Electrofacies Determination of the Asmari Reservoir using Neural Net SOM Method In Qaleh Nar Oil Field

Electrofacies determination of the reservoir plays an important role in the petrophysical evaluation of reservoir zones to optimize production and development of oil fields. The process is based on data clustering that all unique petrophysical set are put in one group to separate from other groups. The present study was done in Asmari Formation, Ghaleh Nar oil field. The primary electrofacies model determined using different clustering methods such as SOM, MRGC, and DYNCLUST in several drilled wells. In the next step, they correlated with fluid units of porosity and permeability of core plot. Of these methods, SOM indicates more correlation and so it was selected to data clustering. According to Gamma and porosity plots, electrofacies were generated and developed to the whole of the field. This is resulted to a model with the potential of separation parts of the reservoir. The model showed that some parts of the reservoir especial zone 1 and zone 3 can be considered as more suitable reservoir quality than other parts. Zone 4 shows normal reservoir quality but two other zones are not in suitable reservoir condition.