Accurate prediction of flow regime and flow profile in wellbore is among the main interests of production engineers in the quest of optimizing wellbore production and increasing reliability of downhole completion tools especially in SAGD projects. This study introduces a methodology for wellbore monitoring by detecting flow phase and flow regime. In order to develop this method, an advanced multi-phase flow injection experiment was designed and commissioned.
A flow injection setup was developed to test distributed fiber optic sensor installation under different operating conditions, including multi-phase flow (oil, brine and gas), and flow fraction scenarios. Different signal processing methods were applied to extract meaningful features and filter the noise from the raw signals. A statistical analysis was performed to assess the trend of the driven data. Then, typical SAGD models were simulated to assess the results of experimental setup for scale-up purpose and determination of local breakthrough of steam along the well.
Results showed that the Distributed Acoustic Sensing (DAS) data contains different levels of signals for each phase and flow regime. We also found that some level of uncertainties is involved in relating the flow regime and DAS information which could be resolved by improving the sensor installation procedure. In addition, the application of data-driven machine learning methods was found necessary to interpret the signal patterns. Initial results have shown that steam breakthrough along the well can be detected using real time DAS high energy/frequency signals. It can be concluded that including the DAS along with Distributed Temperature Sensing (DTS) is necessary to provide a better picture of steam conformance and SAGD wellbore monitoring. The limitations of the current experimental setup restricted further conclusions regarding the hybrid DAS and DTS application.
This paper is a part of an ongoing project to address the application of the combined DAS and DTS in SAGD projects. The ultimate goal is a downhole monitoring system to oversee the flow phase, flow regime and sand ingress in thermal application. The next phase will address the required improvements for developing a flow loop to handle high temperatures, include sand production and mimic thermal operation conditions.