Dewanto, Ordas and Mulyanto, Bagus Sapto and Ordas, Perdana Rizki and Wibowo, Rahmat Catur
Reservoir Properties Prediction Using Seismic Inversion and
Geostatistical Integration.
In: ICSTAR 2020, Bandar Lampung, Indonesia.
(In Press)
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.
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Reservoir Properties Prediction Using Seismic Inversion and
Geostatistical Integration. (deposited 21 May 2021 05:48)
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