National Engineering Conference and Annual General Meeting (Gateway 2006): Technological and National Content Development for Economic Self-Reliance
ABSTRACT
The Nigerian oil and gas industry is, as of today a century old, and inevitably the backbone of the Nigerian economy, accounting for majority of the total foreign exchange revenue. However, a look over the oil and gas pipelines that crisscross the country clearly reveals an image of mismanagement and inappropriate consideration for the local communities. Practices, such as pipeline explosions, vandalism, and saboteurs put the general environment, ecosystem, and public health in great danger.
In limiting chaotic pipeline route location and selection, this paper proposes to find the best pipeline route using multi-criteria decision making process, considering basic constraints like: no pipeline shall pass through a dense populated zone, to find the least expensive route for laying oil pipeline, avoid physical constraints which might influence construction. In addition, environmental constraints will be taken into consideration as relevant authority has identified areas of ecological value, so a route does not touches an ecologically valuable area. The task is thus, to choose a pipeline route that is the least damaging to the environment.
Multicriteria Decision Analysis (MCDA) is integrated with Geographical Information System (GIS). In ArcView 9.1 all data are stored and the criterion values and factor map are generated for all criteria as map layers. The criterion maps are converted into grids and mathematical processes are applied to the criteria using Pairwise Comparison Method (PCM) to calculate the weights. Composite maps are created using Ordered Weighted Averaging (OWA) Method including fuzzy concept on standardization of the criterion values.
INTRODUCTION
Public and private officials have critical decisions to make regarding the management of our national resources at their disposal. Hence, the implementation of any national economic empowerment strategy needs consideration for proper decision making analysis. When a nation succeeds in the economic empowerment of her citizens, someone once made a courageous decision and many nations has perished due to lack of optimum decision-making. Where are Greece, Egypt, Rome and Assyria in world economy today, once mighty and in wealth? The world’s economy is now dominated by the so called third-world nations that are once forgotten and from their silent decision-making strategy have surprise mankind. Nigeria, with her present national economic empowerment strategy in this present and predictable future dispensation is equally positioned to be counted among world economic giants. However, it is all about making the right decision from the multi-criteria factors peculiar to our country.
Figure 1: Pipeline explosions, (Source: BBC News.com)
Nigeria has a network of over 5000Km of oil pipelines with an oil reserve estimated to be over 20 billion barrels and, at the current level of production, Nigeria should be able to produce oil for the next 30 years [1]. To avoid catastrophes, pipelines of this multi-billion dollar business should be selected and designed with satisfactory factors of safety, and selected on the basis of minimum social and environmental impact [2]. However, despite meeting standard regulations, failures have been reported from all over the country. No fewer than 40 residents were injured and many more fainted after an oil pipeline busted in Oke-Odo area of Lagos on Monday 3rd April 2006 [3]. “In July 2000, a pipeline explosion outside the city of Warri caused the death of 250 people. An explosion in Lagos in December 2000 killed at least 60 people. The NNPC reported 800 cases of pipeline vandalisation from January through October 2000. In January 2001, The Nigeria lost about $4 billion in oil revenues in 2000 due to the activities of vandals on our oil installations. Nigeria lost about N7.7 billion in 2002 as a result of vandalisation of pipelines carrying petroleum products. The Nigerian government and oil companies say up to 15 percent of the country’s two million barrels per day oil production is taken illegally taken from pipelines in the Niger Delta and smuggled abroad” [4].
Figure 2: Pipeline exploded killing people. (Source: BBC)
Nationally, there is no other means for now by which Nigeria’s petroleum products are transported more efficiently than pipelines. It is safe, environmentally friendly, and economical. Nigeria’s economic development can be heavily dependent on smooth operation and management of these pipelines. Hence, Oil and Gas related disasters in the country calls for a multicriteria decision consideration in providing a sustainable solution. This paper will show how multi-criteria decision process can be used to locate oil and gas pipeline route as an elements of a sound decision making strategy. The paper will intend for use by decision makers and environmental management personnel on how to analyse different alternative options. This will aid in the selection of a cost effective and environmentally friendly pipeline routes. Moreover, it will provide an overview of the factors that should be considered by the government in evaluating decision making practices in the management of our natural resources.
