Water Wetting Prediction Tool for Pipeline ... - PRCI

S. Nesic, L. Paolinelli, M. Mateer, S. Huizinga

Institute for Corrosion and Multiphase Technology Ohio University

October, 2018

1

Water Wetting Prediction Tool for Pipeline Integrity

IC-1-7 - Progress Report

RUSS COLLEGE OF ENGINEERING AND TECHNOLOGY

Current timeline

2

RUSS COLLEGE OF ENGINEERING AND TECHNOLOGYDept. of Chemical and Biomolecular Engineering3

Institute for Corrosion and Multiphase Technology

Timeline: 2 years

Task Description Cost Planned Duration

Time line Status

MS1-T01

Complete the gap analysisin the current ICDAmethodology.

12,500 2 months January 2018 –March 2018

Completed

MS1-T02

Complete the conceptualframework for the new WWmodel.

18,750 3 months March 2018 –May 2018

Completed

MS1-T03

Develop the first version ofthe WW model and test itagainst lab and field data.

25,000 4 monthsJune 2018-September 2018

Completed

MS1-T04

Build a simple userinterface and present thefirst draft of the tool.

18,750 3 months October 2018-December 2018

Ongoing

Year 1:

RUSS COLLEGE OF ENGINEERING AND TECHNOLOGY4

Gap Analysis of current ICDA methodology – MS1 T01



Current ICDA methodology Based on NACE SP0208-2008 (ICDA Methodology for Liquid Petroleum Pipelines)

Main assessment steps to evaluate a LP (length of pipe) region:

1. Pre-assessment

2. Indirect inspection

3. Detailed examinations (not relevant in this work)

4. Post assessment (not relevant in this work)



1. Pre-AssessmentData collection (only the data relevant to WW prediction is listed):Category Data Listed in the

standardPossible gap/not specific enough

Operating history Changes in flow, type of service

yes ----

Diameter and wall thickness

Nominal pipe diameter yes ----

Water and solids content

BS&W, laboratory yes ----

Composition of liquid petroleum

Crude/product quality specifications

yes Density, viscosity, oil-water interfacial tension (IFT), oil-water inversion point (IP),wettability

Max. and min. flow rates

All inlets and outlets, periods of low/no flow

yes ----



1. Pre-Assessment

Category Data Listed in the standard

Possible gap/not specific enough

Elevation profile Topography yes ----

Temperature Operating temperature yes Specific fluid properties at operating temperature

Inputs/outputs (injection/deliverypoints)

Fluid inputs and outputs to the pipeline

yes ----

Corrosion inhibitors

Injection location, chemical type, batch/continuous, dose

yes Effect on fluid properties (IFT, IP, emulsion stability)

Other chemical treatment

Injection location, chemical type, application type (DRA, emulsifiers, demulsifiers, etc)

yes Effect on fluid properties (IFT, IP, emulsion stability)

Data collection (only the data relevant to WW prediction is listed). Cont.:



Specific comments on physicochemical properties of the oil-water system

Property /Parameter

Importance Mainly affected by

Main impact Possible gap

Oil density High Temperature • Droplet buoyant force.• Water accumulation at

low spots

----

Oilviscosity

High • Temperature• Pressure

(evaporation of volatiles)

• Droplet settling velocity

• Turbulent/laminar flow threshold (Re number)

• Extrapolationto operating temperature

Water density

High • TDS• Temperature

• Droplet buoyant force.• Water accumulation at

low spots

----

Water viscosity

Low Temperature • Droplet settling velocity

----



Good knowledge of the physicochemical properties of the oil-watersystem is crucial for a good estimation of flow pattern and waterdropout:

Property /Parameter

Importance Mainly affected by Main impact Possible gap

Interfacial oil-water tension

High • Surfactants of any kind, Corrosioninhibitors, Some organic Acids, Wax particles, Asphaltenes, Fines, others.

• Droplet size (buoyant force and setting velocity)

• Not available • Difficult to test

Oil-water inversion point

High • Same as above • Critical water concentration for droplet agglomeration and coalescence

• Not available • Difficult to test

Specific comments on physicochemical properties of the oil-water system. Cont. 1



Good knowledge of the physicochemical properties of the oil-watersystem is crucial for a good estimation of flow pattern and waterdropout:

Property /Parameter

Importance Mainly affected by Main impact Possible gap

Pipe wettability

High • Crude oil and water composition

• Water dropout mechanisms

• Not available. • Difficult to test.

