On-Site Bias Noise Correction in Multi-Frequency Slingram-type Electromagnetic Induction Measurements

Abstract

Slingram-type horizontal-loop electromagnetic induction systems are popular for environmental and engineering investigations of relatively shallow subsurfaces. The Slingram method is effective for the detection of anomalous zones by mapping and profiling large areas. However, analogous to airborne electromagnetic and induction borehole logging methods, zero level adjustment is crucial for further inverse analysis to estimate subsurface resistivity structures. To address this problem, we propose a simple and practical procedure for on-site measurement and correction of bias noise. To attenuate the response generated by electromagnetic induction in the ground, we raise the Slingram-type sensor vertically off the ground and measure background noise as the bias noise. By subtracting the bias noise from the original raw data, bias correction is implemented. Two applications, a high-salinity groundwater investigation and a levee assessment survey, demonstrate that this procedure is effective for quadrature data, but is inadequate for in-phase data. For a more precise correction, a more sophisticated method should be developed.

Development of a drone‐borne electromagnetic survey system for searching for buried vehicles and soil resistivity mapping

“…The height of the EM sensor was adjusted by placing the sensor on stacks of 20-cm-thick plastic boxes. The response was estimated by subtracting the bias noise from the raw measurements acquired at each height, where the bias noise was measured by elevating the instrument vertically as described in Mitsuhata and Imasato (2009). In the resistivity mapping experiment described later, the bias noise was measured while hovering the drone with the EM sensor suspended at a high altitude above the ground.…”

“…After the two flights, the drone was hovered at approximately 20 m AGL for several minutes in order to acquire baseline EM data, which we refer to as bias noise. Figure 10 shows a comparison between the measured bias noise and the EM readings measured as described in Mitsuhata and Imasato (2009), who measured bias noise with the EM sensor elevated at a height of approximately 4 m AGL. The bias noise measured with the drone-borne EM sensor exhibited similar characteristics to those measured with a hand-held EM sensor, except that the bias noise for the drone-borne EM sensor was slightly lower.…”

“…Bias noise obtained for in-phase and quadrature components of data acquired with the EM sensor suspended from the drone when hovering approximately 20 m above ground level compared to data acquired by elevating the EM sensor vertically, which was proposed by Mitsuhata and Imasato (2009).…”

Characterization of organic‐contaminated ground by a combination of electromagnetic mapping and direct‐push in situ measurements

“…The level of standard deviations evaluated from the measured values was approximately 100 ppm for the in‐phase and quadrature components. The measured data can be distorted by calibration errors or external noise; therefore, responses free from the ground conductivity effect were measured by raising the sensor to a height of approximately 4 m and applying zero‐level correction to the data (Mitsuhata and Imasato ).…”

“…The in‐phase data were more seriously distorted by various shallow metallic materials than the quadrature data. Moreover, some of the in‐phase data were still negative values after the zero‐level shift correction (Mitsuhata and Imasato ). Therefore, the in‐phase data were not used for the inversion.…”