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'Vaguely Right or Precisely Wrong?': Making Probabilistic Cost, Time, and Performance Estimates for Bluefields Appraisal

机译:“含糊不实或恰恰错?”:制作概率的成本,时间和性能估计为Bluefields评估

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We conducted a practical case study that aims at estimating the shapes and parameters of probability distributions for key cost, time and activity performance inputs required by a risk, resource, and value simulator to conduct a stochastic valuation of a new exploration asset. We analyzed a sample of 73 shallow offshore fields in Australia retrieved from a global field-by-field database that includes reserves, production profiles, financials, valuation, breakeven prices, ownership and other key metrics for global oil and gas fields, discoveries and exploration licenses. The reviewed facilities concepts includes 40 steel platforms, 2 concrete gravity-based developments, 10 projects with extended reach drilling, 4 FPSO, and 17 subsea tie-backs. The aggregate CAPEX of projects in the sample over 1965-2015 is USD 99.1 billion (in nominal terms), which is commensurate with the total asset size of the Australian offshore petroleum industry. We estimate probability distributions for all full-cycle parameters required to generate Monte Carlo CAPEX, OPEX, and production profiles. In particular, these include facility CAPEX per unit peak, development phase duration and scheduling rules, drilling expenditures per barrel of oil equivalent, cost of exploration and appraisal wells, OPEX-to-CAPEX ratio, abandonment cost ratio, fraction of hydrocarbons produced yearly at plateau, fraction of hydrocarbons remaining at end-of-plateau, terminal production rate, and fraction pre-drilled wells. Most of the above were found to be log-normally distributed. The paper presents a simple yet robust workflow relying on real industry data that enabled assessing value, risks, and uncertainties of upstream assets at exploration and early appraisal stages. It can be seamlessly extended to other basins owing to a rich coverage of the online field analogs database. The ultimate outcome of the study-a probabilistic value assessment of new exploration asset- represents a modern appraisal methodology relying on a corporation-wide software platform.
机译:我们进行了一个实用的案例研究,旨在估计风险,资源和价值模拟器所需的关键成本,时间和活动输入的概率分布的形状和参数,以进行新的勘探资产的随机估值。我们分析了澳大利亚的73个浅海上田地的样本,该数据库从一个全球外野数据库中检索,包括储备,生产简介,金融,估值,盈亏平衡价格,所有权和全球石油和天然气领域的所有权和其他关键指标,发现和探索许可证。审查的设施概念包括40个钢铁平台,基于混凝土的重力的发展,10个项目,扩展钻探,4个FPSO和17个海底连接。在1965 - 2015年的示例中项目的总产额为991亿美元(以名义术语),与澳大利亚海上石油工业的总资产规模相称。我们估算生成Monte Carlo Capex,OPEX和生产简介所需的所有全循环参数的概率分布。特别是,这些包括每单位峰值的设施支出,开发阶段持续时间和调度规则,每桶石油等同,勘探和评估井的成本,OPEX-to-Capex比率,遗弃成本比,年度碳氢化合物的一部分高原,碳氢化合物的一部分剩余的碳氢化合物,终端产率和馏分预钻孔井。发现上述大多数是如何分布的。本文提出了一种简单而强大的工作流程,依赖于实际行业数据,使能够评估探索和早期评估阶段的上游资产的价值,风险和不确定性。由于在线现场模拟数据库的丰富覆盖,它可以无缝扩展到其他盆地。研究的最终结果 - 新勘探资产的概率价值评估 - 代表了依赖于公司 - 广泛的软件平台的现代评估方法。

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