Preliminary Exploration of Geotechnical Data Interpretation and GIS Integration: Toward AI Implementation
Kuwait's rapid urban expansion, driven by large-scale projects, such as AI-Mutlaa City and Silk City, highlights the need for comprehensive geotechnical data to support sustainable development. However, detailed studies on the subsurface geotechnical characteristics of the northern regions of Kuwait are lacking. This study focuses on establishing a preliminary geotechnical database, addressing challenges encountered during its development, and conducting a pilot analysis for AI-Mutlaa City. A questionnaire was distributed to geology, environmental, geotechnical, and engineering professionals to identify the challenges associated with creating the database. The survey revealed issues such as inconsistent data formats, limited access to borehole logs, and the hesitancy of private firms to share data due to security concerns. Despite these challenges, borehole data from ministries and private organizations were collected and organized using Microsoft Excel. These data formed the foundation of the geotechnical database, which was analyzed and visualized using Geographic Information System (GIS) tools. The pilot study in AI-Mutlaa City revealed predominantly dense soil layers, with significant variations in soil strength at a depth of 19.5 m, where standard penetration resistance ranged from 10 to 50 blows. These findings emphasize the variability of soil properties in the area and underscore the importance of site-specific investigations. The established geotechnical database provides valuable insights for construction planning, risk assessment, and geohazard management. Moving forward, the integration of artificial intelligence into the database is planned to enhance data processing, automate soil classification, and predict subsurface conditions in an effort to contribute to advanced geotechnical practices in Kuwait.
Authors
- Danah S. Al-Enezi
Institutions
- Kuwait Institute for Scientific Research (KW)
Publication Details
- Published
- 2025-02-03
- DOI
- https://doi.org/10.1109/ai2e64943.2025.10983264
- Primary Topic
- Geological Modeling and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00