Advanced Flow Assurance

Flow Assurance Master Class Nihâl Güler-Quadir, PhD Principal Consultant, EICE International Inc.

What is Flow Assurance?

Economic Justification

Maintain production reliably, economically and safely from sandface to processing facilities

1

Environmental Footprint

Operational Safety

Design

Operations

Optimization

Conceptual

Surveillance

Design

Detailed

Monitoring

Operations

FEED

Diagnostics

Control

Appraisal

Remediation

Planning

Fluid Flow

Heat Transfer

Fluid Properties

Chemical Treatment

Integrated Analysis

Multiphase Flow Pipeline Network Heavy Oil Steam Injection CO2 Sequestration LNG & NGL Lines Transient Analysis

Radial Conduction Free Convection Forced Convection Annulus Radiation Wellbore Heating Pipeline Cooldown Transient Analysis

Black Oil Modeling Vapor-Liquid Equilibria PVT Analysis Hydrate Prediction Wax Deposition Asphaltene Water Analysis

Hydrate Inhibition Wax Suppression Emulsification Corrosion Drag Reduction Water Treatment Asphaltene Inhibition

Reservoir Inflow Nodal Analysis Artificial Lift Pressure Maintenance Integrated Asset Model Well Testing Well Completion

The Challenge of Flow Assurance

Hydrate

14000

Wax

Operational Goals Ensure uninterrupted flow 24x7x365 at target rates Avoid operating in hydrate region for extended periods Control wax deposition in pipeline Limit asphaltene precipitation in well Manage impact of slugs on processing facilities

Design Objectives Adequate throughput capacity for life of field production Ability to monitor entire system from sandface to platform Infrastructure in place to respond operationally

10000 Reservoir 8000

Chemicals

Pressure (psi)

12000

6000

WELLBORE

Insulation 4000

Heating

PIPELINE

Asphaltene Bubble Point

2000

Boosting

RISER

0

0 2

50

Platform

100

150

Temperature (°F)

200

250

Course Outline Day 2 – Applying Flow Assurance

Day 3 - Integrated Workflows

Introduction •Introductions •What is Flow Assurance •The Challenge (Operations and Design) •Course Overview

D. Thermodynamics •Single phase properties – oil, gas and water •Black oil and empirical models •Compositional PVT analysis •Hydrates, wax and asphaltenes prediction •Scales

H. Integrated Flow Assurance Analysis •Combining fluid flow, heat transfer and thermodynamics •Deepwater/subsea systems •Heavy oil transport •Drag reduction •Monitoring and control

A. Fundamentals of Fluid Flow •Single phase flow •One-dimensional momentum balance equation •The concept of friction factor •Pipeline transmission applications

E. Transport Properties •Viscosity prediction methods •Oil-water viscosity – emulsions •Other fluid properties

B. Multiphase Flow Fundamentals •Basic multiphase flow concepts •Flow patterns, holdup and pressure drop •Horizontal and near-horizontal flow •Vertical, inclined and downward flow

F. Heat Transfer Analysis •conduction, convection and radiation •Heat transfer through composite layers •Wellbore heat transfer •Pipeline heat transfer •Wellbore and pipeline heating

Day 1 –Basics of Flow Assurance

C. Multiphase Phenomena in Flow Assurance •Modeling multiphase flow behavior •Three-phase oil-gas-water flow •Impact of multiphase flow on corrosion / erosion •Hydrodynamic slugging

3

G. Transient Phenomena •Basic principles of single phase transient flow •Multiphase flow transients •Pipeline startup, shut-in and blowdown •Terrain induced slugging

I. Integrated Production Analysis •The economics of flow assurance •Reservoir decline – how it impacts production •Introduction to artificial lift methods •Integrated asset modeling – reservoir, production, process plant, economics J. Flow Assurance Considerations in Conceptual Design & Operations A hands-on session where participants will learn to apply the concepts discussed in the preceding sessions in a practical example involving the creation of a field development plan for a hypothetical asset with particular emphasis on the impact of flow assurance issues on the overall design and operation.

A. Fluid Flow Fundamentals

 Single phase flow  One-dimensional momentum balance equation

 The concept of roughness and its influence on friction factor  Pipeline transmission applications

4

Single Phase Flow Type of Pipeline

Primary Operating Consideration

Gas Gathering System

Condensate, Water, Network

Gas Transmission

Throughput, Compression

Gas Distribution

Low Pressure Network

Refined Products

Batch Movement

Heavy Oil

Viscosity

Volatile Hydrocarbon

PVT behavior

Key Flow Assurance Issues • Hydraulics analyze flow and predict pressure from fluid behavior • Heat Transfer analyze and predict temperature behavior • Thermodynamics how pressure and temperature impact fluid behavior 5

Momentum Balance From the Law of Energy Conservation:

L A Potential Energy at A + Kinetic Energy at A

B

φ

-

Friction Loss in Pipe =

Potential Energy at B + Kinetic Energy at B

Total Pressure Gradient = Pressure Gradient due to Friction (Frictional Loss) + Pressure Gradient due to Elevation (Potential Energy) + Pressure Gradient due to Velocity Change (Kinetic Energy) where (with appropriate units): frictional gradient = - f ρ v |v| / (2 gc D) elevation gradient = - ρ g/ gc . Sin φ kinetic energy gradient = - ρ v . dv/dL is relatively small and generally ignored (except for high velocity gradients, e.g. flare lines)

6

Example A1 – Pipeline Pressure Gradients Determine the pressure at B, when the pressure at A is 1000 psi D = 12 inch A

Φ = 5 deg

3) 4) 5) 7

L = 10,000 ft v = 25 ft/sec ρ = 5 lb/ft3 f = 0.01

= - f ρ v |v| / (2 gc 12/12) = - 0.01 * 5 * 252/ (2 * 32.2 * 1) = - 0.49 (lbf/ft2) / ft = - 0.49 / 144 (in^2/ft^2) = -3.37E-3 psi/ft elevation gradient = - ρ g/ gc . Sin φ = - 5 * sin(5) / 144 = -3.03 E-3 psi/ft kinetic energy gradient = 0 Total pressure gradient = - 3.37E-3 - 3.03E-3 = -6.4E-3 psi/ft Pressure at B = 1000 – 10000 * 6.4E-3 = 936 psi

1) friction gradient

2)

B

Friction Factor How to determine the friction factor term f in the frictional gradient: frictional gradient = - f ρ v |v| / (2 gc D) dimensionless Reynolds number: Re = v D ρ / (6.72E-4 * μ)

Moody Chart: f = f(Re,Є/D)

Note: multiplier is to convert viscosity from cp to lb/sec/ft

. •

Laminar Flow Region: 0 < Re < 2300 f = 64 / Re Turbulent Flow Region: Re > 4000 •

Colebrook-White Equation:

f = 1 /(1.74 – 2 log (2 Є/D) + 18.7 / Re f0.5) 2 relative roughness = Є/D •

Jain’s eqn: 1/(f1/2) = 1.14-2 log(e/d+21.25/Re0.9)

Class Question: How do we handle the transition? 2300< Re < 4000

8

Example A2 – Friction Factor Find the friction factor in a 12-inch gas transmission pipeline, given the following data: v = 25 ft/sec, D = 12 inch, Є = 0.0018 inch, ρ = 5 lb/ft3, μ = 0.01 cp 1) 2) 3)

Relative roughness Є/D = 0.0018 / 12 = 0.00015 Reynolds number Re = v (D/12) ρ / (6.72E-4 x μ) = 25 x (12/12) x 5 / (6.72E-4 x 0.01) = 18,601,190 From Moody chart, friction factor f = 0.015 (estimate)

Alternate Numerical Method (Colebrook-White) 1) 2)

3) 4)

9

Set f’ = 0.015 as initial estimate for friction factor Update f for next iteration from Colebrook-White equation: f = 1 /(1.74 – 2 log (2 Є/D) + 18.7 / Re f0.5)2 = 1 / (1.74 – 2 log (2 x 0.00015) + 18.7 / 18601190 x √0.0185) 2 = 0.01302455 Repeat previous step with f’ = 0.01302455 Converge until error within tolerance (3 iterations, f=0.01302956)

Note: Colebrook-White generally converges within 2-3 iterations

Example A3 – Transition Zone Friction Factor Determine the friction factor for a 12-inch heavy oil pipeline, given the following : v = 1 ft/sec, D = 12 inch, Є = 0.0018 inch, ρ = 60 lb/ft^3, μ = 30 cp 1)

Relative roughness Є/D = 0.0018 / 12 = 0.00015

1)

Reynolds number Re = v D ρ / (6.72E-4 x μ) = 1 x (12/12) x 60 / (6.72E-4 x 30) = 2976 (transition)

2)

From laminar flow model, friction factor f = 64 / Re = 0.021504

1)

From Colebrook-White (or Moody chart), turbulent friction factor = 0.0438

2)

From interpolation, weighted friction factor at transition = 0.03039 Note: Pipe roughness has minimal impact in transition zone

10

Terminology Symbol f

Friction factor

ρ

Density (lb/ft^3)

v

Velocity (ft/sec)

gc

Conversion factor (32.2 lbf-sec^2/lb-ft)

g

Acceleration due to gravity (ft/sec^2)

D

Pipe internal diameter (inch)

L

Pipe length (ft)

dv/dL P dP/dL

11

Definition

Velocity gradient (ft/sec^2) Pressure (psi) Pressure gradient (psi/ft)

μ

Absolute viscosity (cp)

Є

Absolute roughness (inch)

Re

Reynolds number

B. Multiphase Flow Fundamentals

 Basic multiphase flow concepts  Flow patterns, holdup and pressure drop

 Horizontal and near-horizontal flow  Vertical, inclined and downward flow

12

Basic Concepts of Two-Phase Flow τwG τi Liquid Phase (with Gas Bubbles)

τi

Diameter

Gas Phase (with Liquid Entrainment)

VG VL

hL

AG AL

τwL Slippage = vG - vL

Holdup HL = AL / (AL + AG)

Extending Single Phase Flow: 

New concept of holdup HL as the volumetric liquid phase fraction and HL holdup

HL ns = qL / (qL + qG )     

as the no-slip

where qL and qG the phase volumetric flow rates at in situ conditions

Significant slippage between phases (gas is faster, except for downhill flow) HL > HL ns Frictional pressure gradient much higher (due to interfacial shear τi) Velocity of wave propagation is orders of magnitude slower Distribution of phases based on prevailing flow pattern (dependent on geometry, in situ rates, fluid properties) Concept of superficial phase velocities: vSL = qL / Area of Pipe = vL x HL vSG = qG / Area of Pipe = vG x (1 - HL)

13

ns

and Mixture Velocity, vm = vSL + vSG

Example B1: Multiphase Flow Parameters Given an average holdup of 0.25, predict all relevant multiphase flow parameters in a horizontal 3-inch ID flowline operating at a pressure of 147 psia and 100 deg F producing 1000 BPD at a GOR of 1000 SCF/BBL. Use an average compressibility factor of 0.9 and assume that none of the gas is in solution. Area = π D2 / 4 = (3.14) x ( 3/12)2 /4= 0.049 ft2 QL = 1000 BPD x 5.615 (ft3/bbl) / 86400 (sec/day) = 0.065 ft3/sec @ Std conditions Assuming incompressible liquid, qL= QL = 0.065 ft3/sec QG = 1000 BPD x 1000 (SCF/bbl) / 86400 (sec/day) = 11.574 ft/sec @ Std conditions qG = QG x Pstd / (P/z) x (T + 460) / (Tstd+ 460) = 11.574 x (14.7 / (147/0.9)) x (460+100) / 520 = 1.122 ft3/sec v SL = qL/ Area = 0.065 / 0.049 = 1.3 ft/sec v SG = qG / Area = 1.122 / 0.049 = 17.3 ft/sec HL ns = qL / (qL + qG ) = 0.065 / (0.065 + 1.122) = 0.055

vL = vSL / HL = 1.3 / 0.25 = 5.3 ft/sec vG = vSG / (1 – HL) = 17.3 / 0.75 = 23 ft/sec Slip = vG – vL = 17.7 ft/sec 14

Multiphase Flow Patterns • Horizontal Flow    



Vertical Flow   



Stratified (both Smooth and Wavy) Intermittent (Elongated Bubble and Slug) Dispersed Bubble Annular

Bubble (Bubbly and Dispersed Bubble) Intermittent (Slug & Churn) Annular

Inclined Flow  

Upward Inclination (see Vertical Flow) Downward Inclination (see Horizontal Flow)

Flow pattern boundaries may vary significantly with even slight changes in inclination angle. As such, empirical horizontal and vertical pattern maps are not suitable for predicting flow patterns in a pipe or wellbore where the inclination deviates by even a few degrees from vertical/horizontal. Computer-generated mechanistic models that rigorously account for inclination (e.g. Barnea et al) are more appropriate for such predictions.

