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Noise attenuation by partial trace summation
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The module does spike-noise attenuation by partial summing of traces. For each trace the module defines a set of traces. This set consists of the current trace and its neighbors from left and right. Size of this set is defined by Trace window parameter. And then one of the following algorithms will be used:
MEAN - it calculates average value of sample for the defined set and replaces the sample value for the current trace with the average value. For random noise attenuation, MEAN is the best option. Run time of MEAN is faster compared to MEDIAN.
Where
= filtered value for trace "i" at time "t"
N = number of neighboring traces on each side
MEDIAN - it is also known as non-linear filter. Median filter replaces each sample with the median value from the trace window across neighboring traces. It calculates median value of sample for the defined set and if current value is more than median multiplied by Median selection factor then the current value will be replaced with median.
For example, 1.2, -0.6, 0.4, 2.6, 1.3 are the values then the MEAN will be 0.98 where as MEDIAN will be 1.2
For spiky/channel bursts, structural preservation etc. MEDIAN is the best option.

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MEAN - at each time sample, the trace value is replaced with the average of the corresponding values in the adjacent traces within the user defined trace window.
MEDIAN - replaces each sample with the median value from the trace window across the neighboring traces.

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In this example workflow, we are applying trace mixing on a post stack gather to attenuate the random noise present in the data.

After making the necessary connections, set up the parameters as per the input data requirement. For this exercise, following parameters were used. Execute the workflow and launch Vista items.


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YouTube video lesson, click here to open [VIDEO IN PROCESS...]
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Yilmaz. O., 1987, Seismic data processing: Society of Exploration Geophysicist
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