Emulsion tendency/stability

Medium • Crude oil and water composition

• Settling of water droplets

• Coalescence of water droplets

• Entrainment of new water

• Not available. • Difficult to test.• Not addressed by

models.

Specific comments on physicochemical properties of the oil-water system. Cont. 2



2. Indirect Inspection For each LP region (only steps relevant to WW prediction are discussed):

2.1. Calculate inclination profile for each region (from topography data)

2.2. Define critical flow velocities and pipeline inclination for waterwetting and water accumulation (Multiphase flow models).

There are several models proposed to predict waterentrainment/stratification.

Most of these models neglect important factors of multiphase oil-waterflow and do not cover all the main mechanisms leading to water dropout/accumulation. Current most important gap!



Multiphase flow models, pros/cons and gapsAuthor/s Criteria Pros Cons and Gaps

Brauner, 2001 (Similar: Trallero1995, Torres 2015)

Main suggested model in the standard

Turbulent suspension of droplets:• Gravity forces vs.

turbulence• Deformation

Good for characterization of water wetting in hydrophilic pipes at low water cuts (droplet sticking and spreading on the pipe wall)

• Do not account for pipe surface wettability

• Do not account for water droplet accum./coales.

• Do not account for water accumulation at low spots

• Drastically overestimates or understimates WW depending on the case (i.e., pipe wettability, water cut)

DensimetricFroude numberFr=2 (Hydrocor, Shell criterion)

Turbulent suspension of droplets

Same as above Same as above



Multiphase flow models, pros/cons and gaps. Cont.

Author/s Criteria Pros Cons and Gaps

Hollenberg and Oliemans 1992(Shell report)

Fr=2 is derived from this model

Turbulent suspension of droplets

Good for characterization of water wetting in hydrophilic pipes at low water cuts (droplet sticking and spreading on the pipe wall)

• Do not account for pipe surface wettability

• Do not account for water droplet accum./coales.

• Do not account for water accumulation at low spots

• Drastically overestimates or understimates WW depending on the case (i.e., pipe wettability, water cut)

Karabelas 1975/Segev 1984

Computation of waterdroplet concentration

Good for characterizing critical droplet concentrations when coalescence is present

• Critical droplet concentration?

• Not suitable for WW prediction in hydrophilic pipe surface



Multiphase flow models, pros/cons and gaps. Cont. 2


Snuverink ookLansik et al. 1987 (Shell report)

Froude numberFr=0.67 (Hydrocor, Shell criterion)

Water gathered at low spots or bends is swept downstream pipes with upward inclination

Good for characterizing critical velocities for water accumulation at low spots

• Do not account for dispersed water droplets

• Do not account for droplet accum./coales.

• Is only suitable for sweeping separated water

Tsahalis 1977 Entrainment of water layers by the shearing action of the oil flow

Same as above Same as above



Multiphase flow models, pros/cons and gaps. Cont. 3


Wicks and Fraser 1975

Assume waterdroplets are entrained as solid particles

Somewhat good for characterizing critical velocities for water accumulation at low spots

• Oil dispersive forces are not assessed properly

• Do not account for droplet accum./coales.

• Predicted critical velocities for water entrainment are too low

In summary, there is no single criterion or model that can cover all thecomplexity of oil-water flows.However, a combination and refinement of the best models and extracriteria to fill the existing gaps can produce a more comprehensive andbetter tool, covering a wide range of water cuts and oil products.


Conceptual framework of the new water wetting model– MS1 T02

16



Water wetting/water dropout predictionThe new water wetting model will aim to predict and/or assess the followingcases:

Critical flow velocities (oil and water) to prevent accumulation of settledwater at low points of pipelines: This is related to the capability of the oilflow to remove or “sweep” settled water accumulated at, i.e., the bottom ofupper bends due to flow upsets or water that drops out from dispersion andsettles preferably at low points.

