HomeMarket NewsMiningThe Maptek Geology Challenge Winner Utilizes Data-Driven Modelling Approach to Map Complex...

The Maptek Geology Challenge Winner Utilizes Data-Driven Modelling Approach to Map Complex Structures

Actionable Trade Ideas

always free

The Maptek Geology Challenge has recently concluded its third year, offering participants access to DomainMCF, Vulcan, and Vulcan GeologyCore software for a month. This year’s challenge involved working with a difficult dataset known as Burden, featuring drillholes collected around 40 years ago. The dataset presented challenges due to the presence of 10-20m long assay intervals and inconsistent lithology records. Additionally, the inclusion of a pit exposed to the elements since the 1990s made structural mapping even more challenging.

In the past, manual flagging of drillholes with different veins was the method used to process the data, often resulting in a repetitive and time-consuming process. However, this year’s winner, Caroline Burden, embraced a more data-driven approach by utilizing the machine learning engine DomainMCF provided by Maptek. This allowed her to observe the 3D trends of grade distribution, visualize patterns, and incorporate subsurface thrusts and faults that aligned with the structural mapping. By refining the veining in the models, Burden was able to better identify and understand the structures controlling the mineralization.

Incorporating the structural data with machine learning proved to be essential in developing a more comprehensive model. While data-driven models are ideal, the ability to handle statistical uncertainties and fill gaps is crucial. The use of machine learning enabled Burden to achieve a more complete model, aligning with the objective of the challenge.

GeologyChallengers2023
From left: Caroline Burden, Anthony Bottrill and Evelyn Charlesworth. Image from Maptek.

Maptek also recognized the achievements of the second-place winner, Anthony Bottrill of InterGEO Resource Consulting. Bottrill combined different data types and utilized DomainMCF to rapidly generate a 3D geochemical model, showcasing natural trends before conducting any interpretation. He was surprised to discover that DomainMCF presented plausible extrapolation beyond the known data extents, providing new insights into the relationship between adjacent deposits and identifying a target exploration zone at depth. The ease of use and minimal input required for DomainMCF allowed Bottrill to focus on interpretation and spatial analysis in ways that other methods did not permit.

The third-place winner, Evelyn Charlesworth of Kōmanawa Solutions, leveraged DomainMCF to enhance her project on understanding coastal heterogeneity. She found the juxtaposition viewing slider particularly useful in comparing geological outputs of models created from different datasets.

All participants in the Maptek Geology Challenge showcased innovative techniques to address a variety of geological and engineering geology problems. Senior Geologist Richard Jackson, the convenor of the challenge, expressed his gratitude to all participants and highlighted the exceptional submissions that utilized DomainMCF to control and understand the complexity within their models.

Swing Trading Ideas and Market Commentary

Need some new swing ideas? Get free weekly swing ideas and market commentary from Jonathan Bernstein here: Swing Trading.

Explore More

Weekly In-Depth Market Analysis and Actionable Trade Ideas

Get institutional-level analysis and trade ideas to take your trading to the next level, sign up for free and become apart of the community.