Purpose

DeBoerAsphalteneScreening places an oil on NeqSim’s implementation of the De Boer undersaturation-pressure versus live-oil-density chart. Use it for early triage: it can identify cases that merit laboratory work or a calibrated thermodynamic study.

The result is an empirical risk category. It is not an asphaltene-onset pressure, a deposition model, or a probability of failure.

Inputs and units

Provide all three values for the same reservoir fluid and condition basis.

Input	NeqSim unit	Interpretation
Reservoir pressure	bara	Current or scenario reservoir pressure
Saturation pressure	bara	Bubble-point pressure at reservoir temperature
In-situ oil density	kg/m³	Live-oil density at reservoir pressure and temperature

NeqSim calculates the undersaturation pressure as

\[\Delta P = P_{\mathrm{reservoir}} - P_{\mathrm{saturation}}.\]

Because both pressures are absolute, their difference is in bar. Do not pass gauge pressure for one input and absolute pressure for the other.

Executable screening example

The example uses explicit measured or previously calculated properties, so it isolates the screening correlation from fluid-model uncertainty. Java assertions document the expected result and are enabled by the documentation test.

import neqsim.pvtsimulation.flowassurance.DeBoerAsphalteneScreening;
import neqsim.pvtsimulation.flowassurance.DeBoerAsphalteneScreening.DeBoerRisk;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;

public final class DeBoerScreeningExample {
  private static final Logger logger =
      LogManager.getLogger(DeBoerScreeningExample.class);

  private DeBoerScreeningExample() {}

  public static void main(String[] args) {
    double reservoirPressureBara = 350.0;
    double saturationPressureBara = 150.0;
    double liveOilDensityKgM3 = 750.0;

    DeBoerAsphalteneScreening screening =
        new DeBoerAsphalteneScreening(
            reservoirPressureBara, saturationPressureBara, liveOilDensityKgM3);

    DeBoerRisk risk = screening.evaluateRisk();
    double riskIndex = screening.calculateRiskIndex();

    assert risk == DeBoerRisk.MODERATE_PROBLEM;
    assert Double.isFinite(riskIndex);
    assert Math.abs(riskIndex - 1.6) < 1.0e-12;

    logger.info(
        "De Boer screen: risk={}, index={}, undersaturation={} bar",
        risk,
        riskIndex,
        screening.getUndersaturationPressure());
  }
}

For these inputs, $\Delta P = 200$ bar. The current implementation classifies the case as MODERATE_PROBLEM and returns a risk index of 1.6. The assertions, rather than a copied console transcript, are the maintained result contract.

Interpreting the API

Risk category

evaluateRisk() returns one of four DeBoerRisk values:

Enum value	Screening meaning	Engineering response
NO_PROBLEM	Below the lowest implemented boundary	Record assumptions; monitor if conditions or fluid properties change
SLIGHT_PROBLEM	Above the no-problem boundary	Review data quality and consider laboratory screening
MODERATE_PROBLEM	Above the slight-problem boundary	Escalate to measured onset/deposition work and mitigation evaluation
SEVERE_PROBLEM	Above the severe-problem boundary	Treat as a strong screening flag; obtain specialist validation

These labels report position relative to the implemented boundary curves. They do not by themselves establish operating limits.

Risk index

calculateRiskIndex() divides the actual undersaturation by the implementation’s lower problem boundary for the supplied density. It is an implementation-specific screening ratio, not a probability or a universal severity scale. If setAsphalteneContent(...) is used, NeqSim applies an additional heuristic multiplier; document the supplied weight fraction and sensitivity when using that option.

Thermodynamic-system constructor

The constructor that accepts a SystemInterface can calculate saturation pressure and density from a fluid model. In that workflow:

• characterize and tune the fluid before screening;
• set reservoir temperature in kelvin and pressure in bara;
• check that bubble-point and live-oil-density calculations are finite and physically credible;
• preserve the measured-property screen as a comparison when suitable data exist.

A fluid model adds property-model uncertainty; it does not convert the empirical chart into a thermodynamic precipitation model.

Applicability and limitations

Use the screen as one line of evidence. It does not predict deposition rate, plugging, or inhibitor dose. It also does not represent changes in composition caused by gas injection, blending, biodegradation, or production history unless those changes are reflected in defensible input properties.

Before an operating or design decision:

1. check pressure basis, temperature basis, density units, and representative sampling;
2. compare nearby depletion or injection scenarios, especially near a category boundary;
3. validate against measured SARA data and onset/deposition observations;
4. use a calibrated model when composition effects or a pressure-temperature envelope matter; and
5. retain uncertainty margins appropriate to the consequence of plugging or deposition.

For deeper analysis, see Asphaltene modeling overview, CPA calculations, and method comparison.

Verification contract

DeBoerScreeningDocumentationTest extracts the exact marked Java block, requires it to be the only Java fence on this page, compiles it for Java 8, enables assertions, and runs main. The test also protects the input units and the limitations above from drifting into unsupported claims.