Description

The construction of a reliable subsurface model is a technical challenge in the field of construction and risk management. Real-time monitoring of drilling by recording drilling parameters is a technical solution for the unbiased acquisition of ground characteristics. At present, there is no metrologically correct and accurate measurement system. Real-time collection of this data in shared databases can help to limit the difficulties associated with difficult soil layers and natural or anthropogenic underground cavities. The heterogeneity of the terrain cannot be properly assessed, and the very partial view of the site obtained at the end of the investigations leads to variable results depending on the number and location of the survey points. In addition, the machine operator, who is unfamiliar with the lithology, does not always adapt the machine's control to the terrain correctly.
We propose to develop a new type of innovative, accurate, intelligent, and wireless sensor to use drilling parameters and measurements of the soil's response to the drilling process and enable the identification of local heterogeneities using geostatistical tools to establish a reliable terrain model in near real time and ultimately control the machine.
Finally, an artificial intelligence algorithm (or, more simply, an expert system configured by the operator) will be developed to automatically control the drill and adjust both the drilling parameters and the depth of the hole in order to meet the design requirements as closely as possible.
These developments could lead to the design of a new electronic architecture enabling the robotization of drilling rigs, which will reduce machine time and energy consumption, and ultimately reduce production costs and save natural resources.

Skills required

- Student majoring in Civil Engineering, Geotechnical Engineering, or Continuum Mechanics - A solid foundation in soil mechanics and a strong interest in data handling and analysis (Big Data) are essential. - Scientific rigor, the ability to synthesize information, and strong interpersonal skills to collaborate with field teams and data scientists.

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Keywords

Geotechnics, drilling, in-situ testing, geostatistics, monitoring