slurry carrying pipeline integrity management_ibp1313_11_tcm4-593273

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______________________________1MSc, Business Development Manager, AIMS, DNV Software2Ph.D, Business Development and Product Manager AIMS, DNV Software3Mech Engineer Samarco Mineracao, SA

IBP1313_11- Slurry Carrying Pipeline Integrity Management supported

by the SilverPipe software from DNVJrgen Piene

1, Anders Hvidsten

2, Ricardo Bruno Andrade

3

Copyright 2011, BrazilianPetroleum, Gas and Biofuels Institute - IBPThis Technical Paper was prepared for presentation at the Rio Pipeline Conference & Exposition 2011, held between September,

20-22, 2011, in Rio de Janeiro. This Technical Paper was selected for presentation by the Technical Committee of the event. The

material as it is presented, does not necessarily represent Brazilian Petroleum, Gas and Biofuels Institute opinion or that of its

Members or Representatives. Authors consent to the publication of this Technical Paper in the Rio Pipeline Conference &

Exposition 2011.

Abstract

Most Pipeline Integrity Management software systems available in the market, the DNV Software system SilverPipe

among them, are reflecting the oil and gas pipeline industry requirements and fitting with the prevailing pipelinestandards and best practices as defined by ASME/ANSI/API, DNV and others. Hence the various analysis and

assessment tools are developed upon these standards.

When Samarco Mineracao SA (Samarco) commissioned SilverPipe, this implied tight collaboration between Samarco

and DNV to arrive at practical solutions relevant to the specifics of transport of slurries in pipelines.

The most dominant time dependent threats are the pipe wall thinning due to erosion and corrosion. The coupled risk

analysis subject to pipeline rupture due to erosion and corrosion growth analysis became therefore the prime focus of the

software delivery program. An efficient function to cover this threat aspect was early in the project decided to be on

Remaining Life assessment, with the emphasis to quickly isolate those parts of the pipeline that should be subject to

more detailed inspections and further analysis. The solution that was established by Samarco and DNV Software to

support the slurry pipeline business case has its background in the Oil and Gas industrys assessment practices and the

DNV Risk assessment approach.

1 Introduction

Det Norske Veritas (DNV) has since 5 years been investing in its software system for Asset Integrity Management,

named SilverPipe, (formerly marketed as Orbit+ Pipeline) The system builds on the forerunner Orbit Pipeline, a

software system, mainly developed for Integrity Management for Subsea pipelines. During the course of the

development, DNV decided that the new system should embrace functions for Onshore Pipelines carrying hydrocarbons,

gas and oil products and building on the predominant ASME and API standards as well as Subsea pipelines building on

DNV Subsea pipeline standards and vast industrial experience for such transport facilities.

Samarcos acquisition of SilverPipe as part of their business objectives to develop their capacities for Asset Integrity

Management defines a new era for the system and underpins its versatility to cover most types of pipeline transportsystems and products. The collaboration with Samarco has been extensive, both in way of understanding the particulars

of a iron slurry transportation system and the development of the various specifications required for the functions that

should be delivered as part of the contract obligations, where the dominant one as mentioned above is the Risk

assessment for the erosion and corrosion thinning effects on the pipeline wall.


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Rio Pipeline Conference & Exposition 2011

2

Founded in 1977, Samarco is a privately held Brazilian mining company, controlled in equal parts by two shareholders:

Vale S.A. and BHP Billiton. Our main product is iron ore pellets. We transform minerals with low ore content into a

valuable product, with high added value, and sell them to steelmakers worldwide. We have customers in more than 15

countries, on all the continents.

Our current production capacity is 22.250 million tons annually, we create some four thousand direct and indirect jobs

and we are the second largest exporter on the seaborne iron ore pellet market in the world.

We have two concentrators, installed in the Germano unit, located in the cities of Mariana and Ouro Preto, in Minas

Gerais, which beneficiate the ore and increase its iron content, and three pellet plants (which transform the ore into

pellets) at the Ubu unit, in the municipality of Anchieta, in Esprito Santo.