15

Horizontal Flow Patterns Dispersed Bubble Flow • • • •

at high rates in liquid dominated systems the flow is a frothy mixture of liquid and entrained gas bubbles flow is steady with few oscillations. also called as froth or bubble flow.

Stratified Flow

Slug Flow • at moderate gas and liquid velocities • alternating slugs of liquid and gas bubbles flow through the pipeline. • Possible vibration problems, increased corrosion, and downstream equipment problems due to its unsteady behavior.

Mandhane Map (Empirical) SUPERFICIAL LIQUID VELOCITY VSL, FT/SEC

• at low flow rates the liquid and gas separated due to gravity • at low gas velocities the liquid surface is smooth, (stratified smooth) • at higher gas velocities, the liquid surface becomes wavy, (stratified wavy, or wavy flow) • some liquid droplets might form in the gas phase.

Annular Flow

16

• at high rates in gas dominated systems • part of the liquid flows as a film around the pipe circumference • the gas and remainder of the liquid (entrained droplets) flow in the center • of the pipe. • the liquid film thickness asymmetric due to gravity also called as annular-mist or mist flow..

Dispersed Flow Bubble, Elongated Bubble Flow

Slug Flow

Annular, Annular Mist Flow

Stratified Flow Wav e Flo w

SUPERFICIAL GAS VELOCITY VSG, FT/SEC

Vertical Flow Patterns Well Flow

Superficial Liquid Velocity (m/s2)

Taitel-Dukler-Barnea Model (Mechanistic)

DISPERSED BUBBLE

BUBBLY

BARNEA TRANSITON ANNULAR

SLUG OR CHURN

BUBBLE FLOW

22)) 2) SuperficialLiquid Liquid Velocity (m/s Superficial Velocity (m/s Gas Velocity (m/s

17

Vertical Pipe Flow Patterns

SLUG FLOW

CHURN FLOW

ANNULAR FLOW

Example B2: Predicting Flow Pattern Find the prevailing multiphase flow pattern in a horizontal 3-inch ID flowline operating at a pressure of 147 psia and 100 deg F producing 1000 BPD at a GOR of 1000 SCF/BBL. Use an average compressibility factor of 0.9 and assume that none of the gas is in solution.

Procedure:  From inclination angle, determine appropriate prediction map to use  Estimate in situ rates from standard production rates  Compute superficial phase velocities  Predict flow pattern from map Area = 3.14 x (3 /12) 2 /4 = 0.049 ft2 Assuming incompressible liquid qL = 1000 BPD x 5.615 (ft3/bbl) / 86400 (sec/day) = 0.065 ft3/sec qG = 1000 BPD x 1000 (SCF/bbl) / 86400 (sec/day) x (14.7 / (147/0.9)) x (460+100) / 520 = 1.122 ft3/sec v SL = qL / Area = 0.065 / 0.049 = 1.122 ft/sec v SG = qG / Area = 1.122 / 0.049 = 17.261 ft/sec From Mandhane map (horizontal), flow pattern = SLUG 18

Pressure Gradient in Two-Phase Flow

Total Pressure Gradient = Pressure Gradient due to Friction (Frictional Loss) + Pressure Gradient due to Elevation (Potential Energy) + Pressure Gradient due to Velocity Change (Kinetic Energy) where: frictional gradient = - f TP ρ TP vTP |vTP| / (2 gc D) elevation gradient = - ρs g/ gc . Sin φ kinetic energy gradient = - ρTP v TP . dv TP /dL

The new two-phase flow terms introduced are: slip-weighted mixture density (based on holdup correlation): ρs = ρL . HL + (1 – HL) ρG two-phase density, friction factor and velocity: ρTP , fTP , vTP which are all dependent on the pressure drop calculation method (correlation)

19

Recommendations Multiphase Flow Correlations (from Chevron Pipeline Design Manual)



Pressure Drop 



 



Liquid Holdup 









Near Horizontal  Low GOR - Beggs and Brill  Gas/Condensate – none (Eaton better than others) Near Vertical  Gas/Condensate – no slip  Gas/Oil - Hagedorn and Brown Inclined Up  Low GOR - Beggs and Brill  Gas/Condensate  High Velocity – none (use no slip)  Other – none (use Beggs & Brill with caution) Inclined/Vertical Down – none (Beggs & Brill with caution)

Flow Patterns 

20

Near Horizontal  Low GOR - Beggs & Brill  Gas/Condensate  High Velocity – Eaton-Oliemans  Low Velocity – None Near Vertical  Gas/Condensate – Gray, Hagedorn & Brown  Gas/Oil - Hagedorn & Brown Inclined Up - Beggs & Brill (fair) Inclined/Vertical Down – None (Beggs & Brill with caution)



Near Horizontal – Taitel-Dukler (except Dispersed-Bubble boundary where a fixed VSL = 10 ft/sec is recommended) Near Vertical – Taitel-Dukler-Barnea

General Modeling Guidelines 

Liquid holdup accuracy requires detailed pipeline elevation profile



Flow pattern-dependent mechanistic analysis is required for accurate holdup prediction



Pressure profile is dependent on holdup accuracy (elevation gradient)



Kinetic energy losses pressure/high velocity)



Choice of correlation should be based on a range of factors including geometry, fluid characteristics and field history



Mechanistic correlations (OLGAS, Tulsa) generally scale up better



Rigorous 3-phase analysis may be required for low velocity flow with significant water cut

generally

negligible

(except

low

Terminology

Symbol VL , VG VSL , VSG

Phase velocities (ft/sec) Superficial phase velocities (ft/sec)

HL

Liquid Holdup

HL ns

No slip holdup

qL, qG

in situ volumetric flow rates (ft3/sec)

τi, τwL, τwG

Shear at interface / pipe wall (psi/ft)

hL AL , AG

Subscript L, G, O, W

21

Definition

Height of liquid level Cross-sectional area for phase

Definition Liquid, Gas, Oil, Water

i, w

Interface, wall

std

Standard conditions (60 °F, 14.7 psia)

TP

Two-phase

ns

No slip

m

mixture

C. Multiphase Phenomena in Flow Assurance

 Modeling multiphase flow behavior  Three-phase oil-gas-water flow  Impact of multiphase flow on corrosion / erosion  Slugging phenomena

22

Modeling Multiphase Flow Behavior 1 HL P T FP

2 HL P T FP

Inlet Data: Temperature, Fluid Characterization Pressure or Flow Rate Boundary







23

3 HL P T FP

4

5

HL P T FP

HL P T FP

6 HL P T FP

7 HL P T FP

8 HL P T FP Outlet Data: Pressure or Flow Rate Boundary

All flow correlation employ a 3-step approach  Establish Flow Pattern  Determine Holdup  Calculate Pressure Drop Empirical vs. Mechanistic correlations  Empirical correlations are primarily regression-based Pressure  Mechanistic models are based on physics + data To model flow behavior in a pipe (or well)  Input Data  pipe geometry (diameter, length, elevation profile) Temperature  Fluid characteristics (oil, gas & water gravities)  Phase ratios (water cut, GOR)  Specified boundary conditions may be: Holdup  Pressure at inlet and Flow Rate at Outlet  Pressure at both ends  Flow Rate at Inlet and Pressure at Outlet  Calculation Procedure is Sequential and Iterative Distance Along Pipeline, X  Pipe divided into Segments  Temperature traverse calculations in parallel  Fluid properties (e.g. density, viscosity at every segment)  Results: pressure, holdup, flow pattern, temperature and phase properties at every pipe segment Network models (e.g. gathering system) are significantly more complex

Uncertainties in Multiphase Flow Modeling Why will the computed pressure drop for Path 2 ALWAYS be greater? Path 1 A

Path 2 B

Common Uncertainties:   

Flow pattern boundaries are not fully understood (and “blurry”) Holdup predictions do not scale up well for large diameter pipes Pressure drop error could be as high as 20 percent  Errors greater for rough terrain, extreme velocities (high or low)

What Can be Done:  

  24

Define elevation profile in as much detail as possible Define fluid accurately  use measurements (where available), e.g. bubble point, viscosity Use correlations as appropriate for the situation (pipeline geometry, field history, applicability) Validate, validate, validate  leverage available data and past history to adjust model

Three-Phase Flow Analysis Two-Phase Flow τwG Gas Phase (with Liquid Entrainment) τi τi

VG VL Combined Oil + Water Liquid Phase (with Gas Bubbles)

τwL

Slippage = VG - VL

hL

Holdup HL = AL / (AL + AG)

Rigorous Three-Phase Flow τwG Gas Phase (with Oil and Water Entrainment)

VG VO

Oil Phase (with Gas Bubbles and Entrained Water Droplets)

VW

Water Phase (with Gas Bubbles and Entrained Oil Droplets)

Slippage (gas-oil) = VG – VO Slippage (oil-water) = VO - VW

  

τi τi τIW τIW τwL

Holdup HL = AL / (AL + AG) Water Fraction HLW = AOW / AL

Rigorous 3-phase flow analysis is an order of magnitude more complex Most analysis methods tend to lump oil and water into a common homogeneous liquid phase with no slippage between oil and water When segregation does occur, water fraction in the liquid phase

Note: When segregation occurs, the water fraction in the liquid phase may be several times higher than the water cut of the produced fluid. Why? 25

Example C1: Three-Phase Flow Example B1: Given an average holdup of 0.25, predict all relevant multiphase flow parameters in a horizontal 3-inch ID flowline operating at a pressure of 147 psia and 100 deg F producing 1000 BPD at a GOR of 1000 SCF/BBL. Use an average compressibility factor of 0.9 and assume that none of the gas is in solution. Extend your original analysis (in Example B1) to the three-phase flow scenario where there is segregation between oil and water, assuming a produced water cut of 10 percent and the volumetric fraction of the water being 40 percent of the total liquid phase. From Example B1 (two-phase) HL = 0.25 Pipe Area = 0.049 ftt2 qL = 0.065 ft3/sec qG = 1.122 ft3/sec v SG = qG / Area = 1.122 / 0.049 = 17.3 ft/sec HL ns = qL / (qL + qG ) = 0.065 / (0.065 + 1.122) = 0.055 VG = VSG / (1 – HL) = 17.3 / 0.75 = 23 ft/sec With Oil-Water Segregation: Water Cut, FW = 0.10 Water Fraction HLW = 0.40 v SO = qL * (1 - FW) / Area = 0.065 * 0.9 / 0.049 = 1.19 ft/sec v SW = qL * FW / Area = 0.065 * 0.1 / 0.049 = 0.13 ft/sec VO = VSO / HL / (1-HLW) = 1.19 / 0.25 / 0.6 = 7.95 ft/sec VW = VSW / HL / HLW = 0.13 / 0.25 / 0.4 = 1.32 ft/sec Slip G-O = VG – VO = 15.1 ft/sec Slip O-W = VO – VW = 6.62 ft/sec 26

Factors Impacting Corrosion / Erosion 

Corrosion risk is higher when:  Produced gas is sour (definition: partial pressure of H2S and CO2 > 0.05)  > 0.5 percent mole fraction for 1000 psi system pressure  Water volume is high  Water velocity is low  Low lying areas of water accumulation are at highest risk



Flow regime dependency  Stratified Flow – corrosion damage can occur at low water velocity  Slug Flow – high shear increases corrosion rate and reduces inhibitor performance  Annular Flow – high velocity combined with sand accelerates erosion/corrosion



Separation of aqueous phase increases corrosion risk  Higher water volume in line (e.g. 10% water cut has 40% volume)  Lower water velocity (from 5.3 ft/sec to 1.3 ft/sec)



Erosional (maximum) mixture velocity: Vm,max = 100 / ρns(0.5) Where

27

ρns = ρL . HL + (1 – HL) ρG

Hydrodynamic Slugging Hydrodynamic slugs are generated at moderate liquid and gas rates (see flow pattern map) and are a common occurrence in most multiphase flowlines.

