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Jacob Smith | August 24, 2016

Testing on Small Volumes, Processing on Large

Testing on Small Volumes, Processing on Large

Jacob Smith on 25 Aug 2016
With the acquisition of ever larger and denser surveys, it can be challenging to efficiently optimise and run processes on your data. GeoTeric solves this problem by allowing you two different methods to rapidly test your processes on small volumes, before running the processing on the full dataset. An example will be shown below using the Noise Expression tool. The steps assume you have the full dataset loaded into GeoTeric.
  1. Visualise the full dataset in the main viewer.
  2. Click the ‘Extents’ button in the bottom right.
  3. Trim the volume to focus on a target area.
  4. Enter a name in the ‘Subset’ box and click ‘Save Subset’.

  1. Open Noise Expression, selecting the subset from the dropdown.
  2. Optimise your process as normal.
  3. Once you are satisfied with the results, hit ‘Generate 3D Volumes’.
  4. Firstly, note the location and name of the batch job. This can be applied to any dataset at a later point. Instructions for this will be given later.
  5. If you wish to apply the current process to the full volume, simply select it from the dropdown at the top.
  6. If you choose the full volume from the dropdown and click ‘Process’, the processing will be applied to that dataset.
  7. This method can be used in Noise Expression, Spectral Expression, HDFD and Fault Expression.

Using the Batch Job

This will allow you to load up any batch job that has been saved previously, and apply it to any datasets you have available in your project. Care should be taken to only apply processes to appropriate datasets.

  1. From the menus in the top left of the main viewing window, select ‘Workflows’ > ‘Processes and Workflows…'
  2. From the top left of the Processes and Workflows window, select ‘File’ > ‘Open…’ (The window is actually titled ‘Batch Processing Framework’)
  3. Browse to the location of your batch job and open it. This will generally be in the ‘batchjobs’ directory within your project.
  4. On the left hand tab, select the input dataset from the drop down.
  5. The output dataset names can also be changed at the bottom of each tab. This is not essential however.