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An integrated assessment model for cross-country pipelines
Environmental Impact Assessment Review 22 (2002) 703 – 721 www.elsevier.com/locate/eiar
An integrated assessment model for cross-country pipelines Prasanta Kumar Dey Department of Management Studies, University of the West Indies, Cave Hill Campus, PO Box 64, Bridgetown, Barbados Received 1 March 2001; received in revised form 1 April 2002; accepted 1 May 2002
Abstract The cross-country petroleum pipelines are environmentally sensitive because they traverse through varied terrain covering crop fields, forests, rivers, populated areas, desert, hills and offshore. Any malfunction of these pipelines may cause devastating effect on the environment. Hence, the pipeline operators plan and design pipelines projects with sufficient consideration of environment and social aspects along with the technological alternatives. Traditionally, in project appraisal, optimum technical alternative is selected using financial analysis. Impact assessments (IA) are then carried out to justify the selection and subsequent statutory approval. However, the IAs often suggest alternative sites and/or alternate technology and implementation methodology, resulting in revision of entire technical and financial analysis. This study addresses the above issues by developing an integrated framework for project feasibility analysis with the application of analytic hierarchy process (AHP), a multiple attribute decision-making technique. The model considers technical analysis (TA), socioeconomic IA (SEIA) and environmental IA (EIA) in an integrated framework to select the best project from a few alternative feasible projects. Subsequent financial analysis then justifies the selection. The entire methodology has been explained here through a case application on cross-country petroleum pipeline project in India. D 2002 Elsevier Science Inc. All rights reserved. Keywords: Feasibility analysis; Analytic hierarchy process; Cross-country petroleum pipeline project; Present value; Integration
E-mail address: [email protected] (P.K. Dey). 0195-9255/02/$ – see front matter D 2002 Elsevier Science Inc. All rights reserved. PII: S 0 1 9 5 - 9 2 5 5 ( 0 2 ) 0 0 0 2 0 - 3
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1. Introduction Projects transform organization’s vision to reality. Moreover, science and technology are manifested by major projects. Many of them are large-scale construction projects. Therefore, projects stand for sustainable development. However, there are many instances of adverse effects of projects on environment. Therefore, impact assessment (IA) is conducted in advance to determine the socioeconomic and environmental consequences of industrial projects on society. IA of large industrial projects assumes special importance because these projects are likely to affect the socioeconomic fabric of a section of people, generally called the project-affected people. Socioeconomic impacts occur at all the four stages— preconstruction (planning/policy development), construction (implementation), operation and maintenance and decommissioning (abandonment)—of industrial projects (Ramanathan and Geetha, 1998). Cross-country petroleum pipeline mode for transportation of bulk petroleum product has already been established as the most energy efficient, safe and environment friendly and economic mode of transporting hydrocarbon (gas, crude oil and finished product) over long distances within the geographical boundary of a country and beyond. A stage has now been reached when a significant part of a nation’s energy requirement is transported through pipelines. The economy of a country is heavily dependent on smooth and uninterrupted operation of these lines (Dey and Gupta, 2000). Therefore, it is becoming increasingly important to ensure safe and failure-free operation of these pipelines. While pipelines are inherently one of the safest mode of transporting bulk energy, with failure rates much less compared to rail/road transportation, failures do occur and sometimes with catastrophic consequences. A number of pipelines have failed in the recent past with tragic consequences, to name a few in 1993 in Venezuela 51 people were burnt to death when a gas pipeline failed and escaping gas got ignited. Again, in 1994, a 36-in. diameter pipeline in New Jersey, USA failed, which resulted death of one person and injuring more than 50 people (US Department of Transportation, 1995). Such failures are also reported from various other countries across the world viz. UK, Russia, Canada, Pakistan and India, etc. More recently, in 1998, pilferage attempt in a product pipeline leads to a major catastrophe leading to death of 500 persons (Annual Report of CONCAWE, 1994). While pipeline failures have rarely caused fatality but disruption of operation leads to large losses in business. Also, such failures can be very costly and leads to considerable damage to environment (Dey et al., 1998). Traditionally, most pipeline operators ensure that during design safety provisions are created to provide a theoretical minimum failure rate for the life of the pipeline. Safety provisions govern selection of pipes and other fittings. To prevent corrosion, high-resistance external coating materials electrically isolate a pipeline. As a secondary protective measure, a low-voltage direct current is impressed in the pipe at precalculated distances to transfer any corrosion that occurs as a result of breaks in the coating from buried iron junk, rails, etc. This is called impresses-current cathodic protection (CP). The
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quality of the commodity being transported through the line is also ensured. Sometimes, corrosion-preventing chemicals (corrosion inhibitors) are mixed with the commodity. Regular patrolling of the right of way (ROW) from the air as well as on foot helps prevent deliberate damage of the pipeline in isolated locations. All third-party activities near the route are monitored. Various techniques are routinely used to monitor the status of a pipeline. Any deterioration in the line may cause a leak or rupture. Modern methodologies can ensure the structural integrity of an operating pipeline without being taken out of service. Hence, to manage pipelines effectively, pipeline operators design their pipeline system in a very reliable way by choosing optimal pipeline route (Dey and Gupta, 1999) and planning pipeline projects efficiently with the consideration of overall profitability of project in long run (Dey et al., 1996). The shortest distance between demand and supply points governs the current practice of feasibility analysis of cross-country petroleum pipeline projects. A few alternative projects are then developed with the consideration of technical parameters such as throughputs, diameter of pipelines and number of intermediate stations. Subsequent financial analysis selects the best project on the basis of minimum cost with respect to capital and operating cost. Environmental IA (EIA) and socioeconomic IA (SEIA) provide clearance from the statutory regulations. The present feasibility analysis never considers maintenance and the augmentation possibility of the pipeline (Dey, 1999). Both these factors are highly dependent on the pipeline route. Cross-country petroleum pipeline route selection is governed by the following goals:
Establish the shortest possible route connecting the originating, intermediate and terminal locations. Ensure, as far as practicable, accessibility during operation and maintenance stages. Preserve the ecological balance and avoid/minimize environmental damage. The route should be kept clear of forests as much as possible. Avoid populated areas for public safety reasons. Keep rail, road, river and canal crossings to the bare minimum. Avoid hilly or rocky terrain. Avoid a route running parallel to high-voltage transmission lines or DC circuits. Use an existing ROW, if possible. Avoid other obstacles such as wells, houses, orchards, lakes or ponds.
These characteristics must be determined by a reconnaissance survey and the goal of finding the shortest possible route is always important. There are many examples of loss of productivity due to wrong pipeline route selection. A specific stretch of pipeline in eastern India (102 km, 12.75 in./324 mm in diameter, 0.25 in./6.35 mm wall thickness, API 5L X-46 pipe grade) was commissioned in September 1977. The pipeline is protected against external
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corrosion by an impressed current cathodic protection system over and above the coal tar enamel external coating. The ROW includes a waterlog of 30-km area that remains under water for 6 –7 months in 1 year, with a water depth varying between 3 and 4 m. In this 30-km stretch, extensive external corrosion has occurred. Between pipeline chainage (distance from a reference point) of 11 – 41 km, two leaks were encountered. At 203 locations, sleeving (reinforcement cladding) has been carried out due to heavy external corrosion. The pipeline operates at a lower throughput than its designed capacity. It is estimated that this pipeline incurs a loss of 120 million rupees/year on average (115 million rupees in lost production due to reduced capacity operation plus 5 million rupees for additional maintenance cost). This is calculated at a rate of US$1 = 48 rupees as of March 2002. The loss of production due to operation at a reduced capacity was determined with the consideration of the following factors. Under the administrative pricing mechanism (APM), pipeline operators in India get a return on investment from pipeline projects at the rate of 12% of present value (PV) of cost (capital + operating) if pipelines run at full capacity. The return diminishes proportionately with the reduction in capacity. If the pipeline had been rerouted during the initial design phase, the capital cost would have increased by 100 million rupees (50 million rupees for additional mainline cost plus 50 million rupees for an additional station). The benefit of an alternative route is clear. Another example of poor route selection is a 40-km stretch of coal belt along the route of a petroleum pipeline in eastern India. This stretch is vulnerable to failure due to third-party activities (coal mining) in the surrounding area. A risk analysis study determined that the probability and severity of a failure here was very high, with an expected cost of 1000 million rupees (Annual Report of CONCAWE, 1994). Rerouting the pipeline during the design stage would have cost 60 million rupees. Avoiding this area would have been cost effective. Petroleum pipelines are designed to carry a specific capacity for a specific life period and rely on a forecast of a supply – demand scenario of petroleum products. It is quite likely that during a pipeline’s life span the capacity of the line may need to be increased to maximize returns commensurate with petroleum product demand. However, if the pipeline route does not provide adequate room for augmentation, this cannot be accomplished. Pipeline route selection should be governed not only by factors like the shortest total distance, approachability and constructability. Factors such as operability, augmentation capability and maintainability also need to be considered. In the recent years, SEIA and EIA have immerged as a study to ensure a project as a profitable venture to its owner and a contributing agent to the society. However, sometimes, they are not taken in their right spirit by the project owner, causing lots of nonconsensus among the PAP. This results serious damage either to the project or to the society. Fig. 1 shows the current project feasibility analysis process of cross-country petroleum pipeline for the project under study. Rapid growth of industries calls for many pipeline projects, which are scrutinized to identify only a few feasible
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Fig. 1. Current project feasibility analysis process of cross-country petroleum pipelines.
