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基于数据库的钻头选型系统研究

Research on Bit Selection System Based on the Database

【作者】 梁启明

【导师】 邹德永;

【作者基本信息】 中国石油大学 , 油气井工程, 2007, 硕士

【摘要】 钻头是直接破碎岩石延伸井眼的工具,根据地层特性合理的选择钻头能够显著提高机械钻速和钻头进尺,降低钻进成本。地层抗钻特性评价和钻头选型方法是两个关键步骤。总结目前地层抗钻特性评价方法,选取岩石可钻性级值和岩石研磨性作为评价标准。在现有可钻性预测模型基础上,通过室内声波时差、微钻头可钻性、密度和泥质含量测定试验,分别研究了岩性、密度、泥质含量等因素对岩石可钻性级值的影响规律,利用声波时差、密度、伽马三种测井资料分别建立了更为准确的三种岩性岩石的可钻性综合预测模型。对地层岩性、可钻性和研磨性进行分析评价,建立地层抗钻特性剖面。运用Access数据库,对已用钻头资料进行处理,计算出钻头所钻地层的抗钻强度,建立钻头类型与地层抗钻强度的相互对应关系,运用迭代的方法,根据待钻井的地层抗钻强度在钻头数据库中初选钻头,选用效益指数作为选型指标进行二次优选。用VB6.0开发钻头选型软件,可进行地层抗钻特性评价和钻头选型,方便使用。

【Abstract】 Bits are to crush the rock and stretch the well. The appropriate bit matching formation characteristics can enhance drilling speed and footage, and lower the drilling cost. So the standard of evaluating the formation drilling resistance and the method of selecting bit are both critical. According to the summary of the methods to evaluate the formation drilling resistance, the rock drillability and abrasiveness were selected to be the standards. Indoor experiments of acoustic time , micro-bit drillability, density and shale content were done. The emphasis was laid on the effects of lithology, density and shale content on the rock drillability, and these factors were introduced to found new compositive models to predict rock drillability, using acoustic logging, density logging and gamma logging. Then the formation lithology, drillability and abrasiveness were analyzed and evaluated, a profile of formation drilling resistance was erected.The Access data base was used to deal with the data of used bit, to calculate the formation drilling resistance, in order to found the corresponding relationship between the bit type and the formation. The primary selection of bits was done according to the formation drilling resistance of the planned well,using the method of iteration. Then the optimized bit was recommended according to the benefit index. A software was developed with VB6.0, which can predict the formation drilling resistance and select optimized bit according to the well logging data.

  • 【分类号】TE921.1
  • 【被引频次】1
  • 【下载频次】469
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