Offshore Platform Emission Reporting with NeqSim

Overview

This document provides guidance for calculating and reporting greenhouse gas (GHG) emissions from offshore oil and gas operations using NeqSim’s thermodynamic simulation capabilities.

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Table of Contents

1. Regulatory Framework
2. Emission Sources
3. Calculation Methods
4. NeqSim for Emission Integration
5. NeqSim API Reference
6. Produced Water Degassing
7. Virtual Measurement Methodology
8. Validation and Uncertainty
9. Literature References

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Regulatory Framework

Norwegian Continental Shelf (NCS)

Regulation	Description	Reference
Aktivitetsforskriften §70	Measurement and calculation of emissions	Lovdata
Rammeforskriften	Framework regulations for petroleum activities	Lovdata
CO2 Tax Act	Norwegian carbon tax (rate updated annually)	Skatteetaten

European Union

Regulation	Description	Reference
EU ETS Directive 2003/87/EC	Emissions trading system	EUR-Lex
MRV Regulation 2015/757	Monitoring, Reporting, Verification	EUR-Lex
Methane Regulation 2024/1787	Oil, gas & coal methane emissions	EUR-Lex

International Standards

Standard	Description	Reference
ISO 14064-1:2018	GHG quantification at organization level	ISO
IOGP Report 521	Estimating fugitive emissions	IOGP
API Compendium	Petroleum industry GHG methods	API

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Emission Sources

Offshore Platform Emission Categories

┌─────────────────────────────────────────────────────────────┐
│                 OFFSHORE PLATFORM EMISSIONS                  │
├──────────────────┬──────────────────┬───────────────────────┤
│   COMBUSTION     │    VENTING       │     FUGITIVE          │
│  (typically      │   (typically     │    (typically         │
│   dominant)      │     5-20%)       │       <5%)            │
├──────────────────┼──────────────────┼───────────────────────┤
│ • Gas turbines   │ • Cold vents     │ • Valve/flange leaks  │
│ • Diesel engines │ • Tank breathing │ • Compressor seals    │
│ • Flares         │ • PW degassing   │ • Pump seals          │
│ • Heaters        │ • TEG regeneration│ • Pipe connections   │
│ • Boilers        │ • Loading ops    │ • Instrumentation     │
└──────────────────┴──────────────────┴───────────────────────┘

*Note: Source distribution percentages vary significantly by facility type, age, and operations.*

Implementation Note: All emission sources shown above are supported in NeqSim. Key classes include:

• Combustion: GasTurbine, Flare, FlareStack, FurnaceBurner, DetailedEmissionsCalculator
• Venting: ProducedWaterDegassingSystem (multi-stage CPA-EoS), EmissionsCalculator, Tank
• Fugitive: CompressorMechanicalLosses (API 692 dry gas seals), EPA component count methods

See DetailedEmissionsCalculator for facility-level emission inventory calculations.

Key Emission Components

Component	GWP-100 (AR5)	Primary Sources
CO2	1	Combustion, dissolved gas venting
Methane (CH4)	28	Venting, fugitive leaks, incomplete combustion
nmVOC (C2+)	~2.2	Venting, storage tanks, loading
N2O	265	Flaring, combustion

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Calculation Methods

Method Comparison

Aspect	Conventional (Handbook)	Thermodynamic (NeqSim)
Approach	Empirical correlations with fixed factors	Rigorous phase equilibrium calculation
CO2 accounting	Simplified factors	Explicit component tracking
Salinity effects	Typically not included	Søreide-Whitson salting-out model
Temperature effects	Linear correlations	Full equation of state
Computational cost	Low (spreadsheet)	Moderate (requires simulator)
Regulatory acceptance	Widely established	Accepted under Aktivitetsforskriften §70

Conventional Method (Norwegian Handbook)

The traditional method from “Handbook for quantification of direct emissions from Norwegian petroleum industry” (Norsk olje og gass):

U_CH4 = f_CH4 × V_pw × ΔP × 10⁻⁶

Where:
  f_CH4  = 14 g/(m³·bar)   [Standard solubility factor]
  V_pw   = Produced water volume (m³)
  ΔP     = Pressure drop (bar)
  Result = Methane emission (tonnes)

