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      Development and Application of Oil-Spill Risk Assessment Model for Offshore Pipeline

      2014-05-06 06:56:58LUYanWANGJiaWEIWenpuYANGYongandANWei
      Journal of Ocean University of China 2014年3期

      LU Yan, WANG Jia WEI Wenpu, YANG Yong and AN Wei

      1) China Offshore Environment Services Co. Ltd., Tianjin 300425, P. R. China

      2) College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, P. R. China

      3) China National Offshore Oil Co., Beijing 100010, P. R. China

      Development and Application of Oil-Spill Risk Assessment Model for Offshore Pipeline

      LU Yan1),2),*, WANG Jia2), WEI Wenpu3), YANG Yong1), and AN Wei1)

      1) China Offshore Environment Services Co. Ltd., Tianjin 300425, P. R. China

      2) College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, P. R. China

      3) China National Offshore Oil Co., Beijing 100010, P. R. China

      To the potential oil-spill risk caused by offshore pipeline more attention has been paid after the Dalian oil spill incident from oil-pipeline explosion. Since then an issue about how to prevent and control the sudden oil-spill from the offshore pipeline has been raised. In this paper, we proposed an optimized model to analyze the main causes (probability) of spill and the consequence with the fuzzy comprehensive assessment model. Considering the complicated assessment process for oil-spill, the assessment factor system involving the spill probability and consequence was established based on the operative manual and statistic leakage/damage data of offshore pipeline in order to estimate the integrated spill risk score automatically. The evaluated factors of spill probability could be grouped into five aspects: corrosion, fatigue, national damage, third party, and operational fault; the consequence evaluated factors of spill included hazard of oil and impact-controlling capability. With some modifications based on experts’ opinions, each of the evaluated factors in our work was developed with a relative weight and evaluation criterion. A test example for an offshore pipeline in the Bohai waters was described to show how the model can be used for an actual case in more detail. By using the oil-spill risk assessment model, it is easy to determine the risk level associated with the ongoing activity and management level and hence to take the risk mitigation action immediately.

      oil spill risk assessment; spill probability; spill consequence; fuzzy comprehensive assessment model; offshore pipeline

      1 Introduction

      An increasing concern for oil spill pollution of offshore petroleum industries has been raised over the past five years in China in view of the serious and long-term hazard of spilled oil to the marine ecosystem, economy as well as human health. It is well known that the Dalian oil spill incident caused by oil-pipeline explosion in July 2010 released hundreds of tons of oil, which flowed into the nearby harbor and the Yellow Sea; the oil slick spread at least 430 square kilometers. After the incident, greater demands for fulfilling the environmental responsibility and enforcing stricter environmental requirements from the public had led to an issue about how to prevent and control the sudden oil-spill from the specific petroleum facilities. As an important transportation means for offshore petroleum, the pipeline is one of the major risk sources of oil spill incidents. At present, more than 4000-kilometer-long offshore oil pipelines have been in service in China, meanwhile, a number of pipelines have come into the aging period. Thus, the potential spill risk from offshore pipeline is currently obvious in China.

      Risk assessment of oil spill should estimate both how much oil is likely to spill over the life of such petroleum industries, and what is the likelihood that major spills will occur; therefore, risk evaluation should involve analyzing spill probability and the consequence (Stewart and Leschine, 1986; Woolgar, 2008; French McCay, 2009). For the consequence assessment of spilling oil, our previous work had analyzed the spilling volume, property of oil, and spilling location combined with the capability of oil spill contingency (Luet al., 2012). The probability assessment of spill has been developed during the last two decades. The qualitative and quantitative methods, such as fault tree analysis, matter-element theory and fuzzy comprehensive assessment, were successfully used in order to evaluate and calculate the risk probability of spill. Based on the report from MMS (Minerals Management Service), the occurrence rate of oil spill is estimated by adopting the oil spill historical data of outer continental shelf marine transport oil tankers in USA during 1985-1999, and the occurrence rate of oil spill expressed in occurrences of oil spill incidents which may be caused by transporting one barrel of oil (Kruuse-Meyeret al., 2011). Moreover, the Oil Spill Risk Database was established by DNV according to the statistical data of oil spill incidents and experience in the North Sea and Gulf of Mexico,which were collected during 1975-1990 (DNV, 2011). The modeling method developed by DNV is mainly the plotting of fitting curves with historical accident data, the horizontal and vertical coordinates respectively referring to volume spilled and accident probability. This model is currently widely used in oil spill risk assessment. SINTEF (2009) updated the database of blowout and well release with the data collected from 524 spill incidents mostly occurring in Gulf of Mexico, the outer continental shelf of USA, Norway and the North Sea of England since the 1950s. However, most of previous studies about spill probability focused more on the transport tanker and blowout than on oil-pipeline (French McCay, 2003a, b; Shaoet al., 2009), considering a lot of incidents of larger volume of spillage historically associated with the former (Brandtet al., 2010; Brudeet al., 2008). So far, there is limited research referring to the spill probability of offshore pipeline. Based on the statistical result from the updated database of DNV (2011), the spill caused by offshore pipeline is the second common source, which accounts for 28.4% of the total spill frequency around the world. Considering the wide-range location and the relative high spill frequency of offshore pipeline, it is necessary to establish a risk assessment system of oil spill for offshore pipeline in order to promptly identify the risk prior to the spill incident.

