Correlating asset integrity, geohazards, and compliance in one system

Geospatial correlation where integrity risk actually occurs

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

VeriCorr correlates operator-owned integrity and CP data into location-based priorities with auditable rationale. Cross-check surveys, align findings spatially and temporally, and prioritize segments with defensible evidence.

  • Location-based risk ranking derived from multiple aligned data sources
  • Auditable evidence packets for every prioritized segment or site
  • GIS-ready outputs that integrate with existing integrity workflows
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GIS visualization

The operating reality facing integrity teams

Growing datasets

ILI runs, CP surveys, ECDA assessments, and repairs accumulate faster than they can be systematically reviewed. Each survey cycle adds complexity without necessarily adding clarity.

Limited resources

Integrity teams manage expanding pipeline networks with flat or declining staff counts. Every prioritization decision must be defensible under audit while competing for capital and personnel time.

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.

The challenge is not lack of data. The challenge is reconciling data from different sources, survey cycles, and coordinate systems into a coherent view of where risk is concentrated and why action is justified.

Fragmented data creates blind spots

ILI data

Metal loss, crack, and geometry features reported in vendor-specific formats with varying confidence levels and location accuracy.

CP survey data

ON/OFF potentials, rectifier outputs, interference readings, and soil resistivity measurements collected at intervals that rarely align with ILI spacing.

ECDA inputs

Coating condition assessments, soil corrosivity data, and electrical survey results that identify high-risk areas but lack integration with other datasets.

Repair records

Historical interventions documented in spreadsheets or work order systems, often with imprecise coordinates and inconsistent classification schemes.

GIS context

HCA boundaries, land use, environmental sensitivity, and third-party activity attributes and data that affect consequence but exist in separate GIS layers.

Each dataset resides in its own system with its own coordinate reference, update cycle, and quality characteristics. Manually aligning them is time-consuming, inconsistent, and difficult to audit or replicate.

Why prioritization is harder than it appears

01

Compound risk from multiple threats

A segment may have moderate corrosion, marginal CP protection, and elevated consequence exposure. Simple scoring misses the interaction between these factors.

02

Location-specific hazards

Soil conditions, stray current interference, coating age, and operational history vary along the route. Generic models cannot capture local variability without spatial correlation.

03

Inconsistent data quality

Survey coverage gaps, positional uncertainty, and temporal misalignment create false negatives and complicate trend analysis. Not all data points have equal reliability.

04

Insufficient simple scoring

Spreadsheet-based ranking lacks transparency, does not account for spatial clustering of risk factors, and provides limited documentation for why one segment outranks another.

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 only become meaningful when evaluated at precise geographic locations and 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.

What VeriCorr does

VeriCorr functions as a correlation and decision-support layer that aligns operator-owned integrity, corrosion, and geohazard datasets at precise GIS locations. It evaluates where multiple indicators intersect at specific geographic locations over time, supporting defensible, location-based prioritization decisions.

The platform correlates inputs such as ILI features, CP survey readings, ECDA results, repair history, geohazard information, and consequence data to produce ranked segments or sites. Each priority is accompanied by a clear supporting rationale that traces back to the underlying source data, creating an auditable record of why a location was flagged.

VeriCorr does not replace engineering judgment or existing integrity programs. It organizes and correlates available information so integrity teams can make better-informed decisions, with confidence that prioritization is systematic, reviewable, and grounded in the full context of the data.

GIS visualization

Spatial alignment

Reconcile coordinate systems and align features from different surveys to a common pipeline stationing or geographic reference frame.

Temporal correlation

Account for survey timing, identify trends over multiple inspection cycles, and flag locations where conditions are deteriorating.

Evidence synthesis

Combine findings from multiple sources into location-specific evidence packets explaining why a segment was prioritized and what data supports it.

What VeriCorr does not do

VeriCorr is a correlation and decision-support tool, not a replacement for operator expertise or engineering judgment.

Does not replace integrity programs

VeriCorr does not perform integrity assessments, calculate remaining life, or determine repair specifications. Those decisions remain with qualified engineers following procedures and requirements.

Does not eliminate engineering review

Prioritized outputs require validation by integrity personnel who understand local conditions, operational history, and threat mechanisms. VeriCorr organizes data to support review, not bypass it.

Does not dictate actions

The platform provides ranked segments with supporting evidence. Final decisions on excavation, repair, or re-inspection remain with the operator based on risk tolerance, resource availability, and strategic priorities.

VeriCorr delivers structured, auditable inputs to integrity decision-making. It reduces manual data wrangling and improves consistency, but does not replace the expertise and judgment that integrity engineers bring to the process.

Tangible outputs for planning and compliance

Ranked segments icon

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.

Ranked segments icon

GIS-ready layers

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

Ranked segments icon

Evidence packets

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

Ranked segments icon

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.

Ranked segments icon

Exportable tables

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

Example use cases in pipeline integrity

Dig prioritization

Dig prioritization

Rank excavation sites by correlating ILI findings with CP survey results, 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, where CP protection has degraded, or where consequence has increased due to land use changes.

Dig prioritization

Dig prioritization

Assemble evidence packets that document how prioritization decisions incorporate all available data. Demonstrate a systematic approach to integrity management that meets regulatory expectations.

Audit readiness and defensibility

Documented rationale for every decision

Regulatory audits and management reviews require clear explanations of how integrity priorities are determined. VeriCorr generates evidence trails that show which datasets were consulted, what findings were identified, and how they combine to support a given ranking.

Each prioritized location includes references to source data, survey dates, and contributing factors. Engineers can justify their decisions with confidence, knowing the approach is systematic, repeatable, and traceable to operator-owned data.

Audit readiness and defensibility

Traceable methodology

Document how data sources were correlated and which factors influenced prioritization. Support internal QA reviews and external audits.

Version control

Maintain records of datasets used, analysis parameters, and outputs generated. Reproduce past analyses to demonstrate consistency over time.

Gap identification

Highlight where data is missing, outdated, or inconsistent. Improve data governance and target future survey efforts where they add the most value.

Learn more about VeriCorr

VeriCorr helps pipeline operators correlate integrity and CP data into location-based priorities with auditable rationale. If you manage ILI findings, CP surveys, ECDA results, or integrity planning, and need a systematic way to synthesize multiple datasets, we can help.

Request a call to discuss your specific data environment, integrity challenges, and how geospatial correlation can support better prioritization decisions.

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