Description

This module cleans up a surface-consistent amplitude recovery model before it is applied to the data. Surface-consistent decomposition (source, receiver and offset factors) can produce unreliable values at locations with poor fold or noisy data; this module lets you clip those outliers to an acceptable range and replace them with a constant, the nearest good value, or a spatially interpolated (kriged) value. It can also normalize each factor family so its correction stays centred around unity, preventing the amplitude correction from silently rescaling the whole dataset.

Input data

AmplitudeRecoveryDataItem - IN

The surface-consistent amplitude recovery model produced by an earlier decomposition step: separate amplitude factor tables for source points, receiver points and offset classes, plus their coordinates. This is the raw model to be edited/cleaned.

Parameters

Select processed factors

Source factors

Enables editing of the source (shot-point) amplitude factors. Turn this off if you only want to clean up receiver or offset factors and leave the source factors untouched.

Default: On.

Receiver factors

Enables editing of the receiver (geophone/streamer channel) amplitude factors.

Default: On.

Offset factors

Enables editing of the offset-dependent amplitude factors (the amplitude trend across offset classes).

Default: On.

Min clip value

Lower acceptance limit for an amplitude factor. Any factor value below this threshold is considered unreliable (too low, typically caused by dead or very weak traces) and is replaced according to the selected replacement method.

Default: 1.0. Minimum 0.0. Set it based on the expected range of your amplitude factors after reviewing a histogram of the input model; too tight a limit will flag valid variability as outliers.

Max clip value

Upper acceptance limit for an amplitude factor. Values above this threshold (typically caused by very quiet source/receiver locations that would otherwise be boosted too strongly) are replaced according to the selected replacement method.

Default: 2.0. Minimum 0.0. Should be set well above the typical (normalized) factor value of 1.0 so that only genuine outliers are clipped.

Replace clipped values with

Method used to fill in values that fall outside the min/max clip range. "Constant value" replaces every clipped value with a fixed number you specify (fast and predictable, but does not honour spatial trends). "Nearest value" copies the amplitude factor from the closest surviving (in-range) point, preserving local trends. "Value by kriging" spatially interpolates a replacement from nearby good points using a kriging model, giving the smoothest, most geologically-consistent fill but at a higher computational cost.

Default: Constant value. Choose "Nearest value" or "Value by kriging" for datasets where amplitude behaviour varies smoothly across the survey and you want the replacement to blend in rather than introduce a flat patch.

Replace small values with

The fixed replacement value used for factors below the minimum clip value, when "Replace clipped values with" is set to "Constant value".

Default: 1.0. Minimum 0.0. A value of 1.0 effectively neutralises the correction (no boost or attenuation) at the affected locations.

Replace big values with

The fixed replacement value used for factors above the maximum clip value, when "Replace clipped values with" is set to "Constant value".

Default: 2.0. Minimum 0.0.

Kriging covariance type

Shape of the covariance (variogram) model used to weight nearby points when "Value by kriging" is selected. "Exponential" gives more weight to very close points with a gradual falloff; "Spherical" has a well-defined range beyond which points stop contributing; "Gaussian" produces the smoothest interpolation but can over-smooth sharp local variations.

Default: Exponential. A reasonable general-purpose choice; switch to Spherical if you want interpolation influence to stop abruptly beyond the specified range.

Kriging range

Correlation distance of the kriging model: points farther apart than this range are treated as having little to no spatial influence on each other. It should reflect the scale over which source/receiver amplitude behaviour is expected to vary smoothly (e.g. related to near-surface conditions).

Default: 100000 m. Reduce it if your survey is small or if amplitude anomalies are localized; increase it for broad, slowly-varying trends.

Kriging number of points

Maximum number of nearby, in-range points used to build each kriging estimate. More points give a smoother, more stable estimate but slow the calculation and can dilute local detail; fewer points respond faster to local variations but are noisier.

Default: 15.

Normalize factors

When enabled, each selected factor family (source, receiver, offset) is rescaled after clipping/replacement so that its average value (over the positive factors) equals 1.0. This keeps the surface-consistent correction purely relative — redistributing amplitude rather than uniformly boosting or attenuating the whole survey.

Default: Off. Turn this on if you want to guarantee the correction does not change the overall amplitude level of the dataset, only its spatial balance.

Output data

AmplitudeRecoveryDataItem - OUT

The cleaned-up (clipped, replaced and optionally normalized) surface-consistent amplitude recovery model, ready to be applied to the data by the corresponding SC Amplitude correction Apply module.