Recent Updates
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Volume Smoothing
Updated on: May 19, 2022
You can smooth 2D/3D volumes including velocity and other low frequency volumes using the Volume Smoothing process. This process uses the damped least-squares method to suppress derivatives in every spatial dimension of the input volume.
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Generating T-D Pairs from Sonic Log
Updated on: May 04, 2022
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Posting Convention Conversion
Updated on: Apr 28, 2022
<p>The Stacking process allows for the creation of 3D volumes from gather data. This process also supports 2D gathers. Based on the stacking algorithm, Insight calculates the number of samples between the inner and outer mutes (if these are provided) for each Z. Subsequently, a simple arithmetic ... -
Display (Wells and Well Data)
Updated on: Apr 06, 2022
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Instantaneous Attributes
Updated on: Apr 05, 2022
<p>This process allows you to generate instantaneous attributes from an input volume. It creates an analytic representation of the input data by converting the real-valued input traces to complex-valued traces based on the Hilbert transform.</p> <p>The output of this process includes the instant... -
Using Table Maths
Updated on: Apr 03, 2022
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Selecting Files (ASCII Volume)
Updated on: Mar 31, 2022
<p>At this stage, you can select the 3D SEG-Y files you want to import to Insight's DUGIO format. The files you select should all be from the same data type for example, "near stack" or "migrated gathers" or "interval velocity". Each time when you use the SEG-Y Loader, it is designed to load one ... -
Tools (Data and Analysis)
Updated on: Mar 31, 2022
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Header and Trace Interpolation
Updated on: Mar 29, 2022
You can smooth 2D/3D volumes including velocity and other low frequency volumes using the Volume Smoothing process. This process uses the damped least-squares method to suppress derivatives in every spatial dimension of the input volume.
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Match
Updated on: Mar 29, 2022
You can smooth 2D/3D volumes including velocity and other low frequency volumes using the Volume Smoothing process. This process uses the damped least-squares method to suppress derivatives in every spatial dimension of the input volume.