Hydrocarbon Pipeline Third Party Damage Risk Assessment using

Multi Criteria Decision Making

Marthin Simanjuntak, Utomo Sarjono Putro

School of Business and Management, Bandung Institute of Technology, Bandung, Indonesia

Keywords: Multi-Criteria Decision Making, Analytical Hierarchy Process, Risk Assessment, Pipeline

Abstract: Many research studies recognized Third Party Damage (TPD) as one of the significant contributors to pipeline

failure. Maintenance of hydrocarbon pipelines and its right of way (ROW) as protection from TPD is a

significant challenge because massive encroachment and fast-growing third-party activities near pipelines.

Therefore, an organization needs to use risk-based analysis for resource allocation prioritization carefully.

Analytical Hierarchy Process (AHP) and Simple Multi-Attribute Rating Technique (SMART) are popular

Multi-Criteria Decision Making (MCDM) technique that allows multivariable factors to be considered in the

decision-making process. Pipeline risk is a function of a multi-variable risk factor. Therefore, the combination

of AHP and SMART can be used for pipeline risk assessment. Limitation of the presented decision support

system: 1) it still has subjectivity involved, which would introduce uncertainties to the result, 2) the risk result

is a relative risk, which makes the result only can be used resource allocation. This work is expected can help

the organization for improving resource allocation for risk reduction program and maintenance activities.

Although the model is applied for pipeline risk assessment, the same principle can be applied for other risk

assessment exercise.

1 INTRODUCTION

The pipeline is the most common hydrocarbon

transportation over long distances; it is because

pipelines are the safest, reliable, and economical. The

pipelines are designed and operated/maintained for a

purpose, which is to transfer hazardous material from

one location (source or production facility) to another

location. Hydrocarbon pipeline has risk associated

with its operation because it contains pressurized

hazardous material with flammable and toxicity

characteristics. The unintentional release of

containment could be harmful to public and personnel

safety and impair the environment.

Pipelines are subject to various failure

mechanisms (e.g., corrosion, third-party damage,

incorrect operation, material defect, etc.) with various

degrees of impact, from minor to catastrophe and

disastrous consequence, in safety, asset loss, and

environmental aspect.

Third-party damage (TPD) refers to any

accidental damage done to the pipe because of

activities of personnel not associated with the pipeline

(non-operator). The incident is not as frequent as

another damage mechanism (e.g., corrosion), but the

consequence was usually more severe. TPD is the

leading cause of oil and gas pipeline failure (Jackson,

2018).

US Department of Transportation (DOT) pipeline

accident statistics show that third-party damage was

often the initiating event of pipeline failure.

Ironically, the potential for third-party damage is

often overlooked aspects of pipeline hazard

assessment. In most cases, initial pipeline design and

construction have considered the potential of third-

party damage. However, local community

encroachments and infrastructure development

activities are threatening many pipelines. Most

Pipeline Operators had challenges to protect the

pipelines right of way (ROW) to minimize the risk of

third-party encroachment, especially in developing

countries.

Maintenance of hydrocarbon pipelines and ROW

is a major challenge. Two major factors that drive the

challenge are the need to minimize the cost of

operation and, at the same time, shall not

compromising on risk. The reality is no organization

that has an infinite resource to manage the risk.

Therefore, an organization needs to use risk-based

analysis for resource allocation prioritization

Simanjuntak, M. and Putro, U.

Hydrocarbon Pipeline Third Party Damage Risk Assessment using Multi Criteria Decision Making.

DOI: 10.5220/0009959405790586

In Proceedings of the International Conference of Business, Economy, Entrepreneurship and Management (ICBEEM 2019), pages 579-586

ISBN: 978-989-758-471-8

579

carefully. There is a compelling need to have a more

accurate risk picture for various pipeline segments

from third-party damage hazard.