projects for further analysis. The market and demand analysis determines throughput of pipelines and supply – demand points. These select the pipeline route through subsequent reconnaissance survey. In the technical analysis (TA), only a few alternate projects with respect to diameters of pipelines and number of intermediate stations are analyzed and the optimum option is selected on the basis of financial evaluation criteria like net PV, internal rate of return, etc. The EIA and SEIA are then carried out on selected project to mitigate the negative impacts of project on environment. The pipeline operators, while carrying out project feasibility analysis following the steps as explained in Fig. 1, encounter the following problems. 1. It takes longer time to complete a project feasibility study, as all the analyses are taken up subsequently. 2. As during IA only one project is analyzed, quite often, project proposal tries to justify the best alternative generated from financial analysis. 3. IA often demands alteration of project site (pipeline route) and usage of different technology. These cause revision of entire technical and financial analysis. 4. Although sometimes projects get statutory approval from the regulatory authorities on the basis of IA reports, there are evidences of project abandonment at the later stage due to public protest.
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5. Sometimes, the selected projects are proven to be not fully effective in operations stage due to enormous operating and maintenance cost and lack of expansion possibility. The above problems can be resolved by modeling the entire feasibility analysis in an integrated framework. Accordingly, the objective of the study is to develop an integrated project selection model that quantifies the merits and demerits of various alternative projects for selecting the optimal option. The entire methodology has been explained through a case application on crosscountry petroleum pipeline project selection.
2. Proposed model and methodology Fig. 2 shows the proposed model for feasibility analysis of a cross-country petroleum pipeline. The TA, EIA and SEIA are carried out simultaneously. These solve site selection (pipeline route) problems along with a few technological considerations. The least cost option is then identified through financial analysis on a few alternative feasible projects. 2.1. An analytic hierarchy process (AHP)-based approach to project appraisal model The AHP developed by Saaty (1980) provides a flexible and easily understood way of analyzing complicated problems. It is a multiple criteria decision-making technique that allows subjective as well as objective factors to be considered in decision-making process. The AHP allows the active participation of decisionmakers in reaching agreement and gives managers a rational basis on which to
Fig. 2. Proposed project selection model of cross-country petroleum pipelines.
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make decisions. AHP is based on the following three principles: decomposition, comparative judgement and synthesis of priorities. The AHP is a theory of measurement for dealing with quantifiable and intangible criteria that have been applied to numerous areas, such as decision theory and conflict resolution (Vargas, 1990). AHP is a problem-solving framework and a systematic procedure for representing the elements of any problem (Saaty, 1983). Formulating the decision problem in the form of a hierarchical structure is the first step of AHP. In a typical hierarchy, the top level reflects the overall objective (focus) of the decision problem. The elements affecting the decision are represented in intermediate levels. The lowest level comprises the decision options. Once a hierarchy is constructed, the decision-maker begins a prioritization procedure to determine the relative importance of the elements in each level of the hierarchy. The elements in each level are compared as pairs with respect to their importance in making the decision under consideration. A verbal scale is used in AHP that enables the decision-maker to incorporate subjectivity, experience and knowledge in an intuitive and natural way. After comparison matrices are created, relative weights are derived for the various elements. The relative weights of the elements of each level with respect to an element in the adjacent upper level are computed as the components of the normalized eigenvector associated with the largest eigenvalue of their comparison matrix. Composite weights are then determined by aggregating the weights through the hierarchy. This is done by following a path from the top of the hierarchy to each alternative at the lowest level and multiplying the weights along each segment of the path. The outcome of this aggregation is a normalized vector of the overall weights of the options. The mathematical basis for determining the weights was established by Saaty (1980). Project appraisal is a team effort, and the AHP is one available method for forming a systematic framework for group interaction and group decisionmaking (Saaty, 1982). Dyer and Forman (1992) describe the advantages of AHP in a group setting as follows: (1) both tangibles and intangibles, individual values and shared values can be included in an AHP-based group decision process, (2) the discussion in a group can be focused on objectives rather than alternatives, (3) the discussion can be structured so that every factor relevant to the discussion is considered in turn and (4) in a structured analysis the discussion continues until all relevant information from each individual member in a group has been considered and a consensus choice of the decision alternative is achieved. A detailed discussion on conducting AHP-based group decision-making sessions including suggestions for assembling the group, constructing the hierarchy, getting the group to agree, inequalities of power, concealed or distorted preferences and implementing the results can be found in Saaty (1982) and Golden et al. (1989). For problems with using AHP in group decision-making, see Islei et al. (1991).
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Researchers use AHP in various industrial applications. Partovi et al. (1990) used it for operations management decision-making. Dey et al. (1994) used it in managing the risk of projects. Eyrich (1991), Korpela and Tuominen (1996) and Dey (2002), for benchmarking various business functions, also have effectively used AHP. Mian and Christine (1999) used AHP for evaluation and selection of a private sector project. Meredith and Mantel (2000) described AHP as an effective tool for project selection. Dey and Gupta (1999) used AHP for cross-country petroleum pipeline route selection. In this research, a simultaneous analysis of technical, environmental and socioeconomic aspects of the project are carried out using AHP. The following are the rationale for using AHP for project selection:
The factors that lead to project selection are both objective and subjective. They are also conflicting in nature—achievement of one factor may result in sacrificing others. There is a need for a subjective approach to project selection that can incorporate objectivity. AHP provides a flexible and easily understood way to analyze each factor that leads to project selection. It allows subjective as well as objective factors to be considered. AHP calls for the active participation of decision-makers in reaching agreement and gives managers a rational basis on which to make decision. For the present study, decision-makers are the executives of the organization (working in project selection task) from various levels having working experience of more than 15 years. They have established the AHP model for project selection through a few brainstorming sessions. The identification of factors and subfactors along with formation of comparative matrix is made in a group decision-making process through common consensus among the executives. However, if disagreements occur, they are resolved by reasoning and collecting more information. The group collects and analyses data and recommends the selection. Their proposal contains all the necessary details that are required to establish the selection. These give an insight to the approving authority to understand the whole processes and basis of selection. A joint meeting (decisionmakers and approving authority) may also be called for further facilitating the process of approval. The sensitivity utility of AHP provides an opportunity for them to understand the implications of their decision. The following methodology has been adopted in selecting optimal project:
Identification of alternative projects (in this case, alternate pipeline route) and formation of database for each route through geographical information system (GIS) (Montemurro and Barnett, 1998). Identification of factors and subfactors that leads to select the optimal project Formation of project selection model in AHP framework through TA, EIA and SEIA
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Analyzing each factor and subfactor by pairwise comparison and analyzing each alternative with respect to each subfactor by pairwise comparison through the available data Synthesizing the result across hierarchy to select the optimal project. Fig. 3 shows the list of the factors for selecting pipeline project as identified by the executives working in the best pipeline project selection task. 2.1.1. Technical factors The technical factors important to selection of pipeline route include length, operability, approachability and constructability.
Fig. 3. Factor and subfactors for project selection.
