TY - GEN
T1 - Integrated approach for fracture modeling of carbonate reservoir
T2 - 1st International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2015
AU - Haris, Abd.
AU - Riyanto, Agus
AU - Rachmanto, Ambar
AU - Sukmatiawa, Adang
N1 - Publisher Copyright:
© 2016 Author(s).
PY - 2016/4/19
Y1 - 2016/4/19
N2 - Baturaja formation has become one prospective reservoir in field A, which has potential number gas inplace with recovery factor up to 29%. However it has a big challenge for developing because of its structural complexity. From special core analysis data and Formation Micro Imaging (FMI) data analysis, it was shown that this reservoir is dominated by fracture indicated by cementation exponent (m) below 2. This paper aims to perform fracture modeling based on the simultaneous integration of geophysical, geological and engineering data to improve reservoir characterization.These integrated data so called fracture drivers, which contain seismic attributes, curvature, porosity, facies, acoustic impedance, elastic impedance and production data. This fracture driver will be ranked using fuzzy-logic tool. After having rank and eliminating the less influential driver, the effect of each fracture driver on the fracturing was analysed. The ranked drivers were used to establish the complex, non-linear relationship relating the fracture intensity to these drivers. This process is performed by using neural-network algorithm.Our experiments show that this approach succeed in distributing the fracture frequency, which is associated with permeability. Finally, the predicted permeability can be useful for reservoir simulation and helps us in developing carbonate reservoir.
AB - Baturaja formation has become one prospective reservoir in field A, which has potential number gas inplace with recovery factor up to 29%. However it has a big challenge for developing because of its structural complexity. From special core analysis data and Formation Micro Imaging (FMI) data analysis, it was shown that this reservoir is dominated by fracture indicated by cementation exponent (m) below 2. This paper aims to perform fracture modeling based on the simultaneous integration of geophysical, geological and engineering data to improve reservoir characterization.These integrated data so called fracture drivers, which contain seismic attributes, curvature, porosity, facies, acoustic impedance, elastic impedance and production data. This fracture driver will be ranked using fuzzy-logic tool. After having rank and eliminating the less influential driver, the effect of each fracture driver on the fracturing was analysed. The ranked drivers were used to establish the complex, non-linear relationship relating the fracture intensity to these drivers. This process is performed by using neural-network algorithm.Our experiments show that this approach succeed in distributing the fracture frequency, which is associated with permeability. Finally, the predicted permeability can be useful for reservoir simulation and helps us in developing carbonate reservoir.
UR - http://www.scopus.com/inward/record.url?scp=84984555031&partnerID=8YFLogxK
U2 - 10.1063/1.4946985
DO - 10.1063/1.4946985
M3 - Conference contribution
AN - SCOPUS:84984555031
T3 - AIP Conference Proceedings
BT - International Symposium on Current Progress in Mathematics and Sciences 2015, ISCPMS 2015
A2 - Mart, Terry
A2 - Triyono, Djoko
PB - American Institute of Physics Inc.
Y2 - 3 November 2015 through 4 November 2015
ER -