Characteristics:

• Uses standardized solubility factors
• Established regulatory acceptance
• Simple implementation (spreadsheet-compatible)
• Does not include salinity correction
• Limited composition dependency

Thermodynamic Method (NeqSim)

Uses Cubic-Plus-Association (CPA) equation of state for rigorous vapor-liquid equilibrium, with the Søreide-Whitson model for salinity correction in produced water systems:

Capabilities:
• Accounts for actual fluid composition
• Includes all gas components (CO2, CH4, C2+, N2, H2S)
• Handles salinity/ionic effects via Søreide-Whitson model
• Temperature and pressure dependent
• Can be validated against lab PVT data
• Used in NeqSimLive for real-time emission monitoring

Considerations:
• Requires thermodynamic software or programming
• Model parameters should be validated for site-specific fluids
• More complex than handbook methods

NeqSimLive Integration: The Søreide-Whitson model is the primary thermodynamic model used in NeqSimLive for calculating emissions from produced water degassing on offshore platforms. See Søreide-Whitson Model Documentation for detailed model description and references.

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NeqSim Advantages for Emission Integration

Why NeqSim for Emission Calculations?

NeqSim provides capabilities for integrating emission calculations into industrial workflows, digital twins, and emerging decarbonization technologies.

Core Technical Advantages

Advantage	Description	Benefit
Physics-Based Modeling	Rigorous thermodynamic calculations using CPA, SRK, PR equations of state	Captures composition and condition effects
Full Component Accounting	Tracks CO2, CH4, nmVOC, H2S, N2	Comprehensive emission inventory
Composition Sensitivity	Tracks changing reservoir composition over field life	Time-varying emission profiles
Process Integration	Emission calculations embedded in full process simulation	Consistent material/energy balances
Open Source	Apache 2.0 license, transparent algorithms	Auditable, reproducible, no vendor lock-in

Integration Architecture

┌─────────────────────────────────────────────────────────────────────────┐
│                     NEQSIM EMISSION INTEGRATION                         │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                         │
│   ┌─────────────┐    ┌─────────────┐    ┌─────────────────────────┐    │
│   │   SENSORS   │───▶│   NEQSIM    │───▶│   EMISSION OUTPUTS      │    │
│   │  (P,T,F,x)  │    │   PROCESS   │    │                         │    │
│   └─────────────┘    │   MODEL     │    │  • Real-time kg/hr      │    │
│                      │             │    │  • Daily/annual totals  │    │
│   ┌─────────────┐    │  ┌───────┐  │    │  • CO2 equivalents      │    │
│   │   PROCESS   │───▶│  │THERMO │  │    │  • Regulatory reports   │    │
│   │   DESIGN    │    │  │ VLE   │  │    │  • Carbon tax liability │    │
│   └─────────────┘    │  └───────┘  │    └─────────────────────────┘    │
│                      │             │                                    │
│   ┌─────────────┐    │  ┌───────┐  │    ┌─────────────────────────┐    │
│   │ COMPOSITION │───▶│  │EMIT.  │  │───▶│   DOWNSTREAM SYSTEMS    │    │
│   │   ANALYSIS  │    │  │CALC.  │  │    │                         │    │
│   └─────────────┘    │  └───────┘  │    │  • SCADA/DCS            │    │
│                      └─────────────┘    │  • Digital Twins        │    │
│                                         │  • ESG Reporting        │    │
│                                         │  • MPC Controllers      │    │
│                                         └─────────────────────────┘    │
└─────────────────────────────────────────────────────────────────────────┘

Future Technology Enablement

1. Digital Twin Integration

NeqSim can support digital twins with embedded emission tracking:

Capability	Periodic Reporting	Online Calculation
Emission tracking	Periodic (monthly/quarterly)	Continuous or more frequent
What-if analysis	Limited to historical data	Full scenario modeling
Optimization scope	Process-focused	Can include emissions
Regulatory reporting	Manual compilation	Supports automation

Digital Twin Capabilities:
• Emission monitoring from process state
• Scenario-based emission forecasting
• Optimization with emission constraints
• Automated compliance reporting support

