Team Decision View
Each team sees their own budget, resource allocation panel, and event feed. Decisions are captured per round and feed directly into the scoring engine.
Serious Game · Active Development

A browser-based applied game that puts teams inside a live pipeline operations crisis — forcing real decisions under time pressure, with every choice tracked, scored, and debriefed.
What it is
PetroLogic is a facilitator-led applied game for operations and crisis management training. Participants are split into competing teams and placed inside a simulated pipeline management scenario. Each round, a new operational event fires — a leak, a budget overrun, a supply disruption — and teams must allocate limited resources and make go/no-go calls.
The facilitator controls pacing from a live projector view that shows all teams' positions simultaneously. When all rounds are complete, the debrief view unlocks — surfacing individual team curves, cumulative scores, and a ranked comparison to anchor the post-game discussion.
Features
Each team sees their own budget, resource allocation panel, and event feed. Decisions are captured per round and feed directly into the scoring engine.
A distraction-free broadcast panel designed for wall projection — shows all teams' live standings, the current event, and round progress at a glance.
Up to five sequential rounds, each introducing a new event. The engine tracks budget deltas, calculates cumulative scores, and preserves full round history.
Post-game debrief view surfaces per-team performance curves, round-by-round breakdowns, and a comparative ranking table to drive structured reflection.
Full English / Arabic toggle — including RTL layout support and Arabic-safe typography — so the simulation runs natively for both language audiences.
System-aware theme detection with a manual override. The dark theme is optimized for projector brightness; the light theme for daytime workshop settings.
04Tech stack
05About
Fahmy Hassan
Founder & Systems Architect
BEENIAN Labs combines deep production experience in reliable, high-throughput systems with active AI research — bringing graduate-level machine learning expertise from CU Boulder directly into client engagements.
Our work is anchored in practical rigor: systems that are explainable, durable, and maintainable. We transfer that depth to client teams through mentorship and knowledge-sharing, because software that outlasts the engagement requires people who understand it.
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Domain Expert
AppliedGame is in active development. Reach out to discuss facilitation, customization, or partnership.
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