      In view of the above situation, this paper describes a developed methodology to evaluate probability ranking incorporated in the total risk scores in detail. The probability assessment was developed for actual pipeline risk in a practical manner, based on historical data and practical experience. A test example for an offshore pipeline in the Bohai waters is described to show how the model can be used for an actual case in more detail.

      2 Model Development

      2.1 Assessment Procedure

      Risk assessments of pipeline are traditionally based on the historical data for the purpose of safety cases. Even though there have been few studies focusing on the spill risk, the assessment procedure and major elements should be recommended as described in Fig.1; the model of oil spill risk assessment could be used to automatically estimate the spilling probability and pollution impact with the selected elements referring to pipeline characteristics, operator, management, environment, transmission medium,etc. The fuzzy comprehensive assessment model is used as a decision support system to evaluate the spill possibility and consequence scores.

      Fig.1 A multi-step approach to assess the oil spill risk for offshore pipeline, including oil spill probability and pollution consequence assessment.

      2.2 Fuzzy Comprehensive Assessment

      The first step of fuzzy comprehensive assessment should establish the assessment factors index as

      where,uidenotes the set of assessment factor,nis the number of assessment factors. Performance matrix should be set up, which is referred to asV:

      In this paper, five lexically fuzzy grades (m=5) are assigned to each criterion: very low (VL), low (L), moderate (M), high (H), very high (VH). To assist a decision maker to identify the risk degree, the scored risk level ranging from 10 to 100 is predefined, which imposes anumeric measure on the performance as follows:

      Values in the performance matrix are linked to the risk ranking by using a fuzzy membership function which is composed of a single-factor fuzzy evaluation subsetRij=(ri1, ri2,··ri5),rbeing the fuzzy membership matrixRis:

      Combining the predefined first order fuzzy membership matrix (R) and the weight vector (A), the consult of initial evaluation for criterionican be calculated through the following equation:

      The final result is determined by the weighted average method, based on the fuzzy comprehensive evaluation indexbjin this paper.

      where,bj=the value obtained by fuzzy comprehensive evaluation;vj=corresponding evaluation criterion value in performance matrix.

      3 Probability Assessment

      3.1 Assessment Factor System of Spill Probability

      European environmental and safety group CONCAWE (2009) released a public report related to pipeline spillage data from 1971 to 2009, which showed the spillage causes grouped into five main categories: mechanical failure, operational, corrosion, natural hazard and third party. The corrosion and third party damage could be responsible for 65% of the spill incidents on the basis of the investigated data. According to another report from API (2002), which analyzed the oil spill incidents of offshore pipeline from US outer Continental Shelf since 1967, it is demonstrated that corrosion and construction defects were the major cause of spills, accounting for 47% of all the spills. The third party damage was also identified as an important cause for pipeline spills; eighteen percent of the spills were caused by third party damage. There are few offshore pipeline spills databases commercially available in China, while according to the statistic data, almost 80% of offshore pipeline spills are caused by corrosion and third party damage in the recent ten years. When quantitatively evaluating the oil spill risk of offshore pipeline, pipeline corrosion and third party are the most common factors to set focus on adjustment of the generic oil spill frequency. Based on the operation manual and historical spillage data, an assessment factor system of oil spill for offshore pipeline is established as showed in Fig.2.

      Fig.2 Oil-spill probability assessment system for offshore pipeline (W means the weight of each assessment factor).

      In this paper, we propose a third-order fuzzy comprehensive evaluation method to identify the main spill causes for complex spill cases. The first-layer factors are divided into five groups: corrosion (U1), fatigue (U2), natural hazard (U3), third party (U4) and operational fault (U5). Then the elements of the second and third layer are allocated into each corresponding scenario based on the fault tree analysis. The weight of each factor is predefined referring to Pipeline Risk Management Manual (Muhlbauer, 1996) and modified with some experts’ opinions. The relative weights presented in this paper could be adjusted in accordance with specific conditions.

      3.2 Membership Degree Matrix of Evaluation Factors

      The grading standards of each factors are defined based on the Operational Manual and historical statistic data (Bai and Bai, 2005; DNV, 2000, 2004). In order to calculate the probability score of oil spill for each risk element, the membership matrix for each factor in the bottom layer of oil-spill probability risk assessment system shall be determined. In this paper, we take the membership matrixes of corrosion inspection (U13) and pipe wall (U22) for instances (the others were listed in support information A) to illustrate how to grade and quantify the probability risk. To evaluate the impact of corrosion inspection on oil spill probability, the detection period and failure rate are the most important elements. The criteria of corrosion inspection and the corresponding membership matrix are described in Table 1.