Risk is defined as the probability of an event that

causes a loss with absolute magnitude. In short, the

risk is a function of probability and consequences

(Muhlbauer, 2015). With this definition, the risk is

increased when the probability of failure increases, or

the magnitude of the loss or consequence increases.

Risk is not constant; it can change over time. Risk is

not constant; it can change with time. Risk assessment

is taking a snapshot of the risk profile at the moment

in time. The results of the risk assessment are then

used for risk reduction program to achieve risk as low

as reasonably practicable (ALARP).

2 PIPELINE THIRD PARTY

DAMAGE RISK

Risk is a combination of multivariable influencing

factors, which in general can be grouped into

exposure and mitigation. For TPD risk, Muhlbauer

(2015) breakdown the factor as follows.

Exposure is defined as an event that, in the

absence of any mitigation or safeguard, can result in

the incident if insufficient resistance exists. Exposure

of third-party damage consists of:

i. Excavation

Excavation exposure often occurs at new construction

from heavy equipment activities. Excavation

exposure is only applicable to buried pipelines.

ii. Vehicles

Exposure for vehicles hit the pipeline is a function of

the type of vehicle, traffic frequency, speed, and

distance to facilities. Vehicles hit only applicable to

above-ground pipelines

iii. Falling object

Exposure for the falling object could from tools drop,

cranes, falling trees. Falling object exposure only

applied to above-ground pipelines.

Mitigation is defined as the type and effectiveness

of every preventive and mitigative measure designed

to block or reduce exposure. Mitigation of third-party

damage consists of:

i. Cover of depth

Cover depth is the amount of protection over the

buried pipeline that protects it from third-party

activities and impacts. In general, a more in-depth

and stronger cover provides better protection.

ii. Impact barrier

The impact barrier protects above ground

pipelines from exposure to mechanical damage,

falling object, and vehicle collision.

iii. Line locating

Line locating involves pipeline marking, line

locating devices and procedures, marking

practices

iv. Speed control

Speed control is mainly used to reduce vehicles

hit.

v. Sign, Markers, ROW condition

The more recognizable the pipeline sign, markers,

and a ROW can reduce the likelihood of

inadvertent damage.

vi. Patrol

Pipeline patrol is the best practice of reducing

third-party intrusions. It is also intended to detect

an abnormal condition such as evidence of a leak

from pipelines. The patrol also should detect

potential third-party threats to the pipeline. Such

as when there is excavating equipment operating

nearby. The frequency and competency of the

patrol are affecting the patrol effectiveness to

prevent the incident.

vii. Public education programs

Programs to educate the public about the hazard

of critical activities such as excavation near

pipelines. This is important because third-party

damage is unintentional or due to ignorance.

3 ANALYSIS OF BUSINESS

SITUATION

Root Cause Analysis (RCA) with Why Tree method

was conducted. RCA result recommends to lookback

the effectiveness of existing pipeline risk assessment

and management. There should be a stronger risk

assessment process to ensure the resource is allocated

at the right level of prioritization. External factors

such as increased level of activity around the

Company's pipeline is a consequence of growing

development and hence cannot be avoided. Increased

rate of vandalism and oil theft are complex issues

which require the involvement of central government

and law enforcer. This research focuses on

recognizing and managing things within the

Company's influence and controllability. Therefore,

the oil theft sabotage issue is taken out of scope.

The quality of the existing pipeline risk

assessment process is being questioned. At present,

hazard identification and assessment are done on a

regular basis every five years cycle. The current risk-

based inspection result has recognized the hazard of

TPD. However, it failed to be translated into an

actionable risk reduction program that fit for the

specific hazard.

ICBEEM 2019 - International Conference on Business, Economy, Entrepreneurship and Management

580

Another thing to be considered is fast-paced

external condition changes due to the development of

public infrastructures and increased population

around the Company's asset. It signals the need for a

risk assessment process that is simple and robust

enough to allow dynamic input data changes so that

the Company could have an immediate risk reduction

response.

