Abstract
Information is crucial for effective scale management, and it is often the case that scaling events could have been avoided if operations were aware of the evolving risk in real time. Scale management requires an understanding of the produced fluids and the scale threat they create in different parts of the production system as temperatures, pressures and fluid rates change. It requires the timely deployment of preventative and or remedial barriers and appropriate monitoring to ensure these barriers are maintained.
Understanding the parameters that have an impact on the scale risk and the monitoring required to ensure barrier health can be an arduous, manually intensive task, relying on the retrieval and review of source data from multiple locations. However, gaps in this data can lead to an incomplete understanding of the scale risk and/or the barrier health which could result in unexpected scaling events requiring costly intervention work and production deferrals.
This paper describes the suite of cloud based ‘digital twin’ tools that bp has developed and is integrating into its operations, providing on-line, real-time calculation of the scale risk and the health of the barrier deployed to manage the risk on a well-by-well basis. The paper presents field case studies where the suite of tools, integrated into a dashboard, have been implemented. The first, a field that has previously experienced a scaling event after changes in well operating conditions, describes how on-line scale prediction coupled to water chemistry and environmental scanning electron microscopy (ESEM) analysis now provides the operation with live updates on the risk and health of the deployed barriers supporting the timely planning or suspension of treatments.
Other case studies describe the integration of the digital dashboard to specifically optimise wash water injection rates to manage halite in an asset with produced water handling constraints and the use of a squeeze life rate tracker to enhance treatment scheduling. This case describes how the adoption of digital tools allows rapid decision making and minimising over treatment of wash water injection and the impact this has on production.
