Energy Case Study

How an E&P Operator Reduced Well Analysis Time by 75%

From 8-hour assessments to 2-hour intelligent analysis

VP of Operations IntelligenceMid-Cap E&P Operator1,200+ producing wells
The Problem

Every well performance assessment took a full business day.

The Operations Intelligence team managed 1,200+ producing wells across 6 basins. Each well performance assessment required pulling data from SCADA systems, geological databases, production accounting, and maintenance logs — spread across 5 disconnected platforms. Engineers spent 8+ hours per assessment, and the backlog meant emerging issues went undetected for weeks.

8+ hours
per well assessment
5
disconnected data platforms
1,200+
wells to monitor
Weeks
of detection delay
Signal Studio in Action

From data chaos to instant answers

Signal Studio connected to SCADA, geological databases, production accounting, and maintenance systems — creating a unified view of every well. Petroleum engineers began asking natural language questions instead of manually querying 5 systems.

Example queries

"Which wells in the Permian showed >10% production decline vs. type curve in the last 30 days?"
"What's the correlation between ESP runtime and production efficiency for Pad 17?"
"Show me wells where maintenance cost per BOE exceeds basin average by 2x"
The Results

Measurable outcomes

75%
faster assessments
From 8 hours to 2 hours
3 weeks
earlier issue detection
Automated anomaly signals
$2.4M
annual savings
From early intervention
12 days
to full deployment
Across all 5 data systems
Compliance & Transparency

Every decision documented

Every anomaly detection signal included the full reasoning chain — which data points triggered the alert, what thresholds were applied, and what maintenance actions were recommended. This documentation satisfied both internal engineering review and external partner reporting requirements.

FAQ

Questions about this deployment

How did Signal Studio handle SCADA data integration?

Signal Studio connected to the existing SCADA historian through pre-built connectors — no custom integration required. Real-time production data was mapped to the semantic layer alongside geological and financial data.

Did field engineers adopt the natural language interface?

Yes. Field engineers who had no data analytics background were asking production-quality queries within the first week. The key was that they could ask questions the way they naturally think about wells — by pad, by basin, by completion type.

What types of anomalies does Signal Studio detect automatically?

Signal Studio continuously monitors production rate deviations from type curves, ESP performance degradation, unusual water-oil ratio changes, and maintenance cost outliers. Each signal includes the complete reasoning chain for engineering review.

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ForwardLane

Decision intelligence for the enterprise. From question to auditable action in seconds — across financial services, private markets, energy, and government.

What is Decision Intelligence?

Decision Intelligence is a category of enterprise software that transforms data into prioritized, auditable actions. Unlike traditional BI (which outputs dashboards), platforms like Signal Studio deliver Next Best Actions with complete audit trails in seconds, closing the gap between question and compliant decision.

What is Decision Velocity?

Decision Velocity measures the speed from a business question to a documented, auditable action within an enterprise. In financial services, traditional analyst-driven cycles take weeks; ForwardLane achieves Decision Velocity in under 11 seconds using AI-native multi-agent orchestration.

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