4 METHODS

4.1 Risk Assessment Selection

In general, there are three alternatives of pipeline risk

assessment method: 1) Simple Decision Support

(e.g., use risk matrix), 2) Hybrid (e.g., risk scoring),

3) Probabilistic Assessment (e.g., Quantitative Risk

Assessment)

Based on discussion with subject matter expert,

Probabilistic Risk Analysis (e.g., QRA) does not meet

the criteria for simple and user-friendly. Therefore,

QRA is dropped from the option. As discussed to

response uptrend of third-party damage risk and a

huge number of pipeline segments to be evaluated,

simple risk assessment is expected. The remaining

option is the Matrix and Risk Scoring Method.

Despite its simplicity, the matrix method has an

inherent weakness for the consistency aspect. The

risk assessment result is highly subjective, which

relies upon the facilitator and the risk assessment

team member. An example of an index method that

has been applied in the Company is the HAZOP

technique. This method is still applicable and useful

for generic pipeline risk assessment, which represents

the worst case for the entire pipeline length. This

method is not valid if we want to differentiate risk

assessment for hundreds of segmented pipeline with

a different condition.

Muhlbauer (WKM) risk scoring technique is one

of the risk assessment methods that famous for

pipeline application. The score is assigned to each

pipeline segment attribute that contributes to the risk

level. The scores are from the suggested procedure

from Muhlbauer. The lower the score, meaning the

lower the quality of safeguard; hence the probability

of failure or risk is higher. The assigned score reflects

the importance of each item relative to the others. The

weighting factor that is used in WKM method is

criticized because different weighting factors could

result in the different final risk scores. The weighting

should be adjusted to field conditions.

Analytical Hierarchical Procedure (AHP) is a

promising method for this application. To make a

decision support system for pipeline risk evaluation,

AHP alone is not adequate. This is because AHP has

limitations in making a pairwise comparison for more

than nine criteria or alternatives. Because the number

of pipeline segments to be evaluated can reach

hundreds or thousands of segments, it is impossible

to evaluate each segment risk with conventional AHP

method.

A combined AHP and SMART method then is

considered. The SMART method is utilized to

determine the pipeline rating score for each attribute

(subfactor) of risk influencing factors. The risk

assessor will rate the attribute (subfactor) of risk

influencing factor. The minimum rating will be

assigned for poor conditions and a maximum rating

for excellent condition. The higher the score meaning,

the better the condition or lower risk. These rates are

multiplied by the risk factor weight before finally

adding all together to obtain the total risk score (0-

100 scale).

The risk score is calculated with the below

equation:

 







(1)

wj = Risk influencing factor weight using AHP

aij = Alternative score performance against factor

using SMART

4.2 AHP and SMART

The AHP, developed by Saaty (1980), provides an

intuitive way to analyze complicated problems.

Practitioners have widely used AHP because of its

ease of applicability and the structure of AHP, which

follows the intuitive way in problem-solving. AHP is

a theory of measurement that uses pairwise

comparisons along with expert judgments. It is one of

the most popular Multi-Criteria Decision Making

(MCDM) techniques that allow subjective as well as

multiple objective factors to be considered in the

decision-making process. The AHP allows the active

participation of subject matter experts to reach an

agreement and gives them a rational basis for making

decisions.

The first step in AHP is problem formulation to

determine the goal for the decision analysis. In this

case, evaluation TPD probability of failure or risk

score of each pipeline segment. After the goal is

defined, the next step is the identification of risk

influencing factors with its attributes first and second

level AHP hierarchy. Once a hierarchy is built, the

expert or decision-maker begins a prioritization

procedure to determine the relative importance of the

Hydrocarbon Pipeline Third Party Damage Risk Assessment using Multi Criteria Decision Making

581

attribute in each level of the hierarchy. It uses "pair-

wise comparisons," and matrix algebra to weight

criteria, and the decision is made by using the derived

weights of the decision criteria. The decision-maker

does not need to provide a numerical judgment;

instead, a relative verbal scale or judgment according

to their importance. Table 1 explains the AHP scale.

