Jan 5th - North Tech Breakfast: Detection of Vertical Hydrocarbon Migration Pathways in Seismic Data:* ...
Complete Title: Detection of Vertical Hydrocarbon Migration Pathways in Seismic Data: Toward the Quantification of Top Seal and Charge Risk
Sponsorsed by: Anadarko and Lumina
Event Location:
Anadarko Petroleum
1201 Lake Robbins Drive
The Woodlands, TX 77380
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Speaker: David Connolly, dGB Earth Science
Most hydrocarbon producing basins of the world are dominated by vertical hydrocarbon migration. This hydrocarbon migration is often directly detected in the seismic record as zones of vertically aligned, chaotic, low energy data, called “gas chimneys”, although they are often associated with oil migration. Chimneys have often been observed in relationship to producing oil and gas fields. However, this relationship has not been systematically documented. Hydrocarbon migration in the interval below the reservoir is particularly overlooked. To address this issue we are compiling an atlas of chimney occurrences associated with known fields and dry holes, using 3D seismic data.
A survey of major exploration companies suggests that seal and charge provide the majority of risk in today’s exploration portfolio. The morphology of chimneys directly above the reservoir provides clues to the top seal integrity. Work in the North Sea (Heggland, 2013) over 100 structural traps shows that traps overlain by gas clouds have a high probability of success, while traps with point sourced or fault related top seal leakage have a higher chance of being breached or having limited hydrocarbon column heights. Traps with chimneys on the flanks of the structure will often have hydrocarbon column heights corresponding to this spill point. In basins, dominated by vertical hydrocarbon charge, the morphology of vertical chimneys directly beneath the reservoir may provide clues to the effectiveness of hydrocarbon charge. Traps can be classified for charge effectiveness based on the abundance of chimneys in direct communication with the reservoir body. These classifications can then be a guideline for risking untested structures.
The diffuse nature of chimneys makes them difficult to map with 3D or 2D seismic data. Thus a method was developed to highlight and visualize these gas chimneys in normally processed seismic data (Meldahl et al., 2001). Gas chimneys are detected using a supervised neural network trained on reliable examples of gas chimneys. Not all chimneys, detected by neural network training, are related to hydrocarbon migration. Thus the resultant chimneys must be validated based on a set of criteria (Connolly et al., 2013). By detecting and mapping these chimneys, we can determine their origin (in a known or suspected source rock interval), their morphology, and how they are linked to known or suspected reservoirs.
Using this chimney detection methodology, an atlas of chimney occurrences over known oil and gas fields (or discoveries) and dry holes in 3D seismic data is being compiled. Dry holes or sub-economic discoveries are chosen over valid anticlinal structures with effective reservoir (failure due to charge or seal). Highlights of this atlas will be shown with examples from the Gulf of Mexico, North Sea, West Africa, and Australia. The atlas is intended to provide useful analogs for hydrocarbon charge and seal assessment in various geologic settings worldwide.
References
Connolly, D., Aminzadeh, F., Brouwer, F., and Nielsen, S., 2013, Detection of Subsurface Hydrocarbon Seepage in Seismic Data: Implications for Charge, Seal, Overpressure, and Gas-hydrate Assessment, in F. Aminzadeh, T. Berge, & D. Connolly, eds., Hydrocarbon Seepage: From Source to Surface, SEG AAPG Geophysical Developments no. 16, p. 199-220.
Heggland, R., 2013, Hydrocarbon Trap Classification Based on Associated Gas Chimneys, in F. Aminzadeh, T. Berge, & D. Connolly, eds., Hydrocarbon Seepage: From Source to Surface, SEG AAPG Geophysical Developments no. 16, p. 221-230.
Meldahl, P., Heggland, R., Bril, B., and de Groot, P., 2001. Identifying Fault and Gas Chimneys Using Multi- Attributes and Neural Networks, The Leading Edge of Geophysics, pp. 474-482.
Biography: David Connolly, dGB Earth Science
David Connolly is dGB Earth Science’s Chief Geologist. He has over 30 years of industry experience in various aspects of petroleum geology and geophysics. He worked for Getty / Texaco from 1981-2001 in a variety of international and national exploration assignments. He has been with dGB since 2001. He is co-editor and a major contributor to the SEG/AAPG Geophysical Developments #16, Hydrocarbon Seepage: From Source to Surface. His poster Using gas chimney detection to assess hydrocarbon charge and top seal effectiveness – offshore, Namibia, presented at the 2014 EAGE Convention, won the Cagniard Award for the best poster. His paper Detecting hydrocarbon expulsion from source rock in seismic data; Case studies from offshore, Namibia and Gulf of Mexico shelf, presented at the 2014 SEG Annual Meeting, was honored as a top paper. He graduated from Washington & Lee University with a B. A. in Geology.
Breakfast will be available starting at 7:00 am
Technical Talk will start at 7:30 am
Event will end by 8:30
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