Slug Length Prediction A. Prudhoe Bay Model (Brill et al) Mean slug length (ft) is given by: ln(Lm) = - 2.663 + 5.441 (ln(D) 0.5 + 0.059 ln(Vm) ln(Lm) = - 3.579 + 7.075 (ln(D) 0.5 + 0.059 ln(Vm) – 0.7712 ln(D)

(16-in 1979) (16+24-in 1981)

B. Hill & Wood (BP 1990) 1) Calculate Lockhart-Martinelli parameter X = (VSL / VSG )0.9 x (ρL / ρ G ) 0.4 x (μL / μG )0.1 2) Estimate holdup from X using Taitel-Dukler stratified model (see Figure) 3) Determine gas and liquid phase velocities from holdup 4) Determine slug frequency (slug/hr) from: Fs = 2.74 HLst x (VG – VL) / (D/12) / (1 – HLst)

Liquid Holdup HLst

log normal distribution predicted

To calculate Slug Frequency from Slug Length (or vice versa): 1) Estimate liquid holdup in slug HL,slug using Gregory-Nicholson-Aziz equation n: 1.39 HL,slug = 1 / (1 =1/(1+ (Vm / 28.4) )) 2) Assume liquid holdup in bubble HL,bubble to be approx 20 percent 3) From material balance, slug factor (ratio of slug length to total slug + bubble length): SF = (HL - HL,bubble) / (HL,slug - HL,bubble) 4) Slug Length is given by: Ls = SF x Vm / (Fs / 3600) 28

Rule of Thumb: Longest slug (for facilities design) = 6 x Mean Slug

X (Lockhart-Martinelli parameter)

Example C2: Slug Size and Frequency The following data are available for a 10 inch horizontal pipeline operating in the slug flow regime: average holdup = 50 percent, vSL = 3 ft/sec, vSG = 6 ft/sec. Predict the mean slug length and slug frequency. Fluid properties: liquid density = 55 lb/ft3, liquid viscosity = 6 cp gas density = 2 lb/ft3 gas viscosity = .01 cp Mixture Velocity, vm = 3 + 6 = 9 ft/sec

Lm = exp(- 3.579 + 7.075 (ln(D)) 0.5+ 0.059 ln(Vm) – 0.7712 ln(D)) = 247 ft From Hill & Wood (BP) Model:

Liquid Holdup HLst

From Prudhoe Bay Model (1980), average slug length

X = X = (VSL / VSG )0.9 (ρL / ρ G ) 0.4 (μL / μG ) 0.1 = 3.84 From chart in preceding slide, Taitel-Dukler stratified model holdup HLst@ X=3.84 is 0.68 Liquid velocity when stratified = vL / HLst = 3 / 0.68 = 4.41 ft/sec Gas velocity when stratified = 6 / (1 – 0.68) = 18.75 ft/sec Slug frequency, Fs = 2.74 HLst x (18.75 – 4.41) / (D/12) / (1 – HLst) = 100 slug/hr Calculate Slug frequency/length: HL,slug = 1/(1+ (Vm / 28.4)1.39)) = 1 / (1 + (9/ 28.4)1.39) = 0.83 HL,bubble = 0.2 (assumed liquid hold up in the bubble) Slug Factor = (HL - HL,bubble) / (HL,slug - HL,bubble) = (0.5 – 0.2) / (0.83 – 0.2) = 0.47 Mean slug length (for Hill & Wood model) Ls = 0.47 x 9 / (100 / 3600) = 154 ft

Slug Frequency (for Brill et al Prudhoe Bay model) = 3600 * 0.47 * 9 / 247 = 62 slug/hr 29

X (Lockhart-Martinelli parameter)

Terminology Symbol HLW

Volumetric water fraction in liquid phase

Lm

Mean slug length

Vm,max ρns

X

HLst

HL,slug

HL,bubble

30

Definition

Maximum mixture velocity (erosional velocity) No slip mixture density

Lockhart Martinelli parameter

Liquid holdup when flow is stratified

Liquid holdup in slug

Liquid holdup in bubble (during slug flow)

Fs

Slug frequency (slug/hr)

SF

Slug Fraction = slug length / (slug length + bubble length)

D. Thermodynamics

 Single component properties  Black oil and empirical models  Compositional PVT analysis  Hydrates, Wax and Asphaltenes prediction and mitigation

31

Single Component (Average) Properties for Oil, Gas, and Water To be able to solve the oil or gas problems, pressure-volumetemperature (PVT) relationships and physical properties of gases, and liquids are essential. To get these properties, one can define a multi-component fluid system compositionally, or just as Liquid, Gas, and Water mixture based on the overall measurable data. • • • • • • • • • •

Apparent molecular weight Specific gravity, Compressibility factor, z Density, Specific volume, v Isothermal gas compressibility coefficient, cg Vapor- Liquid Equilibrium Gas formation volume factor, Bg Gas expansion factor, Eg Oil Formation Volume Factor, Bo

The Gas Oil Ratio, and Water Cut are easy to measure in the field.

32

Ideal Gas Law PV=nRT where p = absolute pressure, psia V = volume, ft3 T = absolute temperature, °R n = number of moles of gas, lb-mole R = the universal gas constant which, for the above units, has the value 10.730 psia ft3/lb-mole °R

n = m/ MW PV = ( m / MW ) R T where m = weight of Gas, lb MW = Molecular Weight of the Gas

ρg = m / V = (P MW) / (R T) where ρg = Density of gas, lb/ft3

Volume of 1 mol Ideal Gas at Standard Conditions, ( Vsc ) at Psc = 14.7 psia, Tsc = 60 °F = 520 °R

Vsc = n R Tsc / Psc = (1) (10.73)(520)/ (14.7) Vsc = 379.4 scf/lb-mol 33

Real Gas

• At a very low pressure, the ideal gas relationship gives reasonable results – 2-3 % • At higher pressures, the use of the ideal gas Lawte may lead to errors as great as 500% • Therefore to express the relationship between the variables P, V, and T, more accurately, the z-factor, is introduced. PV=znRT z = V / Videal = V / ( (n R Tact) / Pact )

34

Black Oil and Empirical Models

Black Oil Model is where the phase behavior of the mixture is based on experimentally derived prediction methods of gas and liquid phases for bubble point pressure, solution GOR, FVF, and viscosity. • •

The relative gravity of the oil, gas, and water phase are required. All three phase gravities has to be known even if they are not expected to be present in the mixture.

Empirical Models predict the fluid properties that will define the behavior of the fluid mixture with changes in Pressure and Temperature. • • • • •

35

Gas Compressibility Solution Gas Oil Ratio Oil, Water Formation Volume Factor Gas, Oil densities Gas, Oil Viscosities

Gas Compressibility Gas Compressibility • Standing-Katz Tpr= T/Tpc Ppr= P/Ppc • Hall-Yarborough

z-factor = f(SG, T, P)

where Tpc = Σ (yi*Tci) where Ppc = Σ (yi*Pci) (wet and dry gas)

z = [ 0.06125 Ppr t/ Y ] exp [ -1.2 (1 –t )2 ] where Ppr = pseudo-reduces pressure t = reciprocal of the pseudo-reduced temperature, i.e., Tpc / T Y = the reduced density that can be obtained as the solution of the following equation: F(Y) = X1 +[( Y + Y2 + Y3 + Y4 ) / ( 1-Y)3 ] – (X2) Y2 + (X3) YX4 = 0 where

•

X1 = - 0.06125 Pprt exp [ -1.2 (1-t)2 ] X2 = ( 14.76 t – 9.76 t2 + 4.58 t3 ) X3 = ( 90.7 t – 242.2 t2 + 42.4 t3 ) X4 = ( 2.18 + 2.82 t )

Contaminants such as CO2 or H2S may be defined to modify the z-factor. i.e. Witcher-Aziz Correction T’pc = T pc – ε P’pc = PpcT’pc / (T pc + B (1-B) ε) ε = 120 [ A0.9 – A1.6 + 15 (B0.5 – B)4.0 ]

36

Example D1 – Gas Thermodynamic Properties Determine the following properties for the natural gas with the given composition. Mol Weight and critical Temperature and Pressure data is also supplied from Pure Component Data tables. Component C1 C2 C3 N2 CO2 H2s Total

y 0.790 0.007 0.004 0.012 0.017 0.170 1.000

M 16.04 30.07 44.10 28.01 44.01 34.08

Tc 343.34 550.07 665.93 227.52 547.73 672.40

Pc 667.00 707.80 615.00 492.80 1070.00 1300.00

1) Calculate the Specific Gravity of the gas. SGgas=0.687461379 2) Using the Standing-Katz Gas Compressibility Chart, find the z-factor for the gas at 90 °F and 1200 psia. ( ignore contaminants)

z-factor = 0.75 3) Update the z-factor for the contaminants

z-factor = 0.82 4) Calculate gas density at 90 °F and 1200 psia. Use the Engineering EOS

ρg=5 lb/cuft 37

Procedure for Predicting Gas Compressibility Procedure       



Calculate the Apparent Molecular Weight of the gas Calculate the Specific Gravity of the gas Calculate the Pseudo Critical temperature Calculate the Pseudo Critical Pressure Calculate the Pseudo Reduced Temperature 1.36 °F Calculate the Pseudo Reduced Temperature Read the corresponding Compressibility Factor from the Standing and Katz Chart

Mg =Σ (yi*Mi) SGg Mg / Mair Tpc = Σ (yi*Tci) Ppc = Σ (yi*Pci) Tpr = T/Tpc

19.93 lb/lb-mol 0.688 404 °F 779 psia

Ppr = P/Ppc

1.54 psia

z-factor

0.75

Check if the sour gas contains more than % 5 contaminants  sum the mol fraction of H2Sand CO2  If more than % 5, calculate the Adjustment Factor, ε, for the contaminants ε= 120*(A0.9-A1.6)+15*(B0.5-B4.0 )

40.9 °F where

A=(yH2S+yco2)

0.187 B

  

