Abstract Due to the importance of formation pore pressure detection, different methods have been established for its estimation. One of these methods is the d-exponent method which is used widely in petroleum industry due to its rapidity and cheapness. In this study we firstly estimate formation pore pressure using the d-exp method by the traditional formula based procedure, then an adaptive network has been applied based on fuzzy interface system (ANFIS) to predict the d-exponent amounts and formation pore pressure in an Iranian oil field. Finally the reliability of resulted network values has been checked by comparing to the traditional methods values. In this network the variables include N (rpm), Average ROP and Bit diameter as the chosen inputs.

中文翻译：

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神经模糊模拟与伊朗南部油田异常压力区检测常用方法的优势

摘要 由于地层孔隙压力检测的重要性，已经建立了不同的估计方法。其中一种方法是 d 指数法，由于其快速和廉价而广泛用于石油工业。在这项研究中，我们首先通过传统的基于公式的程序使用 d-exp 方法估计地层孔隙压力，然后应用基于模糊接口系统 (ANFIS) 的自适应网络来预测 d 指数量和地层孔隙压力。伊朗油田。最后通过与传统方法值的比较来检验所得网络值的可靠性。在这个网络中，变量包括 N (rpm)、平均 ROP 和钻头直径作为选择的输入。