Abstract

The aim of this study is to predict permeability from well log data for a heterogeneous carbonate reservoir in the upper part of the Sarvak Formation (mid-Cenomanian to early Turonian) in an Iranian oil field. The permeability is a crucial parameter for reservoir modeling which is difficult to measure directly. Direct measurements of permeability are obtained form core plugs, if available. Continuous permeability values, however, need to be predcited indirectly from independent data. Three different methods have been tested for estimating the permeability:

  1. permeability from effective porosity

  2. multilinear regression, and

  3. fuzzy logic. The two latter methods utilize raw well logs (gamma ray, density, neutron and sonic) to predict permeability. Core plug measurements have been used to validate the predictions.

Results from the study show that fuzzy logic yields better results than the two other methods. The multilinear regression is unable to represent the dynamic range measured on the core plugs (overestimated in low values and underestimated in high value). The permeability predicted from the effective porosity model is more or less similar to multilinear regression model, but relatively narrower. This is however to be expected as these models both indicates narrower ranges than fuzzy logic, because they are trying to fit with average values.

Introduction

Permeability controls how fluid can migrate through the reservoir. The permeability is a key parameter in reservoir development and management because it controls the production rate [1]. In general the permeability increases with increasing porosity, increasing grain size and improved sorting [2,3]. In carbonates connectivity between pores is the main control for the permeability. Heterogeneity occurs in carbonate reservoirs due to variation in depositional environments and subsequent diagenetic processes. Depositional environment is important for creating primary porosity. Generally high energy deposits gives high porosity and permeability, while low energy deposits gives low permeable intervals. Often low energy deposits may have high porosity, but if the pore throat size are too small, permeability may also be low. Diagenesis both construct and destruct porosity. For example, cementation decreases porosity and permeability, but early cementation may prevent compaction and thereby preserve primary porosity, while dissolution mainly increases porosity except in case like some stylolites which may form barriers. The permeability prediction is a challenge in formation evaluation and reservoir modeling because of difficulty to measure it directly. Knowledge of permeability is important in building 3D reservoir models and understanding production of oil and gas and finally development strategy.

The best method for direct permeability measurement is obtained from core plug analysis. It is measured in both vertical and horizontal directions, commonly every thirty centimeters. Coring is very expensive and time consuming limiting such measurements. Another problem with core plug measurements is the scale. Small scale heterogeneities that might not affect flow on a reservoir scale are measured, and these need to be upscaled.

An alternative to estimate the permeability is from electrical logs. The challenge in permeability prediction is that permeability is related more to the pore throat size rather than pore size, which is difficult to measure by logging tools. Determining permeability from well logs is also complicated by the problem of scale, well logs having a vertical resolution of typically 1/2 metre compared to the 5 cm diametre of core plugs.

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