A data-driven modeling approach to zonal isolation of cemented gas wells

Abstract

Gas leakage through the cemented section of a gas well, from a producing zone to other zones or to the open air, poses serious threats to safety and the environment. A number of design variables during drilling and cementing jobs may possibly contribute to such leakage. Decisions on these variables are best made during the design and well construction phase, as remedial operations after the well begins production have limited success rate. Therefore an approach that avoids the problem by ensuring robust zonal isolation during well construction jobs is more suitable. Such an approach involves decisions on a fairly large number of design variables. Building a model based on first principles to predict the effect of all of these variables on leakage is a formidable task. An alternative examined in this paper relies on using multivariate statistics to build an empirical model from available data. The model can then be used to make decisions on design variables such that leakage is avoided. The proposed approach is explained using data from 105 gas wells. The model built predicts leakage with about 75% accuracy in cross-validation tests. In addition, it ranks decision variables in the order of importance and suggests which ones need to receive more attention. The approach presented can be extended to include additional variables for which data is available.