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When the reservoir pressure drops after being produced, the gas recycling method is widely used in the petroleum industry to maintain the pressure and also enhance the recovery factor. With many implementations of gas recycling, the activities to predict the outcome of the process is also increasing...
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id-itb.:295692018-05-15T14:34:46Z#TITLE_ALTERNATIVE# ANINDITO (NIM : 12212062), NAUFAL Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/29569 When the reservoir pressure drops after being produced, the gas recycling method is widely used in the petroleum industry to maintain the pressure and also enhance the recovery factor. With many implementations of gas recycling, the activities to predict the outcome of the process is also increasingly important so that the results obtained will be accurate, despite the limited data, time, and energy. Material Balance Analysis and reservoir simulation are two methods that can be used to make predictions of gas recycling process. <br /> <br /> In this study, both methods will be compared to know Material Balance Analysis’s accuracy relative to reservoir simulation. The study was conducted in the X field which is located in the Natuna Sea. The X field itself has three productive zones: two oil zones and one gas zone. Gas recycling is done on the main oil zone (Asso_1). Material Balance Analysis and reservoir simulation model is updated with recent production data to predict the outcome of the gas recycling process from 2015 until 2028. The prediction of both models will be compared and analyzed to identify the trends. Furthermore, from the total cumulative production of oil and gas then will be determined injection fraction that produces the same level of accuracy between the two models. <br /> <br /> The results of the study showed that the Material Balance Analysis evaluation can produce a fairly accurate prediction relative to reservoir simulation, especially in the oil production. From a comparison between the cumulative total production of oil and gas, it is known that Material Balance Analysis will produce a prediction that has the most excellent level accuracy relative to the reservoir simulation when the injection fraction of 0.75. text |
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When the reservoir pressure drops after being produced, the gas recycling method is widely used in the petroleum industry to maintain the pressure and also enhance the recovery factor. With many implementations of gas recycling, the activities to predict the outcome of the process is also increasingly important so that the results obtained will be accurate, despite the limited data, time, and energy. Material Balance Analysis and reservoir simulation are two methods that can be used to make predictions of gas recycling process. <br />
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In this study, both methods will be compared to know Material Balance Analysis’s accuracy relative to reservoir simulation. The study was conducted in the X field which is located in the Natuna Sea. The X field itself has three productive zones: two oil zones and one gas zone. Gas recycling is done on the main oil zone (Asso_1). Material Balance Analysis and reservoir simulation model is updated with recent production data to predict the outcome of the gas recycling process from 2015 until 2028. The prediction of both models will be compared and analyzed to identify the trends. Furthermore, from the total cumulative production of oil and gas then will be determined injection fraction that produces the same level of accuracy between the two models. <br />
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The results of the study showed that the Material Balance Analysis evaluation can produce a fairly accurate prediction relative to reservoir simulation, especially in the oil production. From a comparison between the cumulative total production of oil and gas, it is known that Material Balance Analysis will produce a prediction that has the most excellent level accuracy relative to the reservoir simulation when the injection fraction of 0.75. |
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ANINDITO (NIM : 12212062), NAUFAL |
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ANINDITO (NIM : 12212062), NAUFAL #TITLE_ALTERNATIVE# |
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ANINDITO (NIM : 12212062), NAUFAL |
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ANINDITO (NIM : 12212062), NAUFAL |
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https://digilib.itb.ac.id/gdl/view/29569 |
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