Calculate Derivatives and Analytic Signal

Use the UXO-Marine Grad > Calculate Derivatives and Analytic Signal menu option (Geosoft.uxo.gxnet.dll(Geosoft.GX.UXO.UxoQuasiAnalyticSignal;Run)*) to calculate the analytic signal along the survey line path for gradient or multi-sensor configuration magnetic data.

When picking targets from gradient data, the analytical signal can be helpful as it will be a single positive anomaly peaks along a profile.

Calculate Derivatives and Analytic Signal dialog options

Sensor Input

Sensor configuration table

The sensor configuration table contains the label, coordinate channels and the sensor data channel for all the sensors.

See the Gradient Sensor Offset Correction Application Notes for information on the format of the Sensor Configuration Table (CSV) file.

Script Parameter: UXQUASIANALYTIC.SENSOR_CONFIGURATION_TABLE

Sensor label position

Select the label position (Suffix, Prefix), which determines how the input channels associated with a sensor are named.

Default value is Suffix.

Script Parameter: UXQUASIANALYTIC.SENSOR_LABEL_POSITION

Sensor

This field indicates the sensor position in the sensor array or configuration.

This is a read-only field.

Sensor Label

Specify the sensor label. This should be a common term for the channels associated with this sensor (for example, port or left, starboard or right).

Script Parameter: UXQUASIANALYTIC.[#]_LABEL

X Channel

Select the X channel.

Default value is determined by the Sensor Label and Sensor label position.

Script Parameter: UXQUASIANALYTIC.[#]_X

Y Channel

Select the Y channel.

Default value is determined by the Sensor Label and Sensor label position.

Script Parameter: UXQUASIANALYTIC.[#]_Y

Z Channel

Select the Z channel.

Default value is determined by the Sensor Label and Sensor label position.

Script Parameter: UXQUASIANALYTIC.[#]_Z

Sensor Data Channel

Select the sensor data channel.

Default value is determined by the Sensor Label and Sensor label position.

Script Parameter: UXQUASIANALYTIC.[#]_FIELD

Derivative Configuration

Output channel prefix

Specify the prefix for the output channel names (dx,dy,dz,AS and mid-point database channels).

Script Parameter: UXQUASIANALYTIC.OUPUT_CHANNEL_PREFIX

Positions

Select the number of positions required for the Derivative configuration table.

Script Parameter: UXQUASIANALYTIC.NUMBER_OF_POSITIONS

+ compound script parameter as:

Script Parameter: UXQUASIANALYTIC.GRADIENT_CONFIGURATION.[Position#] [Dx - Along track A; Dx - Along track B; Dy - Across track A; Dy - Across track B; Dz - Vertical A; Dz - Vertical B]

Dx - Along Track

Select the sensors used to calculate the derivative along the track.

Dy - Across Track

Select the sensors used to calculate the derivative horizontally across the track.

Dz - Vertical

Select the sensors used to calculate the derivative vertically across the track.

[Load Configuration]

Click to select to load a derivative configuration table to apply to your data.

The derivative configuration table determines how the derivatives are calculated along the X, Y, and Z axes.

Script Parameter: UXQUASIANALYTIC.SENSOR_CONFIGURATION

[Save Configuration]

Click to specify a name to save your output derivative configuration table.

Script Parameter: UXQUASIANALYTIC.GRADIENT_CONFIGURATION_FILE

[More]

FFT Sampling Parameters

Distance increment

Specify the distance increment. If not specified, the nominal data spacing will be used.

  • The distance increment should not be significantly smaller than the average original data sampling interval; otherwise, unwanted high frequency noise may be introduced into the output data. If a small distance increment is to be used, the Linear interpolation method should be selected.

    • Script Parameter: UXQUASIANALYTIC.DISTANCE_INCREMENT

    Interpolation method

    Select the interpolation method:

    • Linear (default) 
    • Akima
    • Minimum curvature

    Script Parameter: UXQUASIANALYTIC.INTERPOLATION_METHOD

    Expansion method

    Select the extension fill method:

    • Maximum Entropy (default) 

    • Constrained Linear Prediction

    See the Application Notes bellow for more details.

    Script Parameter: UXQUASIANALYTIC.EXPANSION_METHOD

    Number of smoothing passes

    Select the number of smoothing passes.

  • A Hanning smoothing filter can be applied to the derivative calculated from a single sensor. The measured gradients, generally, do not need smoothing.
    The coefficients of the smoothing filter are 0.2, 0.6, 0.2.

    • Script Parameter: UXQUASIANALYTIC.NUMPASSES

    Apply direction to derivatives

    Select to apply direction to the derivatives.

    The derivatives are calculated along track for use in the analytic signal calculation. Applying the direction information to the derivatives will eliminate the sign reversal between alternate line directions. This parameter has no effect on the Analytic Signal value.

    Script Parameter: UXQUASIANALYTIC.APPLYDIRECTION

    Application Notes

    In addition to derivatives and analytic signal channels, the Calculate Derivatives and Analytic Signal option will also save the mid-points of the X, Y and Magnetic channels in the database. For example:

    • Mag_MidpointDY
    • X_MidpointDY
    • Y_MidpointDY

    If you have two sensors, you will only get one midpoint - DY. We calculate the values for the other two orientations (DX, and DZ), however, they have the same values as DY. Therefore, as these are essentially duplicates of the DY channel, we do not add these channels to the database.

    If you have six different sensors, we will calculate and output three midpoints as they could all be different. They should be close, as this is assumed in the calculation of the Analytic Signal. However, if they are different, it is up to you to choose which one to attribute to the location of the Analytic Signal. Generally, we would suggest using the DY.

    Expansion Methods

    The Maximum Entropy Prediction (MEP) method determines the spectral content or the preceding real data segment. It then predicts a data function that has the same spectral signature as the original data. As a result, the predicted data will not significantly alter the energy spectrum of the original data.

    The Constrained Linear Prediction (CLP) method calculates a series of linear prediction coefficients based on a segment of real data and then uses these coefficients to recursively extrapolate the data. The nature of geophysical data with its wide range of distributions, generally, yields coefficients that produce a reasonable extrapolation. However, if the data contains un-damped oscillations, such as superimposed systematic noise, then CLP may produce an unstable outcome. An additional constrain on the calculation of the coefficients pushes the results back into the stable zone. The details of the CLP are outside the scope of this document. The avid reader can find further information in the reference below.

    *The GX tool will search in the "gx" folder. The GX.Net tools, however, are embedded in the Geosoft.uxo.gxnet.dll located in the bin folder. If running this GX interactively, bypassing the menu, first change the folder to point to the bin folder, then supply the GX.Net tool in the specified format.

    Reference

    • William H. Press, Brian P. Flannery, Saul A. Teukolsky, William T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing, Second Edition, Cambridge University Press, 1992, pp. 564-575.