Bass Strait Oil Company - Managing an Oil Spill - Case Study Example

Decision making: managing an oil spill (Name) (Institution) (Course) (Instructor’s Name) Date of submission Introduction Oil spills either on oil rigs or during transportation, loading or offloading are common accidental occurrences in modern times. As accidents, these occurrences call for urgent responses with better and faster decision making processes than ordinary decision making scenarios (Castaneda et al 2005: Liu & Writz, 2007). This is because the emergency response is aimed at mitigating the effects of the spill hence timing and efficiency in this case is paramount. Other decision making situations may allow enough time for deliberation, mobilising resources and strategising. However, in this case of a hypothetical oil spill in one of the 1000m deep offshore rigs operated by Bass Strait Oil Company in the Gippsland Basin, there is no time for deliberation and it is important to make an informed decision that is effective and minimises cost, utilizes least resources and minimises the damage to the environment and impact on other stakeholders. Therefore, the main considerations here are maximising the amount of oil cleaned to minimise environmental impact and minimise the investments in on equipment and facilities to be used in the process. Given that the oil spills are common occurrences, it is necessary that organizations in the oil drilling industry to have contingency plans when such emergences occur. Nonetheless, it is impossible to design near optimal contingency plans because there are many underlying contextual factors such as weather and climatic conditions, extent of spill among others (Castanedo et al 2005 Krohling & Rigo 2009). Castanedo et al (2005) adds that a contingency plan should basically consist of damage assessment, operational forecasting and restoration systems. Again, the number and nature of stakeholders vary in each case which affects the decision making process given that their interest, which often are in conflict with oil drilling companies, have to be considered. To assist managers in responding to emergency situations, there are a number of decision making theories for such situations proposed by a number of authors. This paper therefore is a response to a hypothetical oceanic oil spill detailing the decision maiming process. The paper uses several books and journal articles to support the hypothetical response to the oil spill, applying relevant management and decision making principles. Literature review The fuzzy decision making method is one of a number of theories suggested by management experts that is best suited in decision making situations where constraints and goals are fuzzy (Nicholson 2009; Krohling & Rigo 2009). Information in such uncertain situations is derived from past experiences. In this case, the goals are also not clearly defined because the main idea in cleaning oil spills is to try as much as possible to revert the situation as it were before the oil spill which more often than not is not clearly defined as well (Nicholson 2009: Liu & Writz, 2007). In order to understand the situation, it is important to involved all the stakeholders in the decision making process which is a simpler way of gaining information that could otherwise be collected through a research study but there is a time constraint. This oil spill carries with it minimum statistical information to assist the decision making process and hence the next best option is to use descriptive of linguistic data. As aforementioned, involvement of stakeholders will be critical in gathering all necessary linguistic data. On the other hand, statistical data available may include the type of oil, the depth of the leak and speed of water currents, speed of the winds available equipments and workforce. Therefore, it is enough to evaluate the impact and efficiency of alternative strategies through a fuzzy set using only descriptive data. This implies that the composition of the sources of descriptive data which happens to be the stakeholders. This is similar to the brainstorming option in decision making model where the creativity and number of parties in a brainstorming team limit the number of alternatives available (Krohling & Rigo 2009). The consequence analysis model suggested by Seip and Wenstop (2006) has also been confirmed to work well in managing oil spill. This model is also based on comparing available alternatives by assessing their impacts on the environment and stakeholders. This theory argues that decision makers have to prepare a criterion and then assess the available alternatives through the consequence analysis. Linkov, Wenning and Kiker (2007) suggest that the multi-criteria decision analysis (MCDA) is best suited for handling oil spills and emergency situations where various alternatives are involved. They argue that in emergency situations, the decision to act or whether not to depend on the perceived consequences of each alternative. They argue that the cost of action sometimes may supersede the cost of inaction. Alternatively, the choice of action gives out different outcomes and costs hence the need to develop multi-criteria. Multi –criteria decision analysis involves using a group of methods to