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Abstract

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

Bahasa Abstract

Teknik principal component proximity transform (PCPT) digunakan untuk memprediksi kandungan volume shale ke dalam data seismik dalam kerangka pemodelan reservoir. Tujuan yang hendak dicapai pada penelitian ini adalah untuk mendapatkan pencitraan volume shale dalam bentuk tiga dimensi sehingga dapat diperoleh gambaran penyebaran reservoir yang ada. Pemodelan reservoir membutuhkan gabungan sumber data kuantitatif dan kualitatif yang dikumpulkan dari berbagai sumber yaitu data sumur dan data seismik. Penggabungan metode PCPT dan geostatistik, dapat menghasilkan informasi yang lebih detil untuk keperluan karakterisasi property reservoir. Akhirnya dapat ditunjukkan bahwa model yang dibuat telah mencapai tingkatan yang cukup baik dengan koefisien korelasi sebesar 0,986 antara data sumur dengan data volume shale seismik yang telah diprediksi. Zona reservoir dapat dilihat pada zona yang memiliki volume shale rendah (

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