融合地质力学和贝叶斯分析的压前套变风险预测:以川南A区龙一段页岩储层为例

Risk Prediction of Pre Fracturing Casing Deformation by Integrating Geomechanics and Bayesian Analysis:Taking the Shale Reservoir of Longyi Member in Block A of South Sichuan as an Example

川南复杂构造区地质力学环境复杂,套变频繁发生,导致水平井压裂改造困难,造成井下工程措施失效和单井产量的巨大损失,从而大大影响产量且延长减产周期。而复杂构造区地质力学因素与套变风险关系紧密,因此,需要明确局部构造内地质力学参数与套变风险之间的关系,构建相应的评价模型来精准预测套变的风险,综合利用已有的微地震监测、套管几何形态监测及多臂井径测井资料,研究了深层页岩气井套变的基本特征,并基于套管变形量和变形程度构建套变风险定量评价的因子级数,并结合已有的多级断缝系统解释资料、地应力场模拟结果及钻井资料,开展套变风险因子级数与储层地质力学参数之间的关系研究,建立了深层页岩气井套变风险智能分级判识算法,并应用于新钻井压前套变风险预警。结果表明:川南深层页岩气井基于套变的程度及其特征可将套变风险等级划分为5个级次,级次越大,套变程度越大,损伤越大;而套变的程度主要与深层储层地质力学参数紧密相关,在构造变形强(曲率>0.25 km-1)、断层倾角较大(>45°),断层走向与最大水平主应力方向的夹角较小(<30°)、两向应力差较大(>18 MPa)、应力状态为局部挤压走滑态(结构指数>1.65)的地区,易于发生三级以上的套变,套变损伤强度较大。基于套变因子级数与储层地质力学参数之间的关系数据库,利用贝叶斯分类判识算法,建立了研究区套变风险预测分析模型并成功应用于新水平井当中,预测精度在90%以上,可以进行推广应用,该方法可减少水平井段压裂前的丢段,提高水平井压裂的成功率,提升深层页岩气井的开发效果和经济效益。

The geomechanical environment in the complex structural area of southern Sichuan is complex and the casing deformation occurs frequently,which leads to the difficulty of horizontal well fracturing transformation,resulting in the failure of downhole engineering measures and the huge loss of single well production,thus greatly affecting the production and prolonging the production reduction cycle.However,the geomechanical factors in complex structural areas are closely related to the risk of casing deformation.Therefore,it is necessary to clarify the relationship between the geomechanical parameters in local structures and the risk of casing deformation,and to construct the corresponding evaluation model to accurately predict the risk of casing deformation.The basic characteristics of casing deformation in deep shale gas wells were studied by using the existing microseismic monitoring,casing geometry monitoring and multi-arm caliper logging data,and the factor series of quantitative evaluation of casing deformation risk was constructed based on the amount and degree of casing deformation.Combined with the existing multi-level fracture system interpretation data,in-situ stress field simulation results and drilling data.The relationship between casing deformation risk factor series and reservoir geomechanical parameters was studied,and the intelligent classification and identification algorithm of casing deformation risk in deep shale gas wells was established,which is applied to the early warning of casing deformation risk before new drilling pressure.The results show that the risk level of casing deformation in deep shale gas wells in southern Sichuan can be divided into five grades based on the degree and characteristics of casing deformation.The greater the grade,the greater the degree of casing deformation and the greater the damage.The degree of casing deformation is mainly closely related to the geomechanical parameters of deep reservoirs.In areas with strong tectonic deformation(curvature>0.25 km-1),large fault dip angle(>45°),small angle between fault strike and maximum horizontal principal stress direction(18 MPa),and local compressive strike-slip stress state(structure index>1.65),casing deformation of grade 3 or above is prone to occur,and the damage intensity of casing deformation is large.Based on the relational database between the casing deformation factor series and the reservoir geomechanical parameters,the Bayesian classification and identification algorithm is used to establish the casing deformation risk prediction analysis model in the study area and successfully applied to the new horizontal well.The prediction accuracy is above 90%,which can be popularized and applied.This method can reduce the loss of horizontal well section before fracturing,improve the success rate of horizontal well fracturing,and improve the development effect and economic benefits of deep shale gas wells.