2018_EJRNL_PP_PRIYADARSHI_CHINMOY_KUMAY_1.pdf
Terbatas  
» Gedung UPT Perpustakaan
Terbatas  
» Gedung UPT Perpustakaan
The Kora volcano, a submarine Miocene andesitic stratovolcano, is documented to be buried
below ~1700m sedimentary strata in the northern Taranaki basin off New Zealand. The
buried volcano and enclosing older sedimentary strata, structurally modulated the
subsurface architecture leading to the formation of structural and stratigraphic traps for
hydrocarbon reservoirs. The Kora field is known for accumulating sub-commercial
hydrocarbon resources within the volcanogenic deposits. Here, we attempt to image such a
complex geological system from 3D time-migrated seismic data using state-of-the-art
artificial neural networks coupled with interpreter’s acquaintances. For this, we have
computed several attributes; optimally amalgamated these and trained over interpreter’s
intelligence. This has resulted into a single new attribute, defined as the intrusion cube (IC)
meta-attribute, to produce the best possible image of the subsurface. The resultant IC metaattribute
has successfully brought out the extension and distribution of volcanic edifice within
the buried volcanic system along with several structural elements such as the sill networks,
dyke swarms, forced folds, drag folds, jacked up strata and pinch-outs (along flanks of the
volcano) in the host sedimentary successions, which are very essential in understanding the
petroleum system of the Kora field. This interpretational approach, based on a blended
output of neural intelligence of artificial networks and interpreters’ knowledge, can be
suitably employed for imaging any complex volcanic system from 3D seismic data.