De Boer Asphaltene Screening

Overview

The De Boer correlation is an empirical screening method developed from field observations of asphaltene problems in producing oil fields. It provides a quick, conservative assessment of asphaltene precipitation risk without requiring detailed thermodynamic modeling.

Theory

De Boer Plot

De Boer et al. (1995) analyzed field data and found that asphaltene problems correlate with two parameters:

Undersaturation Pressure ($\Delta P$): The difference between reservoir pressure and bubble point
In-situ Oil Density ($\rho$): Density of the live oil at reservoir conditions

\[\Delta P = P_{\text{reservoir}} - P_{\text{bubble}}\]

The plot divides the $\Delta P$ vs $\rho$ space into risk zones:

Undersaturation ΔP [bar]
    ^
400 |     SEVERE      |
    |   PROBLEM       |
300 |                 | MODERATE
    |  ─────────────  | PROBLEM
200 |                 |
    |    SLIGHT       |
100 |    PROBLEM      |
    |  ───────────────┼───────────────
  0 |    NO PROBLEM   |
    +─────────────────┼───────────────> ρ [kg/m³]
                    700            800

Risk Zone Boundaries

The correlation uses empirical boundaries:

Zone	Description	Boundary
No Problem	Low risk	$\Delta P < f_1(\rho)$
Slight Problem	Minor risk	$f_1(\rho) < \Delta P < f_2(\rho)$
Moderate Problem	Moderate risk	$f_2(\rho) < \Delta P < f_3(\rho)$
Severe Problem	High risk	$\Delta P > f_3(\rho)$

Where $f_i(\rho)$ are linear functions of density.

Physical Interpretation

High undersaturation + Low density = Severe risk
- Light, gas-rich oils become significantly denser as pressure drops
- Large solubility parameter change destabilizes asphaltenes
Low undersaturation + High density = Low risk
- Heavy oils change less during production
- Asphaltenes more naturally stable

Implementation

Basic Usage

import neqsim.pvtsimulation.flowassurance.DeBoerAsphalteneScreening;

// Create screening with reservoir data
DeBoerAsphalteneScreening screening = new DeBoerAsphalteneScreening(
    350.0,  // Reservoir pressure [bar]
    150.0,  // Bubble point pressure [bar]
    720.0   // In-situ oil density [kg/m³]
);

// Get risk assessment
String riskLevel = screening.evaluateRisk();
System.out.println("Risk Level: " + riskLevel);

Risk Levels

The method returns one of four risk categories:

public enum RiskLevel {
    NO_PROBLEM,        // No action needed
    SLIGHT_PROBLEM,    // Monitor during production
    MODERATE_PROBLEM,  // Consider mitigation
    SEVERE_PROBLEM     // Mitigation required
}

// Usage
String risk = screening.evaluateRisk();
switch (risk) {
    case "NO_PROBLEM":
        System.out.println("No asphaltene issues expected");
        break;
    case "SLIGHT_PROBLEM":
        System.out.println("Minor issues possible - monitor");
        break;
    case "MODERATE_PROBLEM":
        System.out.println("Significant risk - plan mitigation");
        break;
    case "SEVERE_PROBLEM":
        System.out.println("High risk - mitigation required");
        break;
}

Quantitative Risk Index

For more nuanced assessment:

double riskIndex = screening.calculateRiskIndex();

The risk index interpretation:

Index Value	Interpretation
< 0	Stable, no precipitation expected
0 - 0.3	Low risk
0.3 - 0.7	Moderate risk
> 0.7	High risk, likely problems

Detailed Report

String report = screening.performScreening();
System.out.println(report);

Output:

De Boer Asphaltene Screening Results
====================================
Reservoir Pressure: 350.0 bar
Bubble Point Pressure: 150.0 bar
Undersaturation: 200.0 bar
In-situ Density: 720.0 kg/m³

Risk Assessment: MODERATE_PROBLEM
Risk Index: 0.55

Recommendation: Moderate asphaltene risk. 
Consider preventive measures and monitoring plan.

Advanced Usage

Sensitivity Analysis

Evaluate risk over a range of conditions:

import neqsim.pvtsimulation.flowassurance.DeBoerAsphalteneScreening;

// Base case
double bubblePoint = 150.0;
double density = 720.0;

// Pressure depletion scenario
System.out.println("Pressure Depletion Analysis:");
for (double pRes = 400.0; pRes >= 160.0; pRes -= 20.0) {
    DeBoerAsphalteneScreening screening = 
        new DeBoerAsphalteneScreening(pRes, bubblePoint, density);
    
    double deltaP = pRes - bubblePoint;
    String risk = screening.evaluateRisk();
    
    System.out.printf("P_res = %.0f bar, ΔP = %.0f bar: %s%n", 
                      pRes, deltaP, risk);
}

Generate Plot Data

Create data for visualization:

double[][] plotData = screening.generatePlotData(
    650.0,   // Min density [kg/m³]
    850.0,   // Max density [kg/m³]
    25.0     // Density step [kg/m³]
);

// plotData[0] = density values
// plotData[1] = undersaturation values for "slight problem" boundary
// plotData[2] = undersaturation values for "moderate problem" boundary
// plotData[3] = undersaturation values for "severe problem" boundary

// Export for plotting
System.out.println("Density,Slight,Moderate,Severe");
for (int i = 0; i < plotData[0].length; i++) {
    System.out.printf("%.1f,%.1f,%.1f,%.1f%n",
        plotData[0][i], plotData[1][i], plotData[2][i], plotData[3][i]);
}

Batch Screening

Screen multiple samples:

// Sample data: [reservoir P, bubble P, density]
double[][] samples = {
    {350.0, 150.0, 720.0},  // Sample A
    {280.0, 100.0, 780.0},  // Sample B
    {400.0, 200.0, 690.0},  // Sample C
    {300.0, 180.0, 750.0}   // Sample D
};

