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Uncertainty Assessment for Updating Platform Decommissioning Alternatives Cost using Net Present Value Approach

机译:净现值法更新平台退役替代品成本的不确定性评估

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Background/Objectives: Offshore oil and gas platform are aging in Asian Pacific Region and requiring a transparent decommissioning framework to address the major environmental impacts and cost pertaining the removal of offshore structures. This paper endeavors to establish a benchmark model to update platform decommissioning cost for four decommissioning options. Methods/Statistical Analysis: This paper provides a benchmark methodology adopting a case study for a previous decommissioning project to estimate and updateplatform decommissioning cost based on Net Present Value (NPV) approach. Linear regression was established to predict cost inflation in decommissioning projects to be put to use in NPV method. Monte Carlo Simulations were employed to assess and evaluate uncertainty, and variability of each decommissioning alternative cost model to validate their exemplary implementation. Findings: After implementing Net Present Value methodology to attain platform decommissioning cost, it was found that platform decommissioning costs were USD91,997,398.97 USD29,312,019.08 USD36,913,049.82, and USD21,185,843.13 for complete removal, partial removal, conversion to reef, and re-using platform for wind turbine power generation respectively. These cost data reveal the tremendous cost incurred by platform’s owners due to decommissioning. Uncertainty and variability of cost update estimation were demonstrated through Monte Carlo Simulations. After running 100,000 simulations, the results showed insignificant discrepancy with uncertainty ratio varies between 0.023% and 0.10% for the four decommissioning alternatives. Therefore, Monte Carlo Simulation exhibits a very good agreement with the cost estimate using NPV which just confirms the viability and applicability of utilizing NPV method in updating decommissioning cost for offshore installations. Hence, the contribution of this study is significant and timely efficient, allowing for cost update through systematic method instead of embracing regression analysis which is tedious and time-consuming. Application/Improvements: Net Present Value methodology may be useful and newly tool in updating platform decommissioning cost, and can strengthen its applicability in this field by incorporating probabilistic method as such Monte Carlo Simulation.
机译:背景/目标:海上石油和天然气平台在亚太地区正在老化,需要透明的退役框架来解决与拆除海上结构有关的主要环境影响和成本。本文致力于建立一个基准模型,以更新四种退役方案的平台退役成本。方法/统计分析:本文提供了一个基准方法,该方法采用了一个先前的退役项目的案例研究,以基于净现值(NPV)方法估算和更新平台的退役成本。建立线性回归以预测将在NPV方法中使用的退役项目的成本上涨。蒙特卡罗模拟被用来评估和评估每个退役替代成本模型的不确定性和可变性,以验证其示例性实施。调查结果:在实施了净现值方法以获取平台退役成本后,发现平台退役成本分别为91,997,398.97美元,29,312,019.08美元36,913,049.82美元和21,185,843.13美元,以进行完全移除,部分移除,转换为珊瑚礁以及重新利用。使用平台分别用于风力发电机发电。这些费用数据显示了平台所有者因退役而产生的巨额费用。成本更新估算的不确定性和可变性通过蒙特卡洛模拟得到了证明。运行100,000次模拟后,结果显示四种退役替代方案的差异不明显,不确定性比率在0.023%和0.10%之间。因此,蒙特卡洛模拟与使用NPV进行成本估算具有很好的一致性,这恰好证实了使用NPV方法更新海上安装退役成本的可行性和适用性。因此,这项研究的贡献是重大而及时的,它允许通过系统的方法更新成本,而不是进行繁琐而费时的回归分析。应用/改进:净现值方法可能是更新平台退役成本的有用和新工具,并且可以通过结合概率方法(例如蒙特卡洛模拟)来增强其在该领域的适用性。

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