impart structure to the decision making process that basically involves four steps namely: 1. Creating a set of criteria relevant to oil spills in order to vet alternatives 2. weighted assessment of the criteria 3. Scoring how well each alternative performs on each criterion 4. Combining scores across criteria to produce an aggregate score for each alternative The MCDA holds a few advantages over other theories. First and foremost, it facilitates a structured examination of objectives and alternatives raised by stakeholders, allows differentiated weighting of the objectives and alternatives by the different groups, provides room for stakeholder value elicitation and non-expert knowledge and accommodates diversified sources and types of information both qualitative and semi qualitative (Linkov, Wenning and Kiker 2007). Kounchev (2007) however criticises this model and says that it does not objectively consider the opinions of all stakeholders but rather generalises a number of stakeholders and groups them for convenience. He thus says that making decisions using this model may overlook some consequences for the chosen path of action. These two theories are relevant in handling the oil spill and this response uses the suggestion of both theories. In both theories, there is need to recognise the role played by stakeholders in informing the decision makers but not necessarily in making decisions. Linkov, Wenning and Kiker (2007) note that government regulations in Australia require stakeholder involvement in the whole process which they observe is very tedious and may prolong the response time and contribute to the worsening of the situation. In that accord, Bass Strait Oil Company will formulate an overseeing committee consisting of the oil spill management team and a number of stakeholders. Krohling and Rigo (2009) notes that majority of stakeholders in oil spills have no expertise regarding the oil spill but its necessary to include them to obtain perspectives that maybe overlooked by the oil spill management team. Formation of a team/overseeing committee This team shall be composed of experts in from the Bass Strait Oil Company, environmental organizations, stakeholders, government representatives and experts in managing oil spills. All these people will provide different approaches to the problem. In this case, the overseeing committee will consist of: fishermen, tourist hotel operators, non-government organizations, government representatives, special interest groups, meteorological experts, oil spill experts, company executives, marine life experts, geologists, financial analysts among other interested parties. The committee shall hold a brainstorming session with the main issues brought forward being short-listed for consideration and to guide the actual decision making process (Krohling and Rigo 2009; Linkov, Wenning and Kiker 2007). The committee shall be responsible for suggesting action alternatives for further evaluations. These alternatives will be evaluated further by the same committees and the most viable options short-listed. As earlier said, the composition of this committee in terms of the expertise of the members and their creativity determines the number of alternatives suggested. The short-listed alternatives are synonymous with possible decisions though their considerations with be greatly determined by their weighted impact and efficiency (Linkov, Wenning and Kiker 2007). Nonetheless, the main emphasis here is reducing the environmental impact because all other considerations in the oil spill are subservient to the environment. Competing Alternatives The fuzzy decision making method requires that all the short-listed strategies in the first stage from the stakeholders meeting be short-listed and their weighted effectiveness assessed. This process is to be carried out by the oil spill management team that comprises of fewer members and professionals only. A simple criterion that captures the basic element of minimising the amount of oil on the environment to guide the decision making process is best suited in this case as it saves time. The criterion used here measures the amount of spilt oil collected, the amount of oil dispersed and the amount of oil washed up to the shoreline in cubic meters. Table 1. strategy alternatives and criteria Alternatives Oil at the shoreline (OS) in ‘000 m3 Oil collected (OC) in ‘000 m3 Oil dispersed (OD) in ‘000 m3 Alt. 1 2.781 0.878 1.887 Alt. 2 4.786 1.912 1.282 Alt.3 3.464 0.897 3.778 Alt.4 2.667 1.221 2.566 Alt.5 1.998 0.234 5.898 Alt.6 6.908 0.432 0.675 Alt.7 4.099 2.990 1.897 The alternative matrix presented above is based on simulations obtained from the first stage. The first stage consists of performance matrix obtained through simulations of the alternative strategies that contain the fuzzy uncertainties suggested in the first session (overseeing committee). In the second stage the oil spill management team in form their preferences in linguistic terms which are then defuzzified and integrated into the model in numerical terms. After this, fuzzy sets shall be chosen to describe the level of impact for the criterion oil at the shoreline (OS); very low (VL), low (L), medium, (M) high (H) and very high (VH) and likewise for oil collected (OC) and oil dispersed (OD). Therefore the number for fuzzy sets for the OS criterion is µi is {VLi, Li, Mi, Hi, VHi}. Then membership functions for each fuzzy set for the criterion i are chosen so that the numerical values of the performance matrix are fuzzified. Different membership functions may be used. Let xi n assign the value of the performance for the alternative n in terms of the criterion i, then xij n indicate the membership degree regarding the j-th fuzzy set of the i-th criterion. The next step involves quantifying the environmental damage in terms of the alternative strategy. This can be expressed from zero (no impact) to one (maximum possible impact) equally spaced represented by a vector [δ1, δ2, δ3, ……..