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2.1.1.1. Pipeline length. Pipeline length governs the capacity requirement of almost all equipment for entire pipeline project, as pipeline head loss is directly proportional to the length of the pipeline. Hence, the shorter the length of a pipeline, the lesser the capital cost of the project and vice versa. 2.1.1.2. Operability. The hydraulic gradient is a major factor in selecting prime mover power for pipeline operations, as negative hydraulic gradient demands for higher prime mover power. Similarly, more route diversion causes more friction loss, resulting in higher prime mover power for the same throughput. These result to more capital investment. A pipeline is designed for specific throughput in line with demand. A pipeline may need to be augmented in the future to cope with the demand for maximizing profit. Therefore, expansion/augmentation capability is one attribute of properly designed pipeline. In addition to improving the existing prime mover capacity, a pipeline can also be augmented by installing more pumping stations along the route and laying loop lines/parallel lines. 2.1.1.3. Maintainability. Though pipelines are designed with adequate safety factors, they are subjected to failure due to various reasons. Pipeline corrosion, pilferage and third-party activities are factors that may create quantum throughput loss along with chances of disaster. Therefore, these factors should be carefully considered during the feasibility study. In a decision model, these factors may influence the selection of a specific route. One of the major causes of pipeline failure is corrosion, an electrochemical process that changes metal back to ore. Corrosion generally takes place when there is a difference of potential between two areas having a path for the flow of current. Due to this flow, one of the areas loses metal. External interference is another leading cause of pipeline failure. It can be malicious (sabotage or pilferage) or be caused by other agencies sharing the same utility corridor. The latter is known as third-party activity. In both cases, a pipeline can be damaged severely. External interference with malicious intent is more common in socioeconomically backward areas, while in regions with more industrial activity third-party damage is common. Poor construction, combined with inadequate inspections and low-quality materials, also contributes to pipeline failure. Other reasons include human and operational error and equipment malfunctions. Computerized control systems considerably reduce the chance of failure from these factors. All activities, industrial or otherwise, are prone to natural calamities, but pipelines are especially vulnerable. A pipeline passes through all types of terrain, including geologically sensitive areas. Earthquakes, landslides, floods and other natural disasters are common reasons for pipeline failures. 2.1.1.4. Approachability. Although a cross-country petroleum pipeline is buried underground, the ROW should allow uninterrupted construction activities as well
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as operation, inspection and maintenance. The ideal pipeline route should be along a railway track or a major highway. This is not always possible due to the long length of pipelines, which may require river crossings and travelling through forests, deserts, etc. Therefore, pipeline route with better approachability gets an edge over other routes. 2.1.1.5. Constructability. Laying pipeline across states/province or national boundaries requires permission from statutory government authorities. Stringent safety and environmental stipulations sometimes are hindrances to project activities. Mobilization is a major construction activity. One factor in pipeline routing is the provision for effective mobilization by the contractor. Distance to market, the availability of power and water and the number of skilled and unskilled laborers are typical requirements for starting effective construction activities. Pipeline construction methods vary greatly with terrain conditions. For example, laying pipeline across a river requires horizontal direction drilling (HDD), while laying across rocky area requires rock trenching techniques. Therefore, location characteristics are a major cost component of pipeline construction. Inappropriate route selection can cause major time and cost overruns.
Fig. 4. AHP model for project selection.
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2.1.2. Environmental factors Pipelines handle hazardous petroleum products. Although pipelines are designed with safety features, failure is not uncommon. Sometimes, failures result in a release of large quantities of petroleum products into the environment. If this should happen, a pipeline located in a remote area is less of a safety concern. The following factors are to be considered to assess environmental impact: Effect Effect Effect Effect Effect
on on on on on
environment environment environment environment environment
during during during during during
failure of pipelines failure of pipeline stations normal pipelines operations normal station operations pipeline construction
The above factors considerably affect the selection pipeline route. 2.1.3. Socioeconomic factors 2.1.3.1. Planning stage. At this stage, pipeline route is finalized. The ROW is required to acquire for construction. This ROW often passes through agricultural land. Acquisition of agricultural land for industrial purposes involves several issues. Some of the important ones are payment of compensation for the land and provision of employment, alternative accommodation and other rehabilitation measures to the PAP.
Table 1 Pipelines database Description a
Throughput (MMTPA ) Length (km) No. of stationsb Terrain detail (km) (a) Normal terrain (b) Slushy terrain (c) Rocky terrain (d) Forest terrain (e) River crossing (f) Populated area (g) Coal belt area Soil conditions Third-party activity Chances of pilferage a b
Route 1
Route 2
Route 3
5 1250 4
5 1360 4
5 1180 4
780 5 – – 3 462
980 5 1 5 4 350 15 Less corrosive soil
1000 45 2 7 5 120 – Corrosive soil for slushy terrain Comparatively less
Less corrosive soil More due to populated area Higher due to populated area
More due to coal belt and populated area Higher due to populated area
Comparatively less
MMTPA = million metric tons/year. Originating pump station/Intermediate pump station/Terminal delivery station.
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Table 2 Scale of relative importance for pairwise comparison Intensity
Definition
Explanation
1 3 5 7 9
Equal importance Moderate importance Essential or strong importance Demonstrated importance Extreme importance
2, 4, 6, 8
Intermediate values
Two activities contribute equally to the object Slightly favors one over another Strongly favors one over another Dominance of the demonstrated in practice Evidence favoring one over another of highest possible order of affirmation When compromise is needed
Source: Saaty (1980).
2.1.3.2. Construction stage. The socioeconomic issues, which need to be addressed during the construction stage of a pipeline project, are mainly the effect of employment generation and a new construction activity leading to an additional burden on local infrastructure facilities. These are only short-term impacts lasting during the construction phase of the project. Effect of employment generation. During the construction phase, the major positive socioeconomic impact will be in the sphere of generation of temporary employment of very substantial numbers. This additional employment generation may lead to an influx of people into the impact area. Effect of construction activity. Construction activity involves movement of heavy vehicles, leading to disruption of other agriculture activities. Pipeline construction sometimes leads to local transport disruption also. 2.1.3.3. Operation stage. The operational stage of the project covers the entire life span of the pipelines. Hence, the impacts of the operational phase
Table 3 Pairwise comparison in factor level Factors
Length
Operability
Maintainability
Approachability
Constructability
Length Operability Maintainability Approachability Constructability
1 1/2 1/2 1/3 1/3
2 1 1 1/3 1/2
2 1 1 1/3 1
4 3 3 1 2
3 2 1 1/2 1
Normalized matrix Factors
Length Operability Maintainability Approachability Constructability Importance
Length Operability Maintainability Approachability Constructability
0.39 0.19 0.19 0.10 0.13
0.41 0.21 0.21 0.07 0.10
0.38 0.19 0.19 0.06 0.19
0.31 0.23 0.23 0.08 0.15
0.40 0.27 0.13 0.07 0.13
0.38 0.22 0.19 0.07 0.14
716
Factors
TA
EIA
Weights
0.38
0.28
Subfactors
Weights LP
GP
Length Operability
0.38 0.22
0.1444 0.0836
Maintainability
0.19
0.0722
Approachability Constructability Failure in pipelines Failure in station Normal operations of station
0.07 0.14 0.43 0.33 0.05
0.0266 0.0532 0.1204 0.0924 0.014
Subfactors
Route characteristics Augmentation possibility Expansion capability Corrosion External interference Construction/ material defect Operational defect Natural hazards
Weights
Normalized
Route 1
Route 2
Route 3
LP
GP
LP
GP
LP
GP
0.28 0.39
0.144 0.023 0.033
0.34 0.33 0.42
0.049 0.008 0.014
0.25 0.29 0.32
0.036 0.007 0.010
0.41 0.38 0.26
0.059 0.009 0.008
0.33 0.3 0.25 0.17
0.028 0.022 0.018 0.012
0.33 0.4 0.35 0.43
0.009 0.009 0.006 0.005
0.42 0.31 0.38 0.38
0.012 0.007 0.007 0.005
0.25 0.29 0.27 0.19
0.007 0.006 0.005 0.002
0.15 0.13
0.011 0.009 0.027 0.053 0.120 0.092 0.014
0.34 0.43 0.35 0.36 0.4 0.39 0.33
0.004 0.004 0.009 0.019 0.048 0.036 0.005
0.33 0.27 0.42 0.4 0.25 0.27 0.34
0.004 0.003 0.011 0.021 0.030 0.025 0.005
0.33 0.3 0.23 0.24 0.35 0.34 0.33
0.004 0.003 0.006 0.013 0.042 0.031 0.005
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Table 4 Project selection date analysis
0.34
0.04
0.0112
0.011
0.33
0.004
0.34
0.004
0.33
0.004
0.15
0.042
0.042
0.42
0.018
0.26
0.011
0.32
0.013
0.43
0.1462
Compensation Employment and rehabilitation
0.7 0.3
0.102 0.044
0.35 0.36
0.036 0.016
0.27 0.23
0.028 0.010 0.000
0.38 0.41
0.039 0.018
Effect during construction
0.36
0.1224
Employment Effect of construction activities
0.5 0.5
0.061 0.061
0.34 0.41
0.021 0.025
0.33 0.24
0.020 0.015 0.000
0.33 0.35
0.020 0.021
Effect during operations
0.21
0.0714
Employment Burden on existing infrastructure Overall weight Ranking
0.2 0.8
0.014 0.057
0.34 0.38
0.005 0.022
0.33 0.27
0.005 0.015
0.33 0.35
0.005 0.020
LP: local percentage, GP: global percentage.
