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AGL - 2013 Gloucester Airborne Survey

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Collect Magnetic and Radiometric data over the Gloucester Basin in PEL285 - AGL

Dataset History

Airborne Survey (Heli).


              Thomson Aviation Pty. Ltd.

        GEOPHYSICAL SURVEY DATA REPORT

                        Date : 28 July 2013

This readme file describes the equipment and specifications of a geophysical

airborne survey conducted by Thomson Aviation Pty. Ltd.

The readme also summarises the data processing parameters and procedures used.

CLIENT DETAILS


Company Flown by : Thomson Aviation Pty. Ltd

Company Processed: Thomson Aviation Pty. Ltd

Client : AGL Energy Limited

Company Job : Thomson 13018

AIRBORNE SURVEY EQUIPMENT:


Aircraft : Bell Jet Ranger

Magnetometer : Geometrics G822A

Magnetometer Resolution : 0.001 nT

Magnetometer Compensation : Post Flight

Magnetometer Sample Interval : 0.05 seconds Hz

Data Acquisition : GeOZ Model 2010

Spectrometer : Radiation Solutions RS 500

Crystal Size : 16.5 lt downward array

Spectrometer Sample Interval : 1 seconds

GPS Navigation System : Novatel OEMV-1VBS GPS Receiver

AIRBORNE SURVEY SPECIFICATIONS


Area: Gloucester, NSW

Flight Line Direction : 090 - 270 degrees

Flight Line Separation : 50 metres

Tie Line Direction : 180 - 000 degrees

Tie Line Separation : 500 metres

Terrain Clearance : 35 metres (MTC)

Survey flown : June 2013

DATUM and PROJECTION


Datum : GDA94

Projection : MGA56

RADIOMETRIC PROCESSING PARAMETERS:


                  Tot.Count    Potassium   Uranium     Thorium

Height Attn 0.007434 0.009432 0.008428 0.007510

CPS to Eq 29.601 111.508 10.833 5.940

RADIOMETRIC STRIPPING RATIOS:


Alpha = 0.276       a = 0.048

    Beta  = 0.418       b = 0.003

    Gamma = 0.759       g = 0.001

            DATA PROCESSING   : MAGNETIC DATA


MAGNETIC PROCESSING FLOW


The final magnetic data processing was performed using the following processing flow:

-  Aircraft magnetic data QC

-  Diurnal magnetic data QC

-  System parallax removal

-  Diurnal variation removal and addition of the mean diurnal base value

-  IGRF removal and addition of mean IGRF value.

-  levelling using polynomial Tie line levelling,

-  Micro levelling if required

-  Reduction to the pole.

-  Gridding using Minimum Curvature algorithm

MAGNETIC QUALITY CONTROL


The processing of the magnetic data firstly involved the routine quality control in the field

of both the aeromagnetic and diurnal data during the acquisition phase. Any data found not

meeting the required specifications were reflown.

MAGNETIC PARALLAX CORRECTION


The total magnetic intensity aircraft data was firstly corrected for the effects of system

parallax. The parallax parameters were determined and checked from the results of opposing

test line flights.

MAGNETIC DIURNAL CORRECTION


The base station magnetometer data was edited and merged into the main database. The

aeromagnetic data was corrected for diurnal variations by subtracting the observed magnetic

base station deviations. There were no magnetic storms recorded by the diurnal monitoring

station during the survey. The mean value was then added back to the data.

MAGNETIC IGRF CORRECTION


The data was corrected for the regional gradient of the International Geomagnetic Reference

Field (IGRF). The IGRF was calculated for every point along the lines with respect to

GPS height using the IGRF Model for 2005 with secular variation applied. The mean IGRF

value was then added back to the data.

MAGNETIC PROFILE LEVELLING


The magnetic traverse line data was then statistically levelled from the tie line data using

Intrepid polynomial levelling. The steps involved in the tie line levelling were as

follows:

-    A primary tie line was chosen as a reference tie.

