Asphaltene Characterization

Documentation for asphaltene modeling using SARA analysis in NeqSim.

Table of Contents

Overview

Package: neqsim.thermo.characterization

Asphaltene precipitation is a critical flow assurance issue that can cause:

NeqSim provides tools for characterizing asphaltene content and predicting precipitation using thermodynamic models (primarily CPA).

Key Classes

Class Description
AsphalteneCharacterization SARA-based characterization
PedersenAsphalteneCharacterization Pedersen’s correlation approach

SARA Analysis

What is SARA?

SARA analysis separates crude oil into four fractions:

Fraction Description Characteristics
Saturates Alkanes (linear, branched, cyclic) Non-polar, lightest
Aromatics Aromatic rings Moderately polar
Resins Polar aromatics with heteroatoms Stabilize asphaltenes
Asphaltenes Large polyaromatic molecules Heaviest, most polar

SARA Fraction Properties

Property Saturates Aromatics Resins Asphaltenes
MW (g/mol) 300-600 300-800 500-1200 1000-10000
H/C ratio ~2.0 1.0-1.5 1.0-1.4 0.9-1.2
Polarity Non-polar Low Medium High
Solubility n-alkanes Toluene Toluene Toluene

Colloidal Instability Index

Definition

The Colloidal Instability Index (CII) predicts asphaltene stability:

\[CII = \frac{Saturates + Asphaltenes}{Aromatics + Resins}\]

Stability Criteria

CII Value Stability Risk
< 0.7 Stable Low precipitation risk
0.7 - 0.9 Metastable Moderate risk
> 0.9 Unstable High precipitation risk

Physical Interpretation

AsphalteneCharacterization Class

Creating a Characterization

import neqsim.thermo.characterization.AsphalteneCharacterization;

// Create from SARA fractions (weight fractions, must sum to 1.0)
AsphalteneCharacterization asphChar = new AsphalteneCharacterization(
    0.45,   // Saturates
    0.30,   // Aromatics
    0.20,   // Resins
    0.05    // Asphaltenes
);

// Or create empty and set values
AsphalteneCharacterization asphChar2 = new AsphalteneCharacterization();
asphChar2.setSaturates(0.45);
asphChar2.setAromatics(0.30);
asphChar2.setResins(0.20);
asphChar2.setAsphaltenes(0.05);

Calculating Stability Indices

// Calculate Colloidal Instability Index
double cii = asphChar.calcColloidalInstabilityIndex();
System.out.println("CII: " + cii);

// Check stability
if (cii < AsphalteneCharacterization.CII_STABLE_LIMIT) {
    System.out.println("Asphaltenes are stable");
} else if (cii < AsphalteneCharacterization.CII_UNSTABLE_LIMIT) {
    System.out.println("Asphaltenes are metastable - monitor carefully");
} else {
    System.out.println("Asphaltenes are unstable - high precipitation risk");
}

// Calculate resin-to-asphaltene ratio
double raRatio = asphChar.calcResinAsphalteneRatio();
System.out.println("R/A ratio: " + raRatio);

Setting C7+ Properties

// Set C7+ fraction properties for better characterization
asphChar.setMwC7plus(350.0);        // g/mol
asphChar.setDensityC7plus(850.0);   // kg/m³

// Estimate asphaltene properties
double mwAsph = asphChar.estimateAsphalteneMW();
double mwResin = asphChar.estimateResinMW();
System.out.println("Estimated asphaltene MW: " + mwAsph + " g/mol");
System.out.println("Estimated resin MW: " + mwResin + " g/mol");

CPA Parameters

Asphaltene Association Parameters

For CPA modeling, asphaltenes are treated as associating molecules:

// Set CPA parameters
asphChar.setAsphalteneMW(1700.0);              // g/mol
asphChar.setResinMW(800.0);                     // g/mol
asphChar.setAsphalteneAssociationEnergy(3500.0); // K
asphChar.setAsphalteneAssociationVolume(0.05);
asphChar.setResinAsphalteneAssociationEnergy(2500.0); // K (cross-association)

// Get parameters for CPA model
double epsilon = asphChar.getAsphalteneAssociationEnergy();  // K
double kappa = asphChar.getAsphalteneAssociationVolume();

Association Scheme

Asphaltenes are typically modeled with:

Interaction Energy (K) Volume
Asphaltene-Asphaltene 3000-4000 0.03-0.07
Resin-Asphaltene 2000-3000 0.02-0.05

Usage Examples

Complete Characterization Workflow

import neqsim.thermo.system.SystemSrkCPAstatoil;
import neqsim.thermo.characterization.AsphalteneCharacterization;
import neqsim.thermodynamicoperations.ThermodynamicOperations;

// Step 1: Create asphaltene characterization from SARA data
AsphalteneCharacterization asphChar = new AsphalteneCharacterization(
    0.42,  // Saturates
    0.32,  // Aromatics
    0.22,  // Resins  
    0.04   // Asphaltenes
);

// Step 2: Set additional properties
asphChar.setMwC7plus(380.0);
asphChar.setDensityC7plus(870.0);
asphChar.setAsphalteneMW(1800.0);
asphChar.setResinMW(850.0);

// Step 3: Calculate stability indices
double cii = asphChar.calcColloidalInstabilityIndex();
double raRatio = asphChar.calcResinAsphalteneRatio();

System.out.println("=== Asphaltene Stability Analysis ===");
System.out.println("CII: " + String.format("%.3f", cii));
System.out.println("R/A ratio: " + String.format("%.2f", raRatio));
System.out.println("Stability: " + asphChar.getStabilityClassification());