0.370 1
0.289 3
0.341 2
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SEIA
Normal operations of pipelines During construction Effect during planning
717
718
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extend over a long period time. However, pipeline projects seldom generate employment opportunity in this stage and provide fewer burdens to existing infrastructure as the pipelines remain buried under the earth. However, agricultural activities remain restricted on ROW throughout the life span of the pipelines.
3. Project selection model Fig. 4 shows the project selection model in AHP framework. Level 1 is the goal, selecting the best cross-country petroleum pipeline project. Levels 2 and 3 are the factors and subfactors, respectively, which are required to be considered for selection. Level 4 presents the alternative projects—various feasible pipeline routes. Table 1 shows the database for each alternate route. These data along with the experience of pipeline operators were utilized to analyze the AHP model to select the best pipeline project. The data were analyzed by using Expert Choice software package. Firstly, the factors and subfactors are pairwise compared using the ‘‘scale of relative importance’’ as per Table 2 to determine their importance. Table 3 shows a sample pairwise comparison matrix in subfactor level. Secondly, the alternative routes are pairwise compared with respect to each subfactor using the ‘‘scale of relative importance’’ to determine preferences. Thirdly, the results are then synthesize across hierarchy to determine the best selection. Table 4 shows the data related to the outcomes of all matrices and selection.
4. Results and findings The analysis of the data indicates that Route 1 is the best route for laying pipeline for the project under study, although this is not the shortest route. This project outranks the other alternatives with respect to its augmentation and expansion possibilities, maintainability, environment friendliness and less impact on society. Table 5 shows the life cycle cost estimate of the project with Route 3 (the shortest route) and the project with Route 1 (the optimal route). The PV of cost of the project with shortest route is much higher than the optimal project. Therefore, the life cycle costing (LCC) model also fevers for the selection of pipeline project through an integrated approach with the consideration of all factors, which effect the pipeline operations and profitability throughout its life cycle. However, collecting all information for deriving the LCC is time consuming and expensive. Moreover, estimate of LCC is generally based on many assumptions. Alternatively, decision support system (DSS) using AHP provides a good model for project selection that relies on the experience of
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Table 5 Life cycle cost estimate for pipelines, figures in rupees in million SN
Description
Shortest route
Optimal route
1 2
Capital cost Operating cost First 5 years Second 5 years Third 5 years Fourth 5 years Net PV (NPV) MARR = 15% (assumed)
63
65
1 each yeara 1.35 each yeara + 2b 1.67 each yeara + 6b 1.8 each yeara + 6b 72.35
0.63 each 0.63 each 0.83 each 0.83 each 69.50
3
yeara yeara yeara + 1c yeara + 1.6c
Figures are in million US$. Source for cost information: Dey and Gupta (2001). a Normal operation and maintenance cost. b Major inspection and maintenance cost in subsequent 5 years that includes additional patrolling, special arrangement for failure, a water logged area, water pollution control and special coating/CP surveillance, intelligent pigging cost including cost for loss of production for not being able to augment the pipeline. c Additional capital cost for augmentation.
project people. This model also considers the life cycle approach while selecting the project.
5. Financial analysis Financial analysis is then carried out with the consideration of a few alternatives design options with respect to pipeline diameters. The least cost option is then selected. This study does not demonstrate the financial analysis of various design options, as this is a standard practice of all pipeline operators.
6. Summary and conclusions Presently, feasibility analysis of the project is taken up in a fragmented framework. Due to strengthening of environmental laws and regulations, IA quite often suggests either quantum changes in project proposal or abandonment of the project on environmental ground. This causes revision of entire project proposal that includes further analysis of alternate sites, usage of alternate technologies and alternate implementation methodologies. This not only increases project feasibility study time considerably but also incurs more cost and energy of the organization. This affects the overall productivity of the project organizations negatively. This article presents an integrated framework in selecting the best project from a few alternatives through traditional feasibility analysis. This study suggests to take up TA along with EIA and SEIA in an integrated framework so as to select the best feasible alternative project among a few alternative possible projects. The
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project selection model has been formed in AHP framework, as project selection factors are subjective as well as objective. Moreover, they are conflicting in nature. The model has the following advantages:
It allows incorporation of interactive input from the executives of related functional areas. This model integrates technical, financial and impacts assessment and provides benefit to both project owner and project-affected people. It helps to make objective decisions by quantifying many subjective factors. Both tangible and intangible elements can be included in the AHP hierarchy. Qualitative judgement and quantitative data can be included in the priority setting process. AHP is an effective tool for conducting group sessions in an analytical and systematic manner. It demands collection of much information that ultimately help during detailed engineering stage. The sensitivity analysis utility of AHP provides the decision-makers a sense of effects of their decisions.
The model suffers from the limitation of not completely removing subjectivity from the decision model. However, this is an improvement over the present practice. Although the application of the model has been explained through a case on laying cross-country petroleum pipeline project, it can be applied universally across various project selection problems. However, considerable research is required in each application. References Annual Report of CONCAWE (Conservation of Clean Air and Water, Europe). Brussels, 1994. Dey PK. Process reengineering for effective implementation of projects. Int J Proj Manage 1999; 17(3):147 – 59. Dey PK. Benchmarking project management practices of Caribbean organizations using analytic hierarchy process. Benchmarking: Int J 2002;9(3). Dey PK, Gupta SS. Decision support system for pipeline route selection. Cost Eng 1999;41(10): 29 – 35 (October). Dey PK, Gupta SS. Analytic hierarchy process boosts risk analysis objectivity. Pipeline Gas Ind J 2000;83(9):69 – 72 (September). Dey PK, Gupta SS. Feasibility analysis of cross-country petroleum pipeline projects: a quantitative approach. Proj Manage J 2001;32(4):50 – 8. Dey PK, Tabucanon MT, Ogunlana SO. Planning for project control through risk analysis: a case of Petroleum Pipeline Laying Project. Int J Proj Manage 1994;12(1):23 – 33. Dey PK, Tabucanon MT, Ogunlana SO. Petroleum pipeline construction planning: a conceptual framework. Int J Proj Manage 1996;14(4):231 – 40. Dey PK, Ogunlana SO, Gupta SS, Tabucanon MT. A risk based maintenance model for cross-country pipelines. Cost Eng 1998;40(4):24 – 31 (April).
