ARA SimQuation provides the INVIDES platform, which delivers simulation-powered digital twins for the entire energy production chain. This platform integrates modeling, HMI creation, data management, automation, and optimization functions into a single application. The solution helps energy companies maximize recovery, minimize operational costs, and improve safety across asset lifecycles.
Funding
Funding not disclosed
Founders
Product
Problem
Energy producers face high operational costs, downtime, and safety risks due to limited visibility into complex, multi‑stage processes from reservoir to refinery. Traditional simulation tools are often siloed, lack real‑time data integration, and require extensive manual setup, hindering rapid decision‑making and predictive maintenance.
Solution
INVIDES is a simulation‑powered digital‑twin platform that models the entire energy production chain, from reservoir fluid entry to hydrocarbon export. The platform combines a modeling environment, human‑machine interface (HMI) creation, data management, automation, and optimization modules within a single application. By ingesting live operational data, INVIDES enables dynamic what‑if scenarios, performance monitoring, and predictive maintenance without disrupting ongoing operations. Results are delivered through configurable dashboards and can be accessed via cloud or on‑premise deployments, supporting both short‑term operational adjustments and long‑term asset lifecycle planning.
Target Audience
The primary customers are upstream, midstream, and downstream energy operators, including oil & gas producers, power‑plant owners, and integrated asset‑management firms that require end‑to‑end simulation and optimization of their production assets.
Features
- Integrated modeling environment supporting reservoir, process, and refinery simulations with granular, physics‑based equations
- Drag‑and‑drop HMI builder for custom operator interfaces and real‑time visualizations
- Centralized data management layer that ingests live sensor streams, historical logs, and life‑cycle data for continuous model updating
- Automation engine for workflow orchestration, virtual metering, and batch scenario execution
- Multi‑objective optimization tools for recovery maximization, cost reduction, and emission minimization
- Scalable, cloud‑ready architecture with open APIs for seamless integration into existing enterprise systems
- Predictive maintenance analytics that flag equipment degradation based on simulation deviations and sensor trends
- Training and learning management module that uses the digital twin for operator skill development and safety drills