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Use of Meta Attributes to Identify Migration Pathways in a Tertiary Basin, Deepwater Sundaland Margin
Occidental and partners have interests in exploration acreage in a Tertiary Basin on the Sundaland Margin. The area currently lies in water depths ranging from 100 m to 2000 m and is lightly explored. The margin is tectonically complex, with many large, through-going, normal faults nearshore, extending to large-scale toe-thrusting in deepwater. Reprocessed 3D seismic data clearly showed amplitude anomalies, believed to be direct hydrocarbon indicators, but sourcing from hydrocarbon source kitchens was poorly understood. To evaluate this acreage, the following workflow utilizing neural network technology was implemented:
1. Picking known or suspected hydrocarbon transport conduits ("chimneys") and non-chimneys from the seismic volume for training and test data sets.
2. Calculating and identifying a set of single-trace and multi-trace seismic attributes that distinguish between chimneys and non-chimneys.
3. Designing and training a neural network with attributes extracted at interpreted chimneys and non-chimney locations.
The output was a "chimney cube" volume from multi-attribute transformation of the 3D seismic volume highlighting vertical disturbances. We used this to interpret migration pathways, distinguish between charged and non-charged prospects and sealing versus non-sealing faults, high-grade areas with hydrocarbon reservoirs, determine vertical migration of gas, identify potential for overpressure and detect shallow gas and geo-hazards.
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