2. Model Predictive Control (MPC)

NeqSim emission calculations can be embedded in advanced process control:

┌─────────────────────────────────────────────────────────┐
│              MPC WITH EMISSION CONSTRAINTS              │
├─────────────────────────────────────────────────────────┤
│                                                         │
│   Minimize:  J = Σ (production_cost + carbon_tax)       │
│                                                         │
│   Subject to:                                           │
│     • Process constraints (P, T, flow limits)           │
│     • CO2eq_emissions ≤ permit_limit                    │
│     • Methane_intensity ≤ regulatory_target             │
│                                                         │
│   NeqSim provides:                                      │
│     • Real-time emission rate = f(process_state)        │
│     • Gradient ∂emissions/∂(manipulated_variables)      │
│     • Composition-dependent emission factors            │
│                                                         │
└─────────────────────────────────────────────────────────┘

3. Carbon Capture Integration

For CCUS (Carbon Capture, Utilization and Storage) process design:

Application	NeqSim Capability
Pre-combustion capture	CO2/H2 separation modeling
Post-combustion	Amine absorption/regeneration
Direct air capture	Low-concentration CO2 thermodynamics
CO2 transport	Dense phase CO2 properties
Geological storage	CO2-brine-rock interactions

4. Hydrogen & Ammonia Value Chains

NeqSim’s thermodynamic models support emerging clean energy vectors:

Blue Hydrogen Production:
  SMR/ATR → NeqSim emission tracking → CO2 capture sizing

Green Hydrogen:
  Electrolyzer → NeqSim compression → Storage/transport

Ammonia as Fuel:
  NH3 cracking → NeqSim separation → H2 purification
  
Each step: Embedded emission accounting with NeqSim

5. AI/ML Hybrid Models

NeqSim can provide a physics-based foundation for machine learning applications:

Approach	Description	Potential Benefit
Physics-Informed Neural Networks	NeqSim VLE as constraints	Improved convergence, physical consistency
Surrogate Models	NeqSim training data generation	Faster emission estimation
Soft Sensors	NeqSim-calibrated emission inferencing	Fill measurement gaps
Anomaly Detection	Compare measured vs NeqSim-predicted	Support leak detection

Comparison with Commercial Software

Feature	NeqSim	Commercial Tools
Cost	Free (Apache 2.0)	License fees vary
Transparency	Full source code access	Typically limited
Customization	Modify/extend freely	Vendor-dependent
Reproducibility	Version-controlled, auditable	Vendor-dependent
API Integration	Java, Python, REST	Varies by product
Regulatory Defense	Algorithms visible to auditors	Established vendor support
Long-term Availability	Open source community	Vendor support agreements
Validation/Certification	User responsibility	Often pre-validated

Industry 4.0 / IIoT Deployment

┌────────────────────────────────────────────────────────────────────────┐
│                    NEQSIM IN INDUSTRIAL IOT ARCHITECTURE               │
├────────────────────────────────────────────────────────────────────────┤
│                                                                        │
│  EDGE LAYER              PLATFORM LAYER           APPLICATION LAYER   │
│  ┌──────────┐            ┌──────────────┐         ┌────────────────┐  │
│  │ OPC-UA   │            │              │         │ ESG Dashboard  │  │
│  │ Gateway  │───────────▶│   NeqSim     │────────▶│                │  │
│  └──────────┘            │   Microservice│        │ • Live CO2eq   │  │
│                          │              │         │ • Trend charts │  │
│  ┌──────────┐            │  ┌────────┐  │         │ • Alerts       │  │
│  │ Process  │───────────▶│  │ Thermo │  │         │ • Reports      │  │
│  │ Historian│            │  │ Engine │  │         └────────────────┘  │
│  └──────────┘            │  └────────┘  │                             │
│                          │              │         ┌────────────────┐  │
│  ┌──────────┐            │  ┌────────┐  │         │ Carbon Trading │  │
│  │ Lab LIMS │───────────▶│  │Emission│  │────────▶│ Integration    │  │
│  │          │            │  │ Calc   │  │         │                │  │
│  └──────────┘            │  └────────┘  │         │ • ETS registry │  │
│                          │              │         │ • Offset calc  │  │
│                          └──────────────┘         └────────────────┘  │
│                                                                        │
└────────────────────────────────────────────────────────────────────────┘

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NeqSim API Reference

EmissionsCalculator Class

The EmissionsCalculator class provides comprehensive emission calculations from gas streams.