Multi-Criteria Decision Analysis is an appropriate methodological procedure for solving complex decision problems, and more appropriate where development for local content are envisaged. Malczewski [5] reviewed that over 80% of data on which a decision will be arrived by any decision marker is geographically related. The advantages of this methodological procedure can not be over-emphasised for a nation like Nigeria. Multi-Criteria Decision Analysis (MCDA), is a systematic modus operandi expected to support and assist decision maker(s) to solve numerous and conflicting decision related problem by evaluating limitations, assumptions, circumstances and criteria involve in a process. Lahdelma et al [6] and Beinat [7] states that all of the economical, political, industrial, and financial decisions are multi-criteria in nature and decision making for a given project require complex derivative analysis. Nigeria characterised in some cases by difficult socio-political, economical, and environmental judgements, needs multi-criteria analysis as an effective procedure in understanding precision, suitability and strength of a decision. This will pave way for a cohesive national content development for economic self-reliance.
STUDY AREA
The study area is in the Delta state of Nigeria which was formally created on August 1991. This area lies between longitudes 5000 and 6045 E and latitudes 5000 and 6030 N. 15 to 20 per cent of the entire Niger Delta lies in Delta State. The study area has a total land area of 16,842 km2. Over 70% of the populations live in rural areas. The area under study is very swampy/marshy of riverine nature, containing about 8,000 sq.km of swampy land, and crisscrossed with rivers and creeks. Though it is the major oil producing area, it is still considered the most neglected area of Nigeria [8]. Pipeline routes location in the study area conventionally focus on the economic optimisation with cost minimisation being the sole objective, with disregard for potential adverse environmental, political and social impacts.
Figure 3: Study area: Delta State of Nigeria
METHODOLOGY
Multicriteria Decision Analysis (MCDA) is integrated with Geographical Information System (GIS). Primary survey was implemented using questionnaires to secure the participation of the civil society (community elders, chiefs, NGOs, youth, women association, professionals etc.) for the development of weight to prioritise the criteria. Policy maker’s opinion on pipeline development in their region and identification of preferred criteria for pipeline networks and facility were sourced. In addition, policy makers contacted were required to suggest environment guidelines in the identification of area of environmental sensitivity with respect to land, forests, water, water bodies, and air.
Figure 4: Multi-Criteria Decision-Thinking Process in Route Selection
Limited fieldwork was conducted since the project is based on secondary data. Landsat satellite imagery, land use cover maps, roads, oil field, railways ArcGIS shape files for the project was obtained from Siraj Nigeria Limited. The above sourced dataset of the study area were prepared in a GIS ready format and used as input into the GIS geodatabase. Banai et al. [9] site-suitability problem evaluation using pairwise comparison method was adopted in the analysis for this study. The criteria for the project were assessed for relative importance considering this method. Two major steps were adopted, generating pairwise and computing criterion weights [5].
| Anchor | Distance from cities/towns | Distance from airports | Distance from railway lines | Proximity to refineries | Distance from conservation areas | Dist. from coastal erosion zone | Distance from road | Distance from streams/rivers |
| Distance from cities/towns | 1.0 | 4.0 | 2.0 | 5.0 | 1/3 | 6.0 | 5.0 | 3.0 |
| Distance from airports | 1/4 | 1.0 | 1/3 | 1.0 | 1/4 | 1/2 | 1.0 | 1/2 |
| Distance from railway lines | 1/2 | 3.0 | 1.0 | 1/2 | 1/4 | 1/2 | 1/2 | 1.0 |
| Proximity to refineries | 1/5 | 1.0 | 2.0 | 1.0 | 1.0 | 1/5 | 1.0 | 1/5 |
| Distance from conservation areas | 3.0 | 4.0 | 4.0 | 1.0 | 1.0 | 9.0 | 8.0 | 4.0 |
| Distance from coastal erosion zone | 1/6 | 2.0 | 2.0 | 5.0 | 1/9 | 1.0 | 1/2 | 1/6 |
| Distance from road | 1/5 | 1.0 | 2.0 | 1.0 | 1/8 | 2.0 | 1.0 | 1/4 |
| Distance from streams/rivers | 1/3 | 2.0 | 1.0 | 5.0 | 1/4 | 6.0 | 4.0 | 1.0 |
| Column sum: | 5.65 | 18.00 | 14.33 | 19.50 | 3.32 | 25.20 | 21.00 | 10.12 |
Table 1: Determination of Relative Criterion Weights
In summary, considerations adopted in this research to route the most optimum route are: (1) Distance from urban areas, and (2) distance from ecological and coastal erosion prone areas, (3) distance from airports, (4) distance from reserves and regional recreation lands of the Niger Delta, (5) distance from political and resistive -zones, and (6) distance from railways, (7) distance from road, and (8) proximity to existing exploration and refining companies.
