大地工程的可靠性與不確定性有關。降低不確定性將提高可靠性和降低風險。此外，評估折射震測法之處理過程是減少不確定性的基礎。折射震測法中的人為誤差是該方法中與不確定性相關的重要問題之一。本研究目的為減少折射震測法的不確定性。折射震測法需要兩個步驟來利用P 波波速的不同決定層與層之間的邊界。即根據時距曲線 (T-D 曲線) 選取初達波並將具有相同波速的資料合為一層。本研究利用了兩種合成地質模型的正演模擬結果，給出了各層的邊界和各層的 P 波速度。第一個模型由五層組成，速度隨深度增加（從上到下為Vp = 700 m/s、1100 m/s、1500 m/s、1800 m/s和2200 m/s），而第二個模型由六層組成，其中有一個盲層（Vp = 1000 m/s、1500 m/s、1700 m/s、1400 m/s、1800 m/s 和 2200 m/s）。根據七位操作員的挑選初達波結果，我們發現不管模型一和模型二，第一層具有高度的不確定性(模型一：11.2%，模型二：13.7%)。層跟層間的邊界的高不確定性及P波速度的低精確度也認為是在挑選初達坡過程中的人為誤差影響。在將相同波速資料合為一層的處理上，模型一第一層P波速度的不確定性較高（11.8%），而模型二的P波速度值精確度較低。盲層放大了不確定性，降低了精確度。從不同的初達波挑選結果，折射震測層析成像只能得到較淺層的資料。此外，與初達波挑選和分層處理相比，折射震測層析成像的不確定性較小。地層厚度數據有效降低了不確定性（7.1%），且P 波速度可以降低不確定性至1.7%(模型一)和3.5%(模型二)。地層厚度資料和波速資料有效地降低了分層處理的不確定性。然而，初達波挑選的不確定性仍然存在。此研究得到的地質模型可能與真實模型有很大的偏差。

Reliability in geotechnical engineering is related to uncertainty. Decreasing uncertainty will affect increasing reliability and low risk. Moreover, evaluating the seismic refraction method is fundamental to reducing uncertainty. Human error in seismic refraction is one of the important issues related to uncertainty in this method. The main research purpose is to evaluate seismic refraction and reduce uncertainty in seismic refraction. Two steps are essential for seismic refraction to determine the boundaries of different layers with different P wave velocity (Vp), picking first arrival data and grouping data into a unified layer with identical wave velocity based on the time-distance curve (T-D curve). This study utilized the forward modeling results of two synthetic geological models. The boundaries of layers (gently dip straight line) and the P wave velocity of each layer was given. The first model is made up of five layers, with velocity increasing with depth (Vp = 700 m/s, 1100 m/s, 1500 m/s, 1800 m/s, and 2200 m/s from top to bottom), while the second model is made up of six layers with a blind layer (Vp = 1000 m/s, 1500 m/s, 1700 m/s, 1400 m/s, 1800 m/s, and 2200 m/s). According to the pick results of seven operators, we discovered high uncertainty (11.2 %) in the first layer for Model 1 and (13.7%) for Model 2. High uncertainty in the boundary layer and low precision of the P wave velocity on Model 2 was also founded on human error in the first arrival picking processing. On the Grouping layer processing, high uncertainty of P wave velocity in the first layer (11.8 %) on the Model 1. However, low accuracy of the P wave velocity value on Model 2. The blind layer amplifies uncertainty and decreases accuracy. Based on different first arrival picking, Seismic refraction tomography will have the narrow zone of the boundary data. Moreover, the uncertainty of seismic refraction tomography is small compared with first arrival picking and grouping layer processing. Thickness data effectively reduces uncertainty (7.1%), and P wave velocity data can reduce uncertainty until (1.7 %) on Model 1 and (3.5 %) on Model 2. Thickness data and velocity data effectively reduce uncertainty in grouping layer processing. However, uncertainty from first arrival picking still exists. The analyzed geological model could have deviated significantly from the true model.

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