Efficient data collection adds value over the life of a mining project, especially when the end purposes of the database are fully considered at the beginning of the exploration stage. The process starts with optimizing entry forms and configuring a database to readily import and organize observations and analytical results.
Development of a representative geological model is one of the main goals of the exploration process. This model’s foundation is accurate and complete data collection from field observations, converted to a usable digital format. Logging of drill core or chips to generate a sub-surface data set is the emphasis, but the principles are also applicable to mapping. The modeling process starts with an effective database design, including input forms that facilitate both quantitative data collection and geological interpretation. Material types in a deposit are the result of many geological processes acting on a rock mass. Geological modeling, and therefore, data collection, is most efficient with a process-based approach.
Initially, the model will depict lithological and other geological contacts and, where mineralized, grade domain boundaries. As a project advances to the development stage, the data set should allow delineation of material types leading to metallurgical, waste rock, and geotechnical characterization.
Many observations, commonly overlooked by exploration geologists, can help define material properties required for designing metallurgical process and mine design. A wide array of mining applications should be considered at the beginning of an exploration program to fully define the data elements to be captured, interpreted and modeled. A complete and consistent data set adds value to the project and reduces risk to future development.
