1. The Problem

Distributed drilling operations required a unified and comparative view of the process (time x depth), with reliable annotations and centralized histories, while maintaining a local UI at the wells for “near-rig” decision-making.

Specific pain points:

• Manual consolidation of disparate data (WITS/WITS0/WITSML) for performance analyses.

• Difficulty comparing wells (current vs. historical) by time and depth.

• Need to maintain local operability (offline/low connectivity) and corporate mobile visualization.

Impact: Delays in diagnostics, lower operational standardization, higher logistics cost, and risk of decisions based on incomplete data.

Example: “Without a consolidated historical trail, each well required ad-hoc compilations for post-operation analyses, impacting the optimization of drilling parameters.”

2. The Solution

• Edge: FrameworX EdgeConnect with local UI.

• Central: FrameworX Enterprise.
  Clients: WebAssembly/HTML5 and SmartClient for operations/engineering.
  Corporate historian: OSI PI (Data Archive/AF as applicable).
  Annotations: Ingestion via WITSML + operators’ manual annotations.
  External calculations: On Edges and central (aggregations, KPIs, prediction), integrated with FrameworX.
  Scale: >30 simultaneous wells sending data; 200+ historical wells available for comparison.

2.1 Logical Diagram (high level)

2.2 Topology

2.3 Network Architecture

Hybrid: cellular/ethernet/VSAT, with TLS and store-and-forward at the Edge.
Logical isolation by well (independent solution) and by environment (dev/test/prod).

2.4 Redundancy & Failover

Edges: Independent operation with local buffering and local UI (continuity even offline).
Central: Redundancy of critical services (ingestion/visualization) and PI backups.

2.5 Protocols & Equipment

Collection: WITS0/WITS (drilling equipment).
Metadata/Annotations: WITSML (events/intervals/observations from the drilling system) + operator input.

2.6 Databases/Historians

Corporate: OSI PI as historical repository and source of corporate reports.
Edge: Local buffer (store-and-forward) + calculations close to the source.

2.7 Scale & Capacity (fill/validate)

• Simultaneous wells: 30+

• Tags/Signals per well: 500

• Ingestion rate: Read cycle each 3s

• Users/connections: 10-15 simultaneous

• LDAP Connection to external users

2.8 Third-Party Integrations

WITSML servers (rig providers), OSI PI (connectors/SDKs), data/ML pipelines (when applicable).

3. Key Enablers

• EdgeConnect with local UI & store-and-forward
  Resilient operation at the well; offline continuity; reliable synchronization.

• WebAssembly/HTML5 Displays
  Mobile and distributed access without tight dependency on the Edge environment.

• Independent solutions (Edge/Central/UI)
  Distributed, versioned, and secure updates, with controlled rollback.

• Dual-axis data model (time/depth)
  Visualization and comparison across wells aligned by time or depth.

• WITS/WITS0/WITSML ingestion/normalization
  Fusion of near-real-time signals and automatic + manual annotations.

Why wasn’t this trivial on other platforms? Combination of resilient Edge + local UI, scalable WebAssembly, solution independence, and WITS/WITSML normalization ready for time/depth comparison.

4. The Results

• Eliminated manual data consolidation - Automated integration of WITS/WITS0/WITSML data streams replaced ad-hoc compilations, reducing analysis time from hours to real-time processing across 30+ simultaneous wells.

• Enabled well-to-well performance comparison - Dual-axis visualization (time/depth) now allows direct comparison of current drilling with 200+ historical wells, improving drilling parameter optimization.

• Achieved offline operational continuity - EdgeConnect with local UI and store-and-forward ensures uninterrupted drilling operations even during network outages, preventing data loss and maintaining near-rig decision capability.

• Centralized historical data trail - Integration with OSI PI corporate historian created a single source of truth for all drilling operations, eliminating previous gaps in post-operation analyses.

• Reduced operational delays and costs - Standardized data collection and automated KPI calculations decreased diagnostic time, lowered logistics costs, and minimized risks from incomplete data.

• Scaled to enterprise-level operations - System successfully handles 500 signals per well, 30+ concurrent drilling operations, and 10-15 simultaneous users with 3-second data refresh rates.

• Preserved local control with global visibility - Maintained critical near-rig UI for immediate decisions while providing corporate teams with mobile and web access for strategic oversight.