Arbejdsgruppemøde - SkyTEM processering Esben Auken and Nikolaj Foged HydroGeophysics Group Department of Earth Sciences, University of Aarhus, Denmark.

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Arbejdsgruppemøde - SkyTEM processering Esben Auken and Nikolaj Foged HydroGeophysics Group Department of Earth Sciences, University of Aarhus, Denmark

Dagsorden Intro til processering Import: stack division, fortegn og linie fil, +30 sekunder Processeringsvindue: højdeprocessering, midlingsfiltre, genkørsel Manuel klipning af data: rådata versus average data Workflow: Koblinger fjerne fra raw data Støjbeskæring i average Fast inversion Evaluering og justering af processering Nye data - tæt sampling til tidlige tider - ny software - nyt møde

Processing, Inversion and Management of SkyTEM Data Esben Auken and Kurt Sørensen HydroGeophysics Group Department of Earth Sciences, University of Aarhus, Denmark

Outline What is in the database? Pitch and roll correction Data filtering Implementation in the Aarhus Workench

Ensuring Best Possible Data Quality Obtain maximum information about the Earth resistivity distribution 5% data reproducibility of SkyTEM data on national test site 5% repeatability at each take off and landing Accurate data processing and inversion

Data Basis Data types measured by the system GPS – 2 per sec. Tilt of transmitter frame – 1.5 per sec. in in- and off-flight directions Laser altitude – 20 per sec. from two devices Transmitter current – 1 per dataset Single decays from 2 or more receiver channels – Mb per hour

Data Processing Voltage data and altitudes corrected with respect to the tilt of the frame To some degree manual intervention is necessary for Altitudes Culling of distorted data caused by coupling to wires and fences Data are not leveled

Altitude and Tilt Correction ”Normal” situation

Altitude and Tilt Correction ”Normal” situation

Altitude and Tilt Correction ”Normal” situation – modelled in the inversion

Altitude and Tilt Correction ”Field” situation

Altitude and Tilt Correction ”Field” situation

Altitude and Tilt Correction ”Field” situation

Altitude and Tilt Correction ”Normal” situation – modelled in the inversion

Tilt data 5 min  3.5 line km Tilt of +/-10°  correction of voltage data y-tilt +/- 4° x-tilt +/- 8° Filtered

Altitude Processing Raw Laser 1 Raw Laser 2 Removed by filtering Final – tilt corrected and relocated Removal of laser reflection from tree tops Correction of altitudes for tilt – non perpendicular reflections from the ground Relocation of altitudes to center of Tx and Rx coils Laser reflections from tree tops Difference due to high y-tilt 5 min  3.5 line km

Box average – Narrow/Wide SkyTEM data example (Airborne TEM) 30s ~ 400m SkyTEM data, 2 min ~ 1.5 Km 5s ~ 65 m gate 1 gate 2 gate gate n

Box average – Narrow/Wide Raw Average 30 s 5 s 2 min ~ 1.5 Km

Trapezoid shaped average combines the best from the narrow and the wide box average used for SkyTEM data Trapezoid shaped average Box shaped average

Average Trapezoid shaped average Average

Trapezoid average - Sounding view Trapezoid average Box average, medium width

Trapezoid average - Sounding view Trapezoid average Box average, medium width 3-4 gates culled Only 2 gates culled High lateral resolution

Summary Shallow part of model section/early time gates maximum lateral resolution is obtain with a narrow data average large data stack is not needed because of a high signal to noise ratio Deep part of model section/late time gates Wide data average suppress the background noise and increase penetration depth. Wide data average does not reduce the lateral resolution Trapezoid shaped average maximum lateral resolution maximum penetration depth Could be applied to any continuous TEM-method

Summary Frame tilt is used for correction of altitudes and voltage data Coupled data are culled before inversion Data average using trapezoid shaped filters and pruning