 38

= yH2S 0.17 Calculate the Adjusted Pseudo Critical Temperature T’pc = Tpc- ε 363 °F Calculate the Adjusted Pseudo Critical Pressure P’pc = (Ppc* T’pc)/(Tpc+B(1-B)*ε 690.6 psia Recalculate the Pseudo Reduced Temperature and the Pseudo Reduced Pressure using the adjusted Pseudo Critical T and P T’pr 1.51 °F P’pr 1.75 psia Read the Gas Compressibility Factor from the Standing and Katz chart z-factor 0.82

Solution Gas Oil Ratio •

Solution Gas Oil Ratio (Rs ) The bubble point pressure equation is reversed to solve for the solution gas oil ratio. When oil is reaches to surface conditions some natural gas to come out of solution due to the P and T change. The gas/oil ratio (GOR) is defined as the ratio of the volume of gas that comes out of solution, to the volume of oil at standard conditions. A point to check is whether the volume of oil is measured before or after the gas comes out of solution, since the oil volume will shrink when the gas comes out. In fact gas coming out of solution and oil volume shrinkage will happen at many stages of the flow while the hydrocarbon stream from reservoir through the wellbore and processing plant to export. •

Pb = f(Rs, γg, T, γo) • •

Lasater for Rs≤Rp Rs = [ (379.3*35*ϒo,,sc)/Mo]/[ϒg /(1-ϒg ] ) Standing for P≥1000 Rs = ( ϒg*(P*X)1.20482/ (18)1.20482 ) for P30

X = 10(1.0125API-0.00091T)

Rs =SG*(P1.0937)1011.172A Rs =SG*(P1.187 )1010.393A where

A= API/(T+460)

( suggested for °API>15

( suggested for °API Pb and API >30

Bo = 1+4.67x 10-4* 0.175 D*10-4 -1.8106RsD*10-8 Bo = 1+4.67x 10-4* 0.175 D*10-4 -1.8106RsD*10-8

where D=(T-60)API / SG

 40

Water Formation Volume Factor ( Bw)

Computed from water densities

Example D2 – Liquid Phase Density Determine the liquid phase density for a 3 phase mixture given the following data. 2200 psia and 190 °F.(Use Standing correlations) Oil gravity= 30 ° API Gas Gravity= .85 Water Cut = 10% Assume oil formation volume factor is 1.2 and Rs is 100 scf/stb at insitu conditions.

SGoil= ρLIQ =

41

0.876 48.11lb/cuft

Composional PVT Analysis Not only the properties of oil, gas, and water, but also the phase behavior changes with the changes in Pressure and Temperature. The phase behavior will determine the condensation or the evaporation of the phases, hence determine the vapor-liquid split and the thermodynamic properties of the phases. Compositional PVT analysis predicts the properties of the Hydrocarbon Water mixture based on the equilibrium, enthalpy, and property correlations. Flash calculations are based on the Equation of State to decide for the phase separation., i.e.:  Peng-Robinson  Suave-Redlich-Kwong

Multiple Component Phase Diagram

42

Example D3 – Liquid Fraction Determine the Liquid Fraction of the HC mixture from the given Phase Diagram at the following conditions: 1)

at 625 °F and 4000 psia

0 mol % 10 mol %

2)

43

At 425 °F and 2250 psia

3)

At 175 °F and 1000 psia

4)

At 100° F and 500 psia

20 mol % 20 mol %

Hydrates  Gas Hydrates are formed by the C1, C2, CO2, H2S at ≈ P>166 psi

 Formation of Hydrates require three conditions:   

the right combination of P and T; favored by low T, above 32 °F and high P Hydrate forming components have to be present in the system Some water must be in the system, not too much, not too little

 Other phenomena that increases Hydrate formation:  Turbulence  

Courtesy of Petrobras

High velocity- through chokes, narrowing valves due to Joule Thompson effect Agitation, i.e. heat exchangers, separators

 Nucleation sites are the points where phase change is favored, such as:      

Imperfections in the pipeline A weld spot Fittings Scale Dirt Sand

 Presence of Free Water not necessary but the gas-water interface creates a nucleation site for hydrate to form 44

Hydrate Prediction The point at which hydrates form is dependent on the composition of the gas.

This particular curve is only based on a correlation that is valid for gases with similar compositions to those shown in the table below. It is invalid in the presence of H2S or CO2.

Hydrate Formation Prediction for Sweet Natural Gases

EXAMPLE: For a gas with a specific gravity of 0.7, and a pressure of 1000 psia, the temperature

below which hydrates would be expected to start forming would be 64ºF. If the pressure is reduced to 200 psia, the temperature below which hydrates would be expected to start forming reduces to 44ºF 45

Hydrate Formation Prevention Hydrate formation prevention can be accomplished through Water removal •

Separation Separation will remove most of the free water from gas stream

•

Higher System Temperatures Pipe insulation and bundling, or steam or electrical heating process

•

Lower System Pressures High temperature system pressure drops design through line choking.

•

Alcohol Inhibitors injection Acting as antifreezes, alcohols will decrease hydrate formation temperature below operating temperature

•

Kinetic (Polymer dissolved in solvent) Inhibitors Will bond on the hydrate surface to prevent crystal growth. shift the hydrate equilibrium conditions towards lower temperatures and higher pressures , or increase hydrate formation time.

•

Antiagglomerants These dispersants will cause water phase be suspended as small droplets in oil or condensate

46

Comparison of Hydrate Formation Prevention Methods • Drying the natural gas • MeOH • EG, DEG, MEG, TEG, and TREG • TEG, TREG are too viscous , too soluble in HCs • Drying is Preferred until not economical • Used : • upstream of chokes • Short gathering lines • Heating the flow line Initial investment Attention needed - minimum Fuel - readly available Cost - low • Adding Ckemicals: • Long flow lines

47

Methanol versus Glycol Methanol • • • • •

•

48

Used at any Temperature Prevents hydrate formation better then DEG and EG on per lb basis Injection technique not critical • Good fraction of Methanol evaporates into gas. Not as economical • Low recovery cost • High vaporization loss Unless feeds into TEG unit, where easily recovered in the regen • Good for • Low gas volumes • Temporary cases • Rarely needed • Long flow lines Dissolves the hydrates already formed

Glycol • • • • •

•

•

Not under 15 oF high viscosity Difficult to separate from liquid HCs DEG has higher vaporization when 30 gal/hr use glycol units If Hydrates already plugged the pipeline, reduce Pressure both upstream and downstream of the hydrate One sided P reduction might result in High velocity of the hydrate plug - may damage bends and even lines - EXPLOSION

50

Cloud Point and Pour Point Definitions Cloud point of a fluid is the temperature at which dissolved solids are no longer completely soluble, precipitating as a second phase giving the fluid a cloudy appearance. In the petroleum industry, cloud point refers to the temperature below which wax in liquid hydrocarbon form a cloudy appearance. The presence of solidified waxes thickens the oil and clogs. In crude or heavy oils, cloud point is synonymous with Wax Appearance Temperature, (WAT) and Wax Precipitation Temperature (WPT).

Pour point of a liquid is the lowest temperature at which it will pour or flow under prescribed conditions. It is a rough indication of the lowest temperature at which oil is readily pumpable. In crude oil a high pour point is generally associated with a high paraffin content.

51

Waxes Waxes are : • The organic compounds of the crude • Insoluble in the crude at the producing conditions • High molecular weight C18-C60 alkanes • C18 to C36 (paraffin waxes, macrocystalline waxes) • C30 to C60 (microcrystalline waxes), • They are: • aliphatic hydrocarbons (both straight and branched chain), • aromatic hydrocarbons, • naphthenes • resins and asphaltenes. • Melting point, Boiling point, and Solubility of the HC mix is profoundly effected by the presence of alicyclic, aromatic, and condensed rings. • Deposits as solid when the temperature falls below the cloud point • The cloud point determines the rheology of waxy crudes • Above the cloud point, flow is Newtonian • Below the cloud point flow is non-Newtonian due to wax/solid precipitation 52

Problems with Waxes When wax forms: • •

• •

53

Reduced permeability around the well bore/formation damage Pumping cost increase because of: • Increase in viscosity can be 10 folds • Increased horse power requirement to transport the fluid through • Area for flow decreases due to wax deposition on the inner pipe wall Increases pressure drop, can eventually plug the production string Loss of production: • Can eventually plug the production string and/or pipeline Can deposit in the surface facilities • Decreased equipment volume, hence reduced volume/flow

Formation of Wax

• Wax deposits usually happen in oil flowlines with components C7+. 

54

Wax deposits have potential to accumulate onto cooled surface when it gets down to the Cloud Point, or Wax Appearing Temperature.



Wax formation Temperature can be determined within ± 5 °C.



GOR, and Pressure effects can be measured, but it is usually calculated via thermodynamic prediction based on Dead Oil values.

Pressure

Wax Formation

Reservoir Fluid

Bubble Point

No Wax

Temperature Temperature/Pressure Relationship in Formation of Wax

Wax Mitigation and Prevention: Wax Deposition Removal Techniques: • Mechanical Pigging - Scraping wax from the pipe wall and mixing it with the crude in front of the pig

•

Thermal

Maintaining or increasing the temperature of the crude above the WAT can prevent wax from settling on the pipe wall, or help to remove softened wax.

•

Chemical

Chemical Solvents and Dissolvers • substituted aromatics blended with gas oil. • Chlorinated solvents – environmental concerns.

Wax Prevention Wax Inhibitors • Crystal Modifiers • Pour Point Depressants • Dispersants • Surfactants 55

Wax Deposition Rate Measurements Wax Deposition Rate Measurement Techniques Test

Static cold finger

Dynamic cold finger

Description

A cold surface is immersed in a reservoir of oil for set duration then removed and inspected. The surface can simple cooled block or finger, cooled tube or sophisticated probe.

Advantages

No flow effects. Risk of depletion of wax in small sample volume.

Useful inhibitor screening tool.

Quick Simple Small volumes of sample. Deposit formed. Deposit directly inspected. Accurate control of temperatures. Adaptable for live oil.

As above but shear can be applied to flow the oil over the surface. This can be achieved with stirring or immersing the surface in a flowing stream. For better control concentric cylinders are used.

As above Addition of shear Accurate control of shear/stress or flow velocity.

Risk of depletion of wax in small sample volume. Difficult to simulate pipeflow and turbulence. Difficult to monitor in-situ deposition until end of test.

Useful inhibitor screening and deposition characterization tool.

56

Disadvantages

Capillary/tube blocking

Warm oil is displaced through a narrow bore tube until pressure increase indicated restriction or blockage. Often used in uncontrolled cooling but better results achievable with set temperature regimes.

Quick Simple Small vols of sample Qualitative measure of in-situ deposition rates. Live oils.

No direct measure of deposit. Laminar flow regimes only. Uncertain temperature profiles and heat transfer rates.

Recirculating flowloops

Oil is pumped through a section of pipe in which conditions of temperature and flow can be defined. Deposition can be detected by increasing pressure and recovering of deposit. Useful qualitative tool for assessing deposition characteristic.

Simulates pipeflow regimes. Limited sample volumes Control of temperature and flow rate. Qualitative measure of in=situ deposition rates/

Complex equipment. No direct measure of deposit at specific points. Need to recondition recirculating oil. DP insensitive in Laminar flow. Potential waxing outside deposition section.

Cloud Point Methods - Recommended Indirect Methods These methods detect an effect caused by wax crystallization Test

Description

Disadvantages

DSC

When wax crystallizes from crude oil, small quantities of heat are generated(Much like heat given off when water freezes). The temperature at which this “heat of fusion” first occurs can be detected by a Differential Scanning Calorimeter, DSC.

Small sample size. Automated. Quick. Can estimate wax content.

High cooling rates potential for subcooling. Sensitivity: low wax contents difficult. Subject to interpretation.

