SeparatorEfficiency GasScrubber ThreePhase

Note: This is an auto-generated Markdown version of the Jupyter notebook SeparatorEfficiency_GasScrubber_ThreePhase.ipynb. You can also view it on nbviewer or open in Google Colab.

Separator & Gas Scrubber Separation Efficiency

This notebook demonstrates the separation-efficiency report for a two-phase gas scrubber and a three-phase separator in NeqSim.

SeparatorMechanicalDesign.calculateSeparationEfficiency() returns a SeparatorEfficiencyReport that combines:

  1. Physics-based entrainment / carry-under (droplet size distributions + grade efficiency curves + the internals database), and
  2. a per-internal Souders-Brown K-factor operating window — is the mist mat / vane pack / cyclone below turndown, in range, or flooding?

The K-factor window comes from resources/designdata/SeparatorInternals.csv (MinKFactor_m_s / MaxKFactor_m_s, open literature).

The report is read-only — it does not change what run() does. Applying the physics model at run time is a separate opt-in switch (setEfficiencyModelEnabled(true/false)); the default keeps the legacy behaviour of no entrainment or manually specified setEntrainment(...).

# --- NeqSim workspace setup (loads Java classes from target/classes) ---
import os
import sys
from pathlib import Path


def find_neqsim_project_root():
    env_root = os.environ.get("NEQSIM_PROJECT_ROOT")
    candidates = []
    if env_root:
        candidates.append(Path(env_root).resolve())
    here = Path.cwd().resolve()
    candidates.extend([here] + list(here.parents))
    for c in candidates:
        if (c / "pom.xml").exists() and (c / "devtools" / "neqsim_dev_setup.py").exists():
            return c
    raise RuntimeError("Could not find NeqSim project root. Set NEQSIM_PROJECT_ROOT.")


PROJECT_ROOT = find_neqsim_project_root()
sys.path.insert(0, str(PROJECT_ROOT / "devtools"))

