Procedure and Attribute Selection  

A volume of 3-D seismic data is provided as an input to a specially designed neural network. This volume is transformed to a chimney probability cube volume using a set of attributes of the input data as shown in, Figure I.

This procedure involves:

1. Calculating and identifying a set of single- trace and multi-trace seismic attributes that distinguishes between chimneys and non-chimneys
2. Designing and training a neural network with known chimneys and non-chimneys
3. Creating a "chimney cube" volume from multi-attribute transformation of the 3D seismic volume highlighting vertical disturbances as the output of the trained neural network
4. Visualizing and interpreting the chimney volume. Using the chimney cube in conjunction with other structural, stratigraphic and geophysical interpretation tools.

Chimney Interpretation

Gas clouds or chimneys appear as low quality seismic response with vertical bodies of varying dimensions. Also shape and distribution may vary, although cigar- shapes and a distribution along faulted zones are common. The internal texture shows a chaotic reflection pattern of low energy. The exact outline of a chimney is very difficult to determine on convention- al seismic displays. Only large chimneys can be recognized. To also detect more subtle disturbances we will transform the data into a new cube that highlights vertical disturbances. A neural network does this by classifying the data into classes: chimney versus non- chimney. Example locations are chosen inside interpreted chimneys as well as outside. 

Chimneys, in most cases, also demonstrate radial pat- terns on time slices of chimney cubes, Figure 2. This is caused by the friction generated from vertical migration of hydrocarbons and possible fracturing of near by rocks. These fractured rocks are subsequently filled with hydrocarbons. Once the chimneys are identified, they can be displayed in conjunction with the structural model or other reservoir property information.

This helps validating certain geologic interpretations such as the origination points of hydrocarbons, spill points, reservoir accumulation and gas seepage to the surface. Although these radial patterns are subtle at times, they can be helpful in making proper diagnosis of the chimneys. Figure 3 shows one such example with the hint of radial patterns going outward from the chimney.

Evidence of leaking faults can also be seen in some cases from chimneycubes. Figure 4 shows a case where some of the chimneys can be traced back to known faults where leakage occurs.

In general, leaks on the fault are characterized by a collection of small circular patters of high probability chimney aligned along a fault. Figure 5 shows a clear example of such suspected leaking fault. The most useful results of chimney processing are realized when they are used in conjunction with other conventional or advanced geologic and geophysical interpretation.

For example to further validate chimneys and their connection with the known faults and structures one can overlay them on geologic models derived from structural interpretation. Figure 6 shows the chimney cloud (in yellow) on top of the structure (red and blue ). Here, a deep fault surface (left hand side of lower red structure) and the associate spill point where vertical gas migration (yellow gas clouds) is shown. This hydrocarbon migration could be linked to formation of the reservoir unit under the shallow red structure. Leaks from part of this reservoir create the shallow chimneys (in yellow) leading to possible shallow gas hazard.

In this newsletter, only some aspects of chimneys are highlighted. Chimney interpretation can also delineate gas prone versus oil prone traps. Chimneys by degassing reservoirs increase the probability of oil reservoirs. The intensity and distribution of chimney anomalies can often be linked directly to the hydrocarbon phase of the reservoir. Chimney cube data can also corroborate, contradict, or provide input into 2D and 3D basin models.  

Other applications of chimney interpretation are: ranking prospects, detect reservoir leakage, spill points & sealing versus non-sealing faults, identifying potential over-pressured zones & drilling (shallow gas) hazards and finding areas of suspected sea bottom instability. The same technology can also be used to detect a variety of other geologic objects such as faults, fractures, salt bodies and other seismic anomalies. Although services for these applications are available now, in a few months time a new seismic interpretation system that is developed around this technology will be released by dGB. There is also an industry supported consortium called dTect to further develop and utilize this new interpretation technology. For more details on how to start a pilot project, please contact the author at faz@dgbusa.com or + 1.713.789.2159.

Acknowledgements Valuable contributions of Roar Heggland, and Paul Meldahl, from Statoil and Paul, de Groot, and Herald Ligtenberg from d GB are acknowledged. We also are thankful for the opportunity to serve many customers including Agip, ChevronTexaco, Forest oil Oil International, Pdvsa and many others for utilizing this technology in their exploration efforts. Particular thanks go to David Connolly for providing us with valuable geologic insight.

 References

1. Aminzadeh, F., Berge, T., de Groot, P. and Valenti, G... Using Gas Chimneys as Exploration Tool, World Oil, Part I, May 2001, Part 2, June 2001.
2. Aminzadeh, F., and de Groot, P., 2001, Gas Chimney Processing & Analysis, Proceeding ofHouston Geophysical Society Spring Symposium, March,2001.
3. Meldahl, P., Heggland, R., de Groot, P., and Bril, A., 1998. Seismic Body Recognition. Patent Application GB. 9819910.2.
4. Heggland, R., Meldahl, P., de Groot, P., and Aminzadeh, F., 2000. Seismic chimney interpretation examples from the North Sea and the Gulf of Mexico. American Oil and Gas Reporter.