Batch Processing: Processes

AGC (Automatic Gain Control)

Time Window: Specify the size of the window to slide over the data. This is the total window so a value of 500 implies 250 ms above and 250 ms below the data sample.

Output RMS:Specify the resulting RMS for the data. The RMS is applied for the window at each sample.

Amplitude Gain

Perform an amplitude gain on the data.

Bulk Gain: A scale factor to apply to each sample of the data. A value greater than one will increase the amplitude of the data. A value less than one will decrease the amplitude of the data Negative values will have the side effect of reversing the polarity of the data.

Gain Exponent:An exponent applied to the gain at each sample. A value greater than one will increase the gain as you move down the trace. This can be used to brighten the data as you move down in time.

Amplitude Spectrum

This calculates the amplitude spectrum on trace by trace basis across the line.

Bandpass Filter

Perform a bandpass filter on the trace data. The filter is performed in the frequency domain using an FFT.

Low Truncation Frequency: All frequencies below this value are removed. Frequencies between this and the Low Cut frequency are smoothly ramped up using a cosine taper.

Low Cut Frequency: Frequencies between the Low Truncation and this frequency are smoothly ramped up using a cosine taper. Frequencies between this and the High Cut frequency are left unchanged.

High Cut Frequency: Frequencies between the Low Cut and this frequency are left unchanged. Frequencies between this and the High Truncation frequency are smoothly ramped down using a cosine taper.

High Truncation Frequency: Frequencies above this value are removed. Frequencies between the High Cut and this frequency are smoothly ramped down using a cosine taper.

Butterworth Filter

Perform a Butterworth filter on the trace data. The filter is performed in the frequency domain using an FFT.

Pass Band Frequency: The frequency at which the amplitude is down by 3dB. The amplitudes between the pass band frequency and the frequency cutoff (midpoint between the pass and stop band frequencies) are ramped from half power to full power.

Stop Band Frequency: The frequency at which the amplitude is down by 3dB. The amplitudes between the frequency cutoff (midpoint between the pass and stop band frequencies) and the stop band frequency are ramped from full power to half power.

Low Slope:The slope of the filter on the pass band side specified in decibels per octave. The slope determines how quickly the power is scaled up from 0 to half power (at the pass band frequency). Frequencies on this side of the filter are also smoothly ramped up using a cosine taper. Low frequency slopes usually are between 9 and 18 dB/octave.

High Slope: The slope of the filter on the stop band side specified in decibels per octave. The slope determines how quickly the power is scaled from half power (at the stop band frequency) down to 0. Frequencies on this side of the filter are also smoothly ramped down using a cosine taper. High frequency slopes usually are between 36 and 72 dB/octave.

Flatten

Flatten the dataset to a given horizon. This requires that you specify the horizon parameters in the main dialog. Each trace is flattened to a sample boundary, so the results may not be identical to the interactive flattening performed in the Seismic Viewer. Because this process effectively applies a variable bulk shift to the dataset, it can be used to force datasets to tie against two different lines where a zero mistie is not possible.

Datum Time: Specify the datum time in milliseconds. The value of the input horizon at each trace will be subtracted from the datum time in order to determine the shift applied to the output trace.

Instantaneous Amplitude

The instantaneous amplitude is calculated along the trace using the Hilbert Transform. This measures the reflectivity strength of the signal and is also known as the amplitude envelope. It is used always a positive number. Strong energy reflections can be associated with major lithologic changes as well as oil and gas accumulation. Lateral energy variations can quantify changes in acoustic rock properties and bed thickness. They can also be used to distinguish massive reflectors from thin-bed composites. In the case of unconformities, reflection strength will vary as subcropping beds change.

Instantaneous Frequency

The instantaneous amplitude is calculated along the trace using the Hilbert Transform. The instantaneous frequency is a measure of time dependent mean frequency and is independent of phase and amplitude. It is useful to look at changes in thickness and acoustic rock properties. Since most reflection events are composed of multiple, closely-spaced thin beds, the superposition of multiple reflections can produce an instantaneous frequency pattern that characterizes the composite reflection. Destructive interference caused by seismic processing artifacts such as incorrect normal move out or statics corrections (prior to stacking) can artificially reduce the frequency content.