The first seven criteria are to be maximised. That is, the farther the route from each of this criterion the better. The last one is minimisation that requires the pipeline route to be closer to these criteria. Each of the above criterions is represented as a map layer or criterion map (Table-3). Analytical Hierarchy Process (AHP) was applied in choosing optimal weights for the criteria. This enables criteria alternatives to be compared.
In ArcView 9.1 software, all data are stored and the criterion values and factor map are generated for all criteria as map layers. The criterion maps are converted into grids and mathematical processes are applied to the criteria using Pairwise Comparison Method (PCM) to calculate the weights. Composite maps are created using Ordered Weighted Averaging (OWA) Method. A suitability map was thus generated pipeline routes.
The eight most important critical criteria, peculiar to the study area were selected for use in Saaty’s [10] pairwise comparison method.
| Definition and expressions | Intensity of importance |
| Equal importance | 1 |
| Equal to moderate importance | 2 |
| Moderate importance | 3 |
| Moderate to strong | 4 |
| Strong importance | 5 |
| Strong to very strong | 6 |
| Very strong importance | 7 |
| Very strong to extreme | 8 |
| Extreme importance | 9 |
Table 2: Saaty’s Scale for Pairwise Comparison
Overview of Saaty’s approach: Let X = {x1, x2, …., xn} be a set of elements, hence Saaty [10] derive priorities for the elements of X which requires that a number; denoted wij be assigned to each pair of elements (xi, xj); this will represent decision numerically, by given a real number between 1 (inclusive) and 10 (exclusive) to rate the relative preferences for two given criteria (Table 2)
Weights in Saaty’s [10] AHP are normally determined by normalising the eigenvector associated with maximum eigenvalue. A positive reciprocal matrix is denoted in one line, and in one column denoting each element x1, x2, …, xn of X. The table is thus filled by inserting at the intersection of the line of xi with the column of xj the number required for each criterion.
For example, assuming that for all i, j ∈ {1, 2, …, n} xi dominates xj if and only if i < j, the format of the positive reciprocal matrix will be:
Finally, Saaty [10] associate with each element xi a “weight” which is a numerical value that we will denote w (xi) by calculating the maximal eigenvalue of the matrix W and determining the respective normalised eigenvector.
Specific to the study area, political and environmental constraints are of the most utmost consideration in locating oil and gas pipeline. This is assumed hypothetically considering numerous violent and near war situation in the region. The study area has been marred by various protests for political and environmental consideration by the local communities for inclusion in all oil and gas related developments in the region. Political campaigns against pipeline installation and protest against environmental dilapidation have all resulted to restlessness in the region. CONCAWE [11], US Department of Transportation [12], Institute for the Analysis of Global Security [13], Rodrigue, et al. (2005), Oduniyi and Segun. [14], Haruna [15], and Shay [16] reports and confirm similar international occurrences.
Therefore, it was considered that distance from towns/cities is “moderate to strong importance” preferred over distance to airports; hence the comparison results in a value of 4 (Table-1).
