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This study explores effective filtering methods and LCI inversion techniques applied to hydrogeophysical data. Utilizing datasets from the Department of Earth Sciences at the University of Aarhus, Denmark, this research evaluates noise removal from raw voltage data, leveraging altitude, angle, and GPS data. We present methodologies to achieve accurate soundings and model parameterizations while maintaining a strong correlation between flight altitude and signal levels. Our findings demonstrate enhanced data processing strategies for improved hydrogeophysical modeling.
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Filtrering og LCI inversion Esben Auken • HydroGeophysics Group • Department of Earth Sciences, University of Aarhus, Denmark • www.hgg.au.dk
Processeringsindstillinger • GPS data • Angle data • Altitude data • Voltage data • Filtering of couplings from raw data • Averaging core set up • Filtering of noise filled data from averaged data
Filtrering af data – lavmoment z-data • Flyvehøjde er 25 – 35 m • Stærk korelation imellem flyverhøjde og signalniveau Raw Voltage Data Altitude of Tx coil
Average center point Average center point Average sounding, Rho-a Average sounding, Rho-a Gamle data Raw Voltage data Raw voltage data 3 min 2 line km Altitude
Average center point Average center point Nye data – lige filtre Averaged Voltage data Raw voltage data 3 min 2 line km Altitude
Average sounding, Rho-a Average sounding, Rho-a Nye data – skrå filtre Average center point Average center point Averaged voltage Data Raw voltage Data 3 min 2 line km Altitude
Inversion Methodology • LCI – soundings
Inversion Methodology • LCI – soundings • Add constraints – a variance between the model parameters
Inversion Methodology • LCI – soundings • Add constraints – a variance between the model parameters • Few layer parameterization – all parameters floating
Inversion Methodology • LCI – soundings • Add constraints – a variance between the model parameters • Smooth model parameterization – fixed layer boundaries