![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-COVER.pdf
PUBLIC Ena Sukmana ![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-BAB 1.pdf
PUBLIC Ena Sukmana ![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-BAB 2.pdf
PUBLIC Ena Sukmana ![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-BAB 3.pdf
PUBLIC Ena Sukmana ![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-BAB 4A.pdf
PUBLIC Ena Sukmana ![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-BAB 4B.pdf
PUBLIC Ena Sukmana ![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-BAB 5.pdf
PUBLIC Ena Sukmana ![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-BAB 6.pdf
PUBLIC Ena Sukmana ![](https://digilib.itb.ac.id/assets/icon/pdf.gif)
2012 TS PP OSKAR PARIANG PAKPAHAN 1-PUSTAKA.pdf
PUBLIC Ena Sukmana
The T- gas field located in offshore Sabah with geology structure is a well-defined four-way dip closure that developed as a result of inversion along the deep-seated NE-SW faults, a series of N-S oriented shear faults formed during the inversion and divided the anticline into several fault blocks. Reservoirs encountered at the T- gas field include fluvial and nearshore / esturine sandstones of Early to Middle Miocene age. A good to high quality 3D near (10⁰-23⁰) and far angle stacks (35⁰-46⁰) seismic is available and 7 wells have been drilled and logged. The lithology is divided into shale, gas sand, brine sand and coal using volume shale cut off as well as saturation logs where several hard streak coals appear above some gas reservoirs which can potentially mask the amplitude interpretation. From the AI/EI logs crossplot: several shale, brine sand and gas sand acoustic and elastic properties points are identified overlay each other while coal are identified having low acoustic and elastic properties. AVO modelling shows that the gas sand demonstrates a normal class III AVO while the presence of coal results in a slight decrease on the amplitude. The Bayesian classification is applied by combining the AI/EI and rock physics probability maps to map the most likely the gas sand reservoir on the area. Additionally, the seismic attribute (instantaneous amplitude multiplied by far angle seismic) are used to help to map the bright amplitudes associated with the gas sand reservoir intervals.
The Bayesian classification result shows several good distributions of gas sands reservoir typical of channel associated with the low EI while the seismic attributes amplitude shows a good match with the gas sand reservoirs distribution interval.