A Dynamic Workflow of Well Health Issue Prediction - Gas Leakage

Due to the corrosive nature of sour natural gas, productions through tubing and casing are susceptible to corrosion, resulting in gas leaking. This issue causes massive production loss. Subsequently, well health monitoring and early detection of existing and developing gas leakage are essential for profitable gas production. Dynamic material balance technique estimates gas initial in place (GIIP) using wellhead or bottom hole pressures and gas rates data at flowing conditions during the production. This method is commonly utilized for estimating GIIP but does not apply to predict gas leakage issues. This work aims to add a leak factor term by modifying the dynamic material balance equation and build a mathematical platform to detect and validate the problem by applying the modified equation. The new platform produces expected well behaviour using the revised equation and curve-fitting tool in MATLAB and then compares with the actual behaviour and detect gas leakage. The deviation from the expected and actual behaviour determines the issue. Each component of the model is validated using know values. After that, the total system is tested with known leakage data. Finally, the platform is applied in the active gas well, and the leak detection of the platform is reasonably well. The new workflow can notify the production engineers so they can take corrective measures about the issue.