利用非线性回归方法预测地层参数分布

Forecasting Formation Parameter Distribution by Using Non-Linear Regression Method

油藏生产数据自动拟合是一个非线性参数估计问题,需要非线性回归分析理论。非线性回归模型参数估计的常见算法有:直接搜索法、Hooke-Jeeves法、Nelder-Mead法、Gauss-Newton法、变尺度法和同伦算法等。运用改进的非线性最小二乘法对主要的油藏参数渗透率和孔隙度分布进行预测,并拟合对应的井底压力,取得了很好的效果,为利用生产数据预测地层参数提供了可行方法。

Production data of the reservoir is an estimation issue of the nonlinear parameters which is necessary to apply nonlinear regression analysis theory.The Common algorithms of Non-linear regression used to estimate model parameters include direct search method,Hooke-Jeeves method,Nelder-Mead method,Gauss-Newton method,variable metric method and homotopy algorithm,etc.The modified nonlinear least-square method is used to predict the main reservoir parameters,including the distribution of permeability and porosity,and to match the corresponding bottom-hole pressure,which acquires a satisfied result and provides a feasible method to forecast parameters by using production data.