Quantifying the effects of near surface density variation on quantum technology gravity and gravity gradient instruments

Natural density variations in the near surface soil (i.e. the top 5 m) cause variations in the values recorded by geophysical surveys undertaken with gravity instruments. Whilst this ‘soil noise’ is too small to be noticeable with current instruments (e.g. Scintrex CG-5 and CG-6), the future use of more accurate instruments such as quantum technology gravity sensors, especially if used in a gradiometer configuration makes this noise source more significant and in need of characterisation and quantification. This paper reviews the magnitude and distribution of density variations in the near surface using data from the British Geological Survey (BGS) national geotechnical properties database which is then used to quantify the effect on practical gravity measurements in computer simulations.

The desk study identified that the scale of density variation in the near surface was typically within a range of 600-900 kg/m³, and showed no obvious relationship with underlying geology, superficial deposits or depth below the surface. The distribution of density varied, from normally distributed to between normal and uniform or bimodal distributions. The forward modelled computer simulations showed a significant impact on the measurements of gravity if new instruments can reach greater levels of accuracy, especially for gravity gradient instruments. Analysing possible methods of suppressing this noise source through the design of gravity gradient instruments showed that, although increasing the height of the instrument above the ground is almost twice as effective at decreasing the scale of the soil noise, increasing the sensor vertical spacing may be the preferred option. This is due to relaxed sensitivity requirements on the new sensors and the preservation of the noise in shorter signal wavelength bands than the targets of interest, which not only reduces the cases of mistaken features of interest but also provides the possibility of spatial filtering to be used in order to enhance the signals from targets of interest.