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3篇 您的检索式:作者名="ARTUN Emre"
    题名 作者 年代 出处 被引量
1基于模糊推理的致密砂岩气储集层重复压裂井选择方法显示文摘建立了一种基于人工智能的致密砂岩气储集层重复压裂井筛选方法,并进行了算例分析。该方法以模糊逻辑为基础,通过语言模糊性的数学表示来处理语言的不精确性和主观性,是1个基于模糊集理论、模糊规则和模糊推理的计算系统。用5个指数分别表征与重复压裂井选择问题相关的水力裂缝质量、储集层特征、初始条件、操作参数、产量,每个指数又包含3个相关参数。将每个指数/参数的值划分为低、中、高3个类别,针对每个指数/参数的每个类别定义梯形隶属函数,并定义所有相关规则。先将某个指数的相关参数输入到基于规则的模糊推理系统中,输出该指数的值,再另建1个模糊推理系统,将储集层指数、操作指数、初始条件指数和产量指数作为输入参数,重复压裂潜力指数作为输出参数,从而筛选重复压裂井。利用已发表文献中的数据验证了该方法的有效性。ARTUN Emre KULGA Burak 2020石油勘探与开发2020,47,2:7
2A parametric study on the benefits of drilling horizontal and multilateral wells in coalbed methane reservoirs 显示文摘Maricic Nikola Mohaghegh Shahab D Artun Emre 2008SPE Reservoir Evalution & Engi- neering2008,11,6:1
3Modeling, analysis, and screening of cyclic pressure pulsing with nitrogen in hydraulically fractured wells显示文摘Cyclic pressure pulsing with nitrogen is studied for hydraulically fractured wells in depleted reservoirs.A compositional simulation model is constructed to represent the hydraulic fractures through local-grid refinement.The process is analyzed from both operational and reservoir/hydraulic-fracture perspectives.Key sensitivity parameters for the operational component are chosen as the injection rate,lengths of injection and soaking periods and the economic rate limit to shut-in the well.For the reservoir/hydraulic fracturing components,reservoir permeability,hydraulic fracture permeability,effective thickness and half-length are used.These parameters are varied at five levels.A full-factorial experimental design is utilized to run 1250 cases.The study shows that within the ranges studied,the gas-injection process is applied successfully for a 20-year project period with net present values based on the incremental recoveries greater than zero.It is observed that the cycle rate limit,injection and soaking periods must be optimized to maximize the efficiency.The simulation results are used to develop a neural network based proxy model that can be used as a screening tool for the process.The proxy model is validated with blind-cases with a correlation coefficient of 0.96.Emre Artun Ali Aghazadeh Khoei Kutay Kose 2016Petroleum Science2016,13,3:0
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