Infrared Detection/ Light Scattering

Infrared Detection/ Light Scattering Wax crystals will deflect and scatter light passing through the oil. Infrared can be absorbed by waxes and will penetrate black oils. Changes in light reflected or absorbed as the oil cools will indicate wax forming.

Sensitive. Small sample size. Suitable for live fluids.

Unrepresentative sample size. Subject to interpretation Little published validation.

Sensitive. Small sample size. Estimate solid wax content. Suitable for live fluids.

Unrepresentative sample size. Little published validation. Subject to interpretation.

NMR

Test

Thermodynamic prediction

57

Advantages

Description

Model uses compositional analysis of oil and published properties of components to predict solubility of wax components.

Advantages

Predicts cloud point and solid wax phase for range of pressures and oil compositions.

Disadvantages

Very detailed input data. Needs tuning to measured value.

Cloud Point Methods- Not Recommended Methods These methods are not recommended to evaluate cloud points Test

Visual and turbidity test

Advantages

Disadvantages

The term cloud point is taken from turbidity test used to determine wax precipitation from fuels. The wax crystals are detected by a change in turbidity as the wax crystallizes. Often this test is performed by eye but turbidity meters increase sensitivity.

Simple. Representative sample size. Adaptable for live fluids. Wide range of cooling rates.

Sensitivity( needs finite amount of crystals) Operator dependent (Visual only) Other solids may be detected Not suitable for Black Oils.

Viscosity

As solid wax crystallizes it will effect the oils rheology causing non-Newtonian behavior. The Newtonian viscosity / temperature relationship of the oil is altered as the solid phase increases.

Representative sample size.

Sensitivity. May require presence of significant solid wax phase. Underestimating initial crystallization. May detect other solids formation. Subject to interpretation.

Pyknometry

Crystallization will change the temperature / density relationship of the fluid as it cools.

Representative sample size. Suitable for live fluids. (New techniques are improving sensitivity)

May detect other solids formation. Sensitivity. May require presence of significant solid wax phase. Underestimating initial crystallization. Subject to interpretation. No published validation.

(ASTM D2500)

58

Description

Asphaltenes Asphaltenes

• • • • • • •

The C:H ratio is approximately 1:1.2 Soluble in toluene but insoluble in lower n- alkanes such as pentane and hexane. Asphaltenes are the heaviest and largest molecules in a typical hydrocarbon mixture Oils from which asphaltenes are likely to precipitate have low API gravity (are more dense), and have higher viscosities. Deposits can be in the form of shiny and black graphite like appearance, or brown sticky soft deposits. Asphaltenes often co-precipitate with wax and even scale.

59

59

Treatment and Prevention of Asphaltenes: • •

It is better to prevent formation of asphaltenes deposits, through design and operating conditions If it cannot be prevented via design and the operating conditions, then treatment is necessary to prevent flocculation of the asphaltenes particles.

Chemical treatments for removing asphaltenes: • • • •

solvents dispersant/ solvents oil/dispersants/solvents The dispersant/solvent approach is used for removing asphaltenes from formation minerals.

Continuous treating may be required to inhibit asphaltenes deposition in the tubing. Batch treatments are common for dehydration equipment and tank bottoms. There are also asphaltenes precipitation inhibitors that can be used by continuous treatment or squeeze treatments 60

60

Asphaltenes

61

Asphaltenes Test Methods Summary

62

Scale and Mitigation Strategies: There are different types of scales. • Calcium Carbonate • naturally exists in the resevoir (carbonate reservoirs) • Scale forms: • with co-mingling of produced fluids from different producing zones or reservoirs • normally with decrease in pressure, carbon dioxide is released, and pH changes to form scale. • Mitigation: • dissolution by acidification or application of calcium carbonate scale inhibitor.

• Barium Sulphate • In general barium sulphate scale results from water incompatibility, • primarily from either seawater injection and / or seawater breakthrough, • co-mingling with produced water rich in barium. • highly insoluble and will deposit at temperature drops across the production processing plant. • Mitigation strategies:: • removal of sulphate ions from seawater for re-injection, • application of barium sulphate scale inhibitors • treatment with dissolvers. 63

Scale and Mitigation Strategies: • Iron Sulphide • Iron Sulphide scale is deposited where microbial enhanced corrosion has become a serious problem. • The scale is derived from the reaction of iron oxide from corrosion and hydrogen sulphide, • a by-product of sulphate reducing bacteria metabolism. • Treatment for iron sulphide is application of a specialist chelating and dissolution agent followed by microbial control with biocide application.

• Calcium Sulphate • Calcium Sulphate scale is relatively soluble and only poses a real problem when conditions are close to the solubility limit and super-saturation occurs.

• Sodium Chloride • Sodium Chloride scale is caused by a saturation and evaporation process and is readily removed by warm water in most cases.

64

E. Transport Properties

 Viscosity prediction methods  Oil-water viscosity – emulsions  Gas viscosity

 Compositional viscosity (LBC)  Oil-water surface Tension

65

Viscosity Definitions μo = F( P,T, SGo,SGg, Rs) usually reported in PVT Analysis. If not available, then the correlations are used.  Dead Oil Viscosity Viscosity of the oil at atmospheric conditions with no gas in solution and the system temperature.

Oil viscosity



Saturated Oil Viscosity



Unsaturated Oil Viscosity Viscosity of the oil at P>PB and Tres

Viscosity of the oil at P= PB and Tres

Estimating Oil viscosity at P≤ PB and at Tres 1. 2.

Calculate the Dead Oil Viscosity μob at Tres Adjust the dead oil viscosity for Gas Solubility effects at the desired temperature

Estimating Oil viscosity at P> PB and at Tres 1. 2.

3.

66

Calculate the Dead Oil Viscosity μob at Tres Adjust the dead oil viscosity for Gas Solubility effects at the desired temperature Include the effects of compression and under saturation of the reservoir

• Viscosity Prediction Methods Dead Oil Viscosity Correlations • Beal •

Beggs-Robinson

•

Glaso

Saturated Oil Viscosity Correlations •

Chew- Connaly

•

Beggs-Robinson μL = 10 X -1 Where X = 103.0324-0.02023 API / T1.163

Dead oil Viscosity at Reservoir Temperature and Atmospheric pressure (after Beal) 67

• Oil-Water Viscosity – Emulsions Emulsion Viscosity • Woelflin Correlation Good Bw< 40% Bw> 40% too high

•

Guth and Simha Good Bw< 40% Bw> 40% not high enough μe/μo = 1 +2.5 Cw

Woelflin Viscosity Data

where Cw is the Water Fraction of the Water Phase

•

Smith and Arnold

use when no other data available

μe/μo = 1 +2.5 Cw+ 14.1 Cw2 68

When Brine in mixture is above 60-70%, brine becomes the continuous phase.

Example E1 –Emulsion Viscosity The viscosity of a heavy crude oil sample has been characterized from lab analysis by the following relationship:

Oil Viscosity vs. Temperature 600.0 500.0

= μo

e-c(T-To)

Where c = 0.035

400.0

Viscosity, cp

μ(T)

300.0

Viscosity at the reference temperature of 50 ° F is 500 cp. Plot the viscosity curve for a range of temperatures.

200.0 100.0 0.0 50.0

1)Determine the viscosity at 100 deg F = 87 cp

2) What is the emulsion viscosity if the water cut is 60 percent? From Woelflin curve (medium), viscosity ratio = 15 Emulsion viscosity = Ratio * Oil Viscosity = 15 x 87 = 1305 cp

Will this flow? 69

90.0 Temperature, deg F

See Plot for viscosity curve.

Oil viscosity at 100 ° F

70.0

110.0

Emulsion Mitigation Causes of emulsions • • • •

High WATER Content That is the way with some wells Poor Cementing Poor reservoir management Poor Operating practices • Production of excess water • Excess turbulence in flow created by • Over pumping • Poor maintenance of plunger • Maintenance Valves in rod pumps • More than needed gas lift gas • Centrifugal pumps with a downstream throttling valve

Suggestions to prevent emulsions: • • • • • •

Do not unnecessarily choke or have control valve before water separation. Maintain plungers, rod pumps, valves Centrifugal pumps without a downstream throttling valve Some operators prefer Cavity Pumps, Reciprocating Pups, or Gear pumps Optimize Gas Lift Optimize production at integrated asset level

Else use: • 70

Emulsifiers

• Other Fluid Properties



Surface Tension  

σ = f (SGoil, SGwater, P, T)

Plays an important role in calculating the flow pattern prediction in multiphase flow. Plays role in Gas – Oil interface, as well as gas –water interface, and oilwater interface.

Surface Tension Calculation Methods:  Baker and Swerdloff  Katz et. al. 

71

Specific Heat Capacity of the fluid - Very important parameter in heat transfer

F. Heat Transfer Analysis

 Basic principles of conduction, convection and radiation  Heat transfer through composite layers  Wellbore heat transfer  Pipeline heat transfer  Wellbore and pipeline heating

72

Heat Transfer Phenomena T ambient T inlet

Buried Pipeline

Area of Cross-Section

T fluid

The rate of heat transfer per unit length (Btu/hr/ft) is given by:

dH/dL = U A (T fluid – T ambient) where

U A T ambient T fluid

overall heat transfer coefficient, Btu/hr-ft2-degF cross-sectional area of pipe, ft2 temperature of surrounding, deg F average temperature of fluid in pipe, deg F

From basic calorimetric calculations, the change in pipeline fluid temperature due to heat transfer to the surroundings is given by:

(Toutlet – Tinlet) = - dH/dL x pipe length / Cp / mass flow rate where

Cp

specific heat capacity of fluid mixture, Btu/lb/deg F

The heat transfer coefficient U is determined by analyzing the combined effect of the three modes of heat transfer:

  

Conduction - within a solid or between solid bodies (e.g. pipe wall and soil) Convection - achieved through the movement of fluid (e.g. submerged pipe) Radiation - energy emitted as electromagnetic waves from a hot body

Note that radiation heat transfer is generally not significant in flow assurance (with the exception of steam injection) 73

Example F1 – Pipeline Heat Transfer T inlet =100 deg F Q = 5000 BPD

T ambient = 40 deg F Buried Pipeline, U = 1.0 Btu/hr-ft^2-degF, Pipe Length = 10,000 ft

Pipe Outer Diameter = 12 inch

Oil Gravity = 0.8, Specific Heat Capacity = 0.5 Btu/lb/degF

Determine the outlet temperature for 12-inch x 10,000 ft buried crude oil (sp gravity = 0.8) pipeline flowing at 5000 BPD, given an overall heat transfer coefficient of 1.0 Btu/hrft2-degF. Temperature at the inlet of the pipeline is 100 deg F and the ambient temperature is 40 deg F. Assume that the specific heat capacity of the oil is 0.5 Btu/lb/de gF.

