Geoscience Reference
In-Depth Information
The vast majority of the responses of geological origin
will be associated with graphitic and sulphide-rich shales
and schists, water- lled structures (faults, porous forma-
tions) and zones of increased weathering. Other forms of
geophysical data and geological maps may allow the prob-
able source of the responses to be determined, e.g. a fault
mapped by magnetic data.
For targeting-related analysis,
the target anomaly will include the effects of the conduct-
ive environment, making quantitative interpretation
dif cult (see Section 5.7.6.1 ). Sometimes it is possible to
identify and remove the responses of the overburden and
the background rocks, but the effects of current
channelling and adjacent conductors can be dif cult to
quantify.
the exponential
time
constant (
) and conductance of confined conductors (see
Section 5.7.2.3 ) can be computed for the full dataset, using
Eqs. (5.24) and (5.25) , for a conductor of specific geometry
and size, usually as a dipping plate model. A map of the
mid- to late-time decay is a convenient means of targeting
discrete conductors, although inhomogeneities in the con-
ductors and the interfering effects of the overburden and
half-space responses will affect accuracy. Stacked channel-
pro
τ
Profile analysis
Spatial information is obtained from the spatial character-
istics of the channel amplitudes, such as shape and width
of anomalies, zero cross-over locations and the nature of
gradients. From these the shape, depth, width, dip and
strike extent of a conductor can be determined. The
changing spatial distribution, if any, of the response over
the measured delay time, as the eddy current system moves
through the body, is related to the geometrical properties
of the conductivity distribution in the body (see Section
5.7.1.4 ) . Having determined the shape of the conductor, its
conductivity and thickness, i.e. its conductance, can be
determined from analysis of its decay (see Section 5.7.2.3 ).
The spatial response is determined by the shape and
orientation of the conductor, the loop con guration used
(see Section 5.7.3.2 ), and whether the target conductor lies
beneath a conductive overburden, its depth from it and
their relative conductivities. The series of computed model
responses shown in Figs. 5.84 to 5.87 illustrate the key
characteristics of the responses obtained with three com-
monly used loop configurations from a finite thin plate
conductor in three orientations. B-field data, approximat-
ing the step response, have been computed for the target
conductor set in a high-resistivity background, with and
without the presence of conductive overburden. Eddy
current flow is restricted to just the dip plane of the plate
(see Section 5.7.1.4 ). The overburden is simulated with a
conductive thin plate 20 m below the surface.
Responses for the moving symmetrical in-loop con gur-
ation ( Fig. 5.84 ) show that both the X and Z components
are zero over the top of a steeply dipping conductor. The
responses are symmetrical across a vertical conductor with
polarity reversal (change of field direction) in the X com-
ponent producing a cross-over. Asymmetry is related to
dip with the strongest responses in the down-dip direction.
The geometrical symmetry of a horizontal plate also pro-
duces symmetrical responses, but in this case the Z com-
ponent peaks over the centre of the plate. As described in
Section 5.7.2.2 , aninnite conductive layer, e.g. a conduct-
ive overburden, produces power-law decay uniformly
les of the EM data are required for targeting subtle
responses.
Anomalies are then parameterised and classi ed in
terms of their amplitude, width and time constant, and
their association with other datasets such as magnetics and
gravity. Quantitative interpretation can then concentrate
on the features identi ed as of interest.
5.7.5.3 Quantitative interpretation
Quantitative analysis requires information about the char-
acteristics of the EM system, i.e. the transmitted waveform,
system geometry, delay times; and the type of measure-
ment, i.e. impulse or step response. It is imperative that all
available geological and topographic information be inte-
grated with the EM data. When modelling EM data, an
exact match between the observed and the computed
responses cannot be expected, owing to the complexity of
variations in electrical properties in the geological environ-
ment and the complex interactions between their electro-
magnetic responses. For example, multiple close-spaced
conductors produce complex responses due to their elec-
tromagnetic interactions, i.e. their secondary
field couples
with the neighbouring conductor, making resolution of the
individual conductors dif cult. This is unlike, say, the
gravity method (see Section 3.2 ) where individual
responses are additive. A common example is the complex
interaction between a discrete conductor and conductive
overburden.
In resistive terrains, and where there is no conductive
overburden, quantitative interpretation can be straightfor-
ward, producing suitable estimates of the target conduct-
or
'
s parameters (see Section 5.7.2.3 ) . In conductive terrains
 
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