For example, if two factors are judged having the

same level of importance, the pairwise score will be

1. If one factor is assumed to be remarkably stronger

than the other, a score of 9 is assigned.











1











…







1/













Where a

is the pairwise comparison between

element i and j

Table 1 AHP Qualitative Judgement Score.

Qualitative

Judgement

Explanation Score

Equally Two attributes have an equal

likelihood of rupture

Moderately The likelihood of rupture due

to one attribute is slightly

more than the other attribute

Strongly The likelihood of rupture due

to one attribute is firmly

more than the other attribute

Very

Strongly

The likelihood of rupture due

to one attribute is very

strongly more than the other

attribute

Extremely The likelihood of rupture due

to one attribute is extremely

more than the other attribute

Intermediate

judgment

The intermediate values are

used when compromise is

needed

2, 4,

6, 8

After comparison Matrices are created, relative

weights are derived. The relative weights of the

elements of each one level concerning an element in

the next upper level are computed as the components

of the associated normalized eigenvector. The

compound weights are determined by adding the

weights through the hierarchy. Stages do this, start

from the top of the hierarchy to each alternative in the

lowest position level, and multiplying the weights

along each segment of the path. The result of this

aggregation is a standard vector of the global weights

of the options. The mathematical basis for calculating

the weights was established by Saaty (1980).

One feature of the AHP method is the Consistency

Ratio (CR) parameter. It provides a consistency check

of relative importance from the pairwise comparison.

The maximum acceptable of CR is 0.1.

















is obtained from the decision matrix [A]









































CR is calculated as follow

i. Determine matrix B by multiplying matrix A

and matrix w





.















(2)

ii. Divide each element in vector B with

element in vector w to get new vector c

























































(3)

iii. Calculate λ_max by averaging element in

vector c

















(4)

iv. Calculate consistency index, CI, using

below equation











1

(5)

v. Calculate consistency ratio, CR, using below

equation, RI is a random index which refers

to Table 2







(6)

Table 2 Random Index Table.

n RI

3 0.58

4 0.9

5 1.12

6 1.24

7 1.32

8 1.41

9 1.45

>9 1.49

ICBEEM 2019 - International Conference on Business, Economy, Entrepreneurship and Management

582

Including several expert's opinions can avoid bias

that may be present single expert judgment. AHP has

a useful feature that enables a group to structure a

hierarchy jointly and participate in the discussion to

decide the pairwise judgment. The discussion

facilitator can lead the discussion to obtain consensus.

When the team is unable to reach consensus, a

geometric mean of participant judgment can be used.

It is possible to resolve such differences by selecting

more consistent judgments.

If a consensus is difficult to achieve, the

geometric mean of individual evaluations is applied

as elements in the pair-wise comparison, and then

priorities are calculated.

4.3 Data Collection and Analysis

Literature research and past incident investigation

report are utilized as a reference in analyzing the

problem. Pipeline integrity conditions and external

conditions are gathered from the Company's

inspection data.

A combination of the Analytical Hierarchy

Process (AHP) and Simple Multi-Attribute Rating

Technique (SMART) will be exercised to assess risk

score.

Group of six experts is appointed for determining

the root cause, risk influencing factor (decision

criteria), the relative importance of each risk factor,

and development of SMART scale standard

definition. The expert is selected based on their level

of competency and experience in process safety, risk

management, asset integrity, operation, and

maintenance.

Pairwise comparison, each risk factor is done by

individual experts independently. The pairwise

comparison is a facilitated session to ensure the

expert uses consistent risk factor definition. The

pairwise comparison and weighting priority synthesis

are conducted with AHP-OS, an online AHP software

tool (Goepel, 2015). The AHP-OS tool also provides

a Consistency Ratio (CR) number and group

consensus level.

5 RESULTS AND DISCUSSION

The decision hierarchy tree is developed based on

the risk influencing factor and subfactor, which

discussed previously.