The two industrial units are connected by two pipelines, measuring almost 400 kilometers in length, which transport the

slurry between two states, passing through 25 municipalities. We are pioneers in this type of transportation and our

pipelines are considered the largest in the world.

3 Short Introduction to DNV

Det Norske Veritas (DNV) is a leading, independent provider of services for managing risk with a global presence and a

network of 300 offices in 100 different countries where most of our 9000 employees are highly qualified engineers and

technical personnel. DNV assists its customers in managing risk by providing three categories of service: classification,

certification and consultancy.

Since its establishment as an independent foundation in 1864 has been a Risk Focused company and is an internationally

recognized provider of technical and managerial consultancy services and one of the worlds leading classification

societies. This means that we are continuously developing new approaches to health, safety, quality and environmental

management, so businesses can run smoothly in a world full of surprises.

DNV operates in multiple industries internationally, but in four industries DNV have a strong market presence and a

large customer base, being, Maritime, Oil & Gas, Process and Transportation.

DNV Software (DNVS) is an independent software vendor and reseller specialized in developing innovative software

solutions for design, construction, strength assessment, and risk and information management. DNV Software is serving

more than 3500 clients in 55 countries. DNVS has offices in Norway (Oslo), UK (London), Taiwan, China (Shanghai),

United Arab Emirates (Abu Dhabi), India (Hyderabad), USA (Houston), Korea (Busan), and Brazil, with more than

240 employees globally.

DNVS has more than 20 years experience in developing quantitative techniques for assisting safety professionals in risk-

based decision making. With software solutions from conception and design to start-up and operation, DNV Software

works together with clients to develop software for risk, safety and reliability analysis.

DNVS has an extensive experience in supporting a broad range of customers in all aspects of Integrity Management and

our software solutions have been developed in close co-operation with the industry. This secures that the solutions arebased on actual needs from the industry through DNVs broad experiences in integrity management.

4 Introduction to SilverPipe

SilverPipe is DNVs novel Pipeline Integrity Management Software system. The system is an advancement of ORBIT

Pipeline, and is made upon modern technologies. SilverPipe is a true web based and multi-user system where all data

2 Short introduction to Samarco Mineracao SA1


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storage and calculation functions are centralized. The intent of SilverPipe is that it shall close the integrity wheel (see

Fig 1 below).

By this, we mean that the system shall cover all required processes to evaluate the condition of the pipeline, and by

means of inspection result screening and analysis tools assess the pipelines technical condition and risk. The resultingrisk profiles from the risk assessments are the basis for the deciding long term inspection plans and the short term

mitigation efforts.

SilverPipe supports all activities required to control, maintain and document integrity of pipeline systems during the

entire operational life through built-in support for the internationally

recognized integrity management standards from DNV (RP-F116), ASME (B31.G, B31.8S, B31.4 & B31.11 API 1160.

SilverPipe is configurable to also include company guidelines and practices for e.g. code checks and threat

configurations as well as other national regulations.

Pipeline Integrity Management (PIM) involves all activities required to control and document the integrity; that is

fulfillment of the design requirements for the pipeline during its entire operational lifecycle. DNV has developed a risk

based methodology for PIM, which forms the foundation for the SilverPipe functionality. This, together with functions

for ASME standards, ensures that the software expresses DNVs interpretation of the best industry practices andrecognized standards for pipeline integrity management. Particularly for slurry carrying pipelines the ASME standard

B31.11 forms the basis. The NACE recommended practices for corrosion direct assessment is also an important

function in the system.

The objective of SilverPipe is to:

Provide Management Insight into the integrity status of the pipeline assets as well as the current status of allimplicit work-processes by simple web reporting tools

Support pipeline engineers in their daily work;

Document pipeline data, inspections, condition evaluations, inspection planning and actions;

Serve as a calculation tool for code compliance, condition and defect assessments;

Be a practical framework for control and assessment of pipelines for the entire operational phase; Fill in the gap between existing company databases by extracting the required information.