from neqsim_dev_setup import neqsim_init, neqsim_classes

ns = neqsim_init(project_root=PROJECT_ROOT, recompile=False, verbose=True)
ns = neqsim_classes(ns)
print("NeqSim classes loaded from", PROJECT_ROOT / "target" / "classes")
Output ``` NeqSim project root: C:\Users\ESOL\Documents\GitHub\neqsim Classpath: 1. C:\Users\ESOL\Documents\GitHub\neqsim\target\classes 2. C:\Users\ESOL\Documents\GitHub\neqsim\src\main\resources 3. C:\Users\ESOL\.m2\repository\com\h2database\h2\2.4.240\h2-2.4.240.jar 4. C:\Users\ESOL\.m2\repository\org\apache\logging\log4j\log4j-api\2.26.1\log4j-api-2.26.1.jar 5. C:\Users\ESOL\.m2\repository\org\apache\logging\log4j\log4j-core\2.26.1\log4j-core-2.26.1.jar 6. C:\Users\ESOL\.m2\repository\com\thoughtworks\xstream\xstream\1.4.21\xstream-1.4.21.jar 7. C:\Users\ESOL\.m2\repository\io\github\x-stream\mxparser\1.2.2\mxparser-1.2.2.jar 8. C:\Users\ESOL\.m2\repository\xmlpull\xmlpull\1.1.3.1\xmlpull-1.1.3.1.jar 9. C:\Users\ESOL\.m2\repository\org\apache\commons\commons-lang3\3.20.0\commons-lang3-3.20.0.jar 10. C:\Users\ESOL\.m2\repository\org\apache\commons\commons-math3\3.6.1\commons-math3-3.6.1.jar 11. C:\Users\ESOL\.m2\repository\org\ejml\ejml-all\0.46.0\ejml-all-0.46.0.jar 12. C:\Users\ESOL\.m2\repository\org\ejml\ejml-core\0.46.0\ejml-core-0.46.0.jar 13. C:\Users\ESOL\.m2\repository\org\ejml\ejml-fdense\0.46.0\ejml-fdense-0.46.0.jar 14. C:\Users\ESOL\.m2\repository\org\ejml\ejml-ddense\0.46.0\ejml-ddense-0.46.0.jar 15. C:\Users\ESOL\.m2\repository\org\ejml\ejml-cdense\0.46.0\ejml-cdense-0.46.0.jar 16. C:\Users\ESOL\.m2\repository\org\ejml\ejml-zdense\0.46.0\ejml-zdense-0.46.0.jar 17. C:\Users\ESOL\.m2\repository\org\ejml\ejml-dsparse\0.46.0\ejml-dsparse-0.46.0.jar 18. C:\Users\ESOL\.m2\repository\org\ejml\ejml-simple\0.46.0\ejml-simple-0.46.0.jar 19. C:\Users\ESOL\.m2\repository\org\ejml\ejml-fsparse\0.46.0\ejml-fsparse-0.46.0.jar 20. C:\Users\ESOL\.m2\repository\gov\nist\math\jama\1.0.3\jama-1.0.3.jar 21. C:\Users\ESOL\.m2\repository\org\jfree\jcommon\1.0.24\jcommon-1.0.24.jar 22. C:\Users\ESOL\.m2\repository\org\jfree\jfreechart\1.5.6\jfreechart-1.5.6.jar 23. C:\Users\ESOL\.m2\repository\com\googlecode\matrix-toolkits-java\mtj\1.0.4\mtj-1.0.4.jar 24. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\all\1.1.2\all-1.1.2.pom 25. C:\Users\ESOL\.m2\repository\net\sourceforge\f2j\arpack_combined_all\0.1\arpack_combined_all-0.1.jar 26. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\core\1.1.2\core-1.1.2.jar 27. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_ref-osx-x86_64\1.1\netlib-native_ref-osx-x86_64-1.1-natives.jar 28. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\native_ref-java\1.1\native_ref-java-1.1.jar 29. C:\Users\ESOL\.m2\repository\com\github\fommil\jniloader\1.1\jniloader-1.1.jar 30. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_ref-linux-x86_64\1.1\netlib-native_ref-linux-x86_64-1.1-natives.jar 31. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_ref-linux-i686\1.1\netlib-native_ref-linux-i686-1.1-natives.jar 32. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_ref-win-x86_64\1.1\netlib-native_ref-win-x86_64-1.1-natives.jar 33. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_ref-win-i686\1.1\netlib-native_ref-win-i686-1.1-natives.jar 34. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_ref-linux-armhf\1.1\netlib-native_ref-linux-armhf-1.1-natives.jar 35. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_system-osx-x86_64\1.1\netlib-native_system-osx-x86_64-1.1-natives.jar 36. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\native_system-java\1.1\native_system-java-1.1.jar 37. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_system-linux-x86_64\1.1\netlib-native_system-linux-x86_64-1.1-natives.jar 38. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_system-linux-i686\1.1\netlib-native_system-linux-i686-1.1-natives.jar 39. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_system-linux-armhf\1.1\netlib-native_system-linux-armhf-1.1-natives.jar 40. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_system-win-x86_64\1.1\netlib-native_system-win-x86_64-1.1-natives.jar 41. C:\Users\ESOL\.m2\repository\com\github\fommil\netlib\netlib-native_system-win-i686\1.1\netlib-native_system-win-i686-1.1-natives.jar 42. C:\Users\ESOL\.m2\repository\com\google\code\gson\gson\2.14.0\gson-2.14.0.jar 43. C:\Users\ESOL\.m2\repository\com\google\errorprone\error_prone_annotations\2.48.0\error_prone_annotations-2.48.0.jar 44. C:\Users\ESOL\.m2\repository\com\fasterxml\jackson\core\jackson-databind\2.22.0\jackson-databind-2.22.0.jar 45. C:\Users\ESOL\.m2\repository\com\fasterxml\jackson\core\jackson-annotations\2.22\jackson-annotations-2.22.jar 46. C:\Users\ESOL\.m2\repository\com\fasterxml\jackson\core\jackson-core\2.22.0\jackson-core-2.22.0.jar 47. C:\Users\ESOL\.m2\repository\com\fasterxml\jackson\dataformat\jackson-dataformat-yaml\2.22.0\jackson-dataformat-yaml-2.22.0.jar 48. C:\Users\ESOL\.m2\repository\org\yaml\snakeyaml\2.5\snakeyaml-2.5.jar JVM started: C:\Users\ESOL\graalvm\graalvm-jdk-25.0.1+8.1\bin\server\jvm.dll Ready — call neqsim_classes(ns) to import classes All NeqSim classes imported OK NeqSim classes loaded from C:\Users\ESOL\Documents\GitHub\neqsim\target\classes ``` 
import json
import numpy as np
import matplotlib.pyplot as plt

