Synteqs (SEQUENT)

Problem

Field engineers were navigating raw historian data well by well, without a shared KPI framework or a way to compare current behaviour against history at scale. Management saw monthly PDFs. The layer between continuous sensor streams from wells, pumps, and equipment and an operational decision was missing — anomalies surfaced after they had already cost production.

Approach

Built that missing layer as a thin analytics platform on top of the historian. A SAX engine converts each well's time series into symbolic representations, so patterns and anomalies can be matched across thousands of wells at once rather than read one trend at a time. On top of that sit reservoir-connectivity analysis, field-wide surveillance, run-life analysis, and real-time alerting — with pipelines normalised across plants and KPIs defined jointly by engineering and finance, so field and exec dashboards read from a single source of truth. The stack integrates with industrial-data and edge partners (Canary Labs historian data, ASRock industrial compute, Rajant wireless mesh) for collection across remote sites.

Outcome

3+ years serving Oman's O&G sector across oil & gas, geothermal, and water-well operations. Field engineers and management work off the same numbers, and anomalies are caught from continuous monitoring instead of monthly reports — SEQUENT's SAX engine is built for field-wide surveillance at scale.