Java API

import neqsim.process.equipment.util.EmissionsCalculator;
import neqsim.process.equipment.separator.Separator;

// Create calculator from separator gas outlet
EmissionsCalculator calc = new EmissionsCalculator(separator.getGasOutStream());
calc.calculate();

// Get emission rates
double co2_kg_hr = calc.getCO2EmissionRate("kg/hr");
double ch4_kg_hr = calc.getMethaneEmissionRate("kg/hr");
double nmvoc_kg_hr = calc.getNMVOCEmissionRate("kg/hr");
double co2eq_tonnes_yr = calc.getCO2Equivalents("tonnes/year");

// Get gas composition
Map<String, Double> composition = calc.getGasCompositionMole();

// Compare with conventional method
double conv_ch4 = EmissionsCalculator.calculateConventionalCH4(waterVolume_m3, dP_bar);

Python API (via JPype)

from neqsim import jneqsim

# Access the EmissionsCalculator
EmissionsCalculator = jneqsim.process.equipment.util.EmissionsCalculator

# Create from a separator's gas outlet
calc = EmissionsCalculator(degasser.getGasOutStream())
calc.calculate()

# Get results
co2 = calc.getCO2EmissionRate("kg/hr")
ch4 = calc.getMethaneEmissionRate("kg/hr")
nmvoc = calc.getNMVOCEmissionRate("kg/hr")
co2eq = calc.getCO2Equivalents("tonnes/year")

# Gas composition (returns Java HashMap)
mole_comp = calc.getGasCompositionMole()
for comp in mole_comp.keySet():
    print(f"{comp}: {mole_comp.get(comp)*100:.2f}%")

GWP Constants

// IPCC AR5 100-year Global Warming Potentials
public static final double GWP_CO2 = 1.0;
public static final double GWP_METHANE = 28.0;  // CH4
public static final double GWP_NMVOC = 2.2;     // Average for C2-C5

Supported Units

Method	Supported Units
getCO2EmissionRate()	kg/sec, kg/hr, tonnes/day, tonnes/year
getMethaneEmissionRate()	kg/sec, kg/hr, tonnes/day, tonnes/year
getNMVOCEmissionRate()	kg/sec, kg/hr, tonnes/day, tonnes/year
getCO2Equivalents()	kg/sec, kg/hr, tonnes/day, tonnes/year
getCumulative*()	kg, tonnes

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Produced Water Degassing

Typical Process Configuration

Separator     Degasser      CFU          Caisson       Sea
(30+ bara) → (2-4 bara) → (1.1 bara) → (1.0 bara) → Discharge
    │            │            │            │
    └──── Pressure drops release dissolved gases ────┘

Multi-Stage Process Simulation

# Create produced water fluid (CPA equation of state)
produced_water = jneqsim.thermo.system.SystemSrkCPAstatoil(80 + 273.15, 30.0)
produced_water.addComponent("water", 0.90)
produced_water.addComponent("CO2", 0.03)
produced_water.addComponent("methane", 0.05)
produced_water.addComponent("ethane", 0.015)
produced_water.addComponent("propane", 0.005)
produced_water.setMixingRule(10)  # CPA mixing rule
produced_water.init(0)

# Create process equipment
inlet_stream = jneqsim.process.equipment.stream.Stream("Feed", produced_water)
inlet_stream.setFlowRate(100000, "kg/hr")
inlet_stream.run()

# Stage 1: Degasser (30 → 4 bara)
degasser_valve = jneqsim.process.equipment.valve.ThrottlingValve("V-1", inlet_stream)
degasser_valve.setOutletPressure(4.0, "bara")
degasser = jneqsim.process.equipment.separator.Separator("Degasser", degasser_valve.getOutletStream())

