model. Do the resistivity variations follow the
expected trends? How well do resistivity anomalies
fit with the anticipated results? If the results are not as
expected, it does not necessarily mean that the inversion results are wrong. It can just as well be that the
existing geomodel is wrong and needs to be redefined.
It is within this integrated interpretation process
between electromagnetic-, seismic- and well-data
that valuable additional information can be extracted.
20.2.6 Interpretation and Integration
of CSEM Results
Interpretation of CSEM data involves explaining the
resistivity changes that we observe from real CSEM
data, and relating these to lithology and fluid changes
in the subsurface. The interpretation needs to be integrated
with other geophysical and geological data to build a
geological model that honours all the available data.
When interpreting CSEM data it is important to
keep in mind that the ability to detect hydrocarbon
reservoirs is not only dependent on the resistivity
contrast between the reservoir and the surroundings,
but also on burial depth, target size and net pay thickness of the reservoir. Furthermore the acquisition
geometry will also be of importance. A dense receiver
grid will be able to detect smaller targets than a coarse
receiver grid. The presence of a resistor could indicate
a hydrocarbon reservoir, but could also be explained
by other resistivity anomalies. It could for example be
caused by low porosity rocks (e.g. cemented or tightly
compacted sandstones), highly organic-rich shale
(source rocks), carbonates, volcanic rocks, salt or
other high resistivity strata or structures in the subsurface. Further, integration of seismic data, well logs and
geological understanding will help to reduce the possible explanations of an observed resistivity anomaly.
Interpretation of CSEM data can be done at a very
early stage in the processing flow by analyzing relative
differences between receivers. This can for example
be done on normalised magnitude vs. offset (NMVO)
displays, or phase difference vs. offset plots (PDVO).
An increase in NMVO indicates a resistivity increase
in the subsurface relative to the reference receiver
used for the normalisation (Fig. 20.1). Similarly a
decrease in PDVO (Fig. 20.3) will indicate a resistivity
decrease in the subsurface. Such interpretations will
give a first indication of resistivity changes in the
subsurface. It will mainly provide information about
lateral resistivity changes, but can also give rough
estimates of burial depth to a resistor. A deeply buried
resistor will show up at larger source-receiver offsets
and lower frequencies than a shallow resistor. As a
rule of thumb the burial depth to a resistor can be
approximated to half the source-receiver offset at the
onset of the anomaly. This approximation assumes a
1D Earth. Interpretation of receiver data attributes
(such as NMVO and PDVO) is important as it directly
evaluates the recorded data. The Troll case is included
as an example of receiver interpretation. In the other
cases the interpretation is based on inversion results.
Inverted resistivity models can be directly
integrated with depth converted seismic and well log
data. When interpreting CSEM inversion results it is
useful to look at vertical depth sections as well as
resistivity maps. Depth windows for resistivity maps
can be selected by constant depth intervals, or to
follow seismic depth converted horizons. Such maps
give the lateral outline of resistive anomalies which
can be correlated with seismically defined structures.
It is also important to quality control and interpret
the CSEM data at different processing levels from
attributes in the receiver domain to full 3D inversion.
Figure 20.11 shows an example where a resistor is
consistent at different processing steps. A significant
normalised magnitude anomaly (purple shadow) is
clearly visible early in the processing (receiver level,
upper left picture). In this image the source-receiver
offset is plotted along the vertical axis. The burial
depth to the resistor can be approximated to 1.5 km
which is half the source-receiver offset of the anomaly
onset. The same anomaly also stands out in the 2.5D
inversion result along the line (middle left picture).
The burial depth and lateral extent agree with the
initial interpretation of the NMVO attribute. The
lower left picture shows the 3D inversion result
along the same acquisition line and the areal extent
of the anomaly is shown in map view in the upper right
picture in Fig. 20.11. The anomaly also conforms to a
faulted structure when overlain seismic data (lower
right picture). In this case the analyses done on the
CSEM data at different processing levels are consistent, and indicate a subsurface resistor with significant
contrast to the surroundings. However, the detailed
nature of the resistor can only be understood by
using all available geophysical and geological knowledge in the area.
