Reservoir Characterization Using Acoustic Impedance (AI) Seismic Inversion and Seismic Multi-Attribute, Case Study: “BM” Field, Bintuni Basin, West Papua
Author: Faridha Aprilia, Kevin Christopher Febriano, Sheila Kusuma, Warto Utomo*
warto.utomo89@gmail.com
“BM” Field is one of the oil and gas field at Bintuni Basin, West Papua, Indonesia. This field produced crude oil, that is originated from Late Miocene Kais Formation limestone. Other than crude oil, this field also has natural gas potential from Roabiba Sandstone reservoir in Jurassic Lower Kemblangan Formation. Reservoir characterization can be done using two main types of data which are seismic data, well log data, and supported by geological data. There are two methods that can be used together in integrating seismic and well log data which are acoustic impedance seismic inversion and seismic multi-attribute. The processes started with sensitivity and petrophysical analysis of well logs data, followed by well seismic tie using both of seismic and well logs, and finally structural interpretations of the seismic data. Seismic inversion process will distribute AI value, that has been analyzed as correlated to the porosity data, to all the seismic lines. Seismic multi-attribute will also use the inverted AI results as the external attributes and other trained seismic attributes to predict porosity parameter of the seismic lines that later will be distributed to the research zone. Analysis results showed that there is a positive flower structure that act as the hydrocarbon’s trap and migration pathways. Targeted Kais Formation and Roabiba Sandstone zone AI value is in the range of 20.000-50.000 g.ft/cm.s with its dominant distribution direction is Northwest to Southeast. There is also an AI value anomaly on top of the Kais Formation that is indicated caused by shale dominance on top of Kais Formation. It is confirmed further by its absence on Kais Formation multi-attribute porosity map. According to the porosity map, Kais Formation’s porosity value is in the range of 5-25%.
Keywords: seismic, inversion, multi-attribute, reservoir, porosity
View Full ManuscriptDownload