Instantaneous Phase

The instantaneous amplitude is calculated along the trace using the Hilbert Transform. The instantaneous phase makes strong events clearer and is effective at highlighting discontinuities, faults, pinch-outs, angularities, and bed interfaces. Seismic sequence boundaries, sedimentary layer patterns and regions of onlap/offlap patterns often exhibit extra clarity.

Normalization

Normalize all the traces in a dataset. This is useful when trying to balance data of different vintages or data from different processors. This process is a two pass operation. The first pass calculates statistics for the input file. The second pass applies a scalar to the data to normalize to the user specified value.

Statistic: Choose the statistic to use for calculation of the scale factor for normalization.

Peak Value: Set the file peak to this value.
Average Value: Set the file average to this value.
RMS Value: Set the file RMS to this value. This is the most common choice.

Value: The resulting statistic value. For example, if you choose to normalize against the RMS, the resulting RMS in the output file will be this user specified value.

Start of statistics window: The starting time to use for statistics when calculating the scale factor to apply. If not specified the starting time in the input file is used. Normally you will want to specify this to be closer to your zone of interest.

End of statistics window: The end time to use for statistics when calculating the scale factor to apply. If not specified the end time in the input file is used. Normally you will want to specify this to be closer to your zone of interest.

Phase Rotation

Perform a phase rotation on the data. You may optionally specify the horizon parameters in the main dialog. If you are using a horizon as input the Rotation parameter will be ignored. Specifying a horizon as input allows you to apply a variable phase rotation along the length of a line. This is useful when attempting to tie against two different lines where a constant phase will not allow you to resolve a zero mistie.

Rotation: Specify the rotation in degrees. The normal range for this is -180 to 180. This parameter is ignored when using a horizon as input.

Phase Spectrum

Calculates the phase spectrum along the trace and outputs the results in degrees.

Resample

Use this process to resample a dataset.

Output Sample Rate: Specify the new sample rate in milliseconds. This value must be a multiple of the original sample rate, or an even divisor of the original sample rate. For example if the original data is 2 ms data, acceptable values include 4, 8 and 16 and 1, 0.5 and 0.25.

RMS Trace Balance

This balances the RMS of the dataset on a trace by trace basis.

RMS Value: The output RMS value for each trace.

Start Window:The starting time to use for statistics when calculating the scale factor to apply. If not specified the starting time in the input file is used. Normally you will want to specify this to be closer to your zone of interest.

End Window: The end time to use for statistics when calculating the scale factor to apply. If not specified the end time in the input file is used. Normally you will want to specify this to be closer to your zone of interest.

Spectral Balance

Spectral balance performs an amplitude balance on the data. The goal is to produce a result where the amplitude of all frequencies is similar. This process is often known as spectral whitening.
The spectral balance is performed by dividing the frequencies between the low and high pass into the number of frequency bands using a bandpass filter. The AGC is applied to each frequency band to boost it to the same amplitude level. The bands are then combined to produce the output trace.

Low Pass Frequency: Frequencies between the High Pass and this frequency are maintained. Most frequencies below this range are filtered out.

High Pass Frequency: Frequencies between the Low Pass and this frequency are maintained. Most frequencies above this range are filtered out.

Number of Bands: Frequencies between the low and high pass are divided into this number of equal sized frequency bands before the amplitude gain is applied. This number is best determined by examining the frequency content of the actual data.

AGC Window:Specify the size of the automatic gain control window in milliseconds. This is the total window so a value of 250 implies 125 ms above and 125 ms below the data sample.

Output RMS:Specify the resulting RMS for the data. The RMS is applied for the window at each sample.

Static Shift

Apply a bulk shift to the input dataset. The bulk shift is applied to the physical traces rather than just stored in the database. This is useful when exporting to other packages.

Static Shift: The value in milliseconds to shift each trace. If this value does not fall on a sample boundary it will be rounded to the nearest sample.