Figure 1 AHP Decision Hierarchy.

The SMART standard definition also defined to

explain the scoring 0-100 according to the pipeline

attribute.

Table 2 Pipeline Segment Attribute Scale (SMART).

Level

Activity

Above

ground

facilities

Depth of

cover

Line

Locating

High

0 pts

None

0 pts

Shallow

0 pts

None

0 pts

Medium

40 pts

Weak

25 pts

Average

50 pts

Average

50 pts

Low

75 pts

Average

50 pts

Deep

100 pts

Good

100 pts

None

100 pts

Strong

100 pts

ROW

Condition

Patrol

Frequency

Public

Education

Poor

0 pts

None

0 pts

None

0 pts

Average

40 pts

Monthly

25 pts

Weak

25 pts

Good

60 pts

Weekly

50 pts

Average

70 pts

Excellent

100 pts

Daily

100 pts

Strong

100 pts

AHP procedure result from AHP-OS is shown in

Figure 2.

Hydrocarbon Pipeline Third Party Damage Risk Assessment using Multi Criteria Decision Making

583

Figure 2 Consolidated Result of Third-Party Damage Risk

Factor Weighting.

AHP-OS computed the consistency ratio for

individual judgment and consolidated group

judgment. The CR for third-party damage POF

pairwise comparison is 1.4%. Therefore, weighting

can be used for further usage. For group decisions, the

AHP-OS software calculates an AHP consensus

indicator to quantify the consensus of the group

(estimate of the agreement on the outcoming

priorities between participants). This indicator ranges

from 0% to 100%. Zero percent corresponds to no

consensus at all, 100% to full consensus. It is a

measure of homogeneity of priorities between the

participants and can also be interpreted as a measure

of overlap between priorities of the group members

(Goepel, 2015). The group consensus for TPD POF

pairwise comparison is 79.4% (high).

Based on AHP's expert judgment, the top five risk

factor of third-party damage is level of activity

(41.9%), above-ground facility (18.6%), and line

locating (10.9%), the minimum depth of cover

(10.7%), and right of way condition (8.6%). A

comparison with the WKM weighting factor is shown

in Table 3. The difference in weighting factor is also

can affect overall risk score and hence impact to

resource allocation quality.

Table 3 Comparison Risk Influencing Factor Weighting.

Factor WKM WKM-

AHP

Level of Activity 20% 42%

Above Ground Facility 10% 19%

Line Locating 15% 11%

Minimum Depth of Cover 20% 11%

ROW condition 5% 8%

Patrol Frequency 15% 4%

Public Education 15% 5%

The level of activity factor is the most important

factor but also the most complicated factor to be

resolved because the pipeline operator has relatively

little influence to manage the public activity or to

prevent illegal encroachment along the pipeline. The

only possible option is to re-route the existing

pipeline via an alternate location, which still sterile

from public activities.

Above ground, the facility is the second most

important risk factor because most of the Company's

facility was designed and installed above ground. It

was designed and constructed a long time before the

Government of Indonesia implemented the regulation

to mandate the hydrocarbon pipeline to be buried.

The third and fourth factor is directly related with

a buried pipeline segment. The expert has agreed that

both the pipeline depth of cover and line locating are

equally important. The buried pipeline will not be

effective in preventing incidents until it has effective

program for line locating. This is consistent with key

learning points from the past incident investigation

that those incidents due to excavation can be

prevented if the third-party notify the pipeline

operator prior conducted the work.

The fifth important factor, right of way condition,

are relatively equal weighting with line locating and

depth of cover. The expert opined that maintaining

the right of way conditions can ensure the pipeline is

visible and improve leak detection. Public education

is considered a weak component of risk factors

because of learning from experience. The expert

opined that the best way to prevent encroachment is

by installing a mechanical barrier along the pipeline.

