Pengembangan Aplikasi Artificial Intelligence pada Propogasi Rock Type untuk Sumur yang Tidak Memiliki Data Core
Nama Peneliti (Ketua Tim)

Dedy Irawan



Ringkasan Kegiatan

This study presents the effect of permeability anisotropy; maximum horizontal permeability (kx), horizontal permeability of 90o (ky), and vertical permeability (kz), in applying rock typing while only maximum horizontal permeability is commonly used for reservoir characterization. Samples from Berea sandstone (measured in laboratory), Nugget sandstone (published data), and Shannon sandstone (published data) are used in this study which are available for the value of kx, ky, and kz. Common rock typing method, Winland, HFU, GHE, and PGS were applied to classify the samples by using all tensor permeability with each pair of porosity at the same depth. Yet, with those methods, each permeability tensors shows a different classification even though they are from the same depth. Therefore, this study develops a general of rock grouping methods in which by using kx, ky, and kz in rock typing will define an object consistently.



Capaian

Penerapan Teknologi Tepat Guna, Penerapan Karya Tulis



Testimoni Masyarakat

rock grouping methods