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Dyer RF, Forman EH. Group decision support with the analytic hierarchy process. Decis Support Syst 1992;99 – 124. Eyrich HG. Benchmarking to become the best of breed. Manuf Syst 1991 (April). Golden BL, Wasli EA, Harker PT. The analytic hierarchy process: applications and studies. New York: Springer-Verlag; 1989. Islei G, Lockett G, Cox B, Stratford M. A decision support system using judgmental modeling: a case of R&D in the pharmaceutical industry. IEEE Trans Eng Manage 1991;38:202 – 9 (August). Korpela J, Tuominen M. Benchmarking logistic performance with an application of the analytic hierarchy process. IEEE Trans Eng Manage 1996;43(3):323 – 33 (August). Meredith JR, Mantel SJ. Project management, a managerial approach. 4th ed. Singapore: Wiley & Sons, 2000. Mian SA, Christine ND. Decision-making over the project life cycle: an analytical hierarchy approach. Proj Manage J 1999;30(1):40 – 52. Montemurro D, Barnett S. GIS-based process helps Trans Canada select best route for expansion line. Oil Gas J 1998;63 (June 22). Partovi FY, Burton J, Banerjee A. Application analytic hierarchy process in operations management. Int J Oper Prod Manage 1990;10(3):5 – 19. Ramanathan R, Geetha S. Socio-economic impact assessment of industrial projects in India. Impact Assess Proj Apprais 1998;16(1):27 – 32. Saaty TL. The analytic hierarchy process. New York: McGraw-Hill; 1980. Saaty TL. Decision making for leaders. New York: Lifetime Learning; 1982. Saaty TL. Priority setting in complex problems. IEEE Trans Eng Manage 1983;EM-30:140 – 55 (August). US Department of Transportation. Pipeline safety regulation, October 1, 1995. Vargas LG. An overview of the analytic hierarchy process and its applications. Eur J Oper Res 1990;48(1):2 – 8.
An integrated assessment model for cross-country pipelines Prasanta Kumar Dey Department of Management Studies, University of the West Indies, Cave Hill Campus, PO Box 64, Bridgetown, Barbados Received 1 March 2001; received in revised form 1 April 2002; accepted 1 May 2002
Abstract The cross-country petroleum pipelines are environmentally sensitive because they traverse through varied terrain covering crop fields, forests, rivers, populated areas, desert, hills and offshore. Any malfunction of these pipelines may cause devastating effect on the environment. Hence, the pipeline operators plan and design pipelines projects with sufficient consideration of environment and social aspects along with the technological alternatives. Traditionally, in project appraisal, optimum technical alternative is selected using financial analysis. Impact assessments (IA) are then carried out to justify the selection and subsequent statutory approval. However, the IAs often suggest alternative sites and/or alternate technology and implementation methodology, resulting in revision of entire technical and financial analysis. This study addresses the above issues by developing an integrated framework for project feasibility analysis with the application of analytic hierarchy process (AHP), a multiple attribute decision-making technique. The model considers technical analysis (TA), socioeconomic IA (SEIA) and environmental IA (EIA) in an integrated framework to select the best project from a few alternative feasible projects. Subsequent financial analysis then justifies the selection. The entire methodology has been explained here through a case application on cross-country petroleum pipeline project in India. D 2002 Elsevier Science Inc. All rights reserved. Keywords: Feasibility analysis; Analytic hierarchy process; Cross-country petroleum pipeline project; Present value; Integration
E-mail address: [email protected] (P.K. Dey). 0195-9255/02/$ – see front matter D 2002 Elsevier Science Inc. All rights reserved. PII: S 0 1 9 5 - 9 2 5 5 ( 0 2 ) 0 0 0 2 0 - 3
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1. Introduction Projects transform organization’s vision to reality. Moreover, science and technology are manifested by major projects. Many of them are large-scale construction projects. Therefore, projects stand for sustainable development. However, there are many instances of adverse effects of projects on environment. Therefore, impact assessment (IA) is conducted in advance to determine the socioeconomic and environmental consequences of industrial projects on society. IA of large industrial projects assumes special importance because these projects are likely to affect the socioeconomic fabric of a section of people, generally called the project-affected people. Socioeconomic impacts occur at all the four stages— preconstruction (planning/policy development), construction (implementation), operation and maintenance and decommissioning (abandonment)—of industrial projects (Ramanathan and Geetha, 1998). Cross-country petroleum pipeline mode for transportation of bulk petroleum product has already been established as the most energy efficient, safe and environment friendly and economic mode of transporting hydrocarbon (gas, crude oil and finished product) over long distances within the geographical boundary of a country and beyond. A stage has now been reached when a significant part of a nation’s energy requirement is transported through pipelines. The economy of a country is heavily dependent on smooth and uninterrupted operation of these lines (Dey and Gupta, 2000). Therefore, it is becoming increasingly important to ensure safe and failure-free operation of these pipelines. While pipelines are inherently one of the safest mode of transporting bulk energy, with failure rates much less compared to rail/road transportation, failures do occur and sometimes with catastrophic consequences. A number of pipelines have failed in the recent past with tragic consequences, to name a few in 1993 in Venezuela 51 people were burnt to death when a gas pipeline failed and escaping gas got ignited. Again, in 1994, a 36-in. diameter pipeline in New Jersey, USA failed, which resulted death of one person and injuring more than 50 people (US Department of Transportation, 1995). Such failures are also reported from various other countries across the world viz. UK, Russia, Canada, Pakistan and India, etc. More recently, in 1998, pilferage attempt in a product pipeline leads to a major catastrophe leading to death of 500 persons (Annual Report of CONCAWE, 1994). While pipeline failures have rarely caused fatality but disruption of operation leads to large losses in business. Also, such failures can be very costly and leads to considerable damage to environment (Dey et al., 1998). Traditionally, most pipeline operators ensure that during design safety provisions are created to provide a theoretical minimum failure rate for the life of the pipeline. Safety provisions govern selection of pipes and other fittings. To prevent corrosion, high-resistance external coating materials electrically isolate a pipeline. As a secondary protective measure, a low-voltage direct current is impressed in the pipe at precalculated distances to transfer any corrosion that occurs as a result of breaks in the coating from buried iron junk, rails, etc. This is called impresses-current cathodic protection (CP). The
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quality of the commodity being transported through the line is also ensured. Sometimes, corrosion-preventing chemicals (corrosion inhibitors) are mixed with the commodity. Regular patrolling of the right of way (ROW) from the air as well as on foot helps prevent deliberate damage of the pipeline in isolated locations. All third-party activities near the route are monitored. Various techniques are routinely used to monitor the status of a pipeline. Any deterioration in the line may cause a leak or rupture. Modern methodologies can ensure the structural integrity of an operating pipeline without being taken out of service. Hence, to manage pipelines effectively, pipeline operators design their pipeline system in a very reliable way by choosing optimal pipeline route (Dey and Gupta, 1999) and planning pipeline projects efficiently with the consideration of overall profitability of project in long run (Dey et al., 1996). The shortest distance between demand and supply points governs the current practice of feasibility analysis of cross-country petroleum pipeline projects. A few alternative projects are then developed with the consideration of technical parameters such as throughputs, diameter of pipelines and number of intermediate stations. Subsequent financial analysis selects the best project on the basis of minimum cost with respect to capital and operating cost. Environmental IA (EIA) and socioeconomic IA (SEIA) provide clearance from the statutory regulations. The present feasibility analysis never considers maintenance and the augmentation possibility of the pipeline (Dey, 1999). Both these factors are highly dependent on the pipeline route. Cross-country petroleum pipeline route selection is governed by the following goals:
Establish the shortest possible route connecting the originating, intermediate and terminal locations. Ensure, as far as practicable, accessibility during operation and maintenance stages. Preserve the ecological balance and avoid/minimize environmental damage. The route should be kept clear of forests as much as possible. Avoid populated areas for public safety reasons. Keep rail, road, river and canal crossings to the bare minimum. Avoid hilly or rocky terrain. Avoid a route running parallel to high-voltage transmission lines or DC circuits. Use an existing ROW, if possible. Avoid other obstacles such as wells, houses, orchards, lakes or ponds.
