Logging stratigraphy on a drill rig to decide to continue or end the hole is a skill that every geologist should have. Ideally logging happens at the rig in realtime as we are often wanting to determine end of hole critera. Let’s consider how well hyperspectral and image data perform in classifing samples into prospective and non-prospective units. As usual we are going to use this dataset from from the C3DMM project.

Let’s talk about the performance of using chips vs hyperspectral to classify ore and waste in an Iron ore deposit. Before we go onto the technical work let’s discuss the practical uses of this information. Common use cases would be deciding if a sample is ore/waste, screening samples for further analysis or simply selecting the right sensor for you application and trading off cost/speed/performance/technical difficulty considerations. So with all that in mind I hope that you will find a smart application in your workplace.

Good Afternoon Spectroscopists, I though someone might be interested in using pytsg to process hyperspectral data. For this example we are going to use this dataset provided by CSIRO under a CC4 licence collected for the C3DMM project In this post we will use of PLS to predict Fe grade from the spectra. Let us start by installing the libraries that we are going to need. You can use the tsg file reader that I developed here or you can write your own…

Hi All, I want to help you solve one of those occasional problematic issues that come up every now and then, extracting historical tabular data from old reports. Let’s imagine that you’ve aquired a tenement and reading the historical reports it looks like you’re onto something great. But the only historical data that you have available is very old and unfortunately predates the nice digital formats that we have now.

Hi All, I would like to start my posting journey by talking about an issue that is near and dear to my heart: reading data. In Australia lucky geologists and data enthusiasts have access to a fantastic source of open file geoscientific data provided by our geological services such as GSWA and as tenements are released the data from then slowly becomes available as open file data under the fantastic CC4.