Airborne Gravity 2010 - Geoscience Australia

Airborne Gravity 2010
Table 1. Table summarising the improvements to Air-FTG® performance on different aircraft from
2004 to present day.
Aircraft Speed,
knots
Cessna Grand
Caravan surveys
2004
Cessna Grand
Caravan
surveys 2006
Cessna Grand
Caravan surveys
2010
BT67
surveys 2010
Zeppelin NT
120
120
120
105
30 to 35
sampling rate,
metres
62
62
62
55
15-18
146
Tzz residual noise
roof level, Eo 2 km
>20
~10
7 to 8
Innovative QC and data processing of full tensor data
< 6
< 2
Tzz detectability
5 Eo over 400 m
3 Eo over 300 m
2 Eo over 300 m
2 Eo over 200 m
1.7 Eo over 100 m
The dynamic environment presented by airborne platforms presents a significant challenge to FTG
data acquisition. Turbulence caused by weather conditions and / or aircraft motion, and instrument
performance all contribute to the measured signal and are carefully monitored to ensure meaningful
geological signal is indeed measured.
Standard acquisition QC methods that check for deviations from planned survey parameters are
employed. The vertical accelerations (Vacc) acting on the instrument are also monitored. Vacc
thresholds of 60 mg were reported as standard by Murphy (2004). However, with improved acquisition
practices and use of the larger BT67 aircraft, this threshold has now been widened to 70 mg, and
occasionally, data acquired with rates of 100 mg have been deemed acceptable. Much of this new
confidence in terms of accepting data acquired with higher Vacc rates is due to the newer platform but
also relates to the development of improved noise reduction tools. So called ‘Inline Sum’ and
‘AutoEvaluate’ procedures are described here.
The Inline Sum works on the assumption that the sum of the individual gradiometer outputs from any
one of the 3 rotating disks equates to zero, i.e., no signal. However, this is not the case in practice and
is usually caused by measurement of signal arising from sources other than geology. Evaluation of the
Inline Sum values on a survey by survey basis provides a means for establishing a set of thresholds
for acceptable values. The advantage in using the technique is that it uses 3 independent sets of
measurements to derive airborne survey QC thresholds to quickly monitor instrument performance.
Further, the method quickly identifies noise levels and is instrumental in producing high confidence
data in a timely fashion.
AutoEvaluate (Brewster and Humphrey, 2006) works by comparing survey data quality acquired on
separate but neighbouring flight lines to determine deviations from acceptable thresholds. Daily
production is quickly processed to a series of outputs that can be evaluated and compared using
AutoEvaluate to quickly identify problematic survey data. Such data may contain noise levels not
characteristic of the anticipated geophysical response and so are assessed to determine a set of
thesholds for data acceptance.