Estimation of Rock Physical Parameters Based on Digital Rock Physics Image, Case Study: Blok Cepu Oil Field, Central Java, Indonesia

Handoyo Handoyo; Fatkhan Fatkhan; Fourier D. E. Latief; Harnanti Y. Putri

doi:10.36435/jgf.v16i1.53

Handoyo Handoyo Teknik Geofisika, Institut Teknologi Sumatera, Lampung, Indonesia
Fatkhan Fatkhan Teknik Geofisika, Fakultas Teknik Pertambangan dan Perminyakan, ITB, Jalan Ganesa No. 10, Bandung 40132, Indonesia
Fourier D. E. Latief Kelompok Keahlian Fisika Bumi dan Sistem Kompleks, Fakultas Matematika dan Ilmu Pengetahuan Alam, ITB, Jalan Ganesa No. 10,Bandung 40132, Indonesia
Harnanti Y. Putri Teknik Geofisika, Institut Teknologi Sumatera, Lampung, Indonesia

DOI: http://dx.doi.org/10.36435/jgf.v16i1.53

Keywords

Sandstone, Rock Physics, Porosity, Permeability, Elasticity Parameters

Abstract

Modern technique to estimate of the physical properties of rocks can be done by means of digital imaging
and numerical simulation, an approach known as digital rock physics (DRP: Digital Rock Physics). Digital rock
physics modeling is useful to understand microstructural parameters of rocks (pores and rock matrks), quite quickly and in detail. In this paper a study was conducted on sandstone reservoir samples in a rock formation. The core of sandstone samples were calculated porosity, permeability, and elasticity parameters in the laboratory. Then performed digital image processing using CT-Scan that utilizes X-ray tomography. The result of digital image is processed and done by calculation of digital simulation to calculate porosity, permeability, and elastic parameter of sandstones. In addition, there are also predictions of p-wave velocity and wave -S using the empirical equations given by Han (1986), Raymer (1990), and Nur (1998). The results of digital simulation (DRP) in this study provide a higher than the calculations in the laboratory. The digital rock physics
method (DRP) combined with rock physics modeling can be a practical and rapid method for determining the rock properties of tiny (microscopic) rock fragments

References

Andra, H., Combaret N., Dvorkin J., Glatt E., Han J., Krzikalla F., Lee M., Madonna C., Marsh M., Mukerji T., Ricker S., Saenger E.H., Sain R., Saxena N., Wiegmann A. dan Zhan X., 2013. Digital Rock Physics Benchmarks-Part I: Imaging and Segmentation. Journal Computers & Geosciences, ELSEVIER 50 25-32.
Arns, C.H., Knackstedt, M.A., 2002. Computation of Linear Elastic Properties from Microtomographic Images: Methodology and Agreement Between Theory and Experiment. Journal of Geophysics, Vol. 67, No. 5, 1396-1405.
Fourier, D.E.L., 2014. Analysis of Permeability and Tortuosity of Fontainebleau Sandstone and Its Models Using Digital Rock Physics Approach. Physics of Earth and Complex System, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Indonesia.
Handoyo., Fatkhan., Fourier, D.E.L., 2014. Digital Rock Physics Application: Structure Parameters Characterization, Materials Identification, Fluid Modeling, and Elastic Properties Estimation of Saturated Sandstones. HAGI Proceeding 2014 Solo, Bandung Institute of Technology, Indonesia.
Mavko, G., dan Nur, A., 1999. The Rock Physics Handbook, Second Edition Tools for Seismic Analysis of Porous Media. Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK
Sukmono, S. 2002. Seismic Inversion and AVO Analysis for Reservoir. Program Studi Teknik Geofisika ITB. Bandung. Indonesia.
Raymer, L.L., Hunt, E.R., dan Gardner, J. S., 1980. An improved sonic transit time-to-porosity transform. Trans. Soc. Prof. Well Log Analysts, 21st Annual Logging Symposium, Paper P.
R. Sungkorn, A. Morcote, G. Carpio, G. Davalos, Y. Mu, A. Grader, N. Derzhi, J. Toelke, 2015. Multi-Scale And Upscaling Of Digital Rock Physics With A Machine That Can Learn About Rocks. Ingrain Inc., 3733Westheimer Rd., Houston, Texas, 77027, U.S.A.
Wiegman, 2012. Predicting Effective Elastic Properties with Elastodict, Fraunhofer ITW Germany.