-    All other ties were levelled to this tie line using 1st degree polynomial adjustment.

-    lines were adjusted individually to minimize crossover differences, using 2nd degree

         polynomial adjustments.

Any residual flight line effects were removed using Intrepid micro levelling techniques and

the resultant line data saved as a separate field.

MAGNETIC GRIDDING


The data was gridded to a cell size of 20% of line spacing using a Minimum Curvature algorithm.


        DATA PROCESSING   : RADIOMETRIC DATA


RADIOMETRIC PROCESSING FLOW

Radiometric data processing consists of the following processing flow:

Full spectrum 256 channel Overview:





- Noise Adjusted Singular Value Deconvolution (NASVD) noise reduction

- Dead Time correction

- Energy  calibration

- Cosmic and Aircraft background Removal.

- Radon background Removal

- Extraction of IAEA Window data





Windowed data processing Overview:



- Compton Stripping correction.

- Height Attenuation correction using IAEA coefficients.

- Gridding

The specific processing steps are described below:


   256 CHANNEL PROCESSING

NASVD Noise Reduction:


Noise-Adjusted Singular Value Decomposition (NASVD) Smoothing. Correction of the radiometric

data involved the reduction of the 256 channels of raw gamma spectrometer data using Noise-Adjusted

Singular Value Decomposition (NASVD) noise reduction method. The signal to noise ratio of the

multi channel spectra can be substantially enhanced using Noise-Adjusted Singular Value

Decomposition (NASVD) as described by Hovgaard and Grasty (1997), Schneider (1998) and Minty (1998).

This method involves a general linear transformation of groups of spectra (a whole line or flight),

using NASVD to compute the different spectral shapes that make up the measured multi-channel

spectra. New multi-channel spectra are created by recombining the statistically significant

spectral components. Each spectral component contributes an unequal amount to the features

observed in the measured multi-channel spectrum, until a point is reached where the spectral

components represent only noise.

The 1st spectral component is the spectral shape that represents most of the features in the

measured multi-channel spectra. The 2nd spectral component represents those features not

described by the 1st spectral component, etc. By excluding from the recombination those spectral

components that do not represent significant features in the measured multi-channel spectra, the

resulting reconstructed multi-channel spectra have a much larger signal to noise ratio than the

measured multi-channel spectra.

Dead Time Corrections:


The raw 256 channel spectra were corrected for spectrometer dead time using the recorded live time

and the standard formula.

    N = n / (1 - t)



N   =       corrected counts in each second;

n   =   all counts processed in each second by the ADC; and

t   =   the recorded dead time

Where the live time (L) is recorded, the dead time t is replaced by (1 - L).

Energy Calibration:


Energy calibration was undertaken line by line using a maximum of 3 calibration peaks; and a

minimum of 2 calibration peaks dependent upon their clear identification in the spectra. The 3

calibration peaks used were Bi 214 at 0.609 Mev, K-40 at 1.46 Mev and Tl-208 at 2.615 Mev

Cosmic and Aircraft Background Correction:


Cosmic and aircraft background removal utilised the data recorded from a series of calibration flights

over water. These flight produce a normalised cosmic spectra for the system installation, together with

a 256ch spectra for the aircraft background.

The combined correction is calculated using:

N   =   a + bC,

where:

N   =   the combined cosmic and aircraft background in each spectral window;

a   =   the aircraft background in the window

C   =   the cosmic channel count; and

b   =   the cosmic stripping factor for the window.

The values of a and b for each window are determined from the calibration flights over the sea.

Cosmic coefficients and aircraft background coefficients were derived using INTREPID CAL256 program.

Atmospheric Radon:


The influence of atmospheric radon has been minimised using the spectral ratio method described by

Minty (1992). However the effect of radon in the Uranium channel can be considerable; and some

effects of the radon are visable in the character of the final processed data.

