Click to view abstract in PDF format.
Seismic Evidence of Vertical Fluid Migration Through Faults, Applications of Chimney and Fault Detection.
By
Roar Heggland
Statoil ASA, N-4035 Norway
Summary
Columnar
disturbances in seismic data are frequently interpreted as free gas in the
sediments, either as small accumulations captured in the shales, or as upward
migrating free gas. These features, usually termed seismic chimneys, or gas
chimneys, have been observed to tie in to features associated with gas seepage,
like pockmarks and carbonate build-ups, and to shallow gas accumulations and
faults. Recent studies have revealed that chimneys can represent a link to
deeper
hydrocarbon
accumulations.
To improve the consistency in the mapping of chimneys, a method for semi-automated detection of chimneys was developed. This method has also been adapted for fault detection.
Gas seepage features and chimneys have been observed at different stratigraphic levels, which indicates that gas seepage is not a continuous process, but takes place during limited periods on the geological time scale.
Due to capillary resistance, vertical migration of hydrocarbons in shales has to happen through faults or fractures. Examples from 3D seismic data show that most chimneys are located at faults or fractures.
Figure Captions
Figure
1. Standard exploration 3D seismic data before and after chimney detection.
Figure
2. Visualization of 3D seismic data,
Gulf
of
Mexico
. Mapped horizons (brown,
green, blue), high amplitude clusters (red), detected salt diapir (light blue)
and detected chimneys (yellow).
Figure
3. Visualization of 3D seismic data,
Gulf
of
Mexico
. Chimneys (yellow) are
located at faults visible as low amplitude features (dark) on the amplitude map
in display.
Introduction
Since the late 80’s, exploration 3D seismic data have proved to be very useful for shallow gas and geohazards evaluations for E&P drilling sites (Heggland et al., 1996).
As
part of this work, indicators of fluid flow, like gas chimneys, pockmarks,
possible carbonate build-ups, as well as mud volcanoes and diapirs are mapped.
Studies of these shallow features have also been focused on whether they can
give information about deeper
hydrocarbon
accumulations.
Method
The mapping of gas chimneys from seismic data can be time consuming and difficult, because of their diffuse character and often weak appearance. To improve the identification and mapping of gas chimneys, a method was developed to detect gas chimneys in seismic data (Meldahl et al., 1998, 1999, Heggland et al., 1999). The method with examples and interpretation is also described in Heggland et al., 2000, and Meldahl et al., 2001.
The
method makes use of multi trace and multi attribute calculations and a neural
network (de Groot, P., 1999). The neural network is trained at
example
locations
on different attributes to recognize a chimney. In addition, the neural network
is trained at
example
locations not representing a chimney. The network is
finally applied on the total 3D volume to make a classification of the data into
“chimney” and “non chimney”. The output is a 3D probability cube, giving
high values for chimneys and low values in the surrounding volume, see the
example
in Figure 1. In a similar way, the method has been applied to fault
detection (Meldahl et al., 2001, Tingdahl et al., 2001).
To
highlight features associated with gas seepage, various attribute
maps
have been
applied, like “edge detection” and rms amplitude. The “edge detection”
maps
highlight the geometry of the horizons, where features like pockmarks,
carbonate build-ups, mud volcanoes and diapirs can be visualized. Azimuth and
dip
maps
are good alternatives for the study of the shape of a surface. The rms
amplitude
maps
can highlight
hydrocarbon
accumulations and sand deposits (high
amplitudes), as well as faults (low amplitudes).
Results
The
semi-automated detection of seismic chimneys has been applied to several 3D
seismic data sets from the Norwegian shelf and the
Gulf
of
Mexico
(Heggland et
al., 2000), see Figure 2.
Seismic chimneys frequently tie in with pockmarks, carbonate mounds and mud volcanoes, as well as with amplitude anomalies indicating shallow gas accumulations. As such, the mapping of chimneys has significance in geohazards interpretation.
Features associated with gas seepage, and chimneys, appear at different stratigraphic levels, indicating that vertical fluid migration occurs within limited periods of time (Heggland, 1997, 1998).
Possible
hydrocarbon
migration systems have been visualized by the seismic detection
method in areas of proven oil and gas fields. The chimneys indicate fluid and/or
gas migration from a source rock into a reservoir, and between a reservoir and
the seabed. In the same manner, interpretation of detected chimneys are used in
the ranking of prospects.
The semi-automated detection of chimneys has made it possible to make consistent comparisons between chimneys in areas with discoveries and in areas with dry wells. Preliminary results have showed a difference in the density of chimneys. Discovery wells and oil and gas fields are located in areas with a high density of chimneys, whereas dry wells are located in areas with a low density of chimneys, or no chimneys at all.