Critical flow velocities for water entrainment into the oil phase to preventsegregated water layers and rivulets: This concerns at least two main waterwetting mechanisms discussed elsewhere (Pots et al. 2006, Paolinelli andNesic 2016, Paolinelli et al. 2018), described in next slide:



Water wetting/water dropout prediction, Continuation Critical flow velocities for water entrainment into the oil phase to prevent

segregated water layers and rivulets:

1. Water droplets stick and spread on the pipe surface forming waterstreams, which is plausible in pipes with hydrophilic wettability. In casepipe wettability is hydrophobic, water droplet sticking and spreading isnot likely to occur; and so the formation of segregated water layers willwe related to the mechanism described in bullet 2.

2. Water droplet concentration at the pipe bottom reaches a critical value(i.e., the oil-water inversion point) where coalescence is inevitable andwater layers are developed. This phenomenon occurs at lower flowvelocities than the mechanism described in bullet 1.



Water wetting/water dropout prediction,Continuation Maximum water content that can be entrained in the oil phase. The water

phase can be dispersed into the oil phase up to concentrations not largerthan the oil-water inversion point. Larger water concentrations will lead togeneralized or local phase inversion (oil-in-water dispersion); andconsequently, the formation of water layers or water as full continuousphase.

Therefore, whenever the water cut or the water droplet concentration at thepipe cross section is close to or exceeds the oil-water phase inversion point,it is considered as a high risk for water wetting.



Water wetting/water dropout prediction,Continuation

It must be clarified that the new model will only predict the occurrence ofsegregated water phase in oil-water pipe flow. It can happen that even if thepipe surface is in continuous contact with water, actual corrosion rates may below because of inhibitive effects of adsorbed or precipitated compounds fromproduced petroleum and water (Pots et al. 2006, Paolinelli and Nesic 2016). Theassessment of this kind of beneficial effects is not contemplated in this work.



Discrete assessment of pipe sections and user friendly data input

The new model will have the possibility to analyze pipeline facilities inconvenient length sections, where the pipe diameter, inclination, etc., may bedifferent.

The model will have a data input tab were the user will be able to choose simpleoptions to characterize the type of oil or product under evaluation, i.e., bymeans of API numbers and categories such as “crude oil”, “condensate” or“refined oil”.

When choosing a given API and oil category, oil properties such as density andviscosity will be estimated by default. However, the user will also have theoption to customize all the required inputs at leisure.



Easy-to-interpret results and sensitivity analysesThe results from the assessment of water wetting for each pipe section where acritical low spot may exist or water may drop out from dispersion, will beperform by means of simple color codes of easy interpretation.

Each color code will correspond to a status, i.e., the color red will indicate highrisk of water wetting, while green will indicate no risk of water wetting (oilwetting).

The tool will also have the capabilities to perform parametric analyses of thewater wetting model in order to assess its sensitivity to variations oruncertainties of the inputs (i.e., oil and water flow rates, oil and water densitiesand viscosities, oil-water interfacial tension, etc.).


Development of the first version of the WW model and test against lab and field data– MS1 T03

23



Main structure of the WW model

Criteria

Inputs

Calculation of critical water drop diameter

Used sub-models

Water accumulation at low spots

(Laminar/turbulent flow)

Water drop concentration exceeds

a critical value(Turbulent flow)

Water drop sticking and spreading

(Turbulent flow)

Water drop size calculation

Calculation of water drop concentration

Calculation of densimetricFroude number Outputs:

Water wetting regime(water wet/oil wet)

Accumulation of water al low points

(yes/no)



Water accumulation at low spots Evaluation of the densimetric Froude number (𝐹𝐹𝐹𝐹):

𝐹𝐹𝐹𝐹 =𝜌𝜌o

𝜌𝜌w − 𝜌𝜌o 𝑔𝑔𝑔𝑔𝑈𝑈m ≥ 0.67

Accumulated water

Oil or mixture Flow

𝑈𝑈m 𝛽𝛽

Upper pipe bend

Where:𝑔𝑔: Pipe diameter𝑔𝑔: Gravitational constant𝑈𝑈m: Mixture flow velocity

𝛽𝛽: Pipe inclination angle 𝜌𝜌𝑜𝑜: Oil density𝜌𝜌w: Water density

Snuverink ook Lansik et al. 1987 (Shell report)

Accounts for the influence of oil and water densities, gravity and pipe diameter.

