Abstract: Seismic records and sonic log data can all reflect acoustic property of formation.According to seismic wave dynamic mechanics,the reasonable nonlinear mapping relationship between seismic records and log data was established.The model of log data was constructed by using seismic records,on the bases of BP artificial neural network theory.The input layer of BP network is composed of autoregressive coefficient,fractal dimension,maximum Lyapunov index and mutation parameter.The acoustic wave velocity and density of the formation being drilled can be acquired with the log data model,and the elastic property and strength can also be estimated.Based on the nonlinear function curve simulation method,the safe mud weight range model for predicting borehole stability was established and successfully verified in YT101 Well.The prediction model was adapted to predict borehole stability of pre-drilling formation by using the log data of drilled part for the first wild cat well.

Key words: borehole stability, mud weight range, seismic record, drilling prediction, neural network

摘要： 根据地震波动力学,建立了地震记录和测井数据间的合理的非线性映射关系,通过获取地震记录的自回归系数、分形维数、最大Lyapunov指数和突变参数,得到了声波时差和地层密度测井曲线,建立了地层弹性参数、强度参数的获取方法.在利用非线性函数曲线拟合预测钻前井壁稳定模型的基础上,提出了利用地震记录钻前预测维持井壁稳定的安全泥浆密度窗口理论与方法,克服了层速度井壁稳定性预测精度低且不能预测薄夹层的缺陷.该方法主要解决以第一口探井二开有测井数据为前提,预测二开下部待钻地层的井壁稳定性.

关键词: 井壁稳定性, 安全泥浆密度窗口, 地震记录, 钻前预测, 神经网络