A Permeability Predictive Model Based On Hydraulic Flow Unit for One of Iranian Carbonate Tight Gas Reservoir

Abstract

Abstract Carbonate reservoirs show challenges to engineers and geologists to characterize because of their tendency to be tight and generally heterogeneous due to depositional and Diagenetic processes. The value of permeability is very valuable in dynamic reservoir modeling and simulation. Since permeability measurements during coring are very expensive and hard to be achieved, permeability predictive models are very desirable. Among the various quantitative rock- typing techniques presented in the literature, the Hydraulic Flow Unit method (RQI/FZI) is more widely used. ‘D’ is a main carbonate formation in one of the giant gas reservoir in Iran. In this study, available routine core and wireline log data from four wells in this formation are assembled to develop Permeability Predictive Model based on Hydraulic Flow Unit. For this purpose, first whole core data were used to characterize ‘D’ formation by several discrete rock type (DRT) with Hydraulic flow unit concept. Correlation accuracy of each discrete rock type was very good (R2>0.9). It is obvious that permeability can be accurately predicted from porosity if rock type is known. Eight different wireline log data were used to develop a permeability predictive model. For this, the whole log data for all wells were individually interpreted and normalized. After that, the values of the normalized logs were extracted at the exactly core plugs depths for each DRT. A convenient multivariate regression analysis was then performed to develop an explicit mathematical model for predicting permeability in uncored intervals and uncored wells. After some mathematical manipulation, the model was ready to use. For testing the accuracy and reliability of this predictive model, the core data of one well which exists in the same formation was used. Results show that the permeability of predictive model matched well with the tested cored data in ‘D’ formation.