Turning subsurface data and surface operations into a living intelligence loop—so every barrel, electron, and decision flows smarter.
Industry Context
The energy sector is simultaneously data‑rich and insight‑poor. SCADA streams, well files, geology reports, and sensor networks generate terabytes daily, yet operational decisions still rely on manual digestion and fragmented dashboards. With volatile prices and strict ESG mandates, operators need a system that remembers, reasons, and responds in real‑time.
Genio Energy addresses this gap with a recursive memory engine that integrates field telemetry, engineering context, and financial targets into one cognitive loop.
Normalizes units, timestamps, and geospatial tags in real‑time.
INTERPRET → REFLECT
Applies multivariate anomaly detection for flow, pressure, and temperature.
Correlates subsurface models with live production to flag under‑performing zones.
VISUALIZE → EMBED
Auto‑generates well dashboards, decline‑curve updates, and cost variance alerts.
Embeds event vectors in Qdrant for semantic recall and cross‑well comparison.
REPLAY
Timeline playback of every intervention, downtime event, and uplift driver.
Feeds lessons learned into future drill plans and AFE economics.
Deep‑Dive Modules
1. SCADA Fusion
Hourly production, flowback, and artificial lift data are integrated with weather and power pricing. Operators receive predictive set‑points that balance production targets with energy cost curves.
2. Intelligent Well File
Genio parses thousands of legacy PDFs—permits, E‑logs, workover notes—extracting entities and embedding them for instant Q&A. Engineers ask, “When was the last squeeze job on JZ #12?” and get a sourced answer in seconds.
3. ESG & Compliance Lens
Methane sensors, FLIR imagery, and regulatory filings flow into Genio’s truth anchor layer. The system flags emission excursions, auto‑drafts LDAR reports, and tracks carbon intensity per BOE.
4. Market‑Aware Optimization
Spot prices, basis differentials, and pipeline schedules are streamed alongside production data. Genio recommends choke adjustments or storage draws to maximize realized pricing.
Architecture Snapshot
Edge Capture: MQTT / OPC‑UA collectors push encrypted data to Azure IoT or AWS IoT Core.
Stream Processing: Apache Kafka pipelines normalize and batch forward to FastAPI microservices.
Genio Heads: Summarizer, Sentiment (HSE logs), NER, Embed, QA—each containerized with NVIDIA NeMo 2.0 and deployable on GPUs, TPUs, or Groq LPUs.
Memory Layer: PostgreSQL for structured events, Qdrant for vectors, DuckDB for time‑series analytics.
Visualization: Plotly Dash + CesiumJS subsurface viewer, with Omniverse hooks for digital twins.
Why Genio?
Unified Context: One narrative from pore space to profit & loss.
Vendor Freedom: Cloud‑ and hardware‑agnostic deployment.
Recursive Learning: Past fixes inform future design—automatically.