Отправлено: 22.06.09 14:14. Заголовок: Evaluating Different Approaches of Permeability Modeling in Heterogeneous Carbonate Reservoirs

EAGE 2009 Amsterdam

Q046
Evaluating Different Approaches of Permeability Modeling in Heterogeneous Carbonate Reservoirs
F. Khoshbakht* (RIPI), M. Mohammadnia (RIPI), A.M. Bagheri (RIPI), A.A.
RahimiBahar (RIPI) & Y. Beiraghdar (RIPI)
SUMMARY
Permeability, the ability of rocks to flow hydrocarbons is directly determined in the laboratory on cores
taken from the reservoir. Due to high cost associated with coring, many empirical models, statistical
methods and intelligence techniques were suggested to establish robust relationships between permeability
and various easy to obtain and frequent data such as wireline logs. This study launched to put different
approaches of permeability modeling into practice to predict permeability in a heterogeneous carbonate
reservoir (Fahliyan formation in SW Iran) and compare results in order to determine the optimal approach
for utilizing in this formation. Considered methods divide into four groups; a) empirical models (Timur
and dual water), b) regression analysis (simple and multiple), c) clustering methods (MRGC, SOM, DC &
AHC) and d) artificial intelligence techniques (ANN, fuzzy logic and neuro-fuzzy).
This study shows that clustering techniques predict permeability in a heterogeneous carbonate better than
other examined approaches. Among four assessed clustering methods, SOM performs best and could
handle dimensionality and complexity of input data sets. Artificial intelligence techniques are average in
modeling permeability, in addition empirical equations and regression techniques are not capable for
predicting permeability in studied heterogeneous carbonate reservoir.