PDC钻头条件下随钻岩性识别方法研究

Research of lithology identification method while drilling with PDC bit.

使用PDC钻头钻井速度快、岩屑细碎，给随钻岩性识别带来较大的困难。针对这一问题。通过录井仪从现场采集到诸如机械钻速、钻压、泵压和扭矩等参数，这些参数从不同方面反映了地层的岩石性质。与岩性之间的关系密切。采用三层BP神经网络来描述录井仪采集到的参数与岩性之间的关系。用张店油田的张2104井的2500～2700m井段资料建立岩性预测模型。通过对张2104井的2000～2200m井段和张2201井的2600～2800m井段的测试表明，张2104井的砂泥岩层的预测精度为93．6％，张2201井砂泥岩层的预测精度为89．2％。其中纯砂岩和泥岩的预测精度将近100％，过渡性岩石的预测失误是产生误差的主要原因。通过分析表明，用神经网络预测PDC随钻岩性是一个比较可靠的方法。

While drilling with PDC Bit,Some problems are come out when using the methods of traditional recorder well.Lithology identification is crucial.The data collected by mud-logging equipment,for examples,ROP,WOB,torque et al.,reflects the different sides of rock's property in subsurface.The relation among them is complex and BP neural network is adopted in three layers.The section of Zhang 2104 well in Zhangdian oil field is used as predictive model and the depth is between 2500 and 2700 meters.In order to test the precision of the model,the section of Zhang 2104 well(2000-2200 m) and zhang 2201 well(2600-2800 m) are predicted.The precision predicted to Zhang 2104 is 93.6% and zhang2201 well is(89.2)%,as the pure rock is almost 100%.The error remains the identification to the rock filled with nearby 50% clay.The result presents that this method is practical.