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Application of Principal Component Proximity Transform and Geostatistics Methods for Volume Shale Distribution as Reservoir Characreristic Imaging in Seismic 3D
Author(s) -
Nur Islami
Publication year - 2012
Publication title -
makara journal of technology
Language(s) - English
Resource type - Journals
eISSN - 2356-4539
pISSN - 2355-2786
DOI - 10.7454/mst.v15i2.932
Subject(s) - oil shale , principal component analysis , geology , volume (thermodynamics) , geostatistics , reservoir modeling , petroleum engineering , seismic attribute , seismology , mathematics , statistics , paleontology , spatial variability , quantum mechanics , physics

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.

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