Mode Virtual (V) — Overview¶
Design, simulate, and control a virtual drilling system using standardized interfaces. Mode Virtual (V) emphasizes closed-loop control, data semantics, and clear reporting over hardware.
Cases (2025.1)¶
- Connect through D‑WIS to the OpenLab Drilling Simulator and implement detection/response for a simulated influx (kick).
- Focus on reliable signal handling, thresholds/logic for detection, appropriate automated actions, and clear operator feedback.
- Validate against provided test cases; document assumptions, limits, and performance.
- Build a virtual drilling system model and controller that adapts to changing lithology to maximize ROP under constraints.
- Incorporate realistic constraints (e.g., slide/rotate modes, dogleg limits), virtual measurements with uncertainty, and automatic re-planning based on as-drilled surveys.
- Produce trajectory data (Minimum Curvature) and plan-vs-actual plots; log surveys and controller decisions for review.
- Reach TD with low torsional oscillations; demonstrate dysfunction detection/mitigation while meeting constraints.
- Emphasize robust control design and monitoring; present time-aligned evidence from logs and plots.
New team? Start here
Most first-time teams are successful by starting with the OpenLab Drilling Simulator and focusing on the control system and data handling, rather than building a simulator from scratch.
Tooling & Interfaces¶
- D‑WIS semantics: standardized names/metadata for setpoints and measurements. See the D‑WIS Vocabulary Index.
- OpenLab simulator: the plant used for Mode Virtual (V) scenarios. See the OpenLab website.
- Connectivity and discovery, expected signals, and example flows are described in Technical Specs.
Edge‑deployable models
- Expectation: focus your effort on generating/fine-tuning data and optimizing compact multimodal models.
- Inference‑only, offline, JSON outputs (e.g., Explain‑This‑Event or Rig‑State Textualizer).
- Small‑model, edge‑deployable focus: teams may prototype with larger cloud‑hosted models during development, but final deliverables and performance are evaluated using locally run or on‑rig small models under limited inference hardware.
- Suggested caps: ≤2 vCPU or ≤20 W GPU, ≤4–8 GB RAM (non‑LLM) and ≤8 vCPU or ≤1,150 W GPU, ≤16–64 GB RAM (LLM); ≤15 min total inference runtime. Rig compute otherwise open. All AI runs must be offline during judging; no PLC/actuator writes.
- Custom task option: teams may propose a custom offline JSON task with objective ground truth and the same interface for pre‑approval (recommended deadline: 2026‑02‑01). Approved tasks use the same AI sub‑rubric and scale to +10.
Design for discovery
On competition day, endpoints and available signals may change. Your software must discover available D‑WIS signals and adapt accordingly.
Phases & Timing¶
- Phase I — Design: monthly updates plus a design report and optional short video.
- Phase II — Implementation & testing: enhance the model and controllers; final test occurs at the end of the cycle.
Dates vary each year. See the living schedule for what’s open now.
Timeline & Milestones Upcoming Dates
What You Submit¶
- Monthly updates, Phase I design report (and optional video), and a Phase II package with data, plots, and a short presentation.
- Directional option: Minimum Curvature trajectory, plan-vs-actual plots, survey logs with acceptance flags, and controller rationale.
- Well control option: detection and control logic description, test results, and logs.
Full details and file naming live on the Deliverables page.
How You’re Judged¶
- Directional option: drilling system model realism, control scheme quality, app robustness/UX, and performance vs. objectives.
- Well control option: performance, app robustness/UX, and control scheme quality.
Weights and rubrics are on the Judging page.
Quick Links¶
Getting Started Checklist¶
- Confirm your team is registered (registration closed 2025-12-31); if you missed the window, contact the committee at competition@Drillbotics.com
- Review the Technical Specs for D‑WIS and OpenLab expectations.
- Review the three Mode V cases and pick your initial target.
- Stand up a minimal data flow: connect, discover signals, and log data.
- Implement a basic control loop with clear state display and logging.
- Build required plots/reports incrementally as you test.
References¶
- 2024 reference text (archival): 2024 – Group A
- Original PDFs: Resources → Downloads → “2024 – Group A (Virtual)”