GasScrubber = ns.JClass("neqsim.process.equipment.separator.GasScrubber")


def report_to_dict(report):
    """Parse a SeparatorEfficiencyReport into a Python dict."""
    return json.loads(str(report.toJson()))


def print_windows(rep):
    for w in rep["internals"]:
        print("  %-18s %-20s K=%.3f in [%.3f, %.3f]  util=%.2f" % (
            w["name"], w["status"], w["operatingKFactor_m_s"],
            w["minKFactor_m_s"], w["maxKFactor_m_s"], w["utilization"]))

Part 1 — Two-phase gas scrubber

A wet gas (methane with a little condensate) enters a vertical GasScrubber. We size it, fit a standard wire-mesh mist mat, and assess its efficiency and K-factor window.

fluid = ns.SystemSrkEos(273.15 + 25.0, 60.0)
fluid.addComponent("methane", 0.92)
fluid.addComponent("propane", 0.03)
fluid.addComponent("n-heptane", 0.05)
fluid.setMixingRule("classic")

feed = ns.Stream("wet gas", fluid)
feed.setFlowRate(45000.0, "kg/hr")
feed.setTemperature(25.0, "C")
feed.setPressure(60.0, "bara")
feed.run()

scrubber = GasScrubber("inlet scrubber", feed)
scrubber.run()

design = scrubber.getMechanicalDesign()
design.calcDesign()
design.setDesign()                      # push the sized diameter to the scrubber

design.setDemisterType("wire_mesh")
design.setDemisterSubType("Standard Knitted")

report = design.calculateSeparationEfficiency()
rep = report_to_dict(report)

print("Scrubber inner diameter : %.3f m" % design.getInnerDiameter())
print("Operating K-factor      : %.3f m/s" % rep["operatingKFactor_m_s"])
print("Gas-liquid efficiency   : %.4f" % rep["overallGasLiquidEfficiency"])
print("Mist eliminator flooded : %s" % rep["mistEliminatorFlooded"])
print("Verdict                 : %s" % rep["verdict"])
print("K-factor windows:")
print_windows(rep)
Output ``` Scrubber inner diameter : 0.855 m Operating K-factor : 0.100 m/s Gas-liquid efficiency : 0.9947 Mist eliminator flooded : False Verdict : GOOD_PERFORMANCE K-factor windows: mist eliminator IN_RANGE K=0.100 in [0.020, 0.107] util=0.93 ``` 
w = rep["internals"][0]
fig, ax = plt.subplots(figsize=(7.5, 2.6))
ax.axvspan(w["minKFactor_m_s"], w["maxKFactor_m_s"], color="#bfe3bf",
           label="good range [Kmin, Kmax]")
ax.axvline(w["operatingKFactor_m_s"], color="#c0392b", lw=2.5, label="operating K")
ax.set_xlim(0, max(w["maxKFactor_m_s"] * 1.4, w["operatingKFactor_m_s"] * 1.2))
ax.set_yticks([])
ax.set_xlabel("Souders-Brown K-factor [m/s]")
ax.set_title("Mist eliminator operating window - %s (%s)" % (w["type"], w["status"]))
ax.legend(loc="upper right", fontsize=9)
ax.grid(True, axis="x", alpha=0.3)
plt.tight_layout()
plt.show()

Interpretation. If the operating K sits inside the green band, the mist mat is in its good performance range. Near / above Kmax the mat starts to flood and re-entrain captured liquid; well below Kmin the gas load is too low for effective inertial capture (turndown limit).

Part 2 — Three-phase separator (gas / oil / water)

A well fluid with gas, condensate and water enters a ThreePhaseSeparator. We first produce the read-only report (efficiency model OFF, so run() is unchanged), then turn the physics model on so run() applies the computed carry-over.

f3 = ns.SystemSrkCPAstatoil(273.15 + 45.0, 50.0)
f3.addComponent("methane", 0.70)
f3.addComponent("propane", 0.05)
f3.addComponent("nC10", 0.15)
f3.addComponent("water", 0.10)
f3.setMixingRule(10)
f3.setMultiPhaseCheck(True)

feed3 = ns.Stream("well fluid", f3)
feed3.setFlowRate(90000.0, "kg/hr")
feed3.setTemperature(45.0, "C")
feed3.setPressure(50.0, "bara")
feed3.run()

sep3 = ns.ThreePhaseSeparator("1st stage separator", feed3)
sep3.run()

d3 = sep3.getMechanicalDesign()
d3.calcDesign()
d3.setDesign()
d3.setDemisterType("vane_pack")         # vane pack: wider K window than wire mesh

