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This study is an application of artificial intelligence in the form of an expert system that consists of a knowledge <br /> <br /> base and inference engine to select an optimum gas well reactivation method to maintain base production decline of <br /> <br /> the X and Y Fiel...

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Bibliographic Details
Main Author: IRFAN (NIM : 12214024), RAFI
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/30115
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:This study is an application of artificial intelligence in the form of an expert system that consists of a knowledge <br /> <br /> base and inference engine to select an optimum gas well reactivation method to maintain base production decline of <br /> <br /> the X and Y Field in East Kalimantan, Indonesia. The expert system considers various surface and subsurface <br /> <br /> properties and recommends a reactivation method to anticipate liquid loading in the gas wells, while the knowledge <br /> <br /> base used in the expert system itself is derived from theoretical and practical field knowledge. <br /> <br /> The judgment used as the knowledge base for the expert system has been implemented in the X and Y Field which <br /> <br /> has entered its mature state and is experiencing production decline as a result of liquid loading occurring in gas <br /> <br /> wells. The implementation of the reactivation methods on the gas wells yielded positive results, with an increase in <br /> <br /> number of active wells and prolonged production lifetime. <br /> <br /> It is concluded that an expert system can be used to help maintain the base production of the X and Y Field by <br /> <br /> selecting the most compatible well reactivation method. The troubleshooting and decision making in oil and gas <br /> <br /> engineering can be done as long as the available data and knowledge base to create the expert system is sufficient.