MEMS-based Accelerometers - The Quest for Low Frequencies and Weak Signals

Moreau, Maëg; Laine, Jérôme; Serrut, M.

doi:10.3997/2214-4609.20141244

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“…Accelerometers used as seismic sensors must have a high dynamic range and low self-noise (Goujon et al 2012). Seismic MEMS sensors are limited by Brownian noise and electronic flicker noise that primarily affects frequencies below 10 Hz (Moreau, Lainé and Serrut 2014;Tellier and Lainé 2017). In order to achieve the desired performance, MEMS accelerometers are often constructed with a force-feedback loop and the proof mass is placed in a vacuum to minimise noise generated from viscous gas damping (Lainé and Mougenot 2014;Paulson, Husom and Goujon 2015a).…”

Section: Introductionmentioning

confidence: 99%

“…Quantifying sensor noise in the field is challenging because environmental noise often masks the sensor self-noise. Accelerometers are typically taken to ultra-low noise test facilities in order to measure the sensor self-noise (Hewlett-Packard Development Company 2011; Lainé and Mougenot 2014;Moreau et al 2014). Such measurements are suitable for quantifying the sensor noise floor, but they cannot be duplicated during a seismic acquisition project.…”

Section: Introductionmentioning

confidence: 99%

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Measuring accelerometer dynamic range from seismic data using Allan deviation

McDonald

Stigborg

2018

Geophysical Prospecting

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We propose a new approach for calculating the dynamic range of an accelerometer based on an Allan deviation analysis of production seismic data. This test is intended as a field audit technique and does not require an unconditioned dataset from a low‐noise environment. We first show that Allan deviation can measure white noise levels using two commercial accelerometers. The analysis accurately captures the manufacturing noise density specifications and known relationships between white noise, preamplifier gain, and group forming. We then show that a production seismic dataset is suitable for an Allan deviation analysis because the results are not critically affected by a recording filter. Finally, we illustrate the proposed technique by calculating the dynamic range of an accelerometer channel in a seismic streamer using a production dataset.

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