// Step 4: Create fluid system with asphaltene pseudo-component
SystemSrkCPAstatoil fluid = new SystemSrkCPAstatoil(373.15, 200.0);

// Add light components
fluid.addComponent("methane", 0.35);
fluid.addComponent("ethane", 0.08);
fluid.addComponent("propane", 0.05);
fluid.addComponent("n-hexane", 0.12);

// Add characterized fractions including asphaltene
fluid.addTBPfraction("Saturates", 0.20, 0.300, 0.78);
fluid.addTBPfraction("Aromatics", 0.12, 0.350, 0.88);
fluid.addTBPfraction("Resins", 0.06, asphChar.getResinMW()/1000, 0.98);
fluid.addComponent("asphaltene", 0.02);  // As pseudo-component

fluid.setMixingRule(10);  // CPA mixing rule

// Step 5: Run flash calculation
ThermodynamicOperations ops = new ThermodynamicOperations(fluid);
ops.TPflash();

// Check for asphaltene precipitation
if (fluid.hasPhaseType("solid") || fluid.hasPhaseType("asphaltene")) {
    System.out.println("Asphaltene precipitation predicted!");
    double precipAmount = fluid.getPhase("solid").getMolarMass() * 
                         fluid.getPhase("solid").getNumberOfMolesInPhase();
    System.out.println("Precipitated amount: " + precipAmount + " kg");
}

Pressure-Induced Precipitation

// Analyze asphaltene stability vs pressure (common during depressurization)
double temperature = 100.0 + 273.15;  // K
double[] pressures = {400, 350, 300, 250, 200, 150, 100, 50};  // bara

System.out.println("Pressure (bara) | Asphaltene Phase | Amount");
System.out.println("----------------------------------------------");

for (double pressure : pressures) {
    SystemSrkCPAstatoil system = fluid.clone();
    system.setTemperature(temperature);
    system.setPressure(pressure);
    
    ThermodynamicOperations ops = new ThermodynamicOperations(system);
    ops.TPflash();
    
    String phase = system.hasPhaseType("solid") ? "Precipitated" : "Dissolved";
    double amount = system.hasPhaseType("solid") ? 
        system.getPhase("solid").getNumberOfMolesInPhase() : 0.0;
    
    System.out.printf("%8.0f        | %12s     | %.4f%n", 
        pressure, phase, amount);
}

Gas Injection Effect

// Evaluate asphaltene stability during CO2/gas injection
SystemSrkCPAstatoil baseFluid = createReservoirFluid();
AsphalteneCharacterization asphChar = new AsphalteneCharacterization(
    0.40, 0.30, 0.25, 0.05
);

double[] injectionRatios = {0.0, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30};

System.out.println("CO2 Injection Effect on Asphaltene Stability");
System.out.println("--------------------------------------------");

for (double ratio : injectionRatios) {
    SystemSrkCPAstatoil fluid = baseFluid.clone();
    
    // Add injection gas
    double totalMoles = fluid.getTotalNumberOfMoles();
    fluid.addComponent("CO2", totalMoles * ratio / (1 - ratio));
    
    // Flash at reservoir conditions
    fluid.setTemperature(373.15);
    fluid.setPressure(250.0);
    
    ThermodynamicOperations ops = new ThermodynamicOperations(fluid);
    ops.TPflash();
    
    boolean precipitated = fluid.hasPhaseType("solid");
    System.out.printf("CO2: %5.1f%% | Precipitation: %s%n",
        ratio * 100, precipitated ? "YES" : "NO");
}

De Boer Screening

Overview

The De Boer plot is a screening method for asphaltene precipitation risk based on:

De Boer Correlation

\[\Delta\rho = \rho_{res} - \rho_{sat}\]

The risk is assessed by plotting $P_{res} - P_{sat}$ vs $\Delta\rho$:

Region Risk Level
Below lower curve Low risk
Between curves Moderate risk
Above upper curve High risk

Implementation

// De Boer screening calculation
double reservoirPressure = 350.0;  // bara
double saturationPressure = 180.0;  // bara (bubble point)
double reservoirDensity = 650.0;    // kg/m³
double saturationDensity = 580.0;   // kg/m³ (at bubble point)

double deltaP = reservoirPressure - saturationPressure;
double deltaRho = reservoirDensity - saturationDensity;

// De Boer risk assessment
String risk;
if (deltaP > 200 && deltaRho > 100) {
    risk = "HIGH - Asphaltene precipitation very likely";
} else if (deltaP > 100 || deltaRho > 50) {
    risk = "MODERATE - Monitor conditions carefully";
} else {
    risk = "LOW - Unlikely to have problems";
}

System.out.println("De Boer Screening Results:");
System.out.println("ΔP (res - sat): " + deltaP + " bar");
System.out.println("Δρ (res - sat): " + deltaRho + " kg/m³");
System.out.println("Risk: " + risk);

Best Practices

SARA Data Quality

  1. Laboratory method: Ensure consistent SARA analysis method (ASTM D2007, ASTM D4124)
  2. Sample handling: Prevent oxidation and evaporation
  3. Reproducibility: Use average of multiple analyses

Model Tuning

  1. Onset pressure: Tune association parameters to match experimental onset
  2. Amount precipitated: Validate against filtration experiments
  3. Temperature dependence: Check stability at multiple temperatures

Operational Recommendations

CII Range Recommendation
< 0.7 Standard operations
0.7-0.9 Regular monitoring, consider inhibitors
> 0.9 Inhibitor treatment, pressure management

See Also