Mineral Prospectivity Modelling
Kenex
predictive models have helped target highly prospective ground in New
Zealand and Australia and have helped companies such as Auzex Resources, HPD
Exploration, and Aurora Minerals raise million of dollars from market based
investors. Kenex is able to help you acquire highly prospective land before
your competitors even know it exists, tell you which data types are the most
useful to collect in your exploration areas, and help you prioritise work
programs based on the prospectivity of your tenements. Kenex can really add
value to your exploration and allow you to focus your money and time on the
most prospective land.
The development of a mineral prospectivity model by Kenex includes the following steps:
- Data Compilation: The initial step is deciding on the data that will be required to run the model and getting this data into a digital form. Today much of the data required for mineral exploration already distributed in a digital GIS format and is available either free-of-charge or available through a licence agreement from most geological surveys. Kenex organises the digitising of the remaining data and compiles a digital GIS database that will be used for the spatial modelling. Data sets used in a model might include: rock chip, stream sediment, soil, and drill hole geochemistry, geological mapping (faults, folds, lithology, deformation, veining, age), geophysics, mapped alteration zones, mineral occurrences, and existing mine sites.
- Expert Knowledge: No model could be completed without expert subject knowledge provided by leading industry experts. With more than 50 years of combined industry experience in-house and hundreds of contacts, partnerships, and professional associations, Kenex is able to cast a critical eye over all information in the datasets used for the model, determine the importance of key themes, and knows the intricacies of the subject matter. This expert knowledge allows us to develop and use the best and most cutting edge mineral deposit models to find new mineral deposits and re-evaluate existing prospects.
- Data preparation: Themes and datasets are tested using spatial statistics and are converted into the key themes required for the model. This stage is the most time consuming for the modelling geologist as it requires scores of different filtering, analytical, statistical, and data preparation techniques. Modelling: Kenex uses Arc-SDM on an ESRI GIS platform and MI-SDM on a MapInfo GIS platform to run the models and prepare the data themes. As one of the global leaders in prospectivity modelling we maintain close links with the software developers to ensure that we're all constantly developing the modelling techniques and the science behind them. Greg Partington here at Kenex regularly publishes research papers on the subject [paper list].
- Model Output: The modelling process generates a data layer that shows the prospectivity of mineralisation occurring at a given location. This data set can be displayed as a map that high-lights the most prospective areas, it could be applied to a set of land parcels showing which are most likely to have the event modelling occurring in it, or used to rank the importance of existing exploration tenements or land use zones.
- Reporting / Exploration Advice: Models are output to the clients specifications. These can range from a complete digital dataset in the form of a GIS through to a large colour coded map showing the prediction values. Kenex also includes a report on all our models discussing the results, how they were obtained, and what data was included. A common request from our exploration clients is for expert advice on prioritising their exploration, tenement management and sampling programs based on the modelling results. Prospectivity models are also frequently used to showcase the mineral potential during IPO's, project fundraising, and other market related reporting.
For more about the statistics, processes, and science behind this modelling click here
Contact Michelle or Greg for more information about mineral prospectivity modelling by Kenex.
