Making sense of geophysics data to reveal targets
Mineral explorers are looking for anomalies as a sign of an orebody, but not every anomaly in a geophysical dataset is an orebody.
As geophysical data are an indirect measurement of subsurface properties, there is a level of uncertainty around the accuracy of corresponding models and otential targets based on probalisitic inference. For example, there is uncertainty that a base metal target inferred from data is accurate and will be intersected during drilling.
If we can quantify the robustness of the data, targets can be objectively ranked in terms of their likelihood. Objective target ranking and delineation is key for exploration companies to effectively plan follow-up surveys.
Improving the objectivity of target identification
Combining hypothesis testing and geophysical inversion provides the foundation for ranking targets for better informed exploration strategy.
Ranking targets early and combining different geophysical survey datasets reduces uncertainty and means that an exploration program can be directed efficiently.
With a novel and pragmatic approach, we can help reduce the time it takes to come up with robust solutions and rank targets.
Working with industry and government agencies, our focus is on improving the effectiveness of inference models and targets from geophysical data, including:
- target detection – understanding whether data anomalies are caused by expected geological structures or mineralised zones within or beneath them
- target ranking – new quantitative workflows that help companies accurately and objectively rank anomalies to support an efficient exploration program
- target delineation – understanding the extents of a target that is inferred from geophysical data to inform follow up geophysical surveys and drilling programs.