Neglects the influence of oil viscosity, pipe inclination, water holdup and pipe wettability.


0

0.05

0.1

0.15

0.2

0.25

5 15 25 35 45

Uso

, crit

(m

/s)

Settled water volume (ml)

Exp. D=0.027 m, Xu et al. 2011

Exp. D=0.041 m, Xu et al. 2011

Num. sim. D=0.027 m, Xu et al. 2016

Num. sim. D=0.041m, Xu et al. 2016

Num. sim. D=0.027 m, Mangrini et al. 2018

Fr=0.67, D=0.027 m

Fr=0.67, D=0.041 m

Dept. of Chemical and Biomolecular Engineering26Institute for Corrosion and Multiphase Technology

Water accumulation at low spots Comparison with data from experiments and numerical simulations of critical oilvelocities for “sweeping” accumulated water. Effect of water holdup:

Where:𝑈𝑈so: Superficial oil velocity. In this case, 𝑈𝑈so = 𝑈𝑈m

Froude number equal to 0.67 matches fairly well with experimental data from plastic and SS pipes.

Water holdup does not have a significant influence in critical oil velocities.

Data from plastic and SS pipes with 12° inclination



Water accumulation at low spots Comparison with data from experiments and numerical simulations of critical oilvelocities for “sweeping” accumulated water. Effect of pipe inclination angle:

Froude number equal to 0.67 is conservative for inclinations lower than 20 degrees.

A Froude number of about 1 is conservative for inclinations lower than 40 degrees.

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

5 15 25 35 45

Uso

, crit

(m

/s)

Inclination angle (degrees)

Exp. D=0.05 m, Song et al. 2017

Num. sim. D=0.05 m, Song et al. 2017

Fr=0.67, D=0.05 m

Fr=1, D=0.05 m

Data from plastic pipes



Water accumulation at low spots Comparison with data from experiments and numerical simulations of critical oilvelocities for “sweeping” accumulated water. Effect of pipe wettability:

Froude number equal to 0.67 is suited for hydrophobic pipes. However, it underpredicts by ∼25% critical oil velocities in hydrophilic pipe (CA <90 degrees).

A Froude number of about 1 is conservative for all types of pipe wettability.

0

0.05

0.1

0.15

0.2

0.25

20 40 60 80 100 120 140 160

Uso

, crit

(m

/s)

Contact angle (degrees)

Exp. D=0.027 m, Xu et al. 2011

Num. sim. D=0.027 m, Xu et al. 2016

Num. sim. D=0.027 m, Mangrini et al. 2018

Fr=0.67, D=0.027 m

Fr=1, D=0.027 m



Water drop concentration at the pipe bottom Calculation of the water drop concentration (advection-diffusion equation):

Where:�̅�𝑑: Mean drop size𝐶𝐶: Water drop concentration𝐶𝐶D: Drop drag coefficient

𝑢𝑢∗: friction velocity, 𝑢𝑢∗ = ⁄𝜏𝜏w 𝜌𝜌o𝑦𝑦: vertical coordinate of the pipe (coincident with radial direction)𝜁𝜁: Dimensionless eddy diffusivity𝜏𝜏w: Wall shear stress

𝑈𝑈s𝐶𝐶 1 − 𝐶𝐶 cos𝛽𝛽 − 𝜀𝜀𝜕𝜕𝐶𝐶𝜕𝜕𝑦𝑦

= 0;

Karabelas 1977

𝑈𝑈𝑠𝑠 =43�̅�𝑑 𝜌𝜌w − 𝜌𝜌o 𝑔𝑔

𝜌𝜌o𝐶𝐶D;

𝜀𝜀 = 𝜁𝜁𝑔𝑔2𝑢𝑢∗;

Settling velocity of water drops:

Turbulent drop diffusivity:

Water concentration is only function of 𝑦𝑦:

Concentration at the pipe bottom, 𝐶𝐶b

𝑦𝑦 𝑦𝑦

𝑧𝑧 𝐶𝐶(𝑦𝑦)



