This Small Business Technology Transfer Phase I project improves mining and geotechnical drilling activities by eliminating handling of bulky samples.Core drilling consumes about 10,000 gallons of water per day, often in water-deficient areas. The proposed new approach negates the need for water in the drilling process, thereby mitigating the risk of pollution to public and wildlife drinking water sources. Reducing the time required for a typical drilling project from weeks to days reduces the carbon emission from the energy-intensive drilling equipment required. This solution to problems associated with acquiring subsurface data with traditional techniques has an addressable market segment value of $21 billion. The new instrument to be developed will eliminate the need for off-site lab services, core drilling, and site geologists, resulting in lower industry life cycle costs and spurring critical exploration activities for needed US strategic minerals.The intellectual merit of this project is based in the development of a novel drilling module that will be able to acquire subsurface chemistry and geotechnical properties of rocks and soils, to assess the type and value of minerals present both quickly and accurately. The conventional way of evaluating these materials is by core drilling, which presents various problems related to cost, sample quality and logistics. This research uses a combination of optical images, x-ray fluorescence, and gamma-ray density, as well as compressive strength data from a newly curated database that will be developed from open-source geospatial data, collections of geology and geotechnical reports, rock core databases, implicit geology modeling principles, and machine learning methods to characterize rock and soil samples. It aims to solve the technical challenges that currently prevent such a tool from being available to the industry today; these include mud smearing in the drill hole sidewalls, the high pressure and heat of the target environment, and challenges in wireless data transmission. The goal of this research is to create, validate and calibrate a method for automating the characterization of an unknown rock or soil sample in situ via a combination of hardware and software innovations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
