Permeability Evaluation of Carbonate Reservoir Using Hydraulic Unit Analyse: Case Study from Middle East Region

It is well known that permeability is an important parameter in reservoir description and characterization, where it is a key element in fluid dynamic, and hence reservoir modelling. Thus, accurate permeability prediction of uncored wells is required, however it is still a challenge mission in carbonate reservoir due to high heterogeneity.

In this work, we will use two methods to predict the permeability by utilizing available core data. First method, which has been used widely, relays on dividing the reservoir into layers based on geological description, such as the nature of the rock and the depositional environment. Then, permeability-porosity correlation was initiated of each layer. However, the correlations were poor due to considerable variation in petrophysical properties within each layer. The other method requires subdividing the reservoir into hydraulic unit using flow zone indicator and reservoir quality index. After, the data were trained using machine learning to predict best correlation that can be utilized to estimate permeability of each hydraulic unit.

Permeability prediction in the aid of hydraulic units resulted in more reliable estimation. However, microporous hydraulic unit may still produce less efficient permeability prediction. This was examined for various wells located in different places along the reservoirs.