SilverPipe is based on Qualitative Risk Assessment principles, i.e. there is no direct system connection from probability

assessments to the risk score. It is the pipeline engineers best judgment and interpretation of calculation results that

shall be reflected in the risk assessments. The risk assessment is in addition to the manual risk assessment process

supported by a rule based Risk Screener, that based on scoring values for applicable Threats will derive the Current Risk

exposure. Future risk will have to be assessed specifically. In addition to rule based screeners and multipurpose data

viewing specific tools can be provided to support the Probability of Failure assessments.

SilverPipe is based on risk principles, codes and industry recommended practices. However, as such practices may well

vary with both company standards and authority requirements, SilverPipe can be configured to accommodate company

specific guidelines and practices, both for code checks, threat configuration and naming.

5 The Business Case

Figure 1. Integrity Management wheel


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The two Samarco pipelines are the longest iron ore slurry pipelines in the world. Linking the Germano unit to the Ponta

Ubu unit, one is 396 km long, and the other 398 km long.

The slurry travels at an average speed of 6 km per hour (1,7 m/s) and takes about 66 hours to cover this distance.

Pumping stations help the slurry flow overcome obstacles, such as the Capara Range, at 1180 m above sea level, and

on downhill stretches the flow is controlled by a valve system.2

The density of the slurry is about 2200 kg/m3 with an iron/water ratio of about 70%.

The main characteristics of the pipeline 1 are:

Length 396 km with diameters of 180 and 200 mm Nominal Capacity 12 Million DMT/Year

Wall thickness, 8 21 mm Actual Capacity 15 Million DMT/Year

Material: Steel API 5L X60 % Solids 70

Design Life: 20 years Max particle size 74 Microns

Reference3

The transportation of slurry, as opposed to hydrocarbon products, has a grinding effect on the internal pipe wall, leading

to an ovaling of the circumferential shape of the pipe wall. Over years this thinning effect obviously will reduce the

pipelines ability to sustain the internal pressure, risking leaks and bursts. Even though iron slurry is not toxic or

flammable, iron slurry pollution could be severe to the environment and costly to clean. Coupled with corrosion the risk

for unwanted pumping of slurry to the environment increases and Samarcos objective is obviously to keep these risks

under control, at the same time establish a reliable risk based prediction function for when and where eventual pipeline

replacements have to take place within a foreseeable future.

The proactive approach Samarco has taken is based on an active intelligent pigging program, utilizing combined MFL

and UT pigs as well as regular GEO pigging. In addition to the pigging program a range of wall thickness UT measuring

devices are installed along the pipeline measuring the wall thickness at 0 , 90, 180 and 270 degrees.

Figure 3. Pipeline Elevation Profile and main stations

Figure 2. Samarco Pipelines Route


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Recording and analysis of the effects of erosion on the pipe wall at these predetermined points along the pipeline is an

implicit function in Samarcos asset integrity management program, to date based on Excel analysis and reports with

projection of when the pipewall reaches a minimum allowable thickness for burst.

Readings are made at regular intervals for all stations to accomplish an overview of the erosion state. Correlation with

production throughput and pressure profiles provides information of unwanted thinning is taking place at those

instances. See the figure below.

Please note: The measurement figures underneath are fictious data, even though the KP end point is equal to the

Samarco pipeline no. 1 Therefore these graphs should not be construed to provide an actual picture to the erosion

state of this pipeline.

y = -0,0012x + 815,09

R2= 0,8746

765

770

775

780

785

790

795

800

805

810

06-des-

99

19-apr-

01

01-sep-

02

14-jan-

04

28-mai-

05

10-okt-

06

22-feb-

08

06-jul-09 18-nov-

10

01-apr-

12

0

90

180

270

Linear (180)

Recognizing that analysis of data from these fixed positions will not detect certain adverse spots along the pipeline due

to velocity increases due to bending, Samarco plans to develop pigging requirements to also record the reduced pipe

wall thickness due to erosion, thereby achieving a holistic view of the complete corrosion and erosion status of the

pipeline.

