Yang, Ming (2011) Risk and pollution prevention focused environmental management system (RP2EMS): a case of offshore oil and gas operations. Doctoral (PhD) thesis, Memorial University of Newfoundland.
- Accepted Version
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Global offshore oil and gas (OOG) production is rapidly expanding to meet increasing energy demands. Since the offshore environment is sensitive, attention is increasingly devoted to environmental issues associated with OOG operations. An Environmental Management System (EMS) can be utilized to systematically manage all activities in OOG operations that give rise to environmental impacts. However, there is limited literature related to EMSs for OOG operations. This requires academics to examine common EMS frameworks and propose an EMS exclusively for OOG operations. This research was carried out to fill this gap. -- common EMS frameworks have the following limitations: (1) they are not very effective to convey and interpret sufficient information for decision-making; (2) there is no specified performance evaluation system to drive improvement; and (3) there is a burden of extensive documentation. Therefore, it is necessary to revise conventional EMS frameworks to overcome these limitations. The main aim of this study is to integrate Risk-Informed Decision-Making (RIDM) and Pollution Prevention (P2) paradigms within EMS, called Risk and Pollution Prevention focused Environmental Management System (RP2EMS). This framework also addresses the limitations of common EMS frameworks. Moreover, quantitative tools are developed to implement the proposed framework. The specific objectives of this research are: (1) development of an EMS framework; (2) development of a methodology to prioritize environmental issues; (3) development of a methodology for informed environmental decision-making; (4) development of a methodology for environmental performance evaluation; and (5) demonstration of developed methodologies through illustrative examples related to OOG operations. -- As a preferred approach for environmental protection, P2 is integrated into the conventional EMS framework. The risk informed decision-making is coupled with P2 in this framework. This integration can reduce the effort and costs that are needed to develop waste management systems. As the first step, pollution prevention and control options are identified for important environmental issues. For each option, a risk assessment is carried out. Based on the calculated risks and related attributes, the better options are selected using a suitable decision-making method. Implementation of the selected options requires the proper assignment of responsibility and good communication during operations. The framework provides guidance and a procedure for the execution of environmental management emphasizing P2. -- Identification and prioritization of the important environmental issues which are susceptible to causing significant negative impacts are necessary under the constraint of limited resources. This study proposes a hybrid approach using the fuzzy inference system (FIS) and fuzzy AHP for the prioritization of environmental issues in OOG operations. In this approach, a five-level hierarchy is developed. The highest level of the hierarchy corresponds to the goal - prioritization of the significance of environmental issues, and the lowest level corresponds to environmental issues, whereas intermediate levels correspond to major concerns (environmental risks) and sub-parameters of risk. The FIS is applied at the lower levels of the hierarchy to infer the major risk parameters. Subsequently, the scores representing the extent of risk are calculated. Fuzzy AHP is used at the higher levels to synthesize the Significance Scores that will help to prioritize environmental issues. -- To deal with the significant environmental issues, pollution prevention and other sustainable waste management options are investigated. The best options are selected using multi-criteria decision-making. This research proposes a game theoretical approach to solve multi-criteria conflict resolution problem under constrained and uncertain environments. Uncertainties in the quantification of imprecise data are expressed using rough numbers. A multi-criteria game is developed to model a decision problem in which three groups of decision-makers (i.e., operators, regulators and service engineers) are involved. There are three major categories of criteria: (1) costs, (2) environmental risks, and (3) technical feasibility. This game is solved using the generalized maximin solution concept. With the solution (i.e., optimal weights of the criteria), the rough numbers can be aggregated to an expected payoff for each alternative. Finally, the weights of the upper and lower limits of a rough number are employed to transform the expected payoff into a crisp score, based on which all alternatives are ranked to identify the best solution. -- Environmental performance evaluation (EPE) is an essential part of EMS. A method is developed to identify and define specific environmental performance indicators on a case-by-base basis, which consists of five steps: (1) describing environmental requirements; (2) determining favorable outcomes corresponding to the requirements; (3) identifying required activities of issues to achieve the outcomes; (4) searching for proper measures of the activities or issues; and (5) generating a list of key indicators. Based on these steps, a quality function deployment (QFD) approach is developed to determine key indicators and evaluate environmental performance. To handle uncertainties in QFD, the decision makers’ evaluations are quantified using rough numbers. The output of the proposed approach is environmental performance indices. Using these indices, decision makers can determine whether an improved performance has been achieved through an EMS. -- This research provides an innovative EMS framework that integrates paradigms of P2 and risk-informed decision-making to systematically manage environmental issues in OOG operations. All the proposed approaches were validated through numerical examples.
|Item Type:||Thesis (Doctoral (PhD))|
|Additional Information:||Includes bibliographical references (leaves 189-209).|
|Department(s):||Engineering and Applied Science, Faculty of|
|Library of Congress Subject Heading:||Offshore gas industry--Environmental aspects--Computer programs; Offshore gas industry--Risk management--Computer programs; Offshore oil industry--Environmental aspects--Computer programs; Offshore oil industry--Risk management--Computer programs; Wat|
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