عنوان مقاله [English]
There is a high investment risk of executing EOR (Enhanced Oil Recovery) projects, due to reservoir-geology uncertainties and high cost of implementation. Hence, pilot scale EOR, in hydrocarbon field, is implemented. Moreover, selection of the pilot area, in the hydrocarbon field, is one of the key factors, since the results of the pilot implementation will be extended to the entire field.
In this study, reservoir simulation is applied to determine the three-dimensional reservoir quality maps of recovery factor. Subsequently, hydrocarbon field will be segmented into pilot candidate areas. Afterwards, the pilot candidate areas based on its recovery factor array, are optimally clustered using hybrid hierarchical k-means clustering method. The silhouette index is utilized to obtain the number of clusters. The dominant cluster is the one with the highest number of pilot candidate areas according to clustering method. Subsequently, the proximity of each pilot candidate area to the center of dominant cluster could be used as one of the pilot area selection criteria. Moreover, Operational and economic criteria are also involved in choosing a pilot area. Finally, TOPSIS (Technique for Order Preferences by Similarity to Ideal) as multi-criteria decision-making methods are applied to calculate the pilot opportunity index in each candidate area. The pilot candidate areas could be prioritized based on the value of this index and the first priority area may be selected for pilot implementation. Ultimately, the whole methodology is carried out for a real hydrocarbon field.