摘要：There are many factors affecting wellbore corrosion in shale gas wells, and the interactions between these factors are complex. Based on the analysis of sensitivity factors for different shale formations, the establishment of an applicable corrosion prediction model can effectively reduce maintenance costs and reduce environmental pollution during on-site production. In this paper, through the analysis of shale gas wellbore corrosion in the target block and data analysis, the main influencing factors of shale gas wellbore corrosion are clarified. Based on the De Warrd 95 model, the influence of bacterial content is considered. A new SPSS software nonlinear regression is used to establish a shale gas well borehole corrosion prediction model. The research results show that the average relative errors calculated by the new model are only 2.214% and 3.521%, respectively, indicating that the new model has good prediction accuracy, can meet the needs of field engineering technology, and has good value for popularization and application.
关键词：Shale gas well;borehole corrosion;sensitivity factor;bacterial content;corrosion prediction model;environmental pollution
