A New Automated Workflow for Well Monitoring Using Permanent Pressure and Rate Measurements

Abstract

Pressure and rate measurements are essential for the well and reservoir surveillance workflows used in petroleum, geological carbon storage, and geothermal industries. Such well monitoring data are now analyzed in manual, semi-automated and automated modes or in a combination. Automated workflows are widely adopted by the industry nowadays, enabling most efficient knowledge extraction from the data both already accumulated and being received in real-time. The paper describes a new integrated workflow for automated well monitoring using pressure and rate measurements obtained with permanent gauges and flowmeters. The workflow is based on time-lapse Pressure Transient Analysis (PTA) and integrates the following components: virtual flow-metering, transient identification, feature extraction and pattern recognition in transient pressure responses, and assessment of well performance based on PTA-metrics. The methodology behind the workflow combines different physics-informed and data-driven methods described in the paper. Application of the workflow is illustrated on a field case example from the Norwegian Continental Shelf, where changes in the well, reservoir, and well-reservoir connection performances are automatically monitored during its three-year long injection history. Reliability and accuracy of the automated monitoring results are verified via comparison with the conventional model-based time-lapse PTA. The automated workflow may be used for a variety of use cases. Being applied to the well history, the workflow enables establishing a historical performance profile and identifying trends and issues in the past. In everyday well monitoring, it may be employed to detect well performance issues early and indicate their possible reasons. Further, it may provide valuable input for in-depth model-based analysis and other reservoir engineering studies. Using the workflow unlocks knowledge hidden in abundant well-monitoring datasets available at operating companies and empowers reservoir engineers to instantly assess well and reservoir performances, understand their interconnectivity, and make prompt, informed decisions.