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Unravelling the petroleum system by enhancing fluid migration paths in seismic data using a neural network based pattern recognition technique


Corresponding author: J. H. Ligtenberg, dGB Earth Sciences, Boulevard 1945–24, 7511 AE Enschede, the Netherlands.
E-mail: Tel: +31 53 4315155. Fax: +31 53 4315104.


Understanding the hydrocarbon migration system in the sub-surface is a key aspect of oil and gas exploration. It is well known that conventional 3D seismic data contains information about hydrocarbon accumulations. Less known is the fact that 3D seismic data also contains information about hydrocarbon migration paths in the form of vertical noise trails. A method has been developed to highlight vertical noise trails in seismic data semi-automatically, using assemblies of directive multi-trace seismic attributes and neural network technology. The results of this detection method yield valuable information about the origin of hydrocarbons, about migration paths from source to prospect and about leakage or spillage from these prospects to shallow gas pockets or to the sea bed. Besides, the results reveal the sealing quality of faults, provide information on overpressure and whether prospects are charged or not. All these aspects are useful information for basin modelling studies and for an increased understanding of the petroleum system.