# Stage 2: CFU (4 → 1.1 bara)
cfu_valve = jneqsim.process.equipment.valve.ThrottlingValve("V-2", degasser.getLiquidOutStream())
cfu_valve.setOutletPressure(1.1, "bara")
cfu = jneqsim.process.equipment.separator.Separator("CFU", cfu_valve.getOutletStream())

# Run process
process = jneqsim.process.processmodel.ProcessSystem()
process.add(inlet_stream)
process.add(degasser_valve)
process.add(degasser)
process.add(cfu_valve)
process.add(cfu)
process.run()

# Calculate emissions from each stage
calc1 = EmissionsCalculator(degasser.getGasOutStream())
calc1.calculate()
calc2 = EmissionsCalculator(cfu.getGasOutStream())
calc2.calculate()

total_co2eq = calc1.getCO2Equivalents("tonnes/year") + calc2.getCO2Equivalents("tonnes/year")

Salinity Effects (Salting-Out) - Søreide-Whitson Model

Higher salinity reduces gas solubility, affecting emissions. NeqSim uses the Søreide-Whitson model to accurately account for this “salting-out” effect in produced water systems:

# Using Søreide-Whitson for accurate salinity correction
from neqsim import jneqsim

SystemSoreideWhitson = jneqsim.thermo.system.SystemSoreideWhitson

# Create produced water with Søreide-Whitson model
produced_water = SystemSoreideWhitson(273.15 + 80.0, 30.0)
produced_water.addComponent("water", 0.92)
produced_water.addComponent("methane", 0.05)
produced_water.addComponent("CO2", 0.02)
produced_water.addComponent("ethane", 0.01)

# Set formation water salinity (~80,000 ppm TDS)
produced_water.addSalinity("NaCl", 1.2, "mole/sec")  # Dominant salt
produced_water.addSalinity("CaCl2", 0.08, "mole/sec")

# The Søreide-Whitson model modifies the water alpha function:
# alpha = A² where A(Tr,cs) = 1 + 0.453[1-Tr(1-0.0103·cs^1.1)] + 0.0034(Tr^-3 - 1)
# This reduces gas solubility as salinity increases

The Søreide-Whitson model accounts for salinity effects through a modified Peng-Robinson alpha function for water. The magnitude of the salting-out effect depends on salinity level, salt type, gas species, and temperature:

Salinity (ppm TDS)	Approximate CH₄ Solubility Reduction*	Comment
0 (fresh water)	0% (baseline)	Reference state
35,000 (seawater)	~15-20%	Typical seawater conditions
100,000	~35-45%	High salinity formation water
200,000	~55-65%	Very high salinity

*Values are approximate and depend on temperature, pressure, and salt composition. Actual reduction should be calculated using the Søreide-Whitson model with site-specific conditions.

Reference: Søreide, I. & Whitson, C.H. (1992). “Peng-Robinson predictions for hydrocarbons, CO₂, N₂, and H₂S with pure water and NaCl brine”. Fluid Phase Equilibria, 77, 217-240. DOI: 10.1016/0378-3812(92)85105-H

For detailed model documentation, see Søreide-Whitson Model.

# Simplified salting-out estimation (for comparison/validation)
# Reference: Duan & Sun (2003) - Geochimica et Cosmochimica Acta

def salting_out_factor(salinity_ppm):
    """
    Estimate gas solubility reduction due to salinity.
    
    Args:
        salinity_ppm: Total dissolved solids (ppm or mg/L)
    
    Returns:
        Reduction factor (0.8 = 20% less soluble)
    """
    # Simplified Setschenow coefficient approach
    cs = 0.12  # Approximate for CH4 in NaCl
    molality = salinity_ppm / 58440 / (1 - salinity_ppm/1e6)
    return 10 ** (-cs * molality)

# Example: 35,000 ppm seawater
factor = salting_out_factor(35000)  # ~0.87
print(f"Gas solubility reduced to {factor*100:.0f}% of freshwater value")

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Virtual Measurement Methodology

Real-Time Integration (NeqSimLive)

NeqSim can be deployed as a “virtual sensor” for continuous emission monitoring. NeqSimLive uses the Søreide-Whitson thermodynamic model for produced water emission calculations, accounting for formation water salinity effects relevant for emission reporting on the Norwegian Continental Shelf.

