Two-dimensional prediction of the interface of geological formations: a comparative study
The location of the interface of geological formations is an important piece of information for tunneling construction. As site investigation data are usually limited, the uncertainties in locating geological interfaces for the sections between boreholes can be large and challenging to estimate. A s...
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sg-ntu-dr.10356-1619812022-09-28T02:24:39Z Two-dimensional prediction of the interface of geological formations: a comparative study Qi, Xiaohui Wang, Hao Chu, Jian Chiam, Kiefer School of Civil and Environmental Engineering Engineering::Civil engineering Geological Interface Rockhead The location of the interface of geological formations is an important piece of information for tunneling construction. As site investigation data are usually limited, the uncertainties in locating geological interfaces for the sections between boreholes can be large and challenging to estimate. A suitable geostatistical method is thus needed for spatial prediction of the geological interfaces. In this paper, the performance of three commonly used spatial prediction methods, namely the multivariate adaptive spline regression (MARS), conditional random field (CRF) method, and thin-plate spline interpolation (TPSI) methods, are evaluated for two-dimensional cases using the boreholes data from three sites in Singapore. The prediction accuracies, patterns of the predicted surfaces, and prediction uncertainties obtained from the three methods are compared. A zonation is also proposed to improve the prediction accuracy of the MARS method. The results indicate that the MARS method can show the spatial trend of the geological interface more clearly than the other two methods. The TPSI method produces undesirable oscillations of the surface of geological interfaces and the CRF method may underestimate the extreme values of the geological interface elevations. In general, the prediction accuracy of the MARS method is similar to that of the CRF method, but higher than that of the TPSI method. For cases with very limited data in geologically complex areas, the MARS may have larger errors than the CRF method. However, the accuracy of the former can be significantly improved if a reasonable zonation is performed. Ministry of National Development (MND) National Research Foundation (NRF) This research is supported by the Singapore Ministry of National Development and the National Research Foundation, Prime Minister’s Office under the Land and Liveability National Innovation Challenge (L2NIC) Research Programme (Award No. L2NICCFP2-2015-1). 2022-09-28T02:24:38Z 2022-09-28T02:24:38Z 2022 Journal Article Qi, X., Wang, H., Chu, J. & Chiam, K. (2022). Two-dimensional prediction of the interface of geological formations: a comparative study. Tunnelling and Underground Space Technology, 121, 104329-. https://dx.doi.org/10.1016/j.tust.2021.104329 0886-7798 https://hdl.handle.net/10356/161981 10.1016/j.tust.2021.104329 2-s2.0-85121928982 121 104329 en L2NICCFP2-2015-1 Tunnelling and Underground Space Technology © 2021 Elsevier Ltd. All rights reserved. |
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Engineering::Civil engineering Geological Interface Rockhead Qi, Xiaohui Wang, Hao Chu, Jian Chiam, Kiefer Two-dimensional prediction of the interface of geological formations: a comparative study |
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The location of the interface of geological formations is an important piece of information for tunneling construction. As site investigation data are usually limited, the uncertainties in locating geological interfaces for the sections between boreholes can be large and challenging to estimate. A suitable geostatistical method is thus needed for spatial prediction of the geological interfaces. In this paper, the performance of three commonly used spatial prediction methods, namely the multivariate adaptive spline regression (MARS), conditional random field (CRF) method, and thin-plate spline interpolation (TPSI) methods, are evaluated for two-dimensional cases using the boreholes data from three sites in Singapore. The prediction accuracies, patterns of the predicted surfaces, and prediction uncertainties obtained from the three methods are compared. A zonation is also proposed to improve the prediction accuracy of the MARS method. The results indicate that the MARS method can show the spatial trend of the geological interface more clearly than the other two methods. The TPSI method produces undesirable oscillations of the surface of geological interfaces and the CRF method may underestimate the extreme values of the geological interface elevations. In general, the prediction accuracy of the MARS method is similar to that of the CRF method, but higher than that of the TPSI method. For cases with very limited data in geologically complex areas, the MARS may have larger errors than the CRF method. However, the accuracy of the former can be significantly improved if a reasonable zonation is performed. |
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School of Civil and Environmental Engineering |
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School of Civil and Environmental Engineering Qi, Xiaohui Wang, Hao Chu, Jian Chiam, Kiefer |
format |
Article |
author |
Qi, Xiaohui Wang, Hao Chu, Jian Chiam, Kiefer |
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Qi, Xiaohui |
title |
Two-dimensional prediction of the interface of geological formations: a comparative study |
title_short |
Two-dimensional prediction of the interface of geological formations: a comparative study |
title_full |
Two-dimensional prediction of the interface of geological formations: a comparative study |
title_fullStr |
Two-dimensional prediction of the interface of geological formations: a comparative study |
title_full_unstemmed |
Two-dimensional prediction of the interface of geological formations: a comparative study |
title_sort |
two-dimensional prediction of the interface of geological formations: a comparative study |
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2022 |
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https://hdl.handle.net/10356/161981 |
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1745574657989279744 |