— The Problem
Where oil and gas operations lose intelligence
Oil and gas operations generate enormous volumes of data — production readings, sensor telemetry, maintenance logs, HSE records. The challenge isn't collecting it. It's connecting it into a coherent operational picture in time to act on it.
Production reporting that's days old
Daily production reports assembled manually from multiple SCADA systems and operational
logs. By the time data reaches management, decisions have already been made without it. Variance from plan
discovered after the fact.
Reactive maintenance — unplanned downtime
Equipment failures discovered when they occur rather than predicted before they happen.
Unplanned downtime in oil and gas is measured in lost production per day. Predictive maintenance ML reduces it
significantly.
HSE compliance tracked manually
Inspection schedules, permit-to-work records, corrective actions, and incident
documentation managed in spreadsheets or paper. Audit-readiness requires days of manual assembly.
Non-compliance risk goes undetected.
SCADA, ERP, and CMMS disconnected
Production data in SCADA, maintenance records in CMMS, financial data in ERP, HSE in a
separate system. No unified operational view. Correlating a production anomaly with its maintenance cause
requires manual investigation.
Security constraints block standard approaches
Many oil and gas operators have strict restrictions on direct database access, API
connections to production systems, and data egress. Standard BI approaches fail. We've built around these
constraints — including for Atlantic LNG.
No integrated field operations view
Field teams, operations centre, and executive management all work from different data with
different latency. The operations centre can see SCADA; executive management sees the weekly report. Neither
is real-time.
— What We Build
Oil & gas intelligence that works within your constraints
Production BI Platform
Unified production intelligence across all wells, platforms, and assets — updated from
SCADA, historian, and operational systems in near real-time. Variance from plan identified automatically.
Trend analysis and forecasting included.
Predictive Maintenance AI
ML models trained on sensor telemetry and maintenance history detect anomaly patterns
that precede equipment failure — weeks before failure occurs. Maintenance scheduled before the breakdown,
not after it. Unplanned downtime reduced measurably.
HSE Compliance Management
Digital permit-to-work, inspection scheduling, corrective action tracking, and incident
management — all in one system with automated reminders, escalations, and audit-ready reporting. Compliance
visible in real time, not at audit time.
SCADA / ERP / CMMS Integration
Connect production, maintenance, and financial systems into a unified data model.
Production anomalies correlated with maintenance records automatically. Financial impact of downtime
calculated against production plan in real time.
Constrained-Environment BI Architecture
We've built full BI platforms for operators who won't allow direct database access or
API connections to production systems. Staging exports, PowerApps capture layers, SharePoint ingestion —
whatever the constraint, there's an architecture. Atlantic LNG proved this.
Field Operations Mobile App
React Native app for field engineers — inspection checklists, permit-to-work request and
approval, maintenance job updates, and real-time production readings from the field. Offline-capable for
remote locations with intermittent connectivity.
Atlantic LNG — full BI platform with zero direct database access
Atlantic LNG's security constraints prohibited direct access to production databases or API
connections to operational systems. Most BI vendors walked away. We built a two-stream architecture: system
owners deposited scheduled Excel exports to SharePoint, and a PowerApps capture layer handled data with no
digital source. Both fed into Power BI. The result was a fully functional executive and departmental BI
platform — built entirely around the constraint rather than against it. This case established our approach to
constrained-environment BI that we've applied in oil and gas engagements since.
Read the Atlantic LNG case study →
— Featured Case Study
Full BI delivered without touching a production system.
Oil & Gas · Business Intelligence
Atlantic LNG — BI Platform Built Without Direct Database Access
Zero
Direct DB access permitted
Full
Executive BI delivered
2-stream
Architecture: Excel + PowerApps
Atlantic LNG prohibited direct database connections to production systems. Infomaze designed
a two-stream ingestion architecture using SharePoint-staged Excel exports and a PowerApps data capture layer —
both feeding Power BI. Full operational and executive dashboards delivered inside the security constraint. The
approach is now our standard for constrained O&G environments.
Power BI · PowerApps · SharePoint · Excel ETLRead full case study →
— Integrations
Connects across the O&G technology stack
SCADA Systems
Production data ingestion via API, historian, or staged export
CMMS Platforms
Maximo, SAP PM, IFS — maintenance data integration
ERP / SAP
Financial and asset management data
Power BI
Production intelligence and HSE dashboards
SharePoint / Excel
Staged export ingestion for constrained environments
PowerApps
Field data capture where no system access exists
Predictive ML
Sensor telemetry anomaly detection on Azure ML
HSE Systems
PTW, inspection, and incident management integration