Reservoir Characterization of Ngrayong Formation, Sandstone with  Carbonate Intercalation, Using a Geostatistical Approach Based on  Petrophysical Parameters, Northeast Java Basin, Indonesia

Handoyo Geoph; Bernard Cavin Ronlei; Andy Setyo Wibowo; Asido Saputra Sigalingging; Edlyn Yoadan Nathania; Fatkhan Fatkhan; Aurio Erdi; Per Avseth; Ramon Carbonell; Pranowo Nugroho; Riky Hendrawan Bayu Pandito; Aladin Nasibov; Abdullah Ali Ali Husein

doi:10.29017/scog.v48i3.1828

Authors

Handoyo Geoph Teknik Geofisika, Institut Teknologi Sumatera
Bernard Cavin Ronlei Teknik Geofisika, Institut Teknologi Sumatera
Andy Setyo Wibowo Pusat Survei Geologi Bandung
Asido Saputra Sigalingging Teknik Geofisika, Institut Teknologi Sumatera
Edlyn Yoadan Nathania Teknik Geofisika, Institut Teknologi Sumatera
Fatkhan Fatkhan Teknik Geofisika, Institut Teknologi Bandung
Aurio Erdi National Research and Innovation Agency (BRIN)
Per Avseth Dig Technology Oslo
Ramon Carbonell Geosciences Barcelona (GEO3BCN, CSIC)
Pranowo Nugroho Pertamina Hulu Energi OSES (PHE OSES)
Riky Hendrawan Bayu Pandito Pertamina Hulu Rokan (PHR)
Aladin Nasibov Azerbaijan State Oil and Industry University Baku
Abdullah Ali Ali Husein School of Marine Sciences, Sun Yat-Sen University Guangzhou

DOI:

https://doi.org/10.29017/scog.v48i3.1828

Keywords:

low-frequency extrapolation, self-supervised learning, Asri Basin, full waveform inversion, hydrocarbon, geostatistic, petrophysics, porosity, permeability, SGSIM

Abstract

Hydrocarbons have a vital role as a driver of the global economy, which causes demand to continue to increase. To achieve production targets, oil and gas companies try to conduct exploration using efficient and accurate methods to obtain optimal hydrocarbon reserves. One approach in hydrocarbon exploration is to use geostatistical analysis to understand the characteristics of petrophysical parameters of reservoir rocks (e.g. porosity, permeability, water saturation and facies). This study aims to characterize reservoirs in the NE Java Basin using a geostatistical approach that Sequential Gaussian Simulation (SGSIM) to produce random realizations that can be adjusted and validated through geostatistical analysis of data before and after the simulation. The dataset used in this study consist of well data, seismic line, and core data. The results shows the petrophysical properties distribution from the simulation reveals the dominance of carbonate sandstone reservoirs in the central part of the study area with a thinning slope towards the northwest and southeast, while sandstone reservoirs are only dominant in the southeast direction of the study area. This research provides important insights in understanding reservoir characteristics and can be a basis for efficient decision making in the exploration of hydrocarbon resources in this area.

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