Consolidating these measuring point data and correlate them to the blank pipe condition will provide an expression of

the erosion rate along the pipeline since the pipeline was new. The graphs show clearly that the main growth is found in

the bottom section of the pipeline with the following overall values:

Overall Erosion Pipe wall Thinning rate (mm/year)

Linear Calculation

0 deg 90 deg 180 deg 270 deg

Min 0,001 0,001 0,003 0,002

Max 0,080 0,097 0,206 0,094

As part of the consolidation of the measurement data it will be important to critically review the reality of the out-layers

such as shown in the figure 5 below (at about KP 150 and 240 km) so that non realistic figures are used in the further

analysis.

Table 1. Overall Thinning Rate

Fig 4. Sample data from 1 measuring point (wall thickness in mils)


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6 Remaining Life Assessment in SilverPipeThe overall ambition with the developed procedure and SW functions is to enable the user to quickly establish if an

imminent combined effect of erosion wall thinning and corrosion exist along the pipeline, threatening the integrity of the

pipeline. This is accomplished by utilizing sound pipeline engineering principles based on available erosion and

corrosion data and standard code based calculation tools. The strength of the methodology increases with the availability

of sufficient detailed data, and should in any case not lead the user to make incorrect and even costly decisions, without

making a second independent investigation of the potential problem area. Erosion and Corrosion are both deterioration

mechanisms that work on the pipeline and reducing the pipe walls ability to contain the pressure and are assessed

independently of each other, but results will be reviewed in combination in order to address any suspicious points along

the pipeline.

6.1 Erosion Effects

6.1.1 Wall thinning rateAs mentioned above the wall thinning rate is currently based on the recordings at the measuring points, correlated with

the new pipe condition and number of years since the pipeline came into operation or that particular segment in case of a

pipeline replacement. In order to discriminate production throughput, pressure variations and measurement inaccuracies

standard mean value calculation is used, rather than a linear simple calculation as shown above. The difference in the

predicted thinning rate can be as much as 70-80%.

Erosion Growth - Mean Values

-

0,050

0,100

0,150

0,200

0,250

0,300

4

21

37

54

70

87

103

163

179

196

215

232

248

265

281

298

314

331

347

364

380

KP (km )

ThinningRate(mm/year)

0 mean

90 mean

180 deg mean

270 mean

0 linear

Pipewall Thinning due to Erosion (linear calculation)

0,000

0,050

0,100

0,150

0,200

0,250

417

31

44

57

70

83

97

110

120

153

166

179

192

205

219

232

245

258

275

288

301

314

328

344

357

370

Kp (km)

mm/year

-20406080100120140160180200220

OperatingPressu

re

kgmf/cm2

0 Deg

90 Deg

180 Deg

270 Deg

Op pressure

Outlayer

Readings -Need special

attention

Fig 5. Wall thinning due to erosion (linear calculation)

Fig 6. Wall thinning rate (mean values)


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Comparison Thinning rate

Me an vs Linear calculation

-

0,050

0,100

0,150

0,200

0,250

0,300

421

37

54

70

87

103

163

179

196

215

232

248

265

281

298

314

331

347

364

380

KP (km)

ThinningRatemm/year 180 deg mean

180 deg linear

The wall thinning profile that will be used for the erosion effect will for the permanent measuring points be composed

by these fixed figures and the maximum value irrespective of measurement sector. The thinning rate along the pipe wall

between these points will simply alternatively be calculated linearly between the two adjacent points or kept at constant

rate according to the upstream measurement point value or using an linear regression function to derive the growth rate

at these measurement point.

