Subsea Processing Simulatorn Simulator

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Secure Energy for America

RPSEA UDW ForumJune 22 & 23, 2010

David AndersonGE Global Research

[email protected](518) 387 4017

Subsea Processing

Simulator07121‐1901



2Secure Energy for America

Motivation

Need robust subsea processing design processes andequipment

Need capability to model subsea processing systems for

Design – system optimization, validation

Operation – operating envelopes, transients, trouble shooting




Program Objectives

1. Create architecture and library to simulate subseaprocessing systems

2. Experimentally validate Simulator and methodologies




Separator Simulator

Software architecture

Hierarchical structure

Integration with commercial process simulator

Dynamic and steady state analyses

Statistical pre- and post-processing




Architecture

Standardized unit models(nodes)

Connectivity

Arbitrary stream variables

Unit models allow organization& zooming

Steady state, transient

capability

Flashing and linkage to processsimulator - HYSYS

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Multiphase

Oil stream

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NPSS Capabilities

Library Management:

• Security / Encryption (DLL, DLM)

• Version control—RepositorySimulation Management:

• Auto Solver Setup & Constraints

Flexibility:• Open architecture (User Defined Components)

Power:• Batch, Interactive & API operation modes.

Flexible Report Generation



Hierarchical Simulator

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SimpleSimple Processing Systems

Simple Component ModelsSimple Component Interfaces

Simple Fluid Systems & Chemistry

Low Fidelity

Low Resolution

Computationally InexpensiveEasy to build & troubleshoot

ComplexComplex Processing Systems

Complex Component ModelsComplex Component Interfaces

Complex Fluid Systems & Chemistry

High Fidelity

High Resolution

Computationally ExpensiveEvolved from simpler models

Pilot Scale

Equipment Suppliers Design & Optimization

Operation Engineers Specification & Operation

RPSEA Phase 1Lab Scale

Simulator Architectural Entitlement



C++ Unit ModulesAnd

Stream Components

Integration with Process Simulator

HYSYS Environment

Flow Conditioner(Entry)

NPSS Simulator Environment

FlowDe-Conditioner

(Exit)

HYSYSInputs

HYSYSParameters

AdditionalBoundaryDefinitions

Outputs

Integration of Simulator into field modelAugments field model data set

Flashing capability



Simulating Transients

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Three phase separator in virtual test loop



Statistical Package

1) Operational Envelope

2) Net Present Value

3) Design Optimization

4) Model Tuning / Data Mining

Go

No-Go



Modeling Strategy Background

EmpiricalData OnlyDiscreteMay be accurate but not general

AnalyticalEquations

ContinuousGeneral but may not be accurate

Examples:

Heat flux (Fourier’s Law)

Elasticity (Hooke’s Law)

dxdT kAq x −=

ε σ E =

EmpiricalTypical: hybrid approach



Modeling Strategy

1: Analytical Model

X

Y

2: Experimental Data

X

Y

3: Tune

X

Y

topology

anchors

topologypulled toward

anchors(Translation & Rotation)



Summary and Next Step

Simulator ready for validation

Flow loop construction nearingcompletion- Three phase horizontal separator

- Model oils, water, air/nitrogen





Example

LLCC: Liquid-Liquid Cylindrical CycloneC. Oropeza-Vazquez et al (U. Tulsa). G. Kouba (Chevron) Oil-Water Separation in a Novel Liquid-Liquid Cylindrical Cyclone (LLCC ® ) Compact Separator—Experiments and Modeling . Journal of FluidsEngineering, Vol 126, July 2004 (553-564)

C. Oropeza-Vazquez Thesis: Multiphase Flow Separation in Liquid-Liquid Cylindrical Cyclone and Gas-Liquid Cylindrical Cyclone Compact Separators (U. Tulsa, 2001)

4 inlet flow regimes:

• Stratified• Dispersed O/W + W• Double DO/W• DO/W

X’s: VSO & VSW; Split RatioY’s: Water Cut @ Water Out

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Sub Models:

• Flow Regime• Inlet Flow• Nozzle• Cyclone



Tuned Model Results

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Model tuned within flow regime.Validate with additional data. Beware edges(extrapolation)

Much improvement




LLCC Objectives

LLCC Model from papers coded in RPSEA -mediocre agreement with data & U Tulsaversion


RPSEA Simulator

Opportunity: Tune MATLAB LLCC model to test dataDevelop and demonstrate methodologies and tools





Tuning Methodology

Step 1: select tuning parameters

Step 2: choose data subsets

Step 3: optimize TF for each subset

Step 4: Fit TF=TF(X’s)


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Tune empirics, trust physics

Two tuning parameters (Both in Inlet Model):

TP1 on max droplet size

TP2 on skewing of effective Split Ratio




Tuning Methodology






Group Data by flow regime

Option 1: 2 TP for 46 data points: toomuch of smoothing, not enoughaccuracy?

Option 2: further subdivide by Runs: 2TP for each of 5 subsets.

Try Option 2





Tuning Methodology





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Simulate each X within Run using all TPcombos

Choose TP1 & TP2 that minimizes error

If best fit is poor, more/different TPs are neededIf best fit is good, can TP be dropped? (Pareto)

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Tuning Methodology





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10 Tuning Parameters but no continuity wrt V SW & V SO

( polynomial fit) 2x3 parameters--continuous

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Outline

1. Program Overview

2. Modeling Methodology

3. Dry Run before Lab Experiments

4. Conclusions

Documents

Subsea Processing Simulatorn Simulator