Procedure 1. Area of pipe cross-section = 3.14 / 4 * (12/12)2 = 0.785 ft2 2. Mass flow rate = 5000 BPD /24 hr/day * 5.615 ft33/bbl * (0.8 * 62.4) lb/ft3 = 58,396 lb/hr 3. Estimate outlet temperature = 60 deg F 4. Heat transfer gradient, dH/dL = U A (T fluid – T ambient) = 1.0 x 0.785 x (80-40) = 31.4 Btu/hr/ft 5. Change in temperature = dH / Cp / mass flow rate = 31.4 * 10,000 / 0.5 / 58396 = - 10.8 deg F 6. Revised outlet temp (iteration 1) = 100 – 10.8 = 89.2 deg F (error = - 29.2) 7. Repeat Steps 4-6 with new outlet temp 8. Revised outlet temp (iteration 2) = 85.3 deg F (error = 3.9) 9. Repeat iteration steps until convergence 10.Converged outlet temperature (after 4 iterations) = 85.8 deg F (error = 0.1)

Question – will segmentation of the pipe provide greater accuracy? 74

Overall Heat Transfer Coefficient Classical Shell Balance Overall Heat Transfer Coefficient U = 1 / Total Resistance Total Resistance = sum of resistances from convection / conduction layers

Convection due to boundary layer - film Conduction at inner wall, coating, Insulation

Conduction layer resistance = diameter * loge(diaouter/diainner) / 2k

where:

κ - thermal conductivity, Btu/day-ft-degF

Resistance due to film (convection) = diainner / (0.0225 * k * Re where

0.8)

Convection (or conduction) in annulus Conduction at outer wall, coating, Insulation Outer surface: submerged (convection), buried (conduction) or exposed (free convection)

Re - Reynolds number

Outer Surface (buried / submerged / exposed) Resistance due to conduction (buried pipe) = diameter * loge((2Z+ (4Z2 – dout2220.5)/dout) / 2ksoil where Z is the distance from the surface to the centerline of the pipe

Resistance due to convection (submerged in water/exposed to wind) = diameter / (10 k *(0.26694 * log10(Re,surrounding)1.3681))

Where Re,surrounding= 1.47 x Reynolds number calculated from pipe outer diameter and surrounding fluid properties

75

Overall Heat Transfer Coefficient, OHTC

OHTC based on the flowline internal surface Area Ai is:

OHTC based on the flowline external surface Area Ao is:

76

Subsea Flowline Insulation Methods • • • • •

External Coatings Flowline Burial Pipe-in-Pipe (PIP) Electrical Heating Hot WaterAnnulus

U Values for Different Subsea Insulation Methods, (Loch, 2000)

77

Thermal Conductivities of Soil Kersten(1949)

Κsoil = [ 0.9 log(ω) -0.2]*100.01*ρ where Κsoil soil thermal conductivity, [BTU-in/(ft2-hr-°F)] ω ρ

moisture content in percent of dry soil weight dry density , lb/ft3

Thermal Conductivities of Typical Soil Surrounding Pipeline (Gregory,1991)

78

Flowline Burial Depth Loch (2000)

• When the ratio between the burial depth and the Outside Diameter is greater than 4, the decrease in the U value is insignificant. • Available burial techniques may set the limit on Minimum and Maximum Burial Depths. • Potential seafloor scouring and flowline disturbance buckling need to be considered .

79

Example F2 – Overall Heat Transfer Coefficient Calculate the overall heat transfer coefficient for the pipeline in Example F1 given the following data: pipe diameter (inner) pipe wall thickness insulation Burial depth (center line to surface) Pipe Thermal Conductivity Insulation Thermal Conductivity Soil Thermal Conductivity Oil Flow Rate Oil Specific Gravity Oil Specific Heat Capacity Oil Thermal Conductivity Oil Viscosity

12 0.25 0.5 24 600 0.96 24 5000 0.8 0.5 1.6 3.5

inch inch inch inch Btu/day/ft/F Btu/day/ft/F Btu/day/ft/F BPD water = 1 Btu/lb/degF Btu/day/ft/F cp

Determine the relative contribution of insulation and burial on the overall resistance to heat transfer.

Change the heat transfer coefficient in Ex F1 to the calculated value and evaluate the impact.

Procedure 1. Area of cross-section = 3.14 / 4 * (12/12)2 = 0.785 ft2 2. Fluid velocity = 5000 BPD x 5.615 ft3/bbl / 86400 sec/day / 0.785 = 0.41 ft/sec 3. Reynolds number = 1488 * 0.41 * (12/12) * (0.8 * 62.4) / 3.5 = 8785 4. Film resistance (convection) = (12/12) / (0.0225 * 1.6 * 87850.8) = 1.944 E-2 5. Pipe wall resistance (conduction) = (12/12) x 1/(2*600) loge (12.5/12) = 3.4 E-5 6. Insulation resistance (conduction) = (12.5/12) x 1/(2*0.96) loge (13.5/12.5) = 4.175 E-2 7. Soil resistance (conduction) = log( (4*242– 13.52)0.5/13.5)/(2 x 24) = 2.877E-2 8. Total resistance = 1.044E-2 + 3.4E-5 + 4.175E-2 + 2.877E-2 = 9.00 E-02 9. Overall heat transfer coefficient U = 1/(9E-2 x 24) = 0.46 Btu/fr/ft2/degF

Overall contribution of insulation = 4.175 / 9 = 46.4 % Overall contribution of burial = 2.877 / 9 = 32.0 % Updating Ex F1 with U=0.46 changes the calculated outlet temperature from 85.8 deg F to 93 deg F 80

Heat Transfer In Wellbores Aditional Heat Transfer in Wellbores: •

Infinite Conduction For a vertical well, the surrounding formation extends outwards infinitely – the finite depth burial model for conduction described earlier needs to be modified.

•

Transient Considerations In steam injection wells, there may a significant timedependent effect as the surrounding formation heats up and heat transfer rates change as a consequence (heat transfer rate during the early time period will be higher). The Ramey function is used to analyze this time dependent effect. Heating the surrounding formation may also cause the thermal conductivity to change around the wellbore due to the evaporation of water.

•

Annulus Heat Transfer Heat transfer in the annulus due to convection of the static annulus fluid (water/oil/gas/vacuum) needs to be taken into account. Additionally, radiation effects are sometimes important (e.g. in some steam injection systems, a reflecting coating is painted on the inside wall of the casing to reduce radiation effects).

81

Classic Shell Balance Convection due to boundary layer - film Conduction at inner wall, coating, Insulation Convection (or conduction) in annulus Conduction at outer wall, coating, Insulation Outer surface: submerged (convection), buried (conduction) or exposed (free convection)

Terminology Symbol dH dH/dL

Heat transfer rate, Btu/hr Heat transfer gradient, Btu/hr/ft

U

Overall heat transfer coefficient, Btu/hr-ft2-degF

A

Area of pipe cross-section, ft2

T ambient T fluid

Cp k

82

Definition

Temperature of surroundings, deg F Temperature of fluid, deg F

Specific heat capacity, Btu/lb/deg F Thermal conductivity, Btu/day/ft/deg F

G. Transient Phenomena

 Basic principles of single phase transient flow  Multiphase flow transients

 Pipeline startup, shut-in and blowdown  Terrain induced slugging

83

Common Transient Operations Transient Condition

84

Operation

Impact

Ramp Up / Down

Rate change

Rate surge

Startup

Rate change from zero

Pressure surge Rate surge

Shutdown

Compressor / Pump shutdown

Pressure surge

Blowdown

Pressure reduction

Terrain Slugging

Caused by topography

Slug formation, growth and dissipation

Sphering

Periodic operation

Rate surge

Pipeline leak / rupture

Unplanned

Product loss Environmental damage Pressure surge

Flow Rate Ramp Up LIQUID INVENTORY REDUCTION

BEFORE

AFTER

How Big is the Surge?

Marlin Pipeline 67 mile x 20 inch (Cunliffe’s approximation procedure) Predicted Liquid Inventory

Rate ramped up from155 MMscfd to 258 MMscfd

10000

69 bbl/MMscf liquid loading

6000 4000 2000

0.0

100.0

200.0 Rate, MMscfd

  85

1000 800 600 400 200 0

0



Outlet Liquid Rate, bph

Inventory, bbl

1200 8000

300.0

0

20

40

Time, hr

Determine equilibrium inventory (holdup) at initial and final rates  Difference give the amount of liquid to be swept out Estimate transition time as residence time for final inventory Transition Time = Final Inventory / Final Rate Estimate Transition Rate Transition Rate = Final Rate + Inventory Change / Transition Time

60

Example G1 - Marlin Pipeline Transient

35000 30000 25000

69 bbl/MMscf liquid loading

Inventory, bbl

20000 15000 10000 5000 0 0.0

100.0

200.0

Rate, MMscfd

300.0

Outlet Liquid Rate, bph

From the pipeline inventory prediction provided for Marlin, use Cunliffe’s method to approximate the surge rate at the downstream slug catcher when the gas rate at the inlet is ramped up from 155 MMscfd to 258 MMscfd over a period of one hour. Compare the predicted surge rate to the actual data and recommend additional steps to improve the estimation. 1200 1000 800 600 400 200 0 0

10

20

30

40

50

Time, hr

Initial inventory at 155 MMscfd = 19200 bbl (estimated from plot) Final inventory at 258 MMscfd = 17600 bbl Liquid to be swept out = 19200 – 17600 = 1600 bbl Liquid Rate (Final) = Liq Loading x Gas Rate = 69 x 258/ 24 = 742 bph Transition Time = Final Inventory / Final Rate = 17600 / 742 = 23.7 hr Transition Rate = Final Rate + Inventory Change / Transition Time = 742 + 1600 / 23.7 = 809 bph From data: Actual surge rate > 1000 bph – the discrepancy is caused by the high transition time Lowering the effective transition time estimate would improve prediction(see spreadsheet) 86

Pipeline Blowdown (depressurization) Blowdown is the controlled depressurization of a gas (or gas-dominated) pipeline generally achieved over a period of time. Blowdown is generally a safety procedure used to reduce the risk of pipeline rupture and fire in an emergency. The key concerns during blowdown are: 1) How long will it take to depressurize the pipeline (to near atmospheric conditions) 2) What is the cooldown temperature profile given that the temperature will drop below ambient due to Joule-Thompson cooling (potential for hydrate formation)

The discharge rate is generally controlled through an orifice (or valve) to ensure that these operational issued are addressed. Assuming critical flow, the mass flow rate (lb/sec) through an orifice is given by the relationship: W = Cd K A P (MW / zT)0.5 where

87

Cd is the coefficient of discharge K is the specific heat capacity ratio for the gas A is the area of cross-section MW is the molecular weight P is the upstream (pipeline) pressure

Example G2 - Pipeline Blowdown Determine the pressure profile for the blowdown of a 5 mile x 6 inch (ID) gas pipeline operating at 800 psi when the gas (gravity=0.8) is released through a 3-inch orifice (Cd = 1.0). Average compressibility is 0.9, k = 1.4, and assume that the pipeline temperature does not change from its initial value of 39 deg F. Procedure 1. 2. 3. 4. 5. 6. 7.