# 1) Read-only assessment (efficiency model OFF by default -> run() unchanged)
print("Efficiency model enabled (default):", bool(d3.isEfficiencyModelEnabled()))
rep3 = report_to_dict(d3.calculateSeparationEfficiency())
print("three-phase :", rep3["threePhase"], "| verdict:", rep3["verdict"])
print("operating K : %.3f m/s | gas-liquid eff: %.4f" % (
    rep3["operatingKFactor_m_s"], rep3["overallGasLiquidEfficiency"]))
print_windows(rep3)

# 2) Turn the physics model ON so run() applies computed entrainment / carry-under
d3.setEfficiencyModelEnabled(True)
sep3.run()
print("\nEfficiency model enabled now       :", bool(d3.isEfficiencyModelEnabled()))
print("Separator detailed entrainment on   :", bool(sep3.isDetailedEntrainmentCalculation()))

rep3b = report_to_dict(d3.calculateSeparationEfficiency())
print("\nEntrainment / carry-under fractions (three-phase):")
for k, v in rep3b["entrainment"].items():
    print("  %-20s %.3e" % (k, v))
Output ``` Efficiency model enabled (default): False three-phase : True | verdict: MARGINAL_EFFICIENCY operating K : 0.110 m/s | gas-liquid eff: 0.9865 mist eliminator IN_RANGE K=0.110 in [0.020, 0.150] util=0.73 Efficiency model enabled now : True Separator detailed entrainment on : True Entrainment / carry-under fractions (three-phase): oilInGasFraction 1.353e-02 waterInGasFraction 1.353e-02 gasInOilFraction 3.000e-01 gasInWaterFraction 3.000e-01 oilInWaterFraction 1.702e-02 waterInOilFraction 1.298e-02 ``` 
ent = rep3b["entrainment"]
labels = list(ent.keys())
vals = [max(float(ent[k]), 1e-9) for k in labels]  # floor for log axis

fig, ax = plt.subplots(figsize=(8.5, 3.4))
ax.bar(labels, vals, color="#2c7fb8")
ax.set_yscale("log")
ax.set_ylabel("fraction [-] (log, floored at 1e-9)")
ax.set_title("Three-phase separator entrainment / carry-under fractions")
plt.xticks(rotation=30, ha="right")
ax.grid(True, axis="y", alpha=0.3)
plt.tight_layout()
plt.show()

The three-phase report additionally carries the liquid-liquid fractions oilInWaterFraction (oil in produced water) and waterInOilFraction (BS&W in oil), computed from oil/water droplet settling in the vessel.

Part 3 — Turndown: operating K vs feed rate

Keeping the sized vessel diameter fixed, we sweep the gas feed rate. As flow drops the operating K falls through the mist-eliminator window — this is exactly the “good performance range” concept: too little flow → below turndown, too much → flooding.

# Vessel is already sized (Part 1). Keep the diameter fixed and vary flow.
flows = np.linspace(8000.0, 90000.0, 12)  # kg/hr
kops = []
for fr in flows:
    feed.setFlowRate(float(fr), "kg/hr")
    feed.run()
    scrubber.run()
    r = report_to_dict(design.calculateSeparationEfficiency())  # no re-sizing
    kops.append(r["operatingKFactor_m_s"])

# restore design flow
feed.setFlowRate(45000.0, "kg/hr")
feed.run()
scrubber.run()

w0 = rep["internals"][0]
fig, ax = plt.subplots(figsize=(8.5, 4.2))
ax.axhspan(w0["minKFactor_m_s"], w0["maxKFactor_m_s"], color="#bfe3bf", alpha=0.6,
           label="good range [Kmin, Kmax]")
ax.axhline(w0["minKFactor_m_s"], color="#2e7d32", ls="--", lw=1)
ax.axhline(w0["maxKFactor_m_s"], color="#2e7d32", ls="--", lw=1)
ax.plot(flows / 1000.0, kops, "o-", color="#c0392b", label="operating K")
ax.set_xlabel("gas feed rate [tonne/hr]")
ax.set_ylabel("operating K-factor [m/s]")
ax.set_title("Scrubber turndown: operating K vs feed rate (wire-mesh window)")
ax.legend()
ax.grid(True, alpha=0.3)
plt.tight_layout()
plt.show()

Summary

See docs/process/equipment/separators.md (Separation Efficiency Report) and docs/process/equipment/separator-entrainment-modeling.md.