Water drop concentration at the pipe bottom,Cont. Water drop concentration at the pipe bottom:

Where:𝐴𝐴: Pipe cross-sectional area

𝜀𝜀w: Water holdup ∼ water cut𝐼𝐼𝐼𝐼: Phase inversion point (based on water fraction)

Closed-form solution, Karabelas 1977:

𝐶𝐶b = 1 + 21 − 𝜀𝜀w𝜀𝜀w

𝐼𝐼1 𝐾𝐾𝐾𝐾

exp −𝐾𝐾−1

;

𝐾𝐾 =𝑔𝑔𝑈𝑈s2𝜀𝜀

;

𝐼𝐼1 𝐾𝐾 =12𝐾𝐾 1 +

𝐾𝐾2

8+𝐾𝐾4

192+

𝐾𝐾6

9216

�𝐶𝐶 𝑦𝑦 𝑑𝑑𝐴𝐴 = 𝜀𝜀w𝐴𝐴

Closure relationship (drop mass remains constant across the pipe section):

Criteria to avoid local phase inversion and massive drop coalescence

(hydrophobic pipe):

𝐶𝐶b < 𝐼𝐼𝐼𝐼

Pipe surfaceWater layer

Oil

Flow direction

Water droplets



Water drop concentration at the pipe bottom,Cont.

Comparison with experimental data from flow loop experiments in oil-water flow withhydrophobic pipe surfaces:

0

0.5

1

1.5

2

2.5

3

3.5

0 5 10 15 20

Mix

ture

vel

ocity

(m/s

)

Water cut (%)

Full oil wet

< 0.1 mm

0.1-0.5 mm

0.5-2 mm

2-4 mm

Model

Oil phase: Isopar VOil density: 810 kg/m3

Oil viscosity: 10 cPInterfacial tension: 49 mN/mInversion point: 25 %Water phase: 1 % wt. NaCl0.1 m ID Plastic PVC pipe Measuring method: flush-mounted HF impedance probe (phase wetting and water layer thickness)

Paolinelli et al. 2018, ICMT-OU flow loop

Oil wet

Water wet The model (𝐶𝐶b < 𝐼𝐼𝐼𝐼) matches well with experimental data.


0

0.5

1

1.5

2

2.5

3

0 10 20 30 40

Mix

ture

vel

ocity

(m/s

)

Water cut (%)

Dw/o

Semi-dispersed

Stratified

Strat. mixed

Do/w

Model, case 1

Model, case 2

Model, case 3




Oil phase: Tulco Tech 80Oil density: 858 kg/m3

Oil viscosity: 18.8 cPInterfacial tension: 28.5 mN/m (est.)Inversion point: 22 % (Inferred from experiments)Water phase: Tap water0.05 m ID, Acrylic pipe Measuring method: Conductivity probe and HS camera

Vielma et al. 2008, Tulsa U. Flow loop

Oil wet

Water wet

Case 1: Hinze drop size; Case 2: 1.5 times Hinze’s; Case 3: 2 times Hinze’s.

The model (𝐶𝐶b < 𝐼𝐼𝐼𝐼) matches well with experimental data. Inversion point, 𝐼𝐼𝐼𝐼


0

0.5

1

1.5

2

0 10 20 30 40

Mix

ture

vel

ocity

(m/s

)

Water cut (%)

Dw/o (oil wet)

Semi-dispersed (waterwet)Strat. Mixed (water wet)

Stratified (water wet)

Model, case 1

Model, case 2

Model, case 3




Oil phase: Exxsol D60Oil density: 790 kg/m3

Oil viscosity: 1.64 cPInterfacial tension: 43 mN/m (est.)Inversion point: 48 % (Estimated)Water phase: Water0.056 m ID, SS and Plexiglas pipe Measuring method: Gamma densitometry and HS camera

Kumara et al. 2009, Telemark U. Flow loop

Oil wetWater wet


The model (𝐶𝐶b < 𝐼𝐼𝐼𝐼) matches well with experimental data.