From geometry, orifice area = 3.14/4 * (3/12)2 = 0.049 ft2 Pipeline volume = 3.14/4 * (6/12)2 * (5 x 5280) = 5181 ft3 Gas Molecular Weight = 28.97 x 0.8 = 23.18 Initial density of gas = 800 * 23.18 / (0.9 * 10.73 * (460+39) = 3.85 lb/ft 3 Initial mass of fluid (gas) in pipeline = 3.85 * 5181 = 19934 lb Initial rate of gas flowing through the orifice = 1 x 1.4 x 0.049 x 800 * (23.18/0.9/(460+39)) 0.5 = 12.48 lb/sec Starting from time =0, calculate the following at 100 second intervals 1. Mass rate of gas through the orifice (from the orifice equation) 2. Remaining mass of gas in the pipeline (previous mass – mass rate * time increment) 3. Gas density = remaining mass / pipeline volume 4. Average pipeline pressure = density * z * 10.73 * (460+39) / 23.18 5. Determine the gas discharge rate at standard conditions from the mass rate 6. Plot the pressure and gas flow rate profiles as a function of time Pressure Profile (psi vs. time)

Flow Rate Profile (MMcfd vs. time)

1000

20.00

800 15.00 600 400

10.00

200

5.00

0 0

88

1000

2000

3000

4000

0.00 0

1000

2000

3000

4000

Pipeline Cooldown When pipeline is shut-in, the fluid temperature drops over an extended period of time until ambient conditions are achieved. A significant parameter for cooldown analysis is the “no-touch” period which is the time available before the pipeline must be started up again. For a pipeline transporting waxy crude, the no-touch period is the time before pour point (plus safety margin) is reached

From the Lumped Capacitance Cooldown Model, the temperature T is given by : T(t) – To = (Ti - To) x exp (- C x t) where

89

t = period after shut-in C = U * Area of Contact / (mass of fluid * specific heat capacity)

Example G3 - Pipeline Cooldown Given a 10,000 ft x 12 inch subsea pipe with a heat transfer coefficient of 1 Btu/hr/ft2/F and an average fluid temperature of 100 deg F, estimate the no-touch time when the surrounding temperature is 40 deg F. Crude oil characteristics: specific gravity = 0.8, heat capacity = 0.5 Btu/lb/F, pour point = 50 deg F Solution:

T(t) – To = (Ti - To) x exp (- C x t) where

Ti is the inside fluid Temperature T(t) is the inside fluid Temperature at time t To is the ambient temperature t = period after shut-in C = U * Area of Contact / (mass of fluid * specific heat capacity)

120.0 100.0 80.0 Fluid Temp, F

From the Lumped Capacitance Cooldown Model, the temperature T is given by :

60.0 40.0 20.0

Procedure: Fluid mass = 3.14/4 * (12/12) 2 * 10,000 * (62.4 * 0.8) = 391,872 lb C = 1 x (3.14 x (12/12) x 10000) / (391872 * 0.5) = 0.16

0.0 0.00

10.00

For a range of time periods (e.g. 0-24 hrs in 1 hr increment) calculate and plot T(t) From the plot (see right), no-touch time = 11 hr (actual time will be lower)

90

Time, hr

20.00

30.00

H. Integrated Flow Assurance

 Combining fluid flow, heat transfer and thermodynamics  Deepwater/subsea systems  Heavy oil transport  Monitoring and control

91

Fluid Flow, Heat Transfer & Thermodynamics Hydrate Management Thermodynamics establishes hydrate limits Temperature and pressure determine hydrate performance Heat transfer controls temperature profile Fluid Flow influences Heat Transfer

Fluid Flow Analysis

Predicts Flow & Pressure Behavior

Thermodynamic Analysis Predicts Fluid PVT Properties

Heavy Oil Transport Heat Transfer determines temperature profile Temperature controls viscosity behavior Fluid viscosity establishes fluid flow Fluid Flow influences Heat Transfer

Flow Assurance Integrated Analysis of Flow Behavior, Pressure and Temperature Performance, and Fluid Properties

Production Performance Flow rates establish production performance Pressure determines flow rates PVT properties impact pressure and temperature profile Temperature and pressure influence PVT properties

Heat Transfer Analysis 92

Predicts Temperature Behavior

Flow Assurance in Deepwater / Subsea

16000 14000

Fewer wells, minimal intervention Premium on reliability

Wax

12000

Commingling of incompatible fluids

Limited monitoring of wells, pipeline & riser

Pressure

Reservoir

10000 8000

Hydrate

6000

Asphaltene

4000

High back-pressure Need for boosting

Deeper, colder plugging & deposition

Bubble Point

2000 Facilities 0 0

50

100

150

200

250

Temperature

Flow assurance in deepwater is about designing and operating systems that handle the many unique challenges of subsea production while mitigating unnecessary risk to ensure the continuous flow of oil and gas from capital-intensive projects

93

Example H1 – Heavy Oil Throughput Capacity T inlet =100 deg F Q = 5000 BPD

T ambient = 40 deg F Buried Pipeline, U = 1.0 Btu/hr-ft^2-degF, Pipe Length = 20 miles

Pipe Outer Diameter = 12 inch

Oil Gravity = 0.8, Specific Heat Capacity = 0.5 Btu/lb/degF

Determine the throughput (BPD capacity) for a 12-inch x 20 mile heavy oil pipeline with an inlet conditions of 250 psi and 100 deg F. The minimum outlet pressure is 100 psi. The viscosity of the crude is characterized as a function of temperature (deg F) by the following exponential fit of lab data: viscosity, cp = 500 x exp (-0.035 (temp in deg F – 50)) Solution Procedure 1.Set the initial estimate of the throughput to be 30,000 - 50,000 BPD 2. Use the iterative procedure described in Example F1 (Pipeline Heat Transfer) for calculation of outlet temperature for the given inlet temperature of 100 deg F. With a reasonable outlet temperature estimate, the solution should converge in 4 iterations (or less). 3. Compute the velocity from the estimated flow rate. 4. Compute the viscosity at the average fluid temperature (mean of fixed and calculated outlet temp) 5. Update Reynolds number with the new velocity and viscosity 6. Update friction factor using the laminar flow equation (validate that Reynolds number is within range) 7. Calculate the frictional pressure gradient from the friction factor 8. Compute the outlet pressure for the estimated flow rate. 9. Update the estimated flow rate and repeat Steps 2-8 until the outlet pressure is approx 100 psi. This is the calculated throughput for the pipeline.

Calculated throughput = 42,000 BPD (outlet temperature = 83 deg F) 94

Drag Reduction •

Drag Reduction Additives (DRA) are long-chain, ultra-high molecular weight (1-10 million) polymers that are injected into liquid pipelines (both crude and refined products) to increase throughput capacity.

•

DRA does not alter the fluid properties or coat the pipe wall, but rather drag reduction occurs due to the suppression of energy dissipation by eddy currents in the transition zone between the laminar sub-layer near the pipe wall and the turbulent core at the center of the pipe.

•

Turbulent flow in the pipe is therefore a prerequisite for DRA to be effective.

•

In crude oil pipelines, DRA injection rates vary in the range of 10-50 ppm, with the corresponding drag reduction effectiveness, the fractional reduction in frictional pressure drop in the treated line, typically about 30-70 percent, and generally more effective in lighter crudes. Modeling the effect of DRA injection in a pipeline is relatively straightforward.

• •

Vendor supplied Performance Curves the effective drag reduction as a function of flow rate for a range of concentrations.

•

These curves are pipeline specific and are generated from flowline tests conducted by the vendor.

95

I. Integrated Production Analysis

•The economics of flow assurance •Reservoir performance – how it impacts production •Introduction to artificial lift methods •Integrated asset modeling (IAM) – reservoir, production, process plant, economics 96

• Economics of Flow Assurance • • •

•

97

At a high level, the economics of flow assurance involves a balance between Cap Ex and annual Op Ex Costs based on the projected revenue stream. Higher investments in Cap Ex are justified when the field is expected to produce economically for a longer period (the projected life of a typical offshore field varies from 10-30+ years). Several factors effect the Revenue projections, including: •

pricing forecasts for oil and gas

•

the availability of future markets through nearby pipeline connections (especially for gas)

•

fiscal regimes (taxation, royalty, production sharing)

•

the time value of money (relating to deferred production)

• Economics of Flow Assurance Some of the key components of Cap Ex and Op Costs that need to be included in any economic analysis for evaluating flow assurance alternatives: • Capital Expenditure • • • • •

Drilling and completion of wells Pipelines and gathering system installation Installation of prime movers (compressors / pumps / multiphase pumps) Facilities (platform, slug catcher, separator, heaters, recovery and reinjection, other topsides) Artificial lift installations including related facilities such as compression, power lines etc.

• Operating Costs • •

• • • 98

Facilities maintenance Inhibitors/chemicals for hydrates (methanol/glycol), wax, asphaltenes, corrosion, surfactants, etc. Power costs for compressors, pumps, heaters, topsides, etc. Personnel (platform, onshore, central support) QHSE

•

Reservoir performance–how it impacts production

Reservoir Decline Reservoir Pressure (current) = Reservoir Pressure (previous) * Decline Rate * Cum Production Note: for gas fields p/z is sometimes used instead of pressure (p) in the above equation

Maximum Drawdown Drawdown is generally limited to avoid problems such as sand production 99

Bottom Hole Pressure > Reservoir Pressure – Max Drawdown Limit

•

Most oil production reservoirs have sufficient potential to naturally produce- during the early phases of production.

•

As reservoir pressure decrease, water encroachment will naturally cause all wells to slow down in production.

•

At some point, an artificial lift will be used to continue or increase production.

•

On the other hand most water producing wells will need some kind of artificial lift due to the high hydrostatic pressure it creates on the oil, gas, or both. A well with high water rate will be usually put on an artificial lift from the beginning.

• •

Available technologies add energy to the system to lift the fluids to the surface. There are times an oil well may need: • • •

100

ESP Gas Lift Rod Pump

• Hydraulic Pumps • PCP • Plungers

Pressure (Psi)

• Introduction to Artificial Lift Methods

• Integrated Asset Modeling, IAM – Reservoir, Production, Process Plant, Economics IAM help to determine : • • • • • • •

impacts of new drilling best locations to set compression to influence the order and location of the new drilling evaluating the impact of third party activity investigating gathering system improvement opportunities for tubing sizes and evaluation of options versus performance identifying wellwork candidates and other production enhancement opportunities

and to analyze: • • • • • •

upsets and production losses requests from Infill Team on lateral capacity uplift for future pressure changes for future pipeline projects, pressure changes for future compressor projects for debottlenecking

In summary, the reservoir decline, added wellhead compressor, the new wells feeding into the same line, the increased compressor suction pressures, and the availability of processing facilities, along with the economics can be coordinated to give the optimized production scenerios. 101

Flow Assurance Monitoring & Control

Subsea monitoring & control data

seabed data

wellbore data

manifold

ESP DTS 102

FPSO

multiphase pump

multiphase meter

flowline measurements

IAM Visualization Near Real-Time Field Data and Model Results Monitoring Business value of these new operating tools achieved through improved operations efficiency, integrity management, and organizational performance, by integrating activities around reservoir, wells, pipelines, facilities, and commercial decision-making

103

103

Map-based Visualization Near Real-Time Field Data and Model Results Monitoring

104

104

IAM Online Model Calculations • Differential Line Pressure (actual versus model calculated) • Pipeline resistance (DP/Q) • Mixture Velocity • Erosion Rate (Salama)

• Corrosion Rate (de Waard) • Liquid Hold-up

105

Model Error Tracking 105

Reservoir Inflow Inflow Performance Relationship (IPR): Production rate as a function of flowing wellbore pressure, (Pwf).

