Chemical Compatibility and Root Cause Analysis

This guide describes NeqSim’s production-chemistry capabilities for evaluating chemical compatibility and performing root cause analysis (RCA) of chemistry-driven problems in wells, flow assurance, and process operation. It covers scale, corrosion, acid treatment, and H₂S scavenging, with a unified entry point for incident investigation.

1. Overview

The toolkit lives in neqsim.process.chemistry and its sub-packages:

Package Purpose
neqsim.process.chemistry Chemical inventory, interaction rules, compatibility verdict
neqsim.process.chemistry.scale Scale inhibitor performance & control
neqsim.process.chemistry.corrosion Corrosion inhibitor performance
neqsim.process.chemistry.acid Acid stimulation simulator
neqsim.process.chemistry.scavenger H₂S scavenger sizing
neqsim.process.chemistry.rca Rule-based root cause analyser

All classes follow the standard NeqSim pattern: configure with setters, call evaluate() (or analyse()), then read structured results via getters and toMap() / toJson().

2. Chemical Compatibility Screening

2.1 Build a chemical inventory

ProductionChemical ci = ProductionChemical.corrosionInhibitor("CI-quat-50", 50.0);
ProductionChemical si = ProductionChemical.scaleInhibitor("SI-phosphonate", 15.0);
ProductionChemical scav = ProductionChemical.h2sScavenger("MEA-triazine", 100.0);
ProductionChemical hcl = ProductionChemical.acid("HCl-15%", 15.0);

The factory methods set ionic nature, default thermal limits, and chemical type. Sixteen chemical types are supported (see ProductionChemical.ChemicalType).

2.2 Run the assessor

ChemicalCompatibilityAssessor assessor = new ChemicalCompatibilityAssessor();
assessor.addChemical(ci);
assessor.addChemical(si);
assessor.addChemical(scav);
assessor.setTemperatureCelsius(85.0);
assessor.setCalciumMgL(2500.0);
assessor.setMaterial("carbon_steel");
assessor.evaluate();

ChemicalCompatibilityAssessor.Verdict verdict = assessor.getVerdict();
// COMPATIBLE | CAUTION | INCOMPATIBLE

Rules are loaded from src/main/resources/data/chemical_compatibility_rules.csv and cover ~30 known interactions: cationic CI + anionic SI (HIGH), CI + acid, phosphonate + HCl, phosphonate + high Ca, triazine + high T, etc.

2.3 Severity ranking

Issues are tagged HIGH / MEDIUM / LOW / INFO. The worst severity drives the verdict:

Worst severity Verdict
HIGH INCOMPATIBLE
MEDIUM CAUTION
LOW / INFO COMPATIBLE

3. Scale Inhibitor Performance

ScaleInhibitorPerformance predicts the minimum inhibitor concentration (MIC), recommended dose, and efficiency for a given brine.

ScaleInhibitorPerformance sip = new ScaleInhibitorPerformance();
sip.setScaleType(ScaleInhibitorPerformance.ScaleType.CACO3);
sip.setInhibitorChemistry(ScaleInhibitorPerformance.InhibitorChemistry.PHOSPHONATE);
sip.setTemperatureCelsius(80.0);
sip.setSaturationRatio(50.0);    // SR from a scale predictor
sip.setCalciumMgL(2000.0);
sip.setTdsMgL(80000.0);
sip.setAvailableDoseMgL(20.0);
sip.evaluate();

double mic = sip.getMinimumInhibitorConcentrationMgL();
double rec = sip.getRecommendedDoseMgL();
double eff = sip.getEfficiency();

The MIC scales with temperature, TDS, supersaturation, and Ca content. Recommended dose = 1.5 × MIC. Efficiency saturates as 1 − exp(−(dose/MIC − 1)).

3.1 Combined scale prediction + inhibitor

ScaleControlAssessor wraps a ScalePredictionCalculator plus inhibitor models per scale type:

ScalePredictionCalculator predictor = new ScalePredictionCalculator();
predictor.setTemperatureCelsius(80.0);
predictor.setCalciumConcentration(2000.0);
predictor.setBicarbonateConcentration(800.0);
predictor.setSulphateConcentration(500.0);

ScaleControlAssessor assessor = new ScaleControlAssessor(predictor);
assessor.addInhibitor(ScaleInhibitorPerformance.ScaleType.CACO3, sip);
assessor.evaluate();

double residualSI = assessor.getResidualSI(ScaleInhibitorPerformance.ScaleType.CACO3);
boolean controlled = assessor.isControlled(0.5);

The residual SI is approximated as $SI_\text{inh} = SI + \log_{10}(1 - \eta)$.

4. Corrosion Inhibitor Performance

CorrosionInhibitorPerformance uses a Langmuir adsorption framework with chemistry-specific maximum efficiencies (0.90–0.97) and penalty factors for temperature, shear, oxygen, organic acids, and acid service.

CorrosionInhibitorPerformance cip = new CorrosionInhibitorPerformance();
cip.setInhibitorChemistry(CorrosionInhibitorPerformance.InhibitorChemistry.IMIDAZOLINE);
cip.setBaseCorrosionRateMmYr(2.0);
cip.setDoseMgL(50.0);
cip.setTemperatureCelsius(90.0);
cip.setWallShearStressPa(80.0);
cip.setOxygenPpb(20.0);
cip.evaluate();

double inhibitedRate = cip.getInhibitedCorrosionRateMmYr();
double efficiency = cip.getEfficiency();

Warnings are raised for thermal degradation (>150 °C non phosphate-ester), high shear (>150 Pa), oxygen ingress (>50 ppb), acid / sour service.

