Smarter Operations.Deeper Research.
Purpose-built intelligence for amine-based carbon capture and gas sweetening — one platform for operational insight, digital twins and applied research.
Industrial case study · amine gas treating unit
Optimize, Decarbonize and Proactively Maintain Your Plant
Savings from fewer shutdowns and lower maintenance come on top of this, but are not yet quantified.
Digital twin tested on 13 days of one-minute data from an industrial MDEA unit, at constant treated-gas quality. Steam, CO₂ and value figures are modelled steady-state potential, awaiting a plant trial.
From process control to process intelligence
Make Your Plant Operations Smarter with Continuous Intelligence
QemOPS™ adds an intelligence layer on top of the systems you already run. It turns process data into optimized, reliable operations for amine-based carbon capture and gas treating — improving energy efficiency, reducing CO₂ emissions, and increasing operational reliability.
- Field sensors
- PLC / DCS
- Historian
- Modeling & simulation
- Custom tool development
- Analysis & diagnosis
- Optimization & research
- Reports & recommendations
- Decision support
The platform
16 tools. One calibrated plant model.
Every tool reads the same physics model of a real amine train, so their answers agree with each other.
And many more on request. New tools are built on the same plant model to meet each client’s needs.
Make more research happen in your plant
Applied research
Research that turnsoperational questions into decisions
QemOPS combines plant data, first-principles models and applied research to turn complex process questions into actionable outcomes.
Operational question
A real problem from the unit: rising reboiler duty, foaming, an unexplained drop in CO₂ capture.
Plant & simulation data
Historian data lined up against the hybrid digital twin, so measured and modelled behaviour can be compared.
Research-grade analysis
Fault diagnosis, sensitivity studies and first-principles models, documented to publication standard.
Decision / improvement
A clear recommendation: what to change, what it is worth and how confident we are.
01
Operational question
A real problem from the unit: rising reboiler duty, foaming, an unexplained drop in CO₂ capture.
02
Plant & simulation data
Historian data lined up against the hybrid digital twin, so measured and modelled behaviour can be compared.
03
Research-grade analysis
Fault diagnosis, sensitivity studies and first-principles models, documented to publication standard.
04
Decision / improvement
A clear recommendation: what to change, what it is worth and how confident we are.
Current focus
- Fault diagnosis and root cause in amine units
- Energy and solvent-loss reduction with the hybrid digital twin
- Model validation against plant historian data
Have a process question worth researching?
Bring a real operational problem. We scope it, model it and report what the data supports.
Bring us a plant question.
Try the demo on a real amine train, or consult an engineer about your own unit, a custom tool or a research challenge.