In audio-frequency magnetotelluric surveys, electromagnetic radiation from worldwide thunderstorm activity is used as an energy source for geophysical exploration. Owing to its origin, such a signal is inherently transient and short lived. Therefore, special care should be taken in the detection and processing of this transient signal because the interval of time between two successive transient events contains almost no information as far as the audio frequency magnetotellurist is concerned. In this paper, a wavelet transform detection, processing and analysis technique is developed. A complex-compactly-supported wavelet, known as the Morlet wavelet, is selected as the mother wavelet. With the Morlet wavelet, lightning transients can be easily identified in the noisy recordings and the magnetotelluric impedance tensor can be computed directly in the wavelet transform domain. This scheme has been tested on real data collected in the archipelago of Svalbard, Norway as well as on five sets of synthetic data contaminated with various kinds of noise. The results show the superior performance of the wavelet transform transient detection and analysis technique.