 % for aquifer 2 compared to the uncertainty by ordinary kriging.
論文目次 ABSTRACT I
摘要 II
CONTENTS IV
LIST OF TABLES VI
LIST OF FIGURES VII
NOTATION VIIX
CHAPTER 1 INTRODUCTION 1
1.1 MOTIVATION 1
1.2 LITERATURE REVIEW 4
1.3 FLOW CHART 7
CHAPTER 2 METHODOLOGY 9
2.1 BAYES’ THEOREM 9
2.2 BAYESIAN STATISTICAL METHOD 11
2.2.1 Likelihood Function 12
2.2.2 Prior Distribution 14
2.2.3 Posterior Distribution 15
2.2.4 Metropolis-within-Gibbs sampling 16
CHAPTER 3 SITE DESCRIPTION AND DATA ANALYSIS 21
3.1 SITE DESCRIPTION 21
3.2 DATA ANALYSIS 26
3.2.1 Calculation of Averaged Lithology Index 26
3.2.2 Calculation of Apparent Formation Factor 26
3.2.3 Regression Analysis of versus and 28
3.2.4 Spatial Continuity Analysis of 29
CHAPTER 4 SYNTHETIC EXAMPLE 35
4.1 CONSTRUCTION OF SYNTHETIC AND FIELDS 35
4.2 SAMPLING 38
4.3 RESULTS OF ESTIMATION 39
4.3.1 Variogram and Regression Analysis 39
4.3.3 Variance of Estimation 41
4.3.4 Sampling Strategies 42
CHAPTER 5 SITE APPLICATION 48
5.1 CROSS VALIDATION USING BAYESIAN STATISTICAL METHOD 48
5.1.1 Estimation Accuracy and Uncertainty in Aquifer 1 48
5.1.2 Estimation Accuracy and Uncertainty in Aquifer 2 50
5.2 ESTIMATION FOR AQUIFER 1 AND 2 OF CHOUSHUI RIVER ALLUVIAL FAN USING BAYESIAN STATISTICAL METHOD 55
5.2.1 Estimations of Mean and Variance of Aquifer 1 56
5.2.2 Estimations of Mean and Variance in Aquifer 2 59
CHAPTER 6 CONCLUSIONS AND SUGGESTIONS 67
REFERENCES 70
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