Corrology®-IRI: Crude Corrosivity User Manual
Production-grade framework for screening failure likelihood, interpreting findings, and determining remediation paths under crude corrosivity damage mechanisms.
| Manual Focus | Description |
|---|---|
| Primary objective | Support robust integrity prioritization and inspection planning in hot crude service |
| Decision style | Comparative risk signal with engineering judgment |
| Recommended workflow | Baseline -> driver diagnosis -> pathway evaluation -> documented action |
Use this page as your standard runbook during live analysis.
Designed for fast, reliable execution in real workflows. Keep one baseline pinned, test one lever at a time, and document every decision with residual uncertainty.
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Purpose
This manual explains how to use Corrology®-IRI: Crude Corrosivity for practical integrity screening and how to interpret outputs with confidence.
It is written for day-to-day engineering use: run setup, result interpretation, remediation-path usage, and reporting.
At a Glance
- Primary purpose: Prioritize crude-corrosivity risk and support inspection planning decisions in naphthenic-acid and sulfidation-sensitive service.
- Output: A comparative risk indicator that supports engineering judgment. It is not a standalone fitness-for-service (FFS) assessment.
- Recommended workflow: Establish a baseline case, then evaluate the impact of controlled what-if scenarios to understand how potential changes influence the predicted risk.
Quick Start
Run Flow
- Open all expandable input cards Corrology®-IRI: Crude Corrosivity.
- Choose Predictive or Inspection mode.
- Enter required inputs.
- Click Analyze to run the assessment.
- Review the Susceptibility Score, Corrosion Rate Context, and Susceptibility Drivers.
- Pin the baseline case before evaluating multiple what-if scenarios.
- Export to pdf Report. NOTE: report comprises last two cases: Baseline/Prior and Active/Current.
Recommended Operating Practice
- Define a single objective for each analysis set.
- Change only one variable or variable group in each what-if scenario.
- Record one clear engineering conclusion for each analysis set.
Critical Mode Warning
Predictive and Inspection modes are not directly comparable without context translation.
When switching modes, treat the next run as a new analytical context and re-establish baseline before drawing conclusions.
Before You Run
Complete the following checks to ensure reliable results and meaningful comparisons.
✔ Confirm that the intended analysis mode (Predictive or Inspection) is selected.
✔ Confirm that crude chemistry inputs match the intended operating window.
✔ Verify whether the corrosion rate is measured or model-derived, and interpret the results accordingly.
✔ Verify that PTA SCC and morphology settings reflect available inspection evidence.
✔ Ensure that all units, operating ranges, and process data are consistent with site records.
Understanding the Model Outputs
- Susceptibility Score: A comparative integrity indicator used for screening, prioritization, and decision support. It represents a failure likelihood / integrity assessment indicator and should not be interpreted as a complete API RBI risk value derived from a likelihood × consequence framework.
- Corrosion-Rate Context: Indicates whether the analysis is based on measured or model-derived corrosion rates.
- Susceptibility Drivers: Shows the relative contribution of the Severity, Uncertainty, and Detection driver families to the overall susceptibility score.
- Baseline Comparison: Displays the directional change relative to the pinned baseline or a previous analysis.
Interpretation Guidance
Treat the Susceptibility Score as a decision-support indicator rather than a standalone acceptance criterion.
Use the Susceptibility Drivers to determine whether improvement is best achieved through chemistry/process control, improved inspection confidence, inspection quality, or a combination of these elements.
Reading the Results
- Review the overall trend before focusing on the absolute score.
- Identify the dominant driver family.
- Determine whether the dominant contribution is operational (Severity) or related to data quality (Uncertainty or Detection).
- Select the most appropriate response:
- operational changes,
- inspection improvements, or
- a combination of both.
Decision Ladder
- Is the risk increasing compared with the baseline?
- Which driver family contributes most to the result?
- Is the available evidence sufficient to support a decision?
- Select the appropriate response:
- operational adjustment,
- improved inspection or data quality,
- or a combined mitigation strategy.
Decision Flowchart
Decision intent: Move from diagnostic output → one explicit action path → verify impact against baseline.
Short Interpretation Examples
Example A: Severity Dominant
Pattern: severity drivers dominate and corrosion map highlights sulfur, TAN, temperature, or WSS effects.
Interpretation: operating envelope is likely the main risk lever.
Action focus: chemistry/process-window control, then re-check score shift.
Example B: Uncertainty Dominant
Pattern: uncertainty and detection contributions exceed severity.
Interpretation: current confidence is weak; risk may be overestimated or underestimated.
Action focus: inspection evidence quality, coverage, and recency improvements.
Decision Guidance by Driver Dominance
Driver-to-Action Matrix
| Dominant Driver Pattern | Typical Meaning | First Recommended Move | Expected Direction |
|---|---|---|---|
| Severity > Uncertainty/Detection | Real operating stress likely drives risk | Stabilize chemistry/process window and reassess | Score reduction |
| Uncertainty high | Data quality or age limits confidence | Improve inspection evidence and data quality | Confidence increase |
| Detection high | Detectability limitation risk | Adjust inspection method, interval, or coverage | Detectability improvement |
| Mixed profile | Multiple coupled mechanisms | Stage actions and validate after each step | Controlled convergence |
Remediation Paths (Advanced Users)
What Remediation Paths Do
Remediation Paths mode converts risk-driver outputs into actionable pathways and projects scenario impact.