String[] sampleNames = {"A", "B", "C", "D"};

System.out.println("Sample | ΔP [bar] | ρ [kg/m³] | Risk Level");
System.out.println("-------+----------+-----------+----------------");

for (int i = 0; i < samples.length; i++) {
    DeBoerAsphalteneScreening screening = new DeBoerAsphalteneScreening(
        samples[i][0], samples[i][1], samples[i][2]
    );
    
    double deltaP = samples[i][0] - samples[i][1];
    String risk = screening.evaluateRisk();
    
    System.out.printf("   %s   |  %5.0f   |   %5.0f   | %s%n",
        sampleNames[i], deltaP, samples[i][2], risk);
}

Input Requirements

Required Data

Parameter	Unit	How to Obtain
Reservoir Pressure	bar	Formation test (RFT/MDT)
Bubble Point Pressure	bar	PVT lab test or correlation
In-situ Density	kg/m³	PVT lab or flash calculation

Estimating In-situ Density

If density at reservoir conditions is not available:

import neqsim.thermo.system.SystemSrkEos;
import neqsim.thermodynamicoperations.ThermodynamicOperations;

// Create fluid from composition
SystemSrkEos fluid = new SystemSrkEos(373.15, 350.0);  // Reservoir T, P
fluid.addComponent("methane", 0.40);
fluid.addComponent("n-heptane", 0.55);
fluid.addComponent("n-decane", 0.05);
fluid.setMixingRule("classic");

// Flash to get density
ThermodynamicOperations ops = new ThermodynamicOperations(fluid);
ops.TPflash();

// Get liquid density
double density = fluid.getPhase("oil").getDensity("kg/m3");
System.out.println("In-situ density: " + density + " kg/m³");

Limitations

What De Boer Cannot Do

No onset pressure prediction: Cannot tell when precipitation starts
No quantity estimation: Cannot predict how much precipitates
No temperature effects: Only considers isothermal depletion
No composition sensitivity: Cannot evaluate blending/injection effects
No remediation modeling: Cannot assess inhibitor effectiveness

When to Use CPA Instead

Use thermodynamic modeling (CPA) when:

Precise onset pressure is needed
Evaluating gas injection (CO₂, hydrocarbon)
Assessing blending compatibility
Designing inhibitor treatments
Temperature effects are significant

Validation

Field Data Comparison

De Boer was validated against:

Gulf of Mexico fields
North Sea developments
Middle East reservoirs

The correlation correctly predicted:

85% of fields with problems
90% of fields without problems

Conservative Bias

The method is intentionally conservative:

May predict problems where none occur
Rarely misses actual problems
Suitable for screening (not design)

Example: Field Development Screening

import neqsim.pvtsimulation.flowassurance.DeBoerAsphalteneScreening;

// Field data for multiple reservoirs
String[] reservoirs = {"Alpha", "Beta", "Gamma", "Delta"};
double[] pRes = {380.0, 320.0, 290.0, 410.0};  // Reservoir pressure [bar]
double[] pBub = {180.0, 150.0, 120.0, 220.0};  // Bubble point [bar]
double[] rho = {710.0, 750.0, 800.0, 680.0};   // In-situ density [kg/m³]

System.out.println("Field Development Asphaltene Screening");
System.out.println("======================================\n");

int highRiskCount = 0;

for (int i = 0; i < reservoirs.length; i++) {
    DeBoerAsphalteneScreening screening = 
        new DeBoerAsphalteneScreening(pRes[i], pBub[i], rho[i]);
    
    String risk = screening.evaluateRisk();
    double riskIndex = screening.calculateRiskIndex();
    
    System.out.printf("Reservoir %s:%n", reservoirs[i]);
    System.out.printf("  P_res = %.0f bar, P_bub = %.0f bar, ρ = %.0f kg/m³%n",
                      pRes[i], pBub[i], rho[i]);
    System.out.printf("  Risk: %s (index: %.2f)%n%n", risk, riskIndex);
    
    if (risk.equals("SEVERE_PROBLEM") || risk.equals("MODERATE_PROBLEM")) {
        highRiskCount++;
    }
}

System.out.printf("Summary: %d of %d reservoirs require further analysis%n",
                  highRiskCount, reservoirs.length);

References

De Boer, R.B., Leerlooyer, K., Eigner, M.R.P., and van Bergen, A.R.D. (1995). “Screening of Crude Oils for Asphalt Precipitation: Theory, Practice, and the Selection of Inhibitors.” SPE Production & Facilities, 10(1), 55-61.
Hammami, A., and Ratulowski, J. (2007). “Precipitation and Deposition of Asphaltenes in Production Systems: A Flow Assurance Overview.” In Asphaltenes, Heavy Oils, and Petroleomics, Springer.
Akbarzadeh, K., et al. (2007). “Asphaltenes—Problematic but Rich in Potential.” Oilfield Review, 19(2), 22-43.

De Boer Asphaltene Screening

Comprehensive Java library for thermodynamic, physical property, and process simulation. NeqSim provides tools for PVT analysis, phase equilibria, transport properties, and full process simulation.

De Boer Asphaltene Screening

Overview

Theory

De Boer Plot

Risk Zone Boundaries

Physical Interpretation

Implementation

Basic Usage

Risk Levels

Quantitative Risk Index

Detailed Report

Advanced Usage

Sensitivity Analysis

Generate Plot Data

Batch Screening

Input Requirements

Required Data

Estimating In-situ Density

Limitations

What De Boer Cannot Do

When to Use CPA Instead

Validation

Field Data Comparison

Conservative Bias

Example: Field Development Screening

References

See Also