0

0.5

1

1.5

2

2.5

3

3.5

4

0 10 20 30 40

Mix

ture

vel

ocity

(m/s

)

Water cut (%)

Dw/o (oil wet)

Semi-dispersed (water wet)

Stratified wavy (water wet)

Do/w (water wet)

Model, case 1

Model, case 2

Model, case 3




Oil phase: Exxsol D140Oil density: 828 kg/m3

Oil viscosity: 6 cPInterfacial tension: 39.6 mN/mInversion point: 32 %Water phase: Tab water0.038 m ID Stainless steel pipe Measuring method: Impedance probe (continuous phase and phase fraction detection close to wall)

Lovick and Angeli 2004, UCL flow loop

Oil wet

Water wet




0

0.5

1

1.5

2

0 10 20 30 40

Mix

ture

vel

ocity

(m/s

)

Water cut (%)

Dw/o (oil wet)


Strat. Mixed (water wet)


Do/w

Model, case 1

Model, case 2

Model, case 3




Oil phase: Shell Ondina 17Oil density: 845 kg/m3

Oil viscosity: 22-35 cPInterfacial tension: 40 mN/m (est.)Inversion point: 33 %Water phase: Water0.059 m ID Plastic Perspex pipe Measuring method: Impedance probe (continuous phase and phase fraction detection close to wall)

Nadler and Mewes 1997, Flow loop

Oil wet

Water wet




0

0.5

1

1.5

2

2.5

0 10 20 30 40

Mix

ture

vel

ocity

(m/s

)

Water cut (%)

Dw/o (oil wet)


Strat. Mixed (water wet)


Model. case 1

Model, case 2

Model, case 3




Oil phase: Crystex AF-MOil density: 884 kg/m3

Oil viscosity: 28.8 cPInterfacial tension: 36 mN/m (est.)Inversion point: 22 % (Estimated)Water phase: Tap water 0.05 m ID, Acrylic pipe Measuring method: Conductivity probe and HS camera

Trallero 1997, Tulsa U. Flow loop

Oil wet

Water wet


The model (𝐶𝐶b < 𝐼𝐼𝐼𝐼) matches well with experimental data.

Inversion point, 𝐼𝐼𝐼𝐼



Water drop sticking and spreadingForce balance on water droplets (gravity vs. turbulence):

Where:𝑑𝑑max: Maximum water drop size𝑈𝑈o: Oil velocity, 𝑈𝑈o ≅ 𝑈𝑈m

𝛽𝛽′ = 𝛽𝛽 when 𝛽𝛽 <45°𝜎𝜎: Oil-water interfacial tension

Pipe surfaceThin water

layer

Oil

Water droplets

Flow direction

𝑑𝑑cb =38

𝜌𝜌o 𝑓𝑓 𝑈𝑈o2

𝜌𝜌w− 𝜌𝜌o 𝑔𝑔 cos𝛽𝛽

𝑑𝑑cσ =0.4𝜎𝜎

𝜌𝜌w− 𝜌𝜌o 𝑔𝑔 cos𝛽𝛽′

⁄1 2

Critical “buoyancy” droplet size:

Critical “deformation” droplet size:

Criteria to avoid droplet contact with the pipe surface (hydrophilic pipe):

𝑑𝑑crit = 𝑀𝑀𝑀𝑀𝑀𝑀 𝑑𝑑cb ,𝑑𝑑cσ

Critical droplet size, Brauner 2001:

𝑑𝑑max < 𝑑𝑑crit



Water drop sticking and spreading, Cont.

Comparison with experimental data from flow loop experiments in oil-water flow withhydrophilic pipe surfaces:

Paolinelli et al. 2018, ICMT-OU flow loop

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0 5 10 15 20

Mix

ture

vel

ocity

(m/s

)

Water cut (%)

Full oil wet

< 0.1 mm

0.1-0.5 mm

0.5-2 mm

2-4 mm

> 4 mm

Model

Oil phase: Isopar VOil density: 810 kg/m3

Oil viscosity: 10 cPInterfacial tension: 49 mN/mInversion point: 25 %Water phase: 1 % wt. NaCl0.1 m ID Carbon steel pipe Measuring method: flush-mounted HF impedance probe (phase wetting and water layer thickness)

The model (𝑑𝑑max < 𝑑𝑑crit) woks well for relatively low water cuts (< 3%).