20 Interpretation of Marine CSEM and Marine MT Data for Hydrocarbon Prospecting
525
expected trends? How well do resistivity anomalies
fit with the anticipated results? If the results are not as
expected, it does not necessarily mean that the inversion results are wrong. It can just as well be that the
existing geomodel is wrong and needs to be redefined.
It is within this integrated interpretation process
between electromagnetic-, seismic- and well-data
that valuable additional information can be extracted.
20.2.6 Interpretation and Integration
of CSEM Results
Interpretation of CSEM data involves explaining the
resistivity changes that we observe from real CSEM
data, and relating these to lithology and fluid changes
in the subsurface. The interpretation needs to be integrated
with other geophysical and geological data to build a
geological model that honours all the available data.
When interpreting CSEM data it is important to
keep in mind that the ability to detect hydrocarbon
reservoirs is not only dependent on the resistivity
contrast between the reservoir and the surroundings,
but also on burial depth, target size and net pay thickness of the reservoir. Furthermore the acquisition
geometry will also be of importance. A dense receiver
grid will be able to detect smaller targets than a coarse
receiver grid. The presence of a resistor could indicate
a hydrocarbon reservoir, but could also be explained
by other resistivity anomalies. It could for example be
caused by low porosity rocks (e.g. cemented or tightly
compacted sandstones), highly organic-rich shale
(source rocks), carbonates, volcanic rocks, salt or
other high resistivity strata or structures in the subsurface. Further, integration of seismic data, well logs and
geological understanding will help to reduce the possible explanations of an observed resistivity anomaly.
Interpretation of CSEM data can be done at a very
early stage in the processing flow by analyzing relative
differences between receivers. This can for example
be done on normalised magnitude vs. offset (NMVO)
displays, or phase difference vs. offset plots (PDVO).
An increase in NMVO indicates a resistivity increase
in the subsurface relative to the reference receiver
used for the normalisation (Fig. 20.1). Similarly a
decrease in PDVO (Fig. 20.3) will indicate a resistivity
decrease in the subsurface. Such interpretations will
give a first indication of resistivity changes in the
subsurface. It will mainly provide information about
lateral resistivity changes, but can also give rough
estimates of burial depth to a resistor. A deeply buried
resistor will show up at larger source-receiver offsets
and lower frequencies than a shallow resistor. As a
rule of thumb the burial depth to a resistor can be
approximated to half the source-receiver offset at the
onset of the anomaly. This approximation assumes a
1D Earth. Interpretation of receiver data attributes
(such as NMVO and PDVO) is important as it directly
evaluates the recorded data. The Troll case is included
as an example of receiver interpretation. In the other
cases the interpretation is based on inversion results.
Inverted resistivity models can be directly
integrated with depth converted seismic and well log
data. When interpreting CSEM inversion results it is
useful to look at vertical depth sections as well as
resistivity maps. Depth windows for resistivity maps
can be selected by constant depth intervals, or to
follow seismic depth converted horizons. Such maps
give the lateral outline of resistive anomalies which
can be correlated with seismically defined structures.
It is also important to quality control and interpret
the CSEM data at different processing levels from
attributes in the receiver domain to full 3D inversion.
Figure 20.11 shows an example where a resistor is
consistent at different processing steps. A significant
normalised magnitude anomaly (purple shadow) is
clearly visible early in the processing (receiver level,
upper left picture). In this image the source-receiver
offset is plotted along the vertical axis. The burial
depth to the resistor can be approximated to 1.5 km
which is half the source-receiver offset of the anomaly
onset. The same anomaly also stands out in the 2.5D
inversion result along the line (middle left picture).
The burial depth and lateral extent agree with the
initial interpretation of the NMVO attribute. The
lower left picture shows the 3D inversion result
along the same acquisition line and the areal extent
of the anomaly is shown in map view in the upper right
picture in Fig. 20.11. The anomaly also conforms to a
faulted structure when overlain seismic data (lower
right picture). In this case the analyses done on the
CSEM data at different processing levels are consistent, and indicate a subsurface resistor with significant
contrast to the surroundings. However, the detailed
nature of the resistor can only be understood by
using all available geophysical and geological knowledge in the area.
20 Interpretation of Marine CSEM and Marine MT Data for Hydrocarbon Prospecting
525