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Optimizing the location of the gas injection well during gas assisted gravity drainage in a fractured carbonate reservoir using artificial intelligence

机译:使用人工智能优化裂缝碳酸盐岩储层中气体辅助重力驱替过程中的注气井位置

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摘要

Gas assisted gravity drainage (GAGD) is a novel subdivision of gas injection method. In this method the injection wells are located in the upper bed of the oil zone, and the production wells are drilled at the bottom bed of the oil zone. Reservoir simulation is among the decision tools for investigating production rate and selecting the best scenarios for developing the oil and gas fields. Selecting the location of the injection wells for reaching the optimized pressure and production rate is one of the most significant challenges during the injection process. Recent experiences have shown that artificial intelligence (AI) is a reliable solution for taking the mentioned decision appropriately and in a least possible time. This study is attributed to the investigation of applying the artificial neural network (ANN) as an artificial intelligence method and a potent predictor for choosing the most proper location for injection in a GAGD process in a fractured carbonate reservoir. The results of this investigation clearly show the efficiency of the ANN as a powerful tool for optimizing the location of the injection wells in a GAGD process. The comparison between the results of ANN and black oil simulator indicated that the predictions obtained from the ANN is highly reliable. In fact the production flow rate and pressure can be obtained in every possible location of the injection well.
机译:气体辅助重力排水(GAGD)是气体注入方法的一个新细分。在这种方法中,注入井位于油区的上层,而生产井则在油区的下层进行钻探。储层模拟是用于研究生产率并选择开发油气田的最佳方案的决策工具之一。选择注入井的位置以达到最佳压力和生产率是注入过程中最重大的挑战之一。最近的经验表明,人工智能(AI)是一种可靠的解决方案,可以在最短的时间内做出适当的决定。这项研究归因于对将人工神经网络(ANN)作为一种人工智能方法的应用以及在裂缝性碳酸盐岩储层GAGD过程中选择最合适的注入位置的有效预测器的研究。这项调查的结果清楚地表明了人工神经网络作为在GAGD工艺中优化注入井位置的强大工具的效率。 ANN和黑油模拟器的结果之间的比较表明,从ANN获得的预测是高度可靠的。实际上,可以在注入井的每个可能位置获得生产流速和压力。

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