6.1.2 Calculation for Burst condition and Scoring

Burst pressure calculation is based upon the well known formula

where

F = Design Factor (in this case = 1)

T = Temperature derating factor (in this case = 1)

t = wall thickness (for design pressure the nominal wall thickness)

D = Diameter

Then the Psafe capacity of the pipeline due to the erosion caused wall thinning is calculated in accordance with remaining

wall thickness terosionwhich is wall thickness recorded at any of the point along the pipeline and subject to erosion

The pipeline will burst when the local incidental pressure, or the maximum pressure which the pipeline can be exposed

to under its operational condition, taking also the maximum static pressure into account.

trem(n) = Remaining wall thickness at year n

Where n = number of years remaining

Thrate = Thinning rate (mm/year)

= Safety Factor (for B31.11 =0,80 is applied)

Remaining lifeErosion = RLErosion=

Where Plocalincidental is the maximum of either the operational pressure condition or the static pressure.

Fig 7. Comparison Thinning rates;Mean vs Linear

2SMYS* terosion - Plocalincidental*D

SMYS* Thrate

2SMYS* terosion - Plocalincidental*D

SMYS* Thrate

2 SMYS*t

D= F* * TPburst

2 SMYS*t

D= F* * T

2 SMYS*t

D= F* * TPburst


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The calculation will create a detailed Remaining Life profile along the pipeline which from the users perspective will be

unpractical to operate. To increase usability the detailed profile will be matched to a scoring table that matches the PoF

definition in the companys risk matrix. Thus we have an expression for the probability of failure due to erosion wall

thinning. Such scoring could be as shown below, but is fully configurable to the particular companys own preferences.

Condition

Remaining Life

Score

1236 1

A resulting Remaining Life profile along the pipeline could then be reported as shown in figure 8 below.

In order to prioritize between possible high score sections the correlation with the Consequence of Failure profile can be

done, resulting in an expression for the risk for burst.

6.2 Corrosion Effects

Corrosion is also affecting the remaining life of the pipeline and combined deterioration effects have to be seen together.

However as they are only coupled in way of the effective wall thickness at the particular corrosion feature, they are dealt

with separately. The assessment of remaining life due to corrosion will follow the same steps as for Erosion:

Get a comprehensive view of the corrosion growth along the pipeline

Calculate the detailed remaining life profile and match the results to a scoring table

Correlate the results with the CoF profile and get an expression for the remaining life risk

6.2.1 Corrosion Growth Assessment

To get a practical picture of the corrosion defect development over the years to come, assessment of the corrosion

growth along the pipeline has to be made to the extent that available information is at hand such as pigging data,

preferably from several pigging operations over time.

The Corrosion Growth procedure is made in several steps: Viewing the ILI reports comparing the reported girth weld positions with the as laid pipebook

Remaining Life Score

Table 2. Scoring

Fig 8. Remaining Life Segment Profile


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Determination of defect statistics by means of regression analysis

Estimation of corrosion rate from defect statistics

Display of statistics/corrosion rate along pipeline

The implicit inaccuracies in the pigging data are well known, therefore calculating the corrosion growth along the

pipeline by matching feature by feature is avoided. Instead, the least common corrosion growth segment will be thelength of a joint, which is deemed to provide sufficient accuracy and resolution. It may though happen that two pig runs

do not report the same girth welds or reporting offsets between them. The implemented procedure is sufficiently fault

tolerant as it in practical terms does not statistically matter if a two joints are dislocated some meters or even jumping

over a few.

The ILI data is statistically sampled and by simple regression analysis on selected joints, girthweld(s) to girthweld(s) the

user will have a by glance view of how the ILI data from several are matching.

The second step will be to analyze the statically cumulative distribution of the features pertaining to the matched

segments. From the display-set the user shall be able to select parts of the sample he will use for the growth analysis.

The sampling should be based on user selection on depth %, or ERF (Estimated Repair Factor) within KP to KP values

for External and/or Internal Corrosion. The calculation based on statistical sample (say all features with a d/t ratio larger

than 50%) will always be done by correlation to a new pipe condition for the selected range of joints (or girth weld to

girth weld) assuming that the corrosion growth works equally in all directions.

The output from the assessment from these two ILI file samples would be a profile displaying the depth distribution

along the pipeline.