These characteristics must be determined by a reconnaissance survey and the goal of finding the shortest possible route is always important. There are many examples of loss of productivity due to wrong pipeline route selection. A specific stretch of pipeline in eastern India (102 km, 12.75 in./324 mm in diameter, 0.25 in./6.35 mm wall thickness, API 5L X-46 pipe grade) was commissioned in September 1977. The pipeline is protected against external
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corrosion by an impressed current cathodic protection system over and above the coal tar enamel external coating. The ROW includes a waterlog of 30-km area that remains under water for 6 –7 months in 1 year, with a water depth varying between 3 and 4 m. In this 30-km stretch, extensive external corrosion has occurred. Between pipeline chainage (distance from a reference point) of 11 – 41 km, two leaks were encountered. At 203 locations, sleeving (reinforcement cladding) has been carried out due to heavy external corrosion. The pipeline operates at a lower throughput than its designed capacity. It is estimated that this pipeline incurs a loss of 120 million rupees/year on average (115 million rupees in lost production due to reduced capacity operation plus 5 million rupees for additional maintenance cost). This is calculated at a rate of US$1 = 48 rupees as of March 2002. The loss of production due to operation at a reduced capacity was determined with the consideration of the following factors. Under the administrative pricing mechanism (APM), pipeline operators in India get a return on investment from pipeline projects at the rate of 12% of present value (PV) of cost (capital + operating) if pipelines run at full capacity. The return diminishes proportionately with the reduction in capacity. If the pipeline had been rerouted during the initial design phase, the capital cost would have increased by 100 million rupees (50 million rupees for additional mainline cost plus 50 million rupees for an additional station). The benefit of an alternative route is clear. Another example of poor route selection is a 40-km stretch of coal belt along the route of a petroleum pipeline in eastern India. This stretch is vulnerable to failure due to third-party activities (coal mining) in the surrounding area. A risk analysis study determined that the probability and severity of a failure here was very high, with an expected cost of 1000 million rupees (Annual Report of CONCAWE, 1994). Rerouting the pipeline during the design stage would have cost 60 million rupees. Avoiding this area would have been cost effective. Petroleum pipelines are designed to carry a specific capacity for a specific life period and rely on a forecast of a supply – demand scenario of petroleum products. It is quite likely that during a pipeline’s life span the capacity of the line may need to be increased to maximize returns commensurate with petroleum product demand. However, if the pipeline route does not provide adequate room for augmentation, this cannot be accomplished. Pipeline route selection should be governed not only by factors like the shortest total distance, approachability and constructability. Factors such as operability, augmentation capability and maintainability also need to be considered. In the recent years, SEIA and EIA have immerged as a study to ensure a project as a profitable venture to its owner and a contributing agent to the society. However, sometimes, they are not taken in their right spirit by the project owner, causing lots of nonconsensus among the PAP. This results serious damage either to the project or to the society. Fig. 1 shows the current project feasibility analysis process of cross-country petroleum pipeline for the project under study. Rapid growth of industries calls for many pipeline projects, which are scrutinized to identify only a few feasible
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Fig. 1. Current project feasibility analysis process of cross-country petroleum pipelines.
projects for further analysis. The market and demand analysis determines throughput of pipelines and supply – demand points. These select the pipeline route through subsequent reconnaissance survey. In the technical analysis (TA), only a few alternate projects with respect to diameters of pipelines and number of intermediate stations are analyzed and the optimum option is selected on the basis of financial evaluation criteria like net PV, internal rate of return, etc. The EIA and SEIA are then carried out on selected project to mitigate the negative impacts of project on environment. The pipeline operators, while carrying out project feasibility analysis following the steps as explained in Fig. 1, encounter the following problems. 1. It takes longer time to complete a project feasibility study, as all the analyses are taken up subsequently. 2. As during IA only one project is analyzed, quite often, project proposal tries to justify the best alternative generated from financial analysis. 3. IA often demands alteration of project site (pipeline route) and usage of different technology. These cause revision of entire technical and financial analysis. 4. Although sometimes projects get statutory approval from the regulatory authorities on the basis of IA reports, there are evidences of project abandonment at the later stage due to public protest.
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5. Sometimes, the selected projects are proven to be not fully effective in operations stage due to enormous operating and maintenance cost and lack of expansion possibility. The above problems can be resolved by modeling the entire feasibility analysis in an integrated framework. Accordingly, the objective of the study is to develop an integrated project selection model that quantifies the merits and demerits of various alternative projects for selecting the optimal option. The entire methodology has been explained through a case application on crosscountry petroleum pipeline project selection.
2. Proposed model and methodology Fig. 2 shows the proposed model for feasibility analysis of a cross-country petroleum pipeline. The TA, EIA and SEIA are carried out simultaneously. These solve site selection (pipeline route) problems along with a few technological considerations. The least cost option is then identified through financial analysis on a few alternative feasible projects. 2.1. An analytic hierarchy process (AHP)-based approach to project appraisal model The AHP developed by Saaty (1980) provides a flexible and easily understood way of analyzing complicated problems. It is a multiple criteria decision-making technique that allows subjective as well as objective factors to be considered in decision-making process. The AHP allows the active participation of decisionmakers in reaching agreement and gives managers a rational basis on which to
Fig. 2. Proposed project selection model of cross-country petroleum pipelines.
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make decisions. AHP is based on the following three principles: decomposition, comparative judgement and synthesis of priorities. The AHP is a theory of measurement for dealing with quantifiable and intangible criteria that have been applied to numerous areas, such as decision theory and conflict resolution (Vargas, 1990). AHP is a problem-solving framework and a systematic procedure for representing the elements of any problem (Saaty, 1983). Formulating the decision problem in the form of a hierarchical structure is the first step of AHP. In a typical hierarchy, the top level reflects the overall objective (focus) of the decision problem. The elements affecting the decision are represented in intermediate levels. The lowest level comprises the decision options. Once a hierarchy is constructed, the decision-maker begins a prioritization procedure to determine the relative importance of the elements in each level of the hierarchy. The elements in each level are compared as pairs with respect to their importance in making the decision under consideration. A verbal scale is used in AHP that enables the decision-maker to incorporate subjectivity, experience and knowledge in an intuitive and natural way. After comparison matrices are created, relative weights are derived for the various elements. The relative weights of the elements of each level with respect to an element in the adjacent upper level are computed as the components of the normalized eigenvector associated with the largest eigenvalue of their comparison matrix. Composite weights are then determined by aggregating the weights through the hierarchy. This is done by following a path from the top of the hierarchy to each alternative at the lowest level and multiplying the weights along each segment of the path. The outcome of this aggregation is a normalized vector of the overall weights of the options. The mathematical basis for determining the weights was established by Saaty (1980). Project appraisal is a team effort, and the AHP is one available method for forming a systematic framework for group interaction and group decisionmaking (Saaty, 1982). Dyer and Forman (1992) describe the advantages of AHP in a group setting as follows: (1) both tangibles and intangibles, individual values and shared values can be included in an AHP-based group decision process, (2) the discussion in a group can be focused on objectives rather than alternatives, (3) the discussion can be structured so that every factor relevant to the discussion is considered in turn and (4) in a structured analysis the discussion continues until all relevant information from each individual member in a group has been considered and a consensus choice of the decision alternative is achieved. A detailed discussion on conducting AHP-based group decision-making sessions including suggestions for assembling the group, constructing the hierarchy, getting the group to agree, inequalities of power, concealed or distorted preferences and implementing the results can be found in Saaty (1982) and Golden et al. (1989). For problems with using AHP in group decision-making, see Islei et al. (1991).
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Researchers use AHP in various industrial applications. Partovi et al. (1990) used it for operations management decision-making. Dey et al. (1994) used it in managing the risk of projects. Eyrich (1991), Korpela and Tuominen (1996) and Dey (2002), for benchmarking various business functions, also have effectively used AHP. Mian and Christine (1999) used AHP for evaluation and selection of a private sector project. Meredith and Mantel (2000) described AHP as an effective tool for project selection. Dey and Gupta (1999) used AHP for cross-country petroleum pipeline route selection. In this research, a simultaneous analysis of technical, environmental and socioeconomic aspects of the project are carried out using AHP. The following are the rationale for using AHP for project selection:
The factors that lead to project selection are both objective and subjective. They are also conflicting in nature—achievement of one factor may result in sacrificing others. There is a need for a subjective approach to project selection that can incorporate objectivity. AHP provides a flexible and easily understood way to analyze each factor that leads to project selection. It allows subjective as well as objective factors to be considered. AHP calls for the active participation of decision-makers in reaching agreement and gives managers a rational basis on which to make decision. For the present study, decision-makers are the executives of the organization (working in project selection task) from various levels having working experience of more than 15 years. They have established the AHP model for project selection through a few brainstorming sessions. The identification of factors and subfactors along with formation of comparative matrix is made in a group decision-making process through common consensus among the executives. However, if disagreements occur, they are resolved by reasoning and collecting more information. The group collects and analyses data and recommends the selection. Their proposal contains all the necessary details that are required to establish the selection. These give an insight to the approving authority to understand the whole processes and basis of selection. A joint meeting (decisionmakers and approving authority) may also be called for further facilitating the process of approval. The sensitivity utility of AHP provides an opportunity for them to understand the implications of their decision. The following methodology has been adopted in selecting optimal project:
Identification of alternative projects (in this case, alternate pipeline route) and formation of database for each route through geographical information system (GIS) (Montemurro and Barnett, 1998). Identification of factors and subfactors that leads to select the optimal project Formation of project selection model in AHP framework through TA, EIA and SEIA
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Analyzing each factor and subfactor by pairwise comparison and analyzing each alternative with respect to each subfactor by pairwise comparison through the available data Synthesizing the result across hierarchy to select the optimal project. Fig. 3 shows the list of the factors for selecting pipeline project as identified by the executives working in the best pipeline project selection task. 2.1.1. Technical factors The technical factors important to selection of pipeline route include length, operability, approachability and constructability.
