An operator leveraged high-performance edge and cloud computing to achieve a fully autonomous chemical injection system and increased electric submersible pump (ESP) run lives more than threefold.
An operator in Ecuador has 148 wells that use ESPs for artificial lift. Corrosion and scale issues were causing an annual ESP failure rate of 20%–30%. Although the wells were chemically treated to protect against these issues, monitoring the chemical performance was a manual process. Field personnel drove to each well pad to check chemical pumping rates daily, collect produced fluid samples monthly, and retrieve corrosion and scale coupons every 60–90 days. Samples and data were subsequently sent to a laboratory for analysis of treatment effectiveness.
To implement any recommendations for modifying the chemical injection plan, engineers had to return to the well pad and manually adjust the injection pump. The delay between data acquisition and remedial action could be as much as 2–3 months. Because well conditions are very dynamic, the time lag meant that chemical injection decisions were based on data that was usually out of date, and wells were overtreated or undertreated more than 40% of the time. The results were significant unplanned workover costs and loss of production revenue.
Schlumberger recommended its DELFI Production Chemicals application, which was implemented on two wells in a series of steps.
The new system has been in place for 18 months, and ESPs that were previously failing every 6 months on average continue operating flawlessly. Compliance between actual and target injection rates has increased from 60% to 99%, ensuring continuous optimal treatment, with chemical injection adjusted about 275 times per day on average.
The time from detecting a risk to performing the relevant adjustment has decreased by 99%. Monitoring workflows that were typically performed manually on a monthly basis now run every minute, enabling quick detection of system changes and fully autonomous chemical optimization. The real-time models for virtual flow metering and scale prediction are periodically validated against manual methods and have produced results that agree within 3%.
Currently the solution is deployed on two wells, but with 20%–30% of ESPs in this field failing annually because of issues related to corrosion and scale, the operator is planning deployment on additional high‑risk wells as well as on new ones. The goal is to realize substantial reductions in opex, workover costs, and production losses.
Field trips are only required if the system detects a mechanical issue, decreasing vehicle emissions by as much as 90% and reducing the overall carbon footprint. Eliminating multiple trips to the wellsite also significantly lowers HSE risk. Potentially harmful events, such as chemical leaks, are detected in real time before secondary containment is breached, further reducing environmental impact.
Monitor at 1-minute frequency to optimize ESP corrosion protection and run-life extension.
Harness the power of edge computing and data analytics with our open, secure, and scalable platform.
Overcome fluid flow challenges and optimize production.
Optimize well performance through comprehensive modeling of completions and artificial lift systems.
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