融合地下水位與溫度資料於地層三維水力及熱傳參數異質場推估

Abstract

溫度為描述地層狀態的重要指標，亦是影響地下水流場的主因之一。在污染整治或是地熱能交換等有大量熱能產生與交換的研究中，量化溫度對地下水流場的影響更為重要，然此類研究大多忽略水力參數受溫度的影響，且多數研究皆假設熱傳參數場為均質，導致無法準確描述地下水流場及溫度場分布。而為了求得準確的流場及溫度場，本研究開發融合水位與溫度資訊之聯合反演模式，此模式包含三維水流與熱流耦合模擬模式（正演模式）與融合溫度與水位的水力與熱傳參數推估模式（反演模式）。此推估模式以水力掃描概念為基礎，提出融合溫度與水位資訊的演算法，可同時推估三維水力及熱傳參數場。此外，本研究將正演模式與反演模式開發完成後，以多組數值試驗進行正演與反演模式之測試與檢驗。研究結果顯示：(1)考量水流與熱流之交互影響下，融合水位與溫度資訊可同時改善水力與熱傳參數場之推估結果。(2)背景地下水流速之快慢不會影響熱傳參數之推估結果。(3)在地下水溫度變化顯著的條件下，進行水力與熱傳參數的聯合反演可求得更精確之參數場，展現本方法之效益。本研究提出之聯合反演模式可有效推估地層中之三維水力與熱傳參數場，精確地模擬地下水流場與溫度場，未來將可作為污染整治與淺層地熱交換系統設計等研究之基礎。

Subsurface temperature is a crucial indicator to represent the status of the stratum and one of the important factors affecting the groundwater flow field. For the case with abundant thermal energy production or exchange (e.g., contamination oxidation or geothermal energy exchange), quantifying the effect of temperature change on the groundwater fields is an important issue. However, most of these studies neglect the effect of temperature variations on the hydraulic properties and assume the thermal parameter fields are homogenous, causing inaccurate geothermal and groundwater flow field predictions. To obtain accurate flow and geothermal fields, we have developed a joint inversion method consisting of a coupled three-dimensional groundwater and heat transport model and a joint inversion algorithm. The inversion algorithm is developed based on the concept of hydraulic tomography(HT) and successive linear estimator(SLE). Several numerical experiments have been designed to examine the proposed joint inversion model. The main findings include: (1) The joint inversion method can simultaneously improve the hydraulic and thermal properties fields based on the coupled groundwater and heat transport model. (2) Background flow field influences the estimated thermal conductivity fields less. (3) When significant temperature changes occur in groundwater, joint interpolating the head and temperature measurements are essential to derive the accurate parameter fields and accurately predict groundwater flow and thermal fields. The study results can be valuable for geothermal energy exchange and contaminated site remediation studies.