PI = Qo / (PR - Pwf) Vogel’s equation

under-saturated oil reservoir

Linear below the bubble point pressure

Qo = Qomax (1 – 0.2 Pwf /PR – 0.8 (Pwf /PR)2) where Qomax is a hypothetical maximum rate at Pwf = 0

The following equation can be used when Pwf < PB < PR

Flowing Bottom Hole Pressure

Productivity Index

Productivity Index in Under-Saturated Reservoirs

P Pwf r

Slope = 1 / PI

Qo

Qomax

Qo = PI (PR - PB) + 0.5 PI / PB(PB 2 – Pwf2) Oil Production Rate

For Gas Wells (back pressure equation): QG = Cp [ (PR) 2 – (Pwf) 2]n

106

for 0.5 < n < 1.0

Example I1 - Oil Well IPR From a well test, the bottom-hole pressure was measured as 1234 psi at a rate of 2345 bpd. The static pressure in the reservoir after the well was shut-in for 48 hours was measured as 3636 psi. Lab tests show that the bubble point pressure at the reservoir temperature of 200 deg F was 2222 psi. Determine the productivity index and absolute open flow potential and use these values to plot the IPR curve for the well. Since test pressure (1234 psi) < BPP (2222 psi)

Pressure vs. Rate

PI = Qo / [(PR - PB) + 0.5 / PB(PB 2– Pwf2)] = 1.07 bpd/psi

4000

Qomax = Qo / (1 – 0.2 Pwf /PR – 0.8 = 2792 bpd

Calculate Qo for a range of Pwf using the equation: Qo = PI (PR - PB) + 0.5 PI / PB(PB2- Pwf2) Where:

PR = 3636 psi PB = 2222 psi PI = 1,07 bpd/psi

The maximum rate is 2713 bpd (at Pwf = 0) 107

Pressure (psi)

3500

(Pwf /PR) 2)

3000 2500 2000 1500 1000 500 0 0.0

1000.0

2000.0

Rate (bpd)

3000.0

Example I2 - Integrated Production System An integrated gas production system extends from the reservoir through the wellbore, pipeline and compressor flowing into the separation facilities. Estimate the delivery capacity to a downstream trunk line operating at a fixed pressure of 1000 psia. The following data applies: Reservoir Pressure = 5000 psia, Temperature = 200 deg F, Gravity = 0.75 Deliverability: Cp = 7.8E-6, n = 0.9 Well Depth = 10,000 ft, Diameter = 4 inch Average friction factor = 0.015, Average Z = 0.8 Surface Pipeline Length = 20 miles, Diameter = 6 inch Surface Temperature = 80 deg F Average friction factor = 0.01, Average Z = 0.9 Procedure

108

1. Estimate gas deliverability Qg (range: 25 – 35 MMscfd) 2. From the reservoir pressure, calculate the flowing BHP using the gas deliverability equation 3. Estimate the average wellbore temperature to be the average of the reservoir and surface temp (140 F) 4. Approximating the average wellbore pressure to the FBHP, calculate the estimated velocity and density 5. Calculate the frictional pressure gradient from the friction factor, density and velocity 6. Calculate the elevation gradient from the density 7. Determine the wellhead pressure for the estimated rate from the two pressure gradient terms 8. Estimate the surface velocity and density using the same approach as that for the wellbore 9. Calculate the surface frictional gradient and use this to calculate the delivery pressure from the wellhead pressure for the estimated rate. 10.Compare the delivery pressure with the 1000 psia delivery requirement, adjust the estimated rate, and repeat steps 2-9 until convergence is achieved. 11.The final converged estimate of throughput is approximately 31 MMscfd

Flow Assurance Issues

109

Terminology Symbol

110

Definition

Pwf

Flowing bottom hole pressure (psi)

PI

Productivity Index (bpd/psi)

PR

Reservoir pressure (psi)

Qo,max

Absolute open flow (bpd)

Cp

Gas deliverability constant

N

Gas deliverability exponent

PB

Bubble point pressure (psi)

Unit Conversions Unit of Measure

US Oilfield Units

Other Units

Conversion

Pressure (abs)

psia

kPa bar

kPa = psia x 6.8948 bar = psia x 0.068948

Temperature

deg F

deg C

deg C = (deg F – 32) */ 1.8

Oil Gravity

deg API

specific gravity

SG = 141.5 / (131.5 + API)

Pipe Diameter

inch

mm

mm = 25.4 x inch

Pipe Length

ft

meter

meter = ft x 0.3048

Liquid Volume

bbl

ft3 meter3

ft3 = bbl x 5.615 meter3 = ft3 x 0.0283 meter3 = bbl x 0.159

Gas Volume

scf (ft3)

sm3 (meter3)

meter3 = ft3 x 0.0283

Liquid Rate

bpd

m3/d

m3/d = bpd x 0.159

Gas Rate

MMscfd

km3/d MMsm3/d

km3/d = 28.3 x MMscfd MMsm3/d = .0283 x MMscfd

Standard Conditions: 14.7 psia, 60 deg F (1.02 bar, 15.5 deg C) Absolute Zero: -460 deg F (-273 deg C) 111

J. Flow Assurance Considerations in Conceptual Design & Operations

Two participative classroom exercises, J1 and J2, where the concepts discussed in the preceding sessions will be applied to two practical example involving the creation of: • J1

a field development plan with particular emphasis on the impact of flow assurance issues on the overall design.

• J2 a Pipeline throughput increase without significant capital investment

112

Workshop J1- Conceptual Design Problem Platform

Satellite After Year 5

Riser Depth = 5000 ft Diameter = 10 inch U = 6 Btu/hr/ft2/degF MAOP = 1250 psia Roughness = .0012 inch

Subsea Manifold

Contractual Rate = 20 MMscfd Est. Inlet Temp at Manifold = 68 deg F

Pipeline Length = 10 mile Diameter = 8 inch Roughness = .0012 inch U = 3.3 Btu/hr/ft2/degF Ambient Subsea Temp = 39 deg F MAOP = 1550 psia

Well Depth = 14000 ft Diameter = 6 inch U = 6.5 Btu/hr/ft2/degF Geothermal grad = 1.2 deg F / 100 ft Roughness = .0012 inch

Surface Ambient Temp = 60 deg F Minimum Delivery Pressure to Trunk Line = 1750 psia Compressor Power / Stage = 150 HP Overall Compressor Efficiency = 80% Initial Number of Stages (Year 1-5) = 3 Final Number of Stages (Year 6 +) = ?

Riser Base

Gas Gravity = 0.75 Average Compressibility = 0.9 Specific Heat Capacity = 0.7 Cp / Cv Ratio = 1.31 Bottom Hole

Reservoir

Initial Reservoir Pressure = 5000 psia Decline Rate = 0.01 psi/MMscf Reservoir Temperature = 120 deg F Max Drawdown (avoid sand production) = 3000 psi Deliverability Constant Cp = 8 E-6 MMscf/psi2 Deliverability Exponent n = 0.90

Maximize production within the constraints of the operating envelope through the first five years of operation. After five years, a satellite field is being brought on-stream at the subsea manifold with a contractual rate of 20 MMscfd. What is the impact on existing production and how much additional compression is needed to produce both fields? 113

Workshop J1 - Engineering Design Concepts Basic Engineering Concepts Applied: 



 

 

114

Reservoir  Gas deliverability equation (see Reservoir Deliverability)  Reservoir decline  Drawdown limit Wellbore  Pressure gradient (see Momentum Balance)  Heat transfer (see Heat Transfer) Manifold  Fluid mixing – temperature Subsea Pipeline  Pressure gradient  Heat transfer  Hydrate prediction temperature Riser  Pressure gradient  Heat transfer Platform  Compression

Reservoir Decline Reservoir Pressure (current) = Reservoir Pressure (previous) * Decline Rate * Cumulative Production Note: for gas fields p/z is sometimes used instead of pressure (p) in the above equation

Maximum Drawdown Drawdown is generally limited to avoid problems such as sand production Bottom Hole Pressure > Reservoir Pressure – Max Drawdown Limit

Fluid Mixing at Junction (Subsea Manifold) Mixture Temperature (downstream) = (Stream1 Temp*Stream1 Rate + Stream2 Temp*Stream 2 Rate) / (Stream 1 Rate + stream 2 Rate) Note: for multiple streams, the downstream temp is the massweighted temperature of all incoming streams

Simplified Hydrate Prediction The following empirical model (Hammerschmidt) is used: Hydrate formation temp (deg F) =8.9 x psia0.85

Compressor Power HP = 550 * Mass Rate (lb/s) * Head (ft) / Efficiency / g Head = n / (n – 1) * Pinlet * (Ratio ((n-1)/n) – 1))

Workshop J1- Summary of Operating Constraints Location

Minimum Temp

Min Pressure

Max Pressure

Reservoir

NA

NA

NA

Bottom Hole

NA

Drawdown limit

NA

Manifold

Hydrate limit

NA

Pipeline MAOP

Riser Base

Hydrate limit

NA

Riser MAOP

Platform Inlet

Hydrate limit

NA

NA

Delivery

NA

Trunk line pressure

NA

Solution cannot violate any of the above constraints for the projected 10-year operating scenario

115

Workshop J1- (Excel File)

Spread Sheet 1 of the Excel file Workshop J1 defines the full problem to be solved: Lines 5-10 summarizes the results for a simulation scenario in terms of the pressure & temp at the key points along the system. The bright yellow fields in Column D represent the variable to be changed (well rate, satellite rate, cumulative production, compressor stages). DO NOT CHANGE ANY OTHER FIELDS

116

Solution to Workshop J1- (Excel File) Spread Sheet 2 of the Excel file Workshop J1 is the worksheet used to determine the cumulative production volume from the production profile. 1. 2.

3. 4. 5. 6.

7. 8. 9.

In Spreadsheet 1, set satellite production = 0; number of compressor stages = 3 to start the analysis For year 1, set cumulative production = 0 (new field) and adjust Well Production (range: 25-35 MMscfd) until none of the constraints are violated. Enter this value in Sheet 2 for year 1 and determine the cumulative volume produced by the well at the end of the year. Enter the cumulative volume in Sheet 1 and repeat Step 2 for Year 2 Repeat Steps 2-3 for the first five years. At Year 6, set satellite production = 20 MMscfD and determine the flow rate at which the minimum delivery pressure is achieved. Note that the hydrate temperature limit is violated because of the cooler satellite production stream. Add another stage of compression (stages = 4) so that production from the Well increases and the pipeline temperature no longer falls below the hydrate limit. Repeat Steps 2-3 for the remaining years in the scenario Note that the pipeline temperature falls as well production drops dues to reservoir decline. If temperature drops below the hydrate limit, add more compression in Year 6 and repeat the steps through the end. The plot on the right shows the predicted production profile for the ten year scenario.

Well Production Profile Well Production, MMscfd

35 30 25 20 15 10

5 0 0

117

5

10

Years of Production

15

Workshop J2 -Pipeline Operations Problem 88.8 km x16 inch branch line flowing from mainline to refinery (10 ¾ inch pipe for final 8 km) Inlet Pump Station SP1 – 3x500 kW (1 spare), Intermediate Pump Station SP2 – 2x500kW units (1 spare). Inlet Pump Station (SP1) Intermediate Pump Station (SP2) Highest Point 16/10 Switch Refinery

Distance KM 0 44.6 69.4 80.8 88.8

Elevation m 416 740 1263 1100 431

Current Operations: Crude oil gravity = 0.83 avg. viscosity = 3 cSt Operational service = 170day/yr Average sand = 390 ppm

OD inch 16 16 16 10.75 10.75

1500 Elevation, m

Pipeline Profile

1000 500 0 0

20

40

60

80

100

Pipeline pressure profile (bar) from SCADA at 650 m3/hr: SP1 Outlet SP2 Inlet SP2 Outlet High Point Refinery

74.3

27.3

53

2.2

39.7

How much can pipeline throughput be increased without significant capital investment (through a combination of existing pump capacity utilization and DRA injection)? Assume DRA performance is for medium crude per chart on right. Analyze the operational economics given: a) Utility rates of euro 0.10/kWh b) DRA injection cost of euro 10/gallon

118

Solution to Workshop J2 - (Excel File) Spread Sheet 1 (Baseline) is the worksheet used to determine the baseline pipeline operation from current operations data (SCADA pressure profile). •

Key Assumptions: • Line fill compaction = 1.5% (change in volume at in situ pressure and temperature) • Wall thickness = 0.375 inch for 16 inch pipe, 0.365 for 10 inch pipe (Schedule 40)

• •

Adjust pipe roughness and pump efficiency until predicted profile matches SCADA Use adjusted values and calculated pipeline inlet pressure for all subsequent analysis

Spread Sheet 2(Analysis) is the worksheet used to analyze various operating scenarios

• Key Constraints: • •

Pressure at Highest Point > 0 bar (else slack line conditions) Pipeline velocity < erosional limit (const in API RP14E = 135 for solid (sand)