Abstract. We present a quality control methodology for the currents of
marine controlled-source electromagnetic transmitters . The
quality level of the transmitting current directly affects the signal-to-noise
ratio (SNR) of the electromagnetic-field data, as received by a
multicomponent electromagnetic receiver from the seabed. Although the
transmitting-current stability is sufficient under normal circumstances, the
SNR of the received signal can change owing to factors such as outside
noise. In some emergency cases such as instrument failure or a sudden
increase in electromagnetic interference that we are not aware of, the
frequency and properties of the transmitting current, such as its
size and waveform, may change. The traditional current monitoring and data playback
tools fail to detect and evaluate the anomalies well and in a timely manner,
which introduces considerable errors in the later data-processing procedure.
Pertaining to these issues, this paper proposes a comprehensive quality
evaluation method for the transmitting current. The proposed algorithm,
based on the analytic hierarchy process, is first used to analyze five
current stability parameters – current frequency, positive amplitudes,
negative amplitudes, discrepancy of ideal waveform, and waveform repetition – and then to define the harmonic energy and calculate the quality of
transmitting current (QTC) index of the final data to assess the quality of
the transmitting current comprehensively. The results of a marine experiment
performed in 2016 show that the algorithm can identify abnormal current data
and quantitatively evaluate the current conditions. Under normal
circumstances, the QTC index is less than 2 %. The key findings are that the
QTC index changes to more than 4 % and some curvilinear features are
observed if the transmitting-current quality is poor. These results will
provide a positive, significant guide for the evaluation and monitoring of
transmitting-current data in marine experiments.
A new macroeconomic forecasting and policy evaluation method using the analytic hierarchy process
