Robust review and validation of project geotechnical data are essential to provide valuable inputs for subsequent mine modelling and design but are sometimes poorly understood. It is particularly important to ensure that data collection by logging personnel and storage within geotechnical databases are in the best condition possible.
The quality of, and confidence in, subsequent design and modelling are reliant on the acquired dataset including derived rock mass properties. This paper discusses the importance of effective validation of geotechnical, structural, and laboratory data, and suggests some tools to guide the reader through the validation of such data. Once the data have been ‘cleaned’ of errors and further processed in a way that makes them easier to measure, visualise and analyse for a specific purpose, they become more valuable information.
Following the robust validation of logging and laboratory data, a systematic domaining process is suggested, incorporating geological, hydrogeological, structural, and geotechnical data, to ensure the data are reliable and their variability is well understood. Knowledge and insights gained from the data validation and domaining process are crucial to select appropriate inputs into subsequent modelling and design.