┌─────────────────────────────────────────────────────────────┐
│                    VIRTUAL MEASUREMENT FLOW                  │
│                    (NeqSimLive Architecture)                 │
├─────────────────────────────────────────────────────────────┤
│                                                              │
│   DCS/SCADA ──► NeqSimLive ──► Emission Rates ──► Reporting │
│      │              │               │                │       │
│  • Temperature   • Søreide-   • CO2 kg/hr      • EU ETS    │
│  • Pressure       Whitson     • CH4 kg/hr      • NPD       │
│  • Flow rates    • Flash calc  • nmVOC kg/hr    • Dashboard │
│  • Composition   • Salinity    • CO2eq          • Alerts    │
│  • Salinity      correction                                  │
│                                                              │
└─────────────────────────────────────────────────────────────┘

Why Søreide-Whitson for NeqSimLive?

The Søreide-Whitson model is used for NeqSimLive produced water emission calculations because:

1. Formation Water Salinity: Norwegian Continental Shelf formation water typically has 20,000-200,000 ppm TDS
2. Salting-Out Effect: High salinity reduces gas solubility (magnitude depends on conditions)
3. Regulatory Applicability: Salinity correction supports accurate emission reporting
4. Industry Acceptance: The model has been used in petroleum industry since 1992

For more details on the Søreide-Whitson model implementation, see Søreide-Whitson Model Documentation.

Validation Requirements

Per Aktivitetsforskriften §70 and industry best practice:

Requirement	Method
Model validation	Compare vs lab PVT analysis
Uncertainty quantification	Monte Carlo or sensitivity analysis
Periodic recalibration	When fluid composition changes
Audit trail	Version control, calculation logs

Uncertainty Analysis

# Monte Carlo uncertainty example
import numpy as np

def monte_carlo_emissions(base_calc, n_samples=1000):
    """
    Estimate emission uncertainty through Monte Carlo sampling.
    
    Varies input parameters within their uncertainty ranges:
    - Temperature: ±2°C
    - Pressure: ±0.1 bar
    - Flow rate: ±3%
    - Composition: ±5% relative
    """
    results = []
    for _ in range(n_samples):
        # Perturb inputs within uncertainty
        temp_factor = np.random.normal(1.0, 0.006)  # ±2°C on 350K
        press_factor = np.random.normal(1.0, 0.025)  # ±0.1 bar on 4 bar
        flow_factor = np.random.normal(1.0, 0.03)    # ±3%
        
        # Scale result (simplified)
        co2eq = base_calc.getCO2Equivalents("tonnes/year")
        co2eq_adjusted = co2eq * temp_factor * press_factor * flow_factor
        results.append(co2eq_adjusted)
    
    return {
        'mean': np.mean(results),
        'std': np.std(results),
        'p5': np.percentile(results, 5),
        'p95': np.percentile(results, 95)
    }

---

Validation and Uncertainty

Thermodynamic Model Validation

The CPA equation of state has been validated for water-hydrocarbon systems. Typical reported errors from literature:

Property	Typical Error Range	Reference
CH4 solubility in water	<5%	Kontogeorgis & Folas (2010)
CO2 solubility in water	<3%	Duan & Sun (2003)
VLE phase split	<5%	Various validation studies

Note: Actual errors depend on system conditions, composition complexity, and data quality.

Comparison with Field Data

Published studies comparing thermodynamic virtual measurements with physical sampling on Norwegian Continental Shelf operations:

Study	Reported Deviation	Notes
North Sea field study	~4% average	12-month continuous operation
PVT lab validation	~2%	Controlled laboratory conditions
Conventional method comparison	Varies	Different model assumptions

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Literature References

Regulatory Documents

1. Norwegian Petroleum Directorate (NPD)
   • “Resource Report” - Annual emission data
   • URL: https://www.npd.no/en/facts/publications/reports/resource-report/
2. Aktivitetsforskriften (Activity Regulations)
   • Section 70: Measurement and calculation
   • URL: https://lovdata.no/dokument/SF/forskrift/2010-04-29-613
3. Norsk olje og gass (Norwegian Oil and Gas)
   • “Handbook for quantification of direct emissions”
   • “Guidelines for emissions reporting”
   • URL: https://www.norskoljeoggass.no/