| Anchor | Distance from cities/towns | Distance from airports | Distance from railway lines | Proximity to refineries | Distance from conservation areas | Distance from coastal erosion zone | Distance from road |
| Distance from cities/towns | 0.1771 | 0.2222 | 0.1396 | 0.2564 | 0.1003 | 0.2381 | 0.2381 |
| Distance from airports | 0.0443 | 0.0556 | 0.0230 | 0.0513 | 0.0753 | 0.0198 | 0.0476 |
| Distance from railway lines | 0.0885 | 0.1667 | 0.0698 | 0.0256 | 0.0753 | 0.0198 | 0.0238 |
| Proximity to refineries | 0.0354 | 0.0556 | 0.1396 | 0.0513 | 0.3013 | 0.0079 | 0.0476 |
| From conservation areas | 0.5313 | 0.2222 | 0.2791 | 0.0513 | 0.3013 | 0.3571 | 0.3810 |
| From coastal erosion zone | 0.0295 | 0.1111 | 0.1396 | 0.2564 | 0.0334 | 0.0397 | 0.0238 |
| Distance from road | 0.0354 | 0.0556 | 0.1396 | 0.0513 | 0.0377 | 0.0794 | 0.0476 |
| Column Sum | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
Table 3: Normalised matrix for criteria table
Furthermore, knowing that distance from towns/cities is “equal to moderate importance” to distance from railway lines, and then from Table-1 above, this equals a numeric score of 2. Thereafter, assuming that same distance from towns/cities is of “strong importance” compared to proximity to refineries, this equals 5 in the numeric scale. Same scenarios are recorded for all the criteria (Table-1). Remaining entries are computed and entered correspondingly.
Figure 5: Weight comparison chart, showing scale of priority
Using Malczewiski’s [5] concept, this step involves, (a) summing values in each column of the matrix; (b) divide each element in the matrix by its column total; and (c) calculating the average of all elements in each row of “ (b)” above, and dividing the sum scores for each row by 9- the numbers of criteria (Table-1 and Table-3).
APPLICATION RESULTS
The dataset used in the analysis were based on current practices, occurrences, prevalent pipeline incidence and literature judgment of the study area. All the dataset layers were included in the multi-criteria analysis; the procedures described earlier were processed as described. Fig 6-1 to Fig 6- 8 illustrates standardised factor maps for all criteria. Generally, the green areas correspond to high values for suitable areas for pipeline routes, whereas the red areas represent lower values for areas, which are not suitable for pipeline routes. Pairwise comparison method was used for weighting the various layers, which was consider the most critical part in decision support models.
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| Fig 6- 1: Airport factor |
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| Fig 6- 2: Railway factor |
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| Fig 6- 3: Reserved area factor |
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| Fig 6- 4: Roads factor |
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| Fig 6- 5: Political factor |
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| Fig 6- 6: Refinery factor |
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| Fig 6- 7: River factor |
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| Fig 6- 8: Town/villages/ cities factor |
The resulting standardised map factor reveals the ability of the MCDA system to cope with poor data, and allow integration of human judgment into the process of weight determination. This study uses the AHP process to assist in the priority setting process for the criteria. This is evident as there is natural limitation to human’s comprehensions and remembrance of large numbers of things at a time.
Figure 7: Final suitability map for pipeline routes
CONCLUSION
This paper is a first step towards the utilisation of multi-criteria decision analysis (MCDA) in studying and planning for oil and gas pipelines routes in Nigeria. It addresses all MCDA components and made full use of the limited available data. The main barriers that faced the study are the scarcity of information from government bodies and the unwillingness of decision makers to divulge available information at their disposal. With this paper, the floor is open for further research that should be directed at collection of information for database build-up; and the development of additional modelling tools that addresses the remaining parts of MCDA in the Nigerian content.
Prior to embarking on any oil and gas pipeline project, activity, and development in Nigeria, it should be mandatory that proponents and contractors carry out a study using the concept of multi-criteria decision analysis. This will ascertain a more comprehensive impact, and the extent of these impacts on the physical, biological, human, and socio-economic environment. Throughout all stages of the project from its planning phase to operational and decommissioning phases, proponents should be made to ensure that all identified adverse impacts are addressed in different stages of the project. One of the most important aspects of the above process should be consultation with the communities, stakeholders and the regulatory agencies in quantifying a decision.
Dresnack et al., (2000) compare and contrast the United States Pipeline Safety Regulations, that of Canada, Australia, Germany, Japan, and the United Kingdom as they relate specifically to the land use and sitting of pipelines in close proximity to urban and environmentally sensitive areas. The report concludes that all the regulations reviewed are similar in fashion as regards sitting of petroleum pipelines. However, local content development for economic self-reliance in Nigeria needs no comparison or adaptation of any international policies, but rather exploitation of these technologies to make superior decision in our designs.
REFERENCES
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