Typical pathway families:
- Defend Asset Life: operational change pathways (for example temperature, sulfur, TAN, or flow-window changes).
- Inspection Evidence Refresh: inspection-evidence pathways (for example inspection effectiveness upgrades).
- Monitoring and Inspection Upgrade: controls and monitoring pathways (for trend protection and conservative tracking).
Remediation Quick Reference (Example)
Pathway Families
| Pathway Family | Typical Trigger | Typical Action | Expected Direction |
|---|---|---|---|
| Defend Asset Life | Severity-dominant risk, harsh chemistry/flow window | Adjust operating envelope (temperature, sulfur, TAN, WSS) | Score reduction |
| Eliminate Uncertainty | Uncertainty or detection drivers dominate | Upgrade inspection campaign and evidence quality | Confidence increase |
| Strengthen Monitoring | Trend instability or hidden acceleration concern | Enable monitoring and apply conservative control posture | Variability reduction |
How to Use Remediation Paths
- Run Analyze first and review the baseline score.
- Click Activate Remediation Paths.
- Wait until the status changes to Remediation Paths Mode Active.
- Review the Problem detected statement and the grouped pathway cards.
- Select one or more pathway checkboxes.
- Compare projected scenario status and score to baseline.
- Keep only practical pathways, then include justification in your report.
What to Read in Each Pathway Card
- Action: what operational or inspection step is proposed.
- Result: expected outcome and projected score direction.
- Engineering recommendation: API-aligned inspection/coverage guidance when relevant.
- Top matrix scenarios: best candidate operating combinations for Defend Asset Life pathways.
Report Integration
After evaluating pathways, click Append Engineering Justification to Report to include selected pathway rationale in generated reporting output.
Practical Selection Guidance
- Pick pathways that are implementable within your outage, access, and budget constraints.
- Prefer pathways that reduce score and improve evidence quality together.
- Do not select conflicting pathways only because each looks good in isolation.
- Re-run Analyze after implementing real field changes to verify actual effect.
What Good Looks Like
- Selected actions are technically feasible and operationally acceptable.
- Projected reduction is meaningful and not achieved by unrealistic assumptions.
- Data confidence improves, not just the score.
- Follow-up inspection and monitoring steps are explicitly scheduled.
Important Limitations
- Pathway projection is a decision-support estimate, not a guaranteed field outcome.
- If no prior analysis exists, remediation evaluation cannot run.
- PTA SCC hard-stop states remain FFS-gated and should be resolved before claiming PTA-driven reduction.
- Pathway logic is based on configured rule sets and model assumptions; engineering review is still mandatory.
Best practice: apply one practical pathway set at a time, then re-run and validate the real effect against baseline.
Common Mistakes to Avoid
- Assuming direct equivalence when comparing results between Predictive and Inspection modes.
- Changing multiple inputs simultaneously, then over-interpreting the resulting rank order.
- Treating a single score as pass/fail without considering the operational context.
- Ignoring data quality warnings when uncertainty is the dominant driver.
Troubleshooting
Open Troubleshooting Checklist
- No result: verify required fields and date/year validity.
- Unexpected ranking: verify mode, baseline, and PTA/morphology toggles.
- Counter-intuitive trend: verify corrosion-rate source, inspection context, chemistry envelope, and PTA branch flags.
Reporting Template (Short)
When documenting a run, include:
- Run mode and context (asset, unit, operating window).
- Baseline score and dominant drivers.
- Selected remediation pathway(s) and why.
- Expected outcome and residual uncertainty.
- Planned validation step (next inspection/monitoring check).
Report Quality Gate
- What changed is explicitly identified.
- Why it changed is technically justified.
- Residual uncertainty is stated.
- Verification step and timing are scheduled.
Status rule: mark Ready for Approval only when all items are checked.
Key Terms
Open Key Terms
Severity
How damaging current degradation behavior is expected to be.
Uncertainty
How much confidence is limited by data quality and time context.
Detection Limitation
How limited damage detectability is due to inspection effectiveness, monitoring status, and morphology effects.
Low Confidence in Historical Data
Data quality issue (trustworthiness/completeness).
Outdated Inspection Data
Data age issue (staleness over time).
CR Map
A heuristic, model-informed explanation layer that highlights the dominant current corrosion-rate drivers. It does not replace the base corrosion calculation or engineering review.
PTA SCC Present (PASCC Overlay)
Enables the PTA SCC PASCC overlay branch. If thinning DF and PTA SCC DF are both active, the backend combines them through an API 581-style multi-damage-mechanism DF path before Pf/logPf/score are derived. Unresolved crack states trigger FFS gating and keep the run thinning-governed for that calculation.
Need Deeper Technical Detail?
For more details on IRI functionality, please contact Corrology Engineering Team.