Dewanto, Ordas and Mulyatno, Bagus Sapto and Rizki Ordas, Perdana and Wibowo, Rahmat Catur (2020) Reservoir Properties Prediction Using Seismic Inversion and Geostatistical Integration. Journal of Physics: Conference Series, 1673. pp. 1-9. (Submitted)

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Abstract

Abstract. Exploration and production in the sand reservoir still have their challenges due to the low porosity and permeability characteristics. This study was conducted to analyse the characteristics of a tight sand reservoir based on a log property distribution map, using acoustic impedance inversion and multi-attribute analysis. Stepwise regression multi-attribute analysis is a method that uses the best attributes to predict the target log by going through a trial and error process. Choosing the right seismic attributes can provide a better depiction of the target zone. This research was conducted to obtain a map of subsurface geological structures, acoustic impedance volumes. Then, we performed a multi-attribute analysis to obtain a prediction of volume log properties such as pseudo gamma-ray, density and porosity using the stepwise regression method. The results of acoustic impedance seismic inversion and stepwise regression multi-attribute analysis shows that the reservoir is a gas with tight sand lithology, which has a range of acoustic impedance values of 15,000 ((ft/s)*(g/cc)) up to 30,000 ((ft/s)*(g/cc)), porosity of 12% to 24%, and the distribution of Sw of small value (8-13%). The density and porosity maps obtained from the multi-attributes analysis can help in the long-term exploration and production stages The aims are to improve primary recovery and tertiary recovery, understanding the stratigraphic traps, and continuity of reservoir layers.

Item Type:	Article
Subjects:	Q Science > QC Physics Q Science > QD Chemistry Q Science > QE Geology
Divisions:	Fakultas Teknik (FT) > Prodi Teknik Geofisika
Depositing User:	ORDAS DEWA
Date Deposited:	09 Nov 2020 06:16
Last Modified:	09 Nov 2020 06:16
URI:	http://repository.lppm.unila.ac.id/id/eprint/24733

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