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Automatic Construction and Uncertainty Analysis of Geological Profiles in Dredging Engineering Based on Multiple-Point Geostatistics
https://orcid.org/0000-0002-3010-0892
Sparse borehole data and unreasonable sampling strategies pose challenges in accurately constructing geological profiles, resulting in inaccurate soil distribution information and impacting the design of implementation plans for dredging engineering. Therefore, an automatic construction and uncertainty analysis approach to the geological profile of dredging engineering is proposed using multiple-point geostatistics. The approach uses a training image instead of the variogram function, considering the spatial variability of the soil and adapting to learn high-order spatial information. This enables the characterization of spatial relationships and distribution patterns between multiple points. Subsequently, statistical uncertainty analysis is conducted based on the results obtained from stochastic simulations. The effects of neighboring cell numbers, threshold, and borehole spacings on the performance of our approach are systematically investigated and the optimal simulation parameters are determined. Additionally, the simulated geological profiles are categorized into three areas (high, medium, and low) based on the level of uncertainty, quantifying the uncertainty of the proposed approach. The equidistant method is then used for comparison and verification. When applied to a dredging engineering case in the Lianyungang Channel, the approach achieved a prediction accuracy of over 93.7% and successfully quantified boundary areas with high uncertainty in soil layers. This shows the enhanced capacity of the approach to capture characteristics of soil distribution. The approach reduces the area of high uncertainty by 11.4%, demonstrating advancements in selecting drilling locations. The study will provide decision support for geological surveys in dredging engineering and provide reliable soil information for subsequent construction.
Automatic Construction and Uncertainty Analysis of Geological Profiles in Dredging Engineering Based on Multiple-Point Geostatistics
https://orcid.org/0000-0002-3010-0892
Sparse borehole data and unreasonable sampling strategies pose challenges in accurately constructing geological profiles, resulting in inaccurate soil distribution information and impacting the design of implementation plans for dredging engineering. Therefore, an automatic construction and uncertainty analysis approach to the geological profile of dredging engineering is proposed using multiple-point geostatistics. The approach uses a training image instead of the variogram function, considering the spatial variability of the soil and adapting to learn high-order spatial information. This enables the characterization of spatial relationships and distribution patterns between multiple points. Subsequently, statistical uncertainty analysis is conducted based on the results obtained from stochastic simulations. The effects of neighboring cell numbers, threshold, and borehole spacings on the performance of our approach are systematically investigated and the optimal simulation parameters are determined. Additionally, the simulated geological profiles are categorized into three areas (high, medium, and low) based on the level of uncertainty, quantifying the uncertainty of the proposed approach. The equidistant method is then used for comparison and verification. When applied to a dredging engineering case in the Lianyungang Channel, the approach achieved a prediction accuracy of over 93.7% and successfully quantified boundary areas with high uncertainty in soil layers. This shows the enhanced capacity of the approach to capture characteristics of soil distribution. The approach reduces the area of high uncertainty by 11.4%, demonstrating advancements in selecting drilling locations. The study will provide decision support for geological surveys in dredging engineering and provide reliable soil information for subsequent construction.
Automatic Construction and Uncertainty Analysis of Geological Profiles in Dredging Engineering Based on Multiple-Point Geostatistics
https://orcid.org/0000-0002-3010-0892
Sparse borehole data and unreasonable sampling strategies pose challenges in accurately constructing geological profiles, resulting in inaccurate soil distribution information and impacting the design of implementation plans for dredging engineering. Therefore, an automatic construction and uncertainty analysis approach to the geological profile of dredging engineering is proposed using multiple-point geostatistics. The approach uses a training image instead of the variogram function, considering the spatial variability of the soil and adapting to learn high-order spatial information. This enables the characterization of spatial relationships and distribution patterns between multiple points. Subsequently, statistical uncertainty analysis is conducted based on the results obtained from stochastic simulations. The effects of neighboring cell numbers, threshold, and borehole spacings on the performance of our approach are systematically investigated and the optimal simulation parameters are determined. Additionally, the simulated geological profiles are categorized into three areas (high, medium, and low) based on the level of uncertainty, quantifying the uncertainty of the proposed approach. The equidistant method is then used for comparison and verification. When applied to a dredging engineering case in the Lianyungang Channel, the approach achieved a prediction accuracy of over 93.7% and successfully quantified boundary areas with high uncertainty in soil layers. This shows the enhanced capacity of the approach to capture characteristics of soil distribution. The approach reduces the area of high uncertainty by 11.4%, demonstrating advancements in selecting drilling locations. The study will provide decision support for geological surveys in dredging engineering and provide reliable soil information for subsequent construction.
Automatic Construction and Uncertainty Analysis of Geological Profiles in Dredging Engineering Based on Multiple-Point Geostatistics
J. Waterway, Port, Coastal, Ocean Eng.
Chen, Yong (author) / Li, Mingchao (author) / Ren, Qiubing (author) / Tian, Huijing (author) / Qin, Liang (author) / Huang, Keqi (author)
2024-11-01
Article (Journal)
Electronic Resource
English
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