Abstract
ABSTRACTElectromagnetic loop systems rely on the use of non‐conductive materials near the sensor to minimize bias effects superimposed on measured data. For marine sensors, rigidity, compactness and ease of platform handling are essential. Thus, commonly a compromise between rigid, cost‐effective and non‐conductive materials (e.g. stainless steel versus fibreglass composites) needs to be found. For systems dedicated to controlled‐source electromagnetic measurements, a spatial separation between critical system components and sensors may be feasible, whereas compact multi‐sensor platforms, remotely operated vehicles and autonomous unmanned vehicles require the use of electrically conductive components near the sensor. While data analysis and geological interpretations benefit vastly from each added instrument and multidisciplinary approaches, this introduces a systematic and platform‐immanent bias in the measured electromagnetic data. In this scope, we present two comparable case studies targeting loop‐source electromagnetic applications in both time and frequency domains: the time‐domain system trades the compact design for a clear separation of 15 m between an upper fibreglass frame, holding most critical titanium system components, and a lower frame with its coil and receivers. In case of the frequency‐domain profiler, the compact and rigid design is achieved by a circular fibreglass platform, carrying the transmitting and receiving coils, as well as several titanium housings and instruments. In this study, we analyse and quantify the quasi‐static influence of conductive objects on time‐ and frequency‐domain coil systems by applying an analytically and experimentally verified 3D finite element model. Moreover, we present calibration and optimization procedures to minimize bias inherent in the measured data. The numerical experiments do not only show the significance of the bias on the inversion results, but also the efficiency of a system calibration against the analytically calculated response of a known environment. The remaining bias after calibration is a time/frequency‐dependent function of seafloor conductivity, which doubles the commonly estimated noise floor from 1% to 2%, decreasing the sensitivity and resolution of the devices. By optimizing size and position of critical conductive system components (e.g. titanium housings) and/or modifying the transmitter/receiver geometry, we significantly reduce the effect of this residual bias on the inversion results as demonstrated by 3D modelling. These procedures motivate the opportunity to design dedicated, compact, low‐bias platforms and provide a solution for autonomous and remotely steered designs by minimizing their effect on the sensitivity of the controlled‐source electromagnetic sensor.
Highlights
Over the last years, the marine controlled-source electromagnetic method (CSEM) exhibited large steps in the development of new sensor platforms to meet the task of future resource exploration
Comparing the finite element (FE) model responses against the 1D analytical solution shows the successful development of the 3D FE model
Both the response based on the calculated induced voltage in the receiver (RX) coil (Vind,Rx), as well as the solution based on vertical magnetic flux density derived from the central point probe (Bz) show identical solutions
Summary
The marine controlled-source electromagnetic method (CSEM) exhibited large steps in the development of new sensor platforms to meet the task of future resource exploration. Two case studies of highly sensitive, marine CSEM systems with (1) time-domain and (2) frequency-domain coil sensors are analysed to quantify their platform-immanent bias and to develop data calibration and system optimization strategies. The derived bias factors for variable sensor configurations and visualizations based on the computed current density distributions in 3D are especially useful when: (a) developing new or evaluating present CSEM profilers in terms of high sensitivity/low bias, (b) analysing and calibrating existing data sets of other comparable devices to allow for the inversion and full interpretation. The observable variation by the change in seawater conductivity is small due to the generally large amplitude of the bias effect, but becomes more visible at later times (10−3 to 10−2 s) In this relevant time range, the different models are well distinguishable, but still biased by a variation of approximately 0.5 S/m at minimum. The bias can be directly related to the change of the induced current density J in the specified volume of the weights (equation (9))
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