Corrology®-IRI: Sour Water User Manual

Practical guide for running Corrology®-IRI: Sour Water, interpreting NH4HS risk outputs, and using remediation pathways.

Corrology®-IRI: Sour Water User Manual

Production-grade operating guide for integrity screening, driver diagnosis, and remediation-path decisions for assets in alkaline sour water service.

Manual Focus	Description
Primary objective	Support robust integrity prioritization and inspection planning
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 sour-water analysis.

Designed for fast, reliable execution in NH₄HS workflows. Keep one baseline pinned, test one lever at a time, and document every decision with residual uncertainty.

Manual Map

Purpose

This manual explains how to use Corrology®-IRI: Sour Water 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 NH₄HS corrosion risk and support inspection planning decisions.
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 Corrology®-IRI: Sour Water.
Choose Predictive or Inspection mode.
Enter required inputs.
Click Analyze.
Review susceptibility score, corrosion-rate context, and susceptibility drivers.
Pin baseline before running multiple what-if cases.

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 inspection-date context is realistic for the assessed period.
✔ Verify whether the corrosion rate is measured or model-derived, and interpret the results accordingly.
✔ Verify that wet H₂S cracking and morphology settings reflect available inspection evidence.
✔ Ensure that all units and operating ranges are consistent with site records.
✔ Confirm that the assessment remains within carbon-steel NH₄HS sour-water scope rather than a multi-alloy case.

Understanding the Model Outputs

Susceptibility Score: summarized integrity indicator for screening and prioritization.
Corrosion-Rate Context: measured or modeled rate basis used by the run.
Susceptibility Drivers: relative contribution from Severity, Uncertainty, and Detection factors.
Baseline Comparison: directional change relative to prior or pinned baseline case.

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 operating-envelope changes, improved inspection confidence, inspection quality, or a combination of these elements.

Status Pill Colour Mapping

The user interface uses status pills to provide a quick visual indication of the risk band:

● Very Low
● Low
● Moderate
● High

These status pills are displayed in pathway cards and summary panels to indicate the mapped risk band for the calculated logPf. They provide a visual summary only and should always be interpreted together with the numerical results and the identified risk drivers.

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: High severity contribution, moderate uncertainty.

Interpretation: NH₄HS chemistry or velocity is likely the primary risk driver.

Action focus: Adjust H₂S / NH₃ / pH₂S / velocity window where operationally feasible, then re-run analysis and evaluate score shift.

Example B: Uncertainty Dominant

Pattern: Uncertainty and detection limitations exceed severity.

Interpretation: Confidence is limited; risk may be over- or under-estimated.

Action focus: Improve inspection quality, coverage, and data recency before changing operating conditions.

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 sour-water chemistry or velocity 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 H₂S / NH₃ / pH₂S / velocity-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, high sour-water chemistry or velocity stress	Adjust operating envelope	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 chemistry / velocity 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.
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

Switching between Predictive and Inspection modes and interpreting values as directly equivalent.
Comparing Predictive and Inspection runs as if equivalent.
Changing many inputs at once, then over-interpreting ranking order.
Treating one score as pass/fail without context.
Ignoring data quality warnings when uncertainty is dominant.

Troubleshooting

Open Troubleshooting Checklist

No result: verify required fields and date/year validity.
Unexpected ranking: verify mode, baseline, and toggles.
Counter-intuitive trend: verify corrosion-rate source, inspection context, chemistry inputs, and wet H₂S cracking flags.

Reporting Template (Short)

When documenting a run, include:

Run mode and context (asset, date, 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

Susceptibility Score

The reported susceptibility score is a failure likelihood / integrity assessment indicator and should not be interpreted as a complete API RBI risk value derived from a likelihood × consequence framework. Consequence of failure is not included within the scope of this score.

Severity

Extent of expected damage from the identified degradation mechanism.

Uncertainty

Degree to which confidence is limited by data quality, completeness, or time gap.

Detection Limitation

Constraints in identifying damage due to inspection method, coverage, or morphology.

Low Confidence in Historical Data

Data reliability issue due to incompleteness or inconsistency.

Outdated Inspection Data

Data age issue (staleness over time).

Localized Damages Present

Presence of localized morphology that reduces detectability and increases risk variability.

Wet H₂S Cracking Present

Indicates potential wet H₂S cracking susceptibility. In NH₄HS systems, this does not automatically trigger a FFS-requirements hard stop. A hard stop applies only when cracks are confirmed and remain unresolved. In this case, wet H₂S cracking DF and cracking score are not calculated; overall scoring remains based on thinning risk until FFS disposition is resolved.

Need Deeper Technical Detail?

For more details on IRI functionality, please contact Corrology Engineering Team.