Fig. 3. Factor and subfactors for project selection.
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2.1.1.1. Pipeline length. Pipeline length governs the capacity requirement of almost all equipment for entire pipeline project, as pipeline head loss is directly proportional to the length of the pipeline. Hence, the shorter the length of a pipeline, the lesser the capital cost of the project and vice versa. 2.1.1.2. Operability. The hydraulic gradient is a major factor in selecting prime mover power for pipeline operations, as negative hydraulic gradient demands for higher prime mover power. Similarly, more route diversion causes more friction loss, resulting in higher prime mover power for the same throughput. These result to more capital investment. A pipeline is designed for specific throughput in line with demand. A pipeline may need to be augmented in the future to cope with the demand for maximizing profit. Therefore, expansion/augmentation capability is one attribute of properly designed pipeline. In addition to improving the existing prime mover capacity, a pipeline can also be augmented by installing more pumping stations along the route and laying loop lines/parallel lines. 2.1.1.3. Maintainability. Though pipelines are designed with adequate safety factors, they are subjected to failure due to various reasons. Pipeline corrosion, pilferage and third-party activities are factors that may create quantum throughput loss along with chances of disaster. Therefore, these factors should be carefully considered during the feasibility study. In a decision model, these factors may influence the selection of a specific route. One of the major causes of pipeline failure is corrosion, an electrochemical process that changes metal back to ore. Corrosion generally takes place when there is a difference of potential between two areas having a path for the flow of current. Due to this flow, one of the areas loses metal. External interference is another leading cause of pipeline failure. It can be malicious (sabotage or pilferage) or be caused by other agencies sharing the same utility corridor. The latter is known as third-party activity. In both cases, a pipeline can be damaged severely. External interference with malicious intent is more common in socioeconomically backward areas, while in regions with more industrial activity third-party damage is common. Poor construction, combined with inadequate inspections and low-quality materials, also contributes to pipeline failure. Other reasons include human and operational error and equipment malfunctions. Computerized control systems considerably reduce the chance of failure from these factors. All activities, industrial or otherwise, are prone to natural calamities, but pipelines are especially vulnerable. A pipeline passes through all types of terrain, including geologically sensitive areas. Earthquakes, landslides, floods and other natural disasters are common reasons for pipeline failures. 2.1.1.4. Approachability. Although a cross-country petroleum pipeline is buried underground, the ROW should allow uninterrupted construction activities as well
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as operation, inspection and maintenance. The ideal pipeline route should be along a railway track or a major highway. This is not always possible due to the long length of pipelines, which may require river crossings and travelling through forests, deserts, etc. Therefore, pipeline route with better approachability gets an edge over other routes. 2.1.1.5. Constructability. Laying pipeline across states/province or national boundaries requires permission from statutory government authorities. Stringent safety and environmental stipulations sometimes are hindrances to project activities. Mobilization is a major construction activity. One factor in pipeline routing is the provision for effective mobilization by the contractor. Distance to market, the availability of power and water and the number of skilled and unskilled laborers are typical requirements for starting effective construction activities. Pipeline construction methods vary greatly with terrain conditions. For example, laying pipeline across a river requires horizontal direction drilling (HDD), while laying across rocky area requires rock trenching techniques. Therefore, location characteristics are a major cost component of pipeline construction. Inappropriate route selection can cause major time and cost overruns.
Fig. 4. AHP model for project selection.
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2.1.2. Environmental factors Pipelines handle hazardous petroleum products. Although pipelines are designed with safety features, failure is not uncommon. Sometimes, failures result in a release of large quantities of petroleum products into the environment. If this should happen, a pipeline located in a remote area is less of a safety concern. The following factors are to be considered to assess environmental impact: Effect Effect Effect Effect Effect
on on on on on
environment environment environment environment environment
during during during during during
failure of pipelines failure of pipeline stations normal pipelines operations normal station operations pipeline construction
The above factors considerably affect the selection pipeline route. 2.1.3. Socioeconomic factors 2.1.3.1. Planning stage. At this stage, pipeline route is finalized. The ROW is required to acquire for construction. This ROW often passes through agricultural land. Acquisition of agricultural land for industrial purposes involves several issues. Some of the important ones are payment of compensation for the land and provision of employment, alternative accommodation and other rehabilitation measures to the PAP.
Table 1 Pipelines database Description a
Throughput (MMTPA ) Length (km) No. of stationsb Terrain detail (km) (a) Normal terrain (b) Slushy terrain (c) Rocky terrain (d) Forest terrain (e) River crossing (f) Populated area (g) Coal belt area Soil conditions Third-party activity Chances of pilferage a b
Route 1
Route 2
Route 3
5 1250 4
5 1360 4
5 1180 4
780 5 – – 3 462
980 5 1 5 4 350 15 Less corrosive soil
1000 45 2 7 5 120 – Corrosive soil for slushy terrain Comparatively less
Less corrosive soil More due to populated area Higher due to populated area
More due to coal belt and populated area Higher due to populated area
Comparatively less
MMTPA = million metric tons/year. Originating pump station/Intermediate pump station/Terminal delivery station.
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Table 2 Scale of relative importance for pairwise comparison Intensity
Definition
Explanation
1 3 5 7 9
Equal importance Moderate importance Essential or strong importance Demonstrated importance Extreme importance
2, 4, 6, 8
Intermediate values
Two activities contribute equally to the object Slightly favors one over another Strongly favors one over another Dominance of the demonstrated in practice Evidence favoring one over another of highest possible order of affirmation When compromise is needed
Source: Saaty (1980).
2.1.3.2. Construction stage. The socioeconomic issues, which need to be addressed during the construction stage of a pipeline project, are mainly the effect of employment generation and a new construction activity leading to an additional burden on local infrastructure facilities. These are only short-term impacts lasting during the construction phase of the project. Effect of employment generation. During the construction phase, the major positive socioeconomic impact will be in the sphere of generation of temporary employment of very substantial numbers. This additional employment generation may lead to an influx of people into the impact area. Effect of construction activity. Construction activity involves movement of heavy vehicles, leading to disruption of other agriculture activities. Pipeline construction sometimes leads to local transport disruption also. 2.1.3.3. Operation stage. The operational stage of the project covers the entire life span of the pipelines. Hence, the impacts of the operational phase
Table 3 Pairwise comparison in factor level Factors
Length
Operability
Maintainability
Approachability
Constructability
Length Operability Maintainability Approachability Constructability
1 1/2 1/2 1/3 1/3
2 1 1 1/3 1/2
2 1 1 1/3 1
4 3 3 1 2
3 2 1 1/2 1
Normalized matrix Factors
Length Operability Maintainability Approachability Constructability Importance
Length Operability Maintainability Approachability Constructability
0.39 0.19 0.19 0.10 0.13
0.41 0.21 0.21 0.07 0.10
0.38 0.19 0.19 0.06 0.19
0.31 0.23 0.23 0.08 0.15
0.40 0.27 0.13 0.07 0.13
0.38 0.22 0.19 0.07 0.14
716
Factors
TA
EIA
Weights
0.38
0.28
Subfactors
Weights LP
GP
Length Operability
0.38 0.22
0.1444 0.0836
Maintainability
0.19
0.0722
Approachability Constructability Failure in pipelines Failure in station Normal operations of station
0.07 0.14 0.43 0.33 0.05
0.0266 0.0532 0.1204 0.0924 0.014
Subfactors
Route characteristics Augmentation possibility Expansion capability Corrosion External interference Construction/ material defect Operational defect Natural hazards
Weights
Normalized
Route 1
Route 2
Route 3
LP
GP
LP
GP
LP
GP
0.28 0.39
0.144 0.023 0.033
0.34 0.33 0.42
0.049 0.008 0.014
0.25 0.29 0.32
0.036 0.007 0.010
0.41 0.38 0.26
0.059 0.009 0.008
0.33 0.3 0.25 0.17
0.028 0.022 0.018 0.012
0.33 0.4 0.35 0.43
0.009 0.009 0.006 0.005
0.42 0.31 0.38 0.38
0.012 0.007 0.007 0.005
0.25 0.29 0.27 0.19
0.007 0.006 0.005 0.002
0.15 0.13
0.011 0.009 0.027 0.053 0.120 0.092 0.014
0.34 0.43 0.35 0.36 0.4 0.39 0.33
0.004 0.004 0.009 0.019 0.048 0.036 0.005
0.33 0.27 0.42 0.4 0.25 0.27 0.34
0.004 0.003 0.011 0.021 0.030 0.025 0.005
0.33 0.3 0.23 0.24 0.35 0.34 0.33
0.004 0.003 0.006 0.013 0.042 0.031 0.005
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Table 4 Project selection date analysis
0.34
0.04
0.0112
0.011
0.33
0.004
0.34
0.004
0.33
0.004
0.15
0.042
0.042
0.42
0.018
0.26
0.011
0.32
0.013
0.43
0.1462
Compensation Employment and rehabilitation
0.7 0.3
0.102 0.044
0.35 0.36
0.036 0.016
0.27 0.23
0.028 0.010 0.000
0.38 0.41
0.039 0.018
Effect during construction
0.36
0.1224
Employment Effect of construction activities
0.5 0.5
0.061 0.061
0.34 0.41
0.021 0.025
0.33 0.24
0.020 0.015 0.000
0.33 0.35
0.020 0.021
Effect during operations
0.21
0.0714
Employment Burden on existing infrastructure Overall weight Ranking
0.2 0.8
0.014 0.057
0.34 0.38
0.005 0.022
0.33 0.27
0.005 0.015
0.33 0.35
0.005 0.020
LP: local percentage, GP: global percentage.