      The factor of pipe wall in this paper means the wall thickness ratio actually required. The ranking criterion ofwall thickness for offshore pipeline is defined in accordance with Pipeline Risk Management Manual, and the corresponding degree of membership is set up based on the questionnaire survey collected from offshore operators and engineering experts (n >15, shown in Table 2).

      Table 1 Membership matrix of corrosion inspection for offshore pipeline

      Table 2 Membership matrix of wall thickness ratio actually required for offshore pipeline

      3.3 Adjustment Index

      In practical work, the final risk scores should take the historical leak/damage records into account. If the spill probability of the first-layer elements ranked as H or VH, to the final probability scores 20% of the original scores should be added. The adjusting criteria and detailed descriptions are shown in Table 3.

      Table 3 Adjusting criteria of oil spill probability for offshore pipeline

      4 Consequence Assessment and Total Risk Scores

      4.1 Consequence Assessment

      The detailed work related to spill consequence assessment has been reported earlier (Luet al., 2012). In short, the consequence assessment system for offshore oil spill shall contain two elements: hazard (U1) of oil and impact controlling capability (U2) with their weights of 0.30 and 0.70 respectively. The consequence assessment system of offshore oil spill is shown in Fig.3.

      Fig.3 Consequence assessment system for offshore oil spill.

      Table 4 Risk matrix of integrated risk assessment for offshore oil spill

      4.2 Integrated Assessment

      After probability and consequence assessment, the integrated risk assessment could be conducted based on the risk matrix as shown in Table 4. When the total risk is defined as H or VH, measures to remedy the pipeline or control the impact of spill should be carried out immediately. If the risk rank is scored as M, the ALARP (as low as reasonable practical) principle would be considered (API 2000).

      5 Case Study

      We take an exiting offshore pipeline in the Bohai waters for an example and discuss the reliability of the developed frame structure of probability and consequence assessment for offshore oil spill (The detailed information can be found in supporting information B).

      According to the pipeline conditions and the marine environment around here, the spill probability and consequence are calculated. In fuzzy comprehensive model, the last layer factors should be calculated with their weights and membership matrixes, and the results of spill probability and consequence assessment using fuzzy comprehensive model are respectively shown in Table 5 and Table 6.

      Through the process of fuzzy comprehensive assessment, the initial probability score is calculated as 45; however, the corrosion spill-risk is ranked as H (high), and the overall probability risk score is adjusted by additional 20% of the initial score and attains the value 54. If the value of probability level caused by each evaluated factor is higher than M (moderate,Vpro= 50), it suggests that the oil spill incident will have a high probability in the following years, and more attention should be paid to the corresponding factor by trying to avoid worseningconditions. In this case, corrosion is determined as the critical spill-probability factor, thus the corrosion inspection should proceed periodically. Then the consequence result for the oil spill incident is determined as M (Vcon= 43), and the integrated oil-spill risk is also ranked as M according to the risk matrix listed in this paper (Table 4). So ALARP principle should be adopted to determine whether the remedy or controlling measures should be conducted based on the demands of the inspection report. However, if the risk level exceeds an acceptable one, the operator may have to reconsider the attention to be taken.

      Table 5 Probability level of oil spill incident

      Table 6 Consequence level of oil spill incident

      6 Conclusion

      The developed oil-spill risk assessment of offshore pipeline with the application of fuzzy comprehensive assessment model can provide reliable information to control the main spill causes and spill influence in practical work. The integrated assessment factor system of spill probability and consequence caused by offshore pipeline is established in accordance with the operational manual and the statistic data. The evaluated factors of spill probability could be grouped into five aspects: corrosion, fatigue, national damage, third party together with operational fault; while the consequence evaluated factors of spill include hazard of oil and impact-controlling capability. With some modifications based on experts’ opinions, each of the evaluated factors in our work was developed using a relative weight and evaluation criterion. By using the oil-spill risk assessment model, it is easy to determine the risk level associated with the ongoing activity and management level and hence to take the risk mitigation action immediately.

      Acknowledgements

      Funding for this study is provided by the Marine Public Welfare Research Project of China (No. 201205012) and Preferential Funding of Tianjin. We greatly appreciate the valuable comments of Dr. Zhang and Dr. Bai who have sufficient experience on the development of offshore petroleum.

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      (Edited by Ji Dechun)

      (Received January 28, 2013; revised October 17, 2013; accepted December 8, 2013)

      ? Ocean University of China, Science Press and Springer-Verlag Berlin Heidelberg 2014

      * Corresponding author. Tel: 0086-022-25804083

      E-mail: lvyan@coes.org.cn

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