Dewanto, Ordas and Mulyatno, Bagus Sapto and Ordas, Perdana Rizki and Wibowo, Rahmat Catur (2021) Reservoir properties prediction using seismic inversion and geostatistical integration. In: IC-STAR, 1 November 2021, Bandar Lampung.

[img] Text
Internasional Scopus, Dewanto_2021_IOP_Conf._Ser.__Mater._Sci._Eng._1173_012008_compressed.pdf

Download (521kB)
Official URL: https://iopscience.iop.org/issue/1757-899X/1173/1

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 8-13%. The density and porosity maps obtained from the multi-attributes analysis can help in the long-term exploration and production stages. Its aims are to improve primary recovery and tertiary recovery, understanding the stratigraphic traps, and continuity of reservoir layers.

Item Type: Conference or Workshop Item (Lecture)
Subjects: Q Science > Q Science (General)
Q Science > QC Physics
Q Science > QE Geology
Divisions: Fakultas Teknik (FT) > Prodi Teknik Geofisika
Depositing User: ORDAS DEWA
Date Deposited: 06 Nov 2021 08:25
Last Modified: 06 Nov 2021 08:25
URI: http://repository.lppm.unila.ac.id/id/eprint/35287

Actions (login required)

View Item View Item