Perpustakaan Digital ITB

Estimation of permeability values in uncored wells but logged intervals is a worldwide challenge usually encountered in all reservoirs. Permeability estimation is a major risk task in petroleum engineering, as it is a necessity for reservoir description and performance (fluid flow). Permeability obtained from core measurement is usually limited due to the high cost of getting core samples and toilsome analysis required, scoring only being done for certain good sections and well logs are used for predicting permeability in sections where core permeability are unavailable. This makes core derived permeability cost effective and feasible. For this work, statistical and graphical measurement was considered for estimating permeability. Statistical methods employing regression model and flow zone indicator (FZI) were utilized in establishing a mathematical correlation between core data and well logs using equations obtained from plotted graphs. FZImean values obtained from the log-log plot of RQI against ?z, was used to classify the well into different hydraulic flow units (HFUs). Statistical methods were tested using a sample size of over 960 measured permeability data gotten from five wells in an oil field, located in the Niger Delta region of Nigeria. Results obtained from classifying data into hydraulic flow unit using FZI showed better correlation R2 compared to the regression model.