页岩气储层孔隙压力测井预测新方法

页岩气储层中常出现明显的异常高压现象,其孔隙压力会在短距离内大幅上升。若不能及时准确预测这些异常高压值,可能导致井涌、井喷等钻井事故,不仅会给钻井施工造成重大损失,还严重影响储层评价工作。然而,现有的方法却很难准确预测页岩气储层中的异常孔隙压力值。结合页岩气岩心实验数据,在充分考虑孔隙度、有机质含量和有效应力对声波速度影响的基础上,提出了一套基于声波速度模型的页岩气储层孔隙压力预测新方法。该方法通过使用不含气层段的纵波、横波速度关系对储层纵波速度进行含气性校正,消除了气体对异常高压现象在声波测井信息表征上的影响。此外,该方法还能预测因不平衡压实和生烃作用等多种机理引发的页岩气储层异常孔隙压力,弥补了现有传统方法只能预测由不平衡压实引起异常高压的不足。以昭通地区页岩地层S井为例进行储层孔隙压力预测,形成了基于声波速度模型的储层孔隙压力预测方法技术流程。

A new pore pressure logging prediction method in shale gas reservoirs

Obvious abnormal high-pressure phenomena often occur in shale gas reservoir; the pore pressure can increase greatly in a short distance. If the abnormal high-pressure values cannot be predicted timely and accurately, well kick, blowout and other drilling accidents will be caused, not only bringing great losses to drilling construction, but also seriously affecting the reservoir evaluation. However, the existing method is very difficult to predict the abnormal pore pressure value in shale gas reservoir. In combination with the experimental data of shale gas core, based on full consideration of the influences from porosity, organic matter content and effective stress on acoustic velocity, a new pore pressure prediction method for shale gas reservoir is proposed on a basis of acoustic velocity model. In this method, the relationship of P-wave and S-wave velocity in the gas-free horizons is used for gas-bearing correction at the P-wave velocity of reservoir, so as to eliminate the influences of gas on abnormal high pressure phenomenon in terms of acoustic logging information characterization. In addition, this method is able to predict the abnormal pore pressure of shale gas reservoir induced by multiple mechanisms such as unbalanced compaction and hydrocarbon generation function, thus overcoming the deficiency in the traditional method only able to predict the abnormal high pressure caused by unbalanced compaction. Well S in shale reservoir of Zhaotong area is taken as an example for reservoir pore pressure prediction, thus obtaining the technical flow of the reservoir pore pressure prediction method based on acoustic velocity model.