0.370 1
0.289 3
0.341 2
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SEIA
Normal operations of pipelines During construction Effect during planning
717
718
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extend over a long period time. However, pipeline projects seldom generate employment opportunity in this stage and provide fewer burdens to existing infrastructure as the pipelines remain buried under the earth. However, agricultural activities remain restricted on ROW throughout the life span of the pipelines.
3. Project selection model Fig. 4 shows the project selection model in AHP framework. Level 1 is the goal, selecting the best cross-country petroleum pipeline project. Levels 2 and 3 are the factors and subfactors, respectively, which are required to be considered for selection. Level 4 presents the alternative projects—various feasible pipeline routes. Table 1 shows the database for each alternate route. These data along with the experience of pipeline operators were utilized to analyze the AHP model to select the best pipeline project. The data were analyzed by using Expert Choice software package. Firstly, the factors and subfactors are pairwise compared using the ‘‘scale of relative importance’’ as per Table 2 to determine their importance. Table 3 shows a sample pairwise comparison matrix in subfactor level. Secondly, the alternative routes are pairwise compared with respect to each subfactor using the ‘‘scale of relative importance’’ to determine preferences. Thirdly, the results are then synthesize across hierarchy to determine the best selection. Table 4 shows the data related to the outcomes of all matrices and selection.
4. Results and findings The analysis of the data indicates that Route 1 is the best route for laying pipeline for the project under study, although this is not the shortest route. This project outranks the other alternatives with respect to its augmentation and expansion possibilities, maintainability, environment friendliness and less impact on society. Table 5 shows the life cycle cost estimate of the project with Route 3 (the shortest route) and the project with Route 1 (the optimal route). The PV of cost of the project with shortest route is much higher than the optimal project. Therefore, the life cycle costing (LCC) model also fevers for the selection of pipeline project through an integrated approach with the consideration of all factors, which effect the pipeline operations and profitability throughout its life cycle. However, collecting all information for deriving the LCC is time consuming and expensive. Moreover, estimate of LCC is generally based on many assumptions. Alternatively, decision support system (DSS) using AHP provides a good model for project selection that relies on the experience of
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Table 5 Life cycle cost estimate for pipelines, figures in rupees in million SN
Description
Shortest route
Optimal route
1 2
Capital cost Operating cost First 5 years Second 5 years Third 5 years Fourth 5 years Net PV (NPV) MARR = 15% (assumed)
63
65
1 each yeara 1.35 each yeara + 2b 1.67 each yeara + 6b 1.8 each yeara + 6b 72.35
0.63 each 0.63 each 0.83 each 0.83 each 69.50
3
yeara yeara yeara + 1c yeara + 1.6c
Figures are in million US$. Source for cost information: Dey and Gupta (2001). a Normal operation and maintenance cost. b Major inspection and maintenance cost in subsequent 5 years that includes additional patrolling, special arrangement for failure, a water logged area, water pollution control and special coating/CP surveillance, intelligent pigging cost including cost for loss of production for not being able to augment the pipeline. c Additional capital cost for augmentation.
project people. This model also considers the life cycle approach while selecting the project.
5. Financial analysis Financial analysis is then carried out with the consideration of a few alternatives design options with respect to pipeline diameters. The least cost option is then selected. This study does not demonstrate the financial analysis of various design options, as this is a standard practice of all pipeline operators.
6. Summary and conclusions Presently, feasibility analysis of the project is taken up in a fragmented framework. Due to strengthening of environmental laws and regulations, IA quite often suggests either quantum changes in project proposal or abandonment of the project on environmental ground. This causes revision of entire project proposal that includes further analysis of alternate sites, usage of alternate technologies and alternate implementation methodologies. This not only increases project feasibility study time considerably but also incurs more cost and energy of the organization. This affects the overall productivity of the project organizations negatively. This article presents an integrated framework in selecting the best project from a few alternatives through traditional feasibility analysis. This study suggests to take up TA along with EIA and SEIA in an integrated framework so as to select the best feasible alternative project among a few alternative possible projects. The
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project selection model has been formed in AHP framework, as project selection factors are subjective as well as objective. Moreover, they are conflicting in nature. The model has the following advantages:
It allows incorporation of interactive input from the executives of related functional areas. This model integrates technical, financial and impacts assessment and provides benefit to both project owner and project-affected people. It helps to make objective decisions by quantifying many subjective factors. Both tangible and intangible elements can be included in the AHP hierarchy. Qualitative judgement and quantitative data can be included in the priority setting process. AHP is an effective tool for conducting group sessions in an analytical and systematic manner. It demands collection of much information that ultimately help during detailed engineering stage. The sensitivity analysis utility of AHP provides the decision-makers a sense of effects of their decisions.
The model suffers from the limitation of not completely removing subjectivity from the decision model. However, this is an improvement over the present practice. Although the application of the model has been explained through a case on laying cross-country petroleum pipeline project, it can be applied universally across various project selection problems. However, considerable research is required in each application. References Annual Report of CONCAWE (Conservation of Clean Air and Water, Europe). Brussels, 1994. Dey PK. Process reengineering for effective implementation of projects. Int J Proj Manage 1999; 17(3):147 – 59. Dey PK. Benchmarking project management practices of Caribbean organizations using analytic hierarchy process. Benchmarking: Int J 2002;9(3). Dey PK, Gupta SS. Decision support system for pipeline route selection. Cost Eng 1999;41(10): 29 – 35 (October). Dey PK, Gupta SS. Analytic hierarchy process boosts risk analysis objectivity. Pipeline Gas Ind J 2000;83(9):69 – 72 (September). Dey PK, Gupta SS. Feasibility analysis of cross-country petroleum pipeline projects: a quantitative approach. Proj Manage J 2001;32(4):50 – 8. Dey PK, Tabucanon MT, Ogunlana SO. Planning for project control through risk analysis: a case of Petroleum Pipeline Laying Project. Int J Proj Manage 1994;12(1):23 – 33. Dey PK, Tabucanon MT, Ogunlana SO. Petroleum pipeline construction planning: a conceptual framework. Int J Proj Manage 1996;14(4):231 – 40. Dey PK, Ogunlana SO, Gupta SS, Tabucanon MT. A risk based maintenance model for cross-country pipelines. Cost Eng 1998;40(4):24 – 31 (April).
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