Development Of Novel Geophysical–geotechnical Relationships Of Granitic Environments In Penang Island, Malaysia
The characterization of near-surface soil-rock conditions is challenging in tropical crystalline terrains due to complex geology and lack of distinct stratigraphic markers. These features can adequately be mapped using velocity-resistivity relationships via statistically optimized soil-rock quality...
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| 格式: | Thesis |
| 语言: | English |
| 出版: |
2023
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| 主题: | |
| 在线阅读: | http://eprints.usm.my/60231/1/AKINGBOYE%20ADEDIBU%20SUNNY%20-%20TESIS24.pdf |
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| 总结: | The characterization of near-surface soil-rock conditions is challenging in tropical crystalline terrains due to complex geology and lack of distinct stratigraphic markers. These features can adequately be mapped using velocity-resistivity relationships via statistically optimized soil-rock quality modeling, especially in areas with overburden <50 m. The approach has not been used in tropical granitic terrains. To achieve the research goals, Penang Island, Malaysia; a tropical granitic terrain, was considered a suitable area due to its intrinsic soil-rock characteristics and the need to resolve environmental-related issues. This research, therefore, develops velocity-resistivity statistical relationships for granitic terrains based on complex collocated geotomographic (electrical resistivity tomography and seismic refraction tomography [SRT]) modeling. To this end, four detailed methodological scenarios were utilized, leveraging borehole logs, rock quality designation (RQD), soil penetration test (SPT N-values), and supervised regression analysis. The results show that the borehole lithologic logs correlate well with resistivity- and SRT-based lithological models at the eastern (Sungai Ara), southern (Batu Maung), and northern (Jelutong) sections of Penang Island. The areas are characterized by sandy silt topsoil, silty sand to sandy weathered units, weathered/fractured units, and integral/fresh granitic bedrock. The rock quality assessment, via borehole-based RQD, and SRT- and resistivity-based RQD models, had empirical prediction accuracies of 95.8% to 100%. |
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