δi1,] = [0, 0.1,……….. 0.9,1.0] (Krohling & Rigo 2009) Table 2. The damage level fuzzyfication Fuzzy sets Damage levels VL 1 0.8 0.6 0.4 0 0 0 0 0 0 L 0.1 0.80 1 0.8 0.6 0.4 0 0 0 0 M 0 0 0.4 0.6 0.8 1 0.8 0.4 0 0.6 H 0 0 0 0 0 0.4 0.6 1 0.8 1 VH 0 0 0 0 0 0 0.4 0.6 0.8 1 The fuzzy degree of the 1st order represents lexical degrees associated with he environmental damages (vector). Table 2 could be representative of OC criterion. Nevertheless, representing specialist knowledge of the problem, the coefficients of empirical nature can be customized in a way to suit their application in the problem. This manner of decision making involves a lot of work though it is best suited for handling uncertain circumstances (Krohling & Rigo 2009). This fuzzy decision making method is prone to number of mistakes as it involves long and tedious mathematical processes. However, Nicholson (2009) notes that in cases where there are numerous uncertainties such as weather conditions, this decision making model serves managers well in making informed decisions. On the other hand, the model requires meticulous care and attention. Again, its emphasis on the inclusion of many stakeholders in the initial process to give rise to numerous strategic alternatives consumes a lot of time that in such a situation is not available. From a historical context, there are limitations to the number and type of stakeholders to be involved in oil spill management. Fleming (2010) says that in the US, the limit-of-liability clause implies that the claim of compensation or inclusion in the decision making process in case of an oil spill gives the involved parties the right to exclude non affected parties in the decision making process. While Australia has no such clause, it is within ethical parameters to exclude parties in the initial decision making process in order to hasten the process. Conclusions To avoid the tedious calculations involved in the fuzzy decision making method, Nicholson suggest combining fuzzy decision making method with the MCDA approach, she says MCDA uses incident specific approaches that are meant to handle the uncertainties that arise after the initial strategy has been adopted. This is important given the fact that the fuzzy decision making model deals with uncertainties prior to making a definite strategy. On the other hand, the MCDA approach is dynamic as it tends to respond to problems as they arise. This implies that while fuzzy decision making method handles uncertainties in the whole oil spill management process, the MCDA tends to handle uncertainties that come up in the day to day operations of the oil spill cleaning process. Managing this soil spill in the offshore rig in Gippsland Basin will require a fuzzy decision approach. The depth of the oil leak creates some weather conditions that have not been experience before. Therefore, given that that there s no much experience in handling such deep sea leaks, the oil spill management team will relay on making hypothetical consequences of the actions given the situation. The contingency plan thus adopts the fuzzy decision making process while the MCDA model will be adopted in managing problems arising in the day to day affairs of the whole process. References Castanedo, S et al 2005. “The Prestige Oil Spill in Cantabria (Bay of Biscay). Part I: Operational Forecasting System for Quick Response, Risk Assessment, and Protection of Natural Resources.” Journal of Coastal Research, 22,(0), 272-287 Fleming, S. 2010. Oil Spills: Cost of Major Spills May Impact Viability of Oil Spill Liability Trust Fund: Congressional Testimony. New York: DIANE Publishing Kounchev, O. 2007. Scientific Support for the Decision Making in the Security Sector. London: IOS Press Krohling & D. Rigo 2009. “Fuzzy group decision making for managements of soil spill responses” in Mehnen, J, M Koppen & A Tiwari (Eds) Applications of Soft Computing: From Theory to Praxis. Sydney: Springer Linkov, I, R Wenning & G Kiker 2007. Managing critical infrastructure risks: decision tools and applications for port security: Sydney: Springer Liu, X & Writz, K. 2007. “Decision making of oil spill contingency options with fuzzy comprehensive evaluation” Water resource management, 21(4) 663-676 Nicholson, A. 2009. AI 2009: Advances in Artificial Intelligence: 22nd Australasian Joint Conference, Melbourne, Australia, December 1-4, 2009, Proceedings. Sydney: Springer Seip, K & F Wenstop. 2006. A primer on environmental decision-making: an integrative quantitative approach. Sydney: Springer Read More