Author(s)

Mazen Kanj and Jean-Claude Roegiers

Abstract

Perforating is probably the most important of all completion functions in cased holes. The process involves many human/equipment constraints and its effectiveness is influenced by numerous system environment factors. A methodology capable of resolving the difficulties associated with the less optimal historical methods in perforating is a hybrid intelligent system integrating a fuzzy expert-system and an artificial neural-network. Both Ex- pert System and Neural Network technologies have developed to the point that the advantages of each can be combined into more powerful (Hybrid) systems. The goal of this paper is to demonstrate the practicality of making available such a system. The system is aimed at creating an improved perfo- ration design/completion methodology, identifying and treating perforations' damage, and forecasting and projecting actual

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