A workflow-based approach was implemented to improve the efficiency of well-test validation processes and to enhance the reliability of well models. This approach is based on automated validation and management-by-exception rules in order to highlight problematic tests and to execute an engineering validation process for approving or rejecting well-test results.
The well-test validation process is dynamically linked with the ADNOC corporate database to fetch the well-test results automatically in real time. The first-step validation is an automated process that compares well test data against user-defined surface parameters criteria and validates the calculated subsurface parameters. Next, engineering validations of problematic test results are performed to analyze parameter trend plots and to adjust outflow model parameters or subsurface parameters for acceptable well tests. Additionally, a repository of calibrated well models is available for asset utilization.
The well-test validation process was implemented throughout a large asset with multiple fields encompassing different lift types, including natural flow, gas lift and ESP. Automatic validation and in-built management-by-exception methodology reduced the requirement for engineering analysis of well tests by 70%, in an asset which validates more than 700 well tests per month. The most significant result is the reliability of the calibrated well models in the implemented integrated asset operations model (IAOM) to support and improve scenario predictions for the business objectives such as field-capacity test predictions and gas-lift optimization. The results of field-capacity tests achieved 98.8% of the targeted production rate for a particular zone.
The holistic two-step well-test validation process allowed the identification of actual failed well tests in achieving an optimized well testing KPI and focused well test planning. This engineering validation approach enhances the skills of the engineer thereby, optimizing available human resources.
The new management-by-exception approach forms the backbone of all other workflows contained in the IAOM, and has helped assets track well performance over time.