Filters in OpendTect are implemented as Attributes that need to be defined in the attribute set window. Filters with a user interface are grouped under Filters. This group includes convolution, frequency filters, gap decon, and velocity fan filters. Filters without a user interface are filters that are constructed from (chains of) attributes. For example, using Reference Shift, Volume Statistics, and Mathematics, you can extract and manipulate data to construct your own filters. This group of filters contains, among others: dip-steered median filter, dip-steered diffusion filter, fault enhancement filter, and ridge-enhancement filter. A number of these filters are delivered with the system as default attribute sets.
Purpose: Sharpen edges (faults) by filtering along the structural dip. Theory: In diffusion filtering, you evaluate the quality of the seismic data in a dip-steered circle. The center amplitude is replaced by the amplitude where the quality is deemed best. In the vicinity of a fault, the effect is that good quality seismic data is moved from either side of the fault in the direction of the fault plane, hence the fault becomes sharper. Software: OpendTect + Dip-Steering
Workflow:
Open the attribute set window and open the default set called: Dip-steered diffusion filter. Select seismic and steering cube.
Use Evaluate attribute and evaluate the "Stepout" (radius) of the Position attribute on a (small) test element, e.g. part of an inline.
Apply the Diffusion filter to the seismic data in batch: Processing - Create seismic output, or on-the-fly: right-click on the element in the tree.
Tips:
Dip-steered filtering works best when you use a heavily smoothed steering cube (background steering). Smoothing of the steering cube is done in Processing - Steering - Filter. Use e.g. a median filter 4x4x4 to create the background steering cube.
Calculate Similarity (or Coherency) on dip-steered diffusion filtered seismic data if you need to see sharp faults.
Dip-steered diffusion filtering produces unwanted circular patterns in amplitude horizon slices. To reduce this effect, combine dip-steered diffusion filtering with dip-steered median filtering. This is explained in the Fault enhancement filtering work flow.
