Proc. SPIE. 10322, Seventh International Conference on Electronics and Information Engineering
KEYWORDS: Minerals, Detection and tracking algorithms, Data modeling, Imaging systems, Transmission electron microscopy, Convolution, Algorithm development, Electromagnetism, Systems modeling, Data fusion
The airborne electromagnetic (AEM) systems have been used traditionally in mineral exploration. Typically the system transmits a single pulse waveform to detect conductive anomaly. Conductivity-depth imaging (CDI) of data is generally applied in identifying conductive targets. A CDI algorithm with double-pulse transmitting current based on model fusion is developed. The double-pulse is made up of a half-sine pulse of high power and a trapezoid pulse of low power. This CDI algorithm presents more shallow information than traditional CDI with a single pulse. The electromagnetic response with double-pulse transmitting current is calculated by linear convolution based on forward modeling. The CDI results with half-sine and trapezoid pulse are obtained by look-up table method, and the two results are fused to form a double-pulse conductivity-depth imaging result. This makes it possible to obtain accurate conductivity and depth. Tests on synthetic data demonstrate that CDI algorithm with double-pulse transmitting current based on model fusion maps a wider range of conductivities and does a better job compared with CDI with a single pulse transmitting current in reflecting the whole geological conductivity changes.
Coil motion noise is one of the largest noises in airborne electromagnetic exploration, which results from the variations of magnetic flux in the Earth’s magnetic accompanied by the receiver coil’s movement during the flight. On the assumption of attitude measurements, coil motion noise is calculated according to roll, pitch and yaw of the receiver coils. Therefore, the characteristics of coil motion noise are analyzed in time domain, frequency domain and time-frequency domain. And the Gaussianity of coil motion noise is also discussed using the histogram of data and its estimated Gaussian function, and another method termed normal probability paper. All of these are to lay the foundation for removal of coil motion noise in airborne electromagnetic detection.
Conductivity-depth imaging (CDI) of data is generally applied in identifying conductive targets. CDI results will be affected by the bird attitude especially the pitch of the receiver coil due to the attitude, velocity of the aircraft and the wind speed. A CDI algorithm with consideration of pitch is developed based on two-component measurement. A table is established based on two-component B field response and the pitch is considered as a parameter in the table. Primary advantages of this method are immunity to pith errors and better resolution of conductive layers than results without consideration of pith. Not only the conductivity but also the pitch can be obtained from this algorithm. Tests on synthetic data demonstrate that the CDI results with pitch based on two-component measurement does a better job than the results without consideration of pitch and the pitch obtained is close to the true model in many circumstances.