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Digital field mapping and the detection and estimation of uncertainty in 3D geological modelsPICO Session
Convener: Mark Lindsay  | Co-Conveners: Florian Wellmann , Marco Giardino 
 / Wed, 15 Apr, 13:30–15:00  / PICO Spot 2
Recent developments in portable hardware has provided geoscientists with the opportunity to map and gather data in the field directly using digital tools and software rather than using paper maps, notebooks and analogue devices. These emerging techniques present new challenges ranging from training, quality control, hardware and software requirements, as well as cultural issues with heritage practice and community acceptance. Ultimately, they also present the potential for a paradigm step in modernising the science and craft of field geology with efficiency, quality improvement, integration with existing datasets and (perhaps most importantly) uncertainty reduction in field-collected data.

The term geological modelling covers a wide range of activities, including geothermal, geodynamic, hydrogeological, mineral potential, and geophysical modelling in 1, 2 and 3D. As a structural geological model usually forms the basis for geological modelling, its quality will in part determine the success of the overall modelling effort. Structural modelling has benefited from recent advances in code development, increased availability of high-resolution data and access to supercomputing platforms. As impressive as these codes, datasets and computing platforms are, modelling is still subject to errors and uncertainty which adversely affect model quality. The sources of uncertainty can be, but are not limited to, the choice of code or input data, and the conceptual framework with which modelling efforts are framed.

This session aims to merge these approaches by:
- presenting experiences and showcase work in digital mapping including case studies, technology and technical presentations from those experimenting with, and pioneering, digital field mapping.
- analysing the sources of uncertainty in structural geological modelling and discussing what approaches are effective at mitigating the effects of uncertainty.
Contributions are welcome from all geoscientific disciplines that contribute to field mapping and to the generation of 3D structural geological models, especially geophysical methods and field-based data collection, with emphasis placed upon innovative techniques and novel perspectives. A cross-disciplinary scope will provide perspective and possible solutions to common issues associated with managing field mapping issues and uncertainty in geoscientific modelling.