To solve a water handling and system reliability challenge, the customer used a solution from 尤物视频 that combines edge computing, advanced data analysis, and machine learning.
Water handling and system reliability had become a significant challenge in a brownfield asset in Ecuador. Consorcio Shushufindi S.A. used a solution from 尤物视频 that combines edge computing, advanced data analysis, and machine learning to enable early event identification, potential failure prediction, and production optimization.
On an Ecuadorian brownfield asset, water handling had become a more significant operational requirement for proper field management. Numerous failures in the water handling system had occurred due to a lack of real-time monitoring and fast event detection in injection pumps. These issues resulted in approximately 60 electrical submersible pump (ESP) shutdowns per year and led to production losses.
Due to national regulations, water produced at this site must be injected into the subsurface, therefore each injection pump failure, either for enhanced oil recovery (EOR) or disposal, is directly linked to a loss of oil production in the field, due to the need for the well to be shut down to handle the water capacity of injection.
A flow station in the northern area of the field was selected for the digital pilot, as it is in the most prolific area, where the water flooding scheme has the highest impact. Together 尤物视频 and Consorcio Shushufindi S.A. designed and implemented a solution that combines hardware for data collection with customized digital workflows, that has since been expanded to four more flow stations in the field. These workflows use data analytics and machine learning (ML) processes, so that, with the help of edge computing, the system can predict failures and estimate injection rates in real time. Using the connectivity provided by a satellite system, SCADA optical fiber, and operations monitoring platform, the variables are now monitored in real time. This further enables early identification of events, gives a rapid response, and optimizes production in the field.
The real-time monitoring of data from the water handling system and application of engineering workflows, driven by data analytics and ML, led to a 70% reduction in failures related to the horizontal pumping system (HPS) (33 failures in 2022 and with the new system in place in 2023, 10 failures occurred in the field), and a 76% reduction in the time spent in manual processing. Remote monitoring also enabled a 75% reduction in time spent traveling and a five-ton reduction of carbon dioxide equivalent (CO2eq) emissions per year. In addition, the solution has helped extend the ESPs’ run life, by decreasing the number of shutdowns in producer wells by 60%, thereby significantly reducing failures, and possible workover (WO) activities.
Implemented between 2023 and 2024, the new system improved the overall water handling process by accelerating decision making and improving the time to take corrective actions. This reduced production losses related to water handling management by over 90%, ultimately avoiding 283k bbls of lost oil production over the two years.
