Pipeline Integrity Decision Support Software | Geospatial Risk Correlation | VeriCorr
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Geospatial
correlation

Correlating integrity, corrosion, and field data at the locations where engineering decisions are made.

VeriCorr helps integrity teams correlate integrity, corrosion, and geohazard data at precise GIS locations, so prioritization decisions are defensible and reviewable.

Operator-owned integrity and CP data are aligned spatially and temporally to support location-based prioritization with auditable rationale. Cross-check surveys, inspections, and findings converge at the segment and site level, producing evidence that integrates directly into existing integrity workflows.

  • Location-based risk ranking derived from multiple aligned data sources
  • Auditable evidence packages for every prioritized segment or site
  • GIS-ready outputs that integrate with existing integrity and compliance workflows
VeriCorr Location
The operating reality facing integrity teams
Growing Datasets

Growing Datasets

ILI runs, CP surveys, ECDA assessments, and repair records continue to accumulate faster than they can be systematically reviewed. Each new dataset adds volume and complexity without automatically adding clarity.

Growing Datasets

Limited Resources

Integrity teams must expand inspection and mitigation programs while operating with flat or declining staff counts. Every prioritization decision must withstand technical review and audit, competing directly for limited capital and personnel time.

Increasing Scrutiny

Increasing Scrutiny

Regulators expect documented rationale for integrity decisions. Operators must demonstrate how risk assessments incorporate all available data and account for location-specific threats and exposure.

Example use cases in pipeline integrity
Dig Prioritization

Dig Prioritization

Rank excavation sites by correlating ILI findings with CP performance, repair history, and consequence exposure. Focus limited dig budgets on locations with convergent evidence of risk.

CP System Optimization

CP System Optimization

Identify segments with marginal protection that also exhibit corrosion features or coating damage. Prioritize rectifier upgrades or anode bed additions based on spatial correlation with integrity findings.

Re-Inspection Planning

Re-Inspection Planning

Target ILI or ECDA resources to segments where prior surveys identified active threats, CP protection has degraded, or consequence has increased due to land use changes.

Regulatory Justification

Regulatory Justification

Assemble evidence packages that document how prioritization decisions incorporate all available data. Demonstrate a systematic, location-based approach to integrity management that meets regulatory expectations.

Geohazards

"Geohazards are location-specific"

Pipeline integrity risk is not uniform along a system. Geohazards such as slope movement, subsidence, flooding, erosion, soil variability, and construction activity are inherently location-specific and often episodic.

These hazards become meaningful only when evaluated at precise geographic locations in the context of the assets, coatings, CP performance, inspection history, and prior repairs present at that location. Without spatial alignment, geohazard information remains descriptive rather than actionable.

Tangible outputs for planning and compliance

Actionable, auditable outputs that support prioritization, GIS analysis, data quality review, and system integration.

Ranked segments or sites
Ranked segments or sites

Priority-ordered lists of pipeline segments or CP test points, with scores and evidence summaries. Exportable to Excel or CSV for planning and capital allocation.

GIS-ready layers
GIS-ready layers

Shapefiles or geodatabase feature classes that integrate directly into operator GIS environments. Visualize risk concentrations and support spatial analysis.

Evidence packets
Evidence packets

Location-specific reports explaining why each segment was prioritized, which datasets contributed, and what findings support the ranking. Defensible under regulatory audit.

Data quality flags
Data quality flags

Identification of survey coverage gaps, positional mismatches, and missing data elements. Helps integrity teams target future data collection and improve assessment quality.

Exportable tables
Exportable tables

Structured data exports for integration into work management systems, integrity management platforms, or reporting tools. Supports automated workflows and documentation.