Vertical migration of hydrocarbons in shales has to happen through faults or fractures, due to capillary resistance in the shales. Detection of chimneys in 3D seismic data shows that, in most cases, chimneys are located at faults or fractures (see Figure 3).
In
near surface sediments, and where no faults or fractures are visible, chimneys
are still present and they seem to occupy a much larger space than at deeper
levels, where the chimneys are located at faults. Above a certain level, where
the sediments are less consolidated, the capillary resistance may be small
enough to allow for vertical
hydrocarbon
migration. Another explanation could be
that by an upward movement of gas saturated water, gas can be released when the
pressure drops. For other papers on application of chimney detection, see
Aminzadeh et al., 2001.
Conclusions
Results
of detection of chimneys in 3D seismic data, show that chimneys tie in to
features associated with gas seepage, shallow gas accumulations and deeper
hydrocarbon
reservoirs.
The appearance of seepage related features and chimneys at different stratigraphic levels, indicate that vertical fluid migration takes place within limited periods of time.
High concentrations of chimneys are observed in areas where discovery wells and oil and gas fields are present. Low concentrations of chimneys are observed in areas with dry wells.
The appearance of chimneys at locations of faults and fractures, strongly indicates that vertical fluid migration through shales takes place through faults and fractures.
Acknowledgements
Statoil ASA is acknowledged for the use of their data and the permission to publish this paper.
De Groot-Bril Earth Sciences BV (dGB) is acknowledged for the performance of the chimney and fault detection.
References
Aminzadeh, F., T. Berge, P. de Groot and G. Valenti, 2001, Using Gas Chimneys as an Exploration Tool, World Oil, Part 1, May 2001, Part 2, June 2001. Aminzadeh, F., T. Berge, P. de Groot and G. Valenti, 2001, Using Gas Chimneys as an Exploration Tool, World Oil, Part 1, May 2001, Part 2, June 2001.
De Groot, P.F.M., 1999a, Seismic Reservoir Characterisation Using Artificial Neural Networks, 19th Mintrop-Seminar, 16 – 18 May 1999, Münster, Germany.
De Groot, P.F.M., 1999b, Volume transformation by way of neural network mapping, 61st EAGE Conference, Helsinki, 7-11 June 1999.
Heggland, R., 1997, Detection of Gas Migration from a Deep Source by the Use of Exploration 3D Seismic Data, Marine Geology, v. 137, p. 41 - 47.
Heggland, R., 1998, Gas Seepage as an Indicator of Deeper Prospective Reservoirs. A Study Based on Exploration 3D Seismic Data, Marine and Petroleum Geology, v. 15, p. 1 - 9.
Heggland, R., E. Nygaard, J.W. Gallagher, 1996, Techniques and Experiences Using Exploration 3D Seismic Data to Map Drilling Hazards, Proceedings of Offshore Technology Conference (OTC), Houston, 6 - 9 May 1996, v. 1, 111 - 124.
Heggland,
R., P. Meldahl, A.H. Bril and P.F.M. de Groot, 1999, The chimney cube, an
example
of semi-automated detection of seismic objects by directive attributes
and neural networks: Part II; interpretation, SEG 69th Annual Meeting, Houston,
Oct. 31 - Nov. 5, Expanded Abstracts v. 1, p. 935 - 937.
Heggland,
R., P. Meldahl, P. de Groot and F. Aminzadeh, 2000, Chimneys in the
Gulf
of
Mexico
, The American Oil and Gas Reporter, Feb. 2000, p. 78 - 83.
Meldahl, P., R. Heggland, A.H. Bril and P.F.M. de Groot, 1998, Method of Seismic Body Recognition. Patent application GB 9819910.02.
Meldahl,
P., R. Heggland, A.H. Bril and P.F.M. de Groot, 1999, The chimney cube, an
example
of semiautomated detection of seismic objects by directive attributes
and neural networks: Part I; method, SEG 69th Annual Meeting, Houston, Oct. 31 -
Nov. 5, Expanded Abstracts v. 1, pp 931 - 934.
Meldahl, P., R. Heggland, A.H. Bril and P.F.M. de Groot. 2001, Identifying targets like faults and chimneys using multi-attributes and neural networks, The Leading Edge, May 2001.
Tingdahl, K.M., P. De Groot, R. Heggland, and H. Ligtenberg, 2001, Semi-automated object detection in 3-D seismic data, Offshore, Aug. 2001.