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00

Pipe section length [m]

Pipesectionlengt

h[m]

-0.05

-0.04

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00

Pipe section length [m]

Relativeerror[-]

Fig 9. Features matched with jointsFig 10. Relative error between feature data

Fig 11. Data Sampling ILI Files 2005 & 2008


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Fig 12. Defect measure (95% fractile)

The corrosion rate will then simply be calculated by the following formula:

for each joint (or combination of joints)

Where n= number of years since the pipesegment was new.

d= Feature depth

By comparing the results from the calculations one will quickly reveal if a certain corrosion problem exists at some

specific spots along the pipeline as well as deciding what profile that should be used as the basis for the Remaining life

calculations.

Fig 13.Corrosion Rate (95% fractile)

6.3 Remaining Life Assessment for Corrosion and scoring

The corrosion rate is established and using the ASME B31G for code check for the Psafe condition along the pipeline

the remaining life is calculated according to the following formula4:

Where:

Crate (gwm gwm+1) = Mean(d(gwm gwm+1))

nCrate (gwm gwm+1) = Mean(d

(gwm gwm+1))n

RLcorrosion = Psafe

SMYS

Plocalincidental

SMYS- * t *

1

CrateRLcorrosion =

Psafe

SMYS

Plocalincidental

SMYS- * t *

1

Crate

Psafe

SMYS

Plocalincidental

SMYS- * t *

1

Crate


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Tmin Erosion

TRemwt Corrosion

= contingency factor at the users discretion. The ASME B31.11 safety factor of 0,8 is implicitly calculated as part

of the Psafecalculation.

In the same way as for Erosion the detailed calculations are mapped to a scoring table, thereby creating a RLcorrosion

profile along the pipeline. (See table 2 above)

6.4 Combining Erosion and Corrosion effects

The Worst Case condition are composed by two scenarios, 1) those locations along the pipeline where remaining life is

within a few years perspective for both Erosion and Corrosion at the same locations along the pipeline and 2) most

severe condition where the remaining wall thickness for erosion and corrosion (almost) coincide.

All such locations along the pipeline will be picked up by the Hotspot register and mitigation actions set force.

The Results should be displayed in table with export to Excel and as graphical plot as shown in figure 15 below.

2014

2015

2016

2016

2017

2018

2019

2020

2021

2022

Time limit Erosion

Time limit Corrosion

Critical Area

KM

7 Conclusion

Carrying slurries in steel pipelines poses several other aspects of the operation than for traditional hydrocarbon

pipelines, one of them the pipe wall thinning due to the hard particles grinding on internal pipe wall. At some locations

the thinning rate can be up to 0,2 mm/year. Coupled with corrosion, mainly external but also internal, though mostly at

the upper sectors of the pipeline. The wall thinning effects are predominantly operating at the lower part of the pipeline

and thus the combination of erosion wall thinning and corrosion at these sections may be the main causes for pipeline

rupture with those unwanted consequential damages to the environment and the business. In order to control these

mechanisms Samarco and DNVS started a development program for functions in SilverPipe, based on the standard input

data, such as regular measurements from monitoring stations, ILI files, the common pressure operational profiles and

utilizing the common standard practices for Psafe and remaining life calculations. The solution is a practical approach toan important aspect of the integrity management process for slurry pipelines.

Fig 14. Most Adverse Effect of wall

thinning and corrosion

Fig 15. Remaining Life Limit - Combined


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At the time of writing these functions are still under development and will be presented in full during the Rio Pipeline

event in 2011.

7. Acknowledgements

The DNV Software authors will herewith direct our most appreciations to the Samarco Integrity Management team,specially represented by Ricardo Bruno Nebias Andrade for valuable input to the development of the specifications and

as co-author to this paper.

8. References

1

http://www.samarco.com.br/modules/system/viewPage.asp?P=854&VID=default&SID=823351408262745&S=1&C=9

6402http://www.samarco.com/relatorio_anual/en-us/pdf/Samarco_web-process.pdf

3

http://www.bhpbilliton.com/bbContentRepository/20073291012356/samarcopresentationsouthamericansitevisit.pdf4NACE Standard Practoce SP0502 2008, Pipeline External Corrosion Direct Assessment Methodology

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