Scientific Publications

1. Kontogeorgis, G.M. & Folas, G.K. (2010)
   • “Thermodynamic Models for Industrial Applications”
   • John Wiley & Sons. ISBN: 978-0-470-69726-9
   • DOI: 10.1002/9780470747537
2. Duan, Z. & Sun, R. (2003)
   • “An improved model calculating CO2 solubility in pure water and aqueous NaCl solutions”
   • Chemical Geology, 193(3-4), 257-271
   • DOI: 10.1016/S0009-2541(02)00263-2
3. Søreide, I. & Whitson, C.H. (1992) ⭐ Key Model for NeqSimLive
   • “Peng-Robinson predictions for hydrocarbons, CO₂, N₂, and H₂S with pure water and NaCl brine”
   • Fluid Phase Equilibria, 77, 217-240
   • DOI: 10.1016/0378-3812(92)85105-H
   • This is the thermodynamic model used in NeqSimLive for produced water emission calculations
   • See also: NeqSim Søreide-Whitson Model Documentation
4. Michelsen, M.L. & Mollerup, J.M. (2007)
   • “Thermodynamic Models: Fundamentals & Computational Aspects”
   • Tie-Line Publications. ISBN: 87-989961-3-4

Industry Guidelines

1. IOGP Report 521 (2019)
   • “Methods for estimating atmospheric emissions from E&P operations”
   • International Association of Oil & Gas Producers
   • URL: https://www.iogp.org/bookstore/product/methods-for-estimating-atmospheric-emissions-from-e-p-operations/
2. API Compendium of Greenhouse Gas Emissions Methodologies
   • American Petroleum Institute
   • URL: https://www.api.org/oil-and-natural-gas/environment/climate-change/greenhouse-gas-emissions-estimation
3. IPCC AR5 (2014)
   • “Climate Change 2014: Synthesis Report”
   • Global Warming Potentials (Table 8.A.1)
   • Note: AR6 (2021) is now available with updated GWP values
   • URL: https://www.ipcc.ch/report/ar5/syr/

Software & Tools

1. NeqSim - Open Source Process Simulator
   • GitHub: https://github.com/equinor/neqsim
   • Documentation: https://equinor.github.io/neqsim/
   • PyPI: https://pypi.org/project/neqsim/
2. NeqSim Java API Documentation
   • URL: https://equinor.github.io/neqsim/javadoc/

EU Regulatory Framework

1. EU ETS Directive 2003/87/EC
   • Establishing a scheme for greenhouse gas emission allowance trading
   • URL: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32003L0087
2. EU Methane Regulation 2024/1787
   • Methane emissions reduction in the energy sector
   • URL: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1787
3. MRV Regulation (EU) 2015/757
   • Monitoring, reporting and verification of CO2 emissions from maritime transport
   • URL: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32015R0757

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Appendix A: Unit Conversions

From	To	Factor
kg/hr	tonnes/year	× 8.76
tonnes/year	kg/hr	× 0.114
Sm³ gas	kg (CH4)	× 0.717
Sm³ gas	kg (CO2)	× 1.977
bbl water	m³ water	× 0.159

Appendix B: Typical Emission Factors

Note: These are representative values. Actual factors depend on fuel composition, equipment efficiency, and operating conditions. Consult applicable standards for specific applications.

Source	CO2 Factor	Unit	Reference
Gas turbine	200-250	kg/MWh	IOGP 521
Diesel engine	250-280	kg/MWh	IOGP 521
Flaring (98% efficiency)	2.75	kg CO2/Sm³ gas	API
Cold vent	0.72	kg CH4/Sm³	Direct
Produced water (conventional)	14	g CH4/m³/bar	Norsk olje og gass

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Version History

Version	Date	Changes
1.0	2026-02-01	Initial release

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Document maintained by NeqSim development team. For questions or contributions, see https://github.com/equinor/neqsim