Extraction of Four Standard Windows:


The fully processed 256 channel spectra were reduced to the four IAEA (1991) standard windows or

Regions of Interest (ROI): As given by the following Energy windows and channel numbers:

Total Count 0.41 to 2.81 Mev (channels  33 to 238)

Potassium   1.37 to 1.57 Mev (channels 116 to 133)

Uranium     1.66 to 1.86 Mev (channels 140 to 158)

Thorium     2.41 to 2.81 Mev (channels 205 to 238)

WINDOW PROCESSING

Spectral Stripping of Standard Window Data:


Corrections for Compton stripping and height attenuation were applied to the windowed

data using constants supplied by Radiation Solutions Inc.

Due to scattering of gamma rays in the air, the three principle stripping ratios

( Alpha, Beta and Gamma) increase with altitude above the ground:

Stripping Ratio Increase at STP per metre

 Alpha   0.00049

 Beta    0.00065

 Gamma   0.00069

Following adjustment of the stripping ratios for altitude, the technique for producing the corrected

(stripped) count rates in the potassium, uranium and thorium channels (NKC, NUC and NThC) are given

by Grasty and Minty (1995)

The Compton coefficients for the system are given above:

Height Corrections


The stripped count rates vary exponentially with aircraft altitude. Adjustments for variation

in altitude were made using the formula:

Nc  = No e^ -u(H-h)

Where No = uncorrected counts,

Nc  = count rate normalised to height H,

h   = measured height above the ground,

H   = nominal flight height,

u   = attenuation coefficient for the channel being corrected.

Calculation of Effective Height


The Effective Height, which is the aircraft terrain clearance corrected to Standard Temperature

and Pressure was determined as follows:

- Filtering of the temperature field was applied to remove spikes and smooth out the

  instrument noise.

- Filtering of the barometric pressure field was applied to remove spikes and to smooth

  out the instrument noise.

- Filtering of the radar altimeter was applied to remove spikes, spurious reflections from

  groups of tree and very narrow gullies and to smooth out the instrument noise.

- The formula option in the spread sheet editor was used to combine the terrain clearance,

  pressure and temperature.



        h x P x 273

E_height =  _____________________

        1013 x (T + 273)

Where:



E_height=   the effective height;

h   =   the observed radar altitude in metres;

T   =   the measured air temperature in degrees C;

P   =   the barometric pressure in millibars.

Reduction to Ground Concentrations:


The fully corrected window data is then converted to effective ground concentrations by dividing

by the conversion coefficient to produce the following equivalent concentrations for each element.

Total Count : Dose Rate

Potassium   : Percent

Uranium         : PPM

Thorium     : PPM

Radiometric gridding


The data was gridded to a cell size of 20% of line spacing using a Minimum Curvature algorithm.

Dataset Citation

AGL (2014) AGL - 2013 Gloucester Airborne Survey. Bioregional Assessment Source Dataset. Viewed 31 May 2018, http://data.bioregionalassessments.gov.au/dataset/5cffc19a-0ff4-402c-824a-88935f70931a.

Data and Resources

Additional Info

Field Value
Title AGL - 2013 Gloucester Airborne Survey
Type Dataset
Language eng
Licence Creative Commons Attribution 3.0 Australia, http://creativecommons.org/licenses/by/3.0/au/, (c) AGL Energy Ltd
Data Status active
Update Frequency never
Landing Page https://data.gov.au/data/dataset/9ff9f257-cfa0-4f50-a7e0-ec0c279d45a3
Date Published 2018-05-31
Date Updated 2022-04-13
Contact Point
Bioregional Assessment Program
bioregionalassessments@environment.gov.au
Temporal Coverage 2018-05-31 00:00:00
Geospatial Coverage POLYGON ((0 0, 0 0, 0 0, 0 0))
Jurisdiction New South Wales
Data Portal data.gov.au
Publisher/Agency Bioregional Assessment Program