For water cuts > 3 %, there always occur thin water layers (<0.1 mm) that can pose a corrosion risk.

Thin water layers< 0.1 mm

Oil wet

Water wet


0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0 5 10 15 20

Mix

ture

vel

ocity

(m/s

)

Water cut (%)

Oil wet

Unstable oil wet

Unstable water wet

Water wet

Model, case 1

Model, case 2

Model, case 3


Water drop sticking and spreading, Cont.

Comparison with experimental data from flow loop experiments in oil-water flow withhydrophilic pipe surfaces:

Kee et al. 2016, ICMT-OU flow loop Oil phase: LVT 200Oil density: 823 kg/m3

Oil viscosity: 2.7 cPInterfacial tension: 40 mN/mInversion point: 45 %Water phase: 1 % wt. NaCl0.1 m ID Carbon steel pipe Measuring method: Flush-mounted DC conductance mini probes (phase wetting)


The model (𝑑𝑑max < 𝑑𝑑crit) woks well for relatively low water cuts (< 1%).

Thin water layers

Oil wet

Water wet



Calculation of dispersed water drop size

Where:

𝜖𝜖: Mean energy dissipation rate, 𝜖𝜖 = 2𝜏𝜏w 𝑈𝑈o𝐷𝐷𝐷𝐷o 1−𝜀𝜀w

The main droplet break-up mechanism is due to the turbulent stresses in the continuousoil flow:

𝑑𝑑max,o = 0.725𝜎𝜎𝜌𝜌o

⁄3 5

𝜖𝜖 ⁄−2 5

“Dilute” maximum water drop size, Hinze 1955 :

Maximum water drop size for any water holdup (water cut), Mlynek and Resnick 1972 :

𝑑𝑑max = 𝑑𝑑max,o 1 + 5.4 𝜀𝜀w

Mean water drop size (𝑑𝑑50,𝑑𝑑32):

�̅�𝑑 ≅ 0.5 𝑑𝑑max



Flow diagram of the model

Hydrophobic pipe?

Is 𝑑𝑑max < 𝑑𝑑crit?

Is 𝐶𝐶b < 𝐼𝐼𝐼𝐼?

Oil wetting (dispersed flow)

Water wetting(semi-dispersed

/stratified flow)

Water is removed by the oil flow

General inputs:• Flow rate oil and water phases• Pipe geometry (diameter, inclination, roughness)• Water and oil properties (density, viscosity, interfacial tension, phase inversion point)• Pipe surface wettability (Hydrophobic, hydrophilic)

No

Yes

No(Water continuous/

Bottom coalescence)

YesNo

Yes

(Sticking water drops)

Water dispersion module

Water accumulation module

(Flow upsets/Assessment of low spots)

Is 𝐹𝐹𝐹𝐹 > 1? No

Yes

Water accumulates at low spots

Is oil flow turbulent?

Yes

No



What is the wettability of carbon steel in contact with crude oils?

Most of the evaluated crude oilsaltered the wettability of thecarbon steel towards hydrophobic.

However, there are some crudeoils that do not produce thiseffect.

A simpler surface wettability testmethod is still needed for the oiland gas industry.

Richter et al. 2014,


Build a simple user interface and present the first draft of the tool–MS1 T04

43



First draft of the tool

This is an ongoing task. The first draft of the tool is planned to bedelivered for first evaluation in January 15, 2019


Year 2

45



Year 2Task Description Cost Planned

DurationTime line Status

MS2-T01

Improve and debug the toolbased on the feedbackprovided.

18,750 3 months January 2019 –March 2019

Due

MS2-T02

Build a professional userinterface and provide handlesto connect this tool to relatedexternal ones.

18,750 3 months April 2019 –June 2019

Due

MS2-T03

Distribute the tool forevaluation to PRCI membersand collect feedback.

18,750 3 monthsJuly 2019 -September 2019

Due

MS2-T04

Finalize the tool, developdocumentation and support,and build the delivery andlicensing platform (finaldeliverable).

18,750 3 months October 2019 -December 2019

Due


Thanks for your attention

47

Documents

Water Wetting Prediction Tool for Pipeline ... - PRCI