5. Acid Treatment Simulator

AcidTreatmentSimulator models matrix acid jobs and returns the dissolved scale mass, CO₂ generated, and spent-acid pH.

AcidTreatmentSimulator sim = new AcidTreatmentSimulator();
sim.setAcidType(AcidTreatmentSimulator.AcidType.HCL);
sim.setAcidVolumeM3(1.0);
sim.setAcidWtPct(15.0);
sim.setScaleMassKg(500.0);
sim.setScaleMineralogy("CACO3");
sim.setTemperatureCelsius(80.0);
sim.setMaterial("carbon_steel");
sim.evaluate();

double dissolvedKg = sim.getScaleDissolvedKg();
double co2Kg = sim.getCO2GeneratedKg();
double spentPH = sim.getSpentAcidPH();

Reactions covered: $2\,\text{HCl} + \text{CaCO}_3$, $\text{HF} + \text{CaCO}_3$ (with CaF₂ risk), formic / acetic acid for HT applications. Severe-corrosion warnings trigger when HCl > 5 wt% on carbon steel above 60 °C without inhibitor.

6. H₂S Scavenger Sizing

H2SScavengerPerformance sizes triazine and solid-bed scavengers.

H2SScavengerPerformance scav = new H2SScavengerPerformance();
scav.setScavengerChemistry(
    H2SScavengerPerformance.ScavengerChemistry.MEA_TRIAZINE);
scav.setGasFlowSm3PerDay(2.0e6);
scav.setH2SInletPpm(150.0);
scav.setH2SOutletTargetPpm(4.0);
scav.setTemperatureCelsius(50.0);
scav.setInventoryKg(5000.0);
scav.evaluate();

double demandKgPerDay = scav.getH2SRemovedKgPerDay();
double doseLPerDay = scav.getRequiredDoseLPerDay();
double breakthroughDays = scav.getBreakthroughDays();

Conversion uses ISO 13443: 1 Sm³ ≈ 41.6 mol gas. Triazine stoichiometry is set to 1.0 mol triazine per mol H₂S (engineering value, vs. theoretical 2/3) to account for non-ideal contact. Warnings are raised for triazine decomposition (>80 °C), dithiazine deposition risk (>1000 ppm H₂S inlet on MEA-triazine), and pyrophoric FeS handling on solid beds.

7. Root Cause Analysis

RootCauseAnalyser is the integrative entry point. Given observed symptoms and process context, it returns ranked candidate root causes with evidence and mitigation recommendations.

7.1 Symptoms

A Symptom carries a category, a description, optional measurements, and a confidence score.

Category Example
DEPOSIT “White crystalline scale found in cooler tubes”
CORROSION “Internal wall thinning observed in flowline”
EMULSION “Stable rag layer at HP separator”
PH_EXCURSION “Outlet pH dropped to 4.2”
FLOW_RESTRICTION “Pressure drop doubled across tubing”
H2S_BREAKTHROUGH “H₂S = 12 ppm at sales gas, target 4 ppm”
SAMPLE_APPEARANCE “Black gel found at injection manifold”
OFF_SPEC “BS&W exceeded 0.5%”
OTHER Custom

7.2 Run an analysis

RootCauseAnalyser rca = new RootCauseAnalyser();
rca.setTemperatureCelsius(75.0);
rca.setPH(7.5);
rca.setCalciumMgL(2500.0);
rca.setCO2PartialPressureBar(2.0);
rca.setMaterial("carbon_steel");

rca.addSymptom(new Symptom(Symptom.Category.DEPOSIT,
    "White crystalline scale found in cooler tubes")
        .withMeasurement("depositMassGrams", 250.0));
rca.addSymptom(new Symptom(Symptom.Category.CORROSION,
    "Internal wall thinning observed in flowline")
        .withMeasurement("corrosionRateMmYr", 1.2));

rca.analyse();

RootCauseCandidate primary = rca.getPrimary();
List<RootCauseCandidate> all = rca.getCandidates();
String json = rca.toJson();

7.3 Output structure

Each candidate has:

Field Meaning
code Stable machine-readable identifier (e.g. MINERAL_SCALE)
description Plain-language summary
score 0..1 ranked likelihood
tag PRIMARY / CONTRIBUTING / POSSIBLE / RULED_OUT
evidence Narrative justification (auditable)
recommendation Concrete mitigation step

The highest-scoring candidate is always tagged PRIMARY. Scores ≥ 0.4 are CONTRIBUTING, ≥ 0.15 POSSIBLE, below that RULED_OUT.

7.4 Combining RCA with the compatibility assessor

If multiple chemicals are declared, attach a configured ChemicalCompatibilityAssessor so the analyser can elevate chemical-incompatibility candidates:

rca.setCompatibilityAssessor(assessor);

If declared but not attached, a data gap is reported: "Multiple chemicals declared but no ChemicalCompatibilityAssessor configured".

8. Standards and References

Topic Reference
Scale prediction & SI NACE TM 0374, SPE 130901, SPE 169787
Corrosion inhibition NORSOK M-506, NACE SP0775, NACE MR0175
Sour service NACE MR0175 / ISO 15156
Acid stimulation API RP 87, NACE TM 0169
H₂S scavenger GPSA Engineering Data Book, ISO 13443
Material compatibility ASTM G31, DNV-RP-O501

10. Worked Example

See the consolidated notebook chemical_compatibility_and_rca.ipynb for an end-to-end walkthrough covering compatibility screening, scale-control assessment, acid treatment sizing, scavenger sizing, and root-cause analysis on a representative incident.