Pipeline patrol is also considered less effective in

preventing third-party pipeline damage because of

extensive coverage of pipeline surveillance

requirements. However, experts agree that the patrol

program is a crucial component to provide data for

third-party damage risk assessment.

6 CASE STUDY

The proposed Decision Support System is then

implemented for risk assessment of the following

sample six pipeline segments. This segment is

selected to represent a typical pipeline segment

operated in the Company.

Table 3 Pipeline Properties.

No Pipeline Installation Service

1 A Buried Crude

2 B Above ground Crude

3 C Above ground Crude

4 D Above ground Crude

5 E Above ground Crude

6 F Above ground Crude

4.30%

4.90%

8.60%

10.70%

10.90%

18.60%

41.90%

Patrol Frequency

Public Education

ROW Condition

Minimum Depth of Cover

Line Locating

Above Ground Facilities

Level of Activity

ICBEEM 2019 - International Conference on Business, Economy, Entrepreneurship and Management

584

Third-party damage risk score ranking (note:

lower score means higher risk)

1. A: 26

2. B: 28

3. C: 31

4. D: 34

5. E: 49

6. F: 86

Based on this result, pipeline segments A and B

with the current condition are the top two segments

with high risk or most vulnerable. Which, therefore,

it should be prioritized for maintenance resource

allocation to reduce the risk. Segment A has a higher

risk because the segment is located above ground,

crossing busy public areas (due to encroachment),

adjacent with roadways, and not protected with an

adequate barrier to prevent hit incident. While

segment B, which buried, has risk exposure to illegal

excavation damage. Segment B is located nearby

ongoing infrastructure construction (toll road).

Following corrective action are proposed for

pipeline A:

1. Install additional impact barrier at an identified

location which adjacent to roadways

2. Conduct regular housekeeping to clear pipeline

right of way

Following corrective action are proposed for

pipeline B:

1. Improve line locating procedure

implementation, communicate regularly with a

third-party contractor

2. Provide barriers, markers, and warning signs at

a location nearby construction activities.

When the two corrective actions completed, the

risk score will change from 26 to 50 for Pipeline A

and Pipeline B will change score from 28 to 49, which

makes them at safer state.

The proposed decision support system still has

subjectivity involved, which would introduce

uncertainties to the result. Dawotola (2012) uses

combined Hooke's Classical Model structured expert

judgment process and AHP to reduce the subjectivity.

The risk result with the proposed model is a relative

risk and not absolute risk, which makes the result

cannot be used to conclude whether the risk is

tolerable or not.

Full deployment of new decision support will

require further alignment with the existing program in

the Company. The high level of the proposed

workflow is shown in Figure 3.

Figure 3 Proposed New Workflow for Third-Party Damage

Risk Management.

7 CONCLUSION

Decision Support System (DSS) for third-party

damage risk reduction program is presented. The

decision support model uses the Muhlbauer (WKM)

model, which modified with the Analytical Hierarchy

Process (AHP) to improve the prediction probability

of failure (POF) from third-party damage.

The level of activity near pipelines contribute to

41.9% of the probability of failure from third-party

damage, which means pipeline location plays a

crucial role in the overall risk picture. Other factors

contribution: above ground facility 18.6%, line

locating 10.9%, a minimum depth of cover 10.7%

right of way condition 8.6%, public education 4.9%,

and patrol frequency 4.3%.

The study also reveals that pipeline hit incident:

vehicle hit for above-ground pipeline and excavation

hit for the buried pipeline are top two of third-party

damage mechanism. Above ground pipeline, risk

reduction factor is dominantly affected by above-

ground facilities (18.6%), and buried pipeline

reduction factor is dominantly affected by the

minimum depth of cover and line locating (combined

weight 21.6%).

This work is expected can help the organization

for improving resource allocation for risk reduction

program and maintenance activities. Although the

model is applied for pipeline risk assessment, the

same principle can be applied for other risk

assessment exercise.

Hydrocarbon Pipeline Third Party Damage Risk Assessment using Multi Criteria Decision Making

585

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