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is better not to remove these variations and to include
them in the model itself, a strategy worth considering if
the terrain is severe or the regional response dif
cult to
de
ne. The disadvantage with this approach is that the
model must be more complicated if it is to account for
these extraneous effects. Often the constraints that can be
reasonably applied to the deeper and distant parts of the
model, to account for a regional
field, are minor, requiring
assumptions that are no more justified than those associ-
ated with removal of the regional. However, the interpreter
needs to establish the ability of the inversion algorithm
either to accommodate a background as part of the model
or to automatically remove it, and also needs to establish
the (mathematical) nature of the removal. It may be pref-
erable, and indeed necessary, for the interpreter to remove
a regional
a volume of rock in a range of directions.
Usually measurements are restricted to a plane or near
plane. A signal is generated by a transmitter, and some
property of the signal, usually strength, is measured on the
other side of the volume. Any change to the signal, after
accounting for the source
'
across
'
receiver separation, depends on
the properties of the rock through which it has passed. The
method is the geophysical equivalent of computer-axial
tomography (CAT scans) which uses X-rays to create
images of
-
through the interior of the human body.
The volume-slice is represented by a cellular model, and
by combining many measurements it is possible, using
inversion, to determine the physical property within each
cell. The model is usually 2D, i.e. it is only one cell
'
slices
'
'
deep
'
,
so the results represent a
through the volume of
interest. Good results require the signal to cross each cell
over a wide range of directions, otherwise the results tend
to show anomalies elongated in the measurement direc-
tion. This restricts this kind of survey to areas with a
suitable number of drillholes and underground access.
Even then the directions may be limited to a less than
optimal range.
Tomographic surveys are relatively specialised, being
mostly restricted to in-mine investigations. Surveys of this
type using seismic and electromagnetic waves are described
in
Section 6.8.2
and online
Appendix 5
.
'
slice
'
eld
first and apply the inversion to the residual
dataset.
Variations in the properties of the near-surface are
another source of noise. In general, these effects appear
as short-wavelength variations in the data and should be
identi
ed for what they are and either
filtered from the
data before modelling deeper sources, or included as part
of the model. The interpreter should be aware that aliasing
(see
Section 2.6.1
)
of these responses can introduce non-
existent longer-wavelength variations into the data.
2.11.3.2
Choosing a model type
The choice of model type and its dimensionality are of
fundamental importance in geophysical modelling. The
choice requires consideration of the complexity of setting
up the model and adjusting its parameters, and the com-
putation effort and time required to obtain the response.
For example, for simulating a dipping thin body or a
layered feature, a thin-plate parametric model is simpler
to de
2.11.3
Modelling strategy
In modelling all types of geophysical data, model accuracy
is determined not just by the match with the observed data,
but also in deciding what aspects of the observed response
to actually model, the type of model to use to represent the
possible source and the degree of accuracy required. Per-
haps most important is the skill in recognising the limita-
tions of the result, which in turn dictates the appropriate
use of the outcomes. The fundamental phenomenon of
non-uniqueness is described in
Section 2.11.4
.
ne and faster to compute than a cell-based model.
Conversely, a cell-based model may provide the only
means of accurately simulating a complex 3D physical
property distribution, but with the added complexity of
de
ning and computing the responses of a very large
number of model parameters.
2.11.3.1
Accounting for noise
It is important to remember that the observed variations
will contain a noise component (see
Section 2.4
)
. There is
no advantage in modelling the data to obtain a match
better than the noise level permits. In addition to noise
inherent in the actual measurements, noise may be created
by incorrect removal of, say, terrain effects and, in particu-
lar, the regional response (see
Section 2.9.2
). Sometimes it
2.11.3.3
Source resolution
The further away a geophysical sensor is from an anomal-
ous source the more like a point the source appears to be,
and the less is the information obtainable about the source
from the measured response. This means that simpler
model shapes can be used to obtain valid estimates of only
the fundamental body parameters, i.e. depth and overall
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