Vol 15, No 2 (2011) > Articles >

Application of Principal Component Proximity Transform and Geostatistics Methods for Volume Shale Distribution as Reservoir Characreristic Imaging in Seismic 3D

Nur Islami 1

Affiliations:

  1. Program Studi Fisika, Jurusan Pendidikan Matematika dan Ilmu Pengetahuan Alam,Fakultas Keguruan dan Ilmu Pendidikan, Universitas Riau, Pekanbaru 28293, Indonesia

 

Abstract:

Principal component proximity transform (PCPT) technique was used to predict the content of volume shale into seismic data in reservoir modeling framework. The goal in this research is to get the volume shale imaging in three dimensions and allow for reservoir modelling. The reservoir modelling requires an integrated quantitative and qualitative data sources collected separately, such as well and seismic data. Integrating PCPT and Geostatistic methods can generate the detail information for characterization of reservoir’s properties. Finally, it shows that the model was valid with correlation coefficient of 0.986 between volume shale in the well and predicted volume shale in the seismic. Reservoir zone can be found with low level of volume shale (<0.5) that it was visualized by colour dark-grey.

Keywords: geostatistic, PCPT, reservoir, seismic, volume shale
Published at: Vol 15, No 2 (2011) pages: 147-152
DOI:

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References:

A.R. Brown, Interpretation of Three-Dimensional Seismic Data, Fifth Edition, AAPG Memoir 42 SEG Investigations in Geophysics, No. 9, Oklahoma, 2000.

S. Sigit, Application of Multi-attribute Analysis in Mapping Lithology and Porosity in the PematangSihapas Groups of Central Sumatra Basin, Indonesia, The Leading Edge, 2007.

M. Sonja, M. Greve, K. Savage, New Zealand Earth Planet. Sci. Lett. 285/1-2 (2009) 16.

Hazairin, A. Linawati, A. Widiyantoro, Earth Modeling Application for Reservoir Heat Management in Duri Field, Proceedings Indonesian Petroleum Association, Indonesia, 2001.

J. Walls, Well Logs and Rock Physics in Seismic Reservoir Characterization, OTC paper No. 16921, Houston, 2004.

J. Pendrel, CSEG Recorder 26/1 (2001) 16.

M.W. Lee, T.S. Collett, Gulf of Mexico Mar. Pet. Geol. 25/9 (2008) 924.

K. Payrazyan, J.R. Scheevel, Principal Component Analysis Applied to 3-D Seismic Data for Reservoir Property Estimation, Society Petroleum Engineering (SPE) No. 56734, 1999.

K. Payrazyan., K. Kelsch, Seiswell Technique for Seismic Based Reservoir Characterization, ETRC

KDK. PT. CPI, 2001.

Y.Q. Ni, X.T. Zhou, J.M. Ko, J. Sound Vibr. 290 (2006) 242.

M. Yong-Guang, C. Si-Yuan, J. Pet. Sci. Eng. 41/1-3 (2004) 159.

V. Linari, M. Santiago, C. Pastore, K. Azbell, M. Poupon, The Leading Edge 22 (2003) 32.

T. Zouaghi, M. Bédir, M.H. Inoubli, J. Afr. Earth Sci. 43/4 (2005) 464.

J.C. Davis, Statistical and Data Analysis in Geology. 2nd ed., John Wiley & Sons, New York, 1986, p.646.

A.E. Barnes, Geophysics 72/3 (2007) 33.