非常规资源的随机石油经济学应用:估算富含液体的非常规开发项目的天然气盈亏平衡价格

Michael Macphee, Shamsul Anuar, Abdulbari Alhayaf
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引用次数: 0

摘要

为了评估富含液体的非常规天然气项目的经济可行性,需要确定一个收支平衡的天然气销售价格(BEP)。由于市场定价和二次液体生产收入不确定,因此计算出的此类项目的 BEP 也不确定。二次收入可部分但显著地抵消资本和运营成本。通过应用随机方法,可以计算出与所需项目销售气体 BEP 相关的不确定性,为管理决策提供依据。使用合成数据对一般非常规天然气开发进行了随机经济评估。流体窗口的范围从贫气(干气)到富液,这些流体窗口的多种不确定次级产品收入流对最终的销售气 BEP 影响很大。进一步影响销售天然气 BEP 的其他不确定输入包括:资本成本、运营成本、产量和项目时间安排。概率分布用于预测二次产品价格、资本成本和运营成本。通过应用该模型并结合计算 BEP(税后)的新方法,可以计算出与所产生的 BEP 相关的不确定性。该模型可以清楚地显示 BEP 的不确定性。主要统计数据包括平均值、中位数、百分位数以及项目 BEP 超过规定价格阈值的概率。完成资本密集型油气项目的随机经济评估的主要目的是了解与预期项目净现值相关的不确定性,以便做出项目 FID 决策。在对天然气市场进行监管的辖区,选定的天然气项目会获得固定的长期天然气价格,并且很少有机会重新谈判天然气价格。固定天然气价格由监管机构制定,旨在为生产商提供固定回报率。然而,对于富含液化气的项目来说,由于这些次生产品的市场定价等因素的影响很大,因此项目回报率从来都不是真正固定的。因此,了解 BEP 的概率性质至关重要。鉴于必要的上游和中游基础设施需要大量资金,一旦做出投资决定,就必须持续开展钻探活动,以确保充分利用这些固定的基础设施。一旦这些基础设施的主要建设完成,并考虑到相对确定的钻井和无钻机成本,主要的不确定性就变成了二级产品的定价和收入。该模型提供了预期 BEP 和 BEP 可能范围的可视性,从而为决策提供支持。模型结果还确定了天然气 BEP 与二级产品定价之间的明确关系。与侧重于项目净现值的传统随机经济分析不同,该分析的重点在于隐含的税后 BEP。由于进行随机分析时需要进行数千次迭代,因此使用常见的基于 excel 的目标搜索函数来确定 BEP 是不切实际的。因此,我们采用了一种公式化的方法来估算税后 BEP,从而能够在随机模拟的每次迭代中同时计算税后项目 BEP。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Stochastic Petroleum Economics for Unconventional Resources: Estimating the Gas Break-Even Price for a Liquids Rich Unconventional Development
To assess the economic viability of a liquids rich unconventional gas project, a break-even sales gas price (BEP) is determined. The calculated BEP for such projects is uncertain as market pricing and revenue from secondary liquid production is uncertain. This secondary revenue provides a partial yet significant offset to capital and operating costs. Through the application of stochastic methods, uncertainty associated with the required project sales gas BEP can be calculated to inform management decision making. Stochastic economic evaluation of a generic unconventional gas development was undertaken using synthetic data. Fluid windows range from lean (dry) gas to liquid-rich with multiple uncertain secondary product revenue streams from these fluid windows impacting heavily on the resulting sales gas BEP. Further impacting the sales gas BEP are other uncertain inputs including: capital costs, operating costs, production, and project timing. Probability distributions were assigned to forecast secondary product prices, capital and operating costs. Through the application of this model combined with a novel approach to calculating the BEP (after-tax), uncertainty associated with the resulting BEP can be calculated. The model delivered clear visibility on BEP uncertainty. Key statistics include the mean, median, percentiles, and probability of the project BEP exceeding defined price thresholds. The primary purpose of completing a stochastic economic evaluation for capital intensive oil and gas projects is to understand uncertainty associated with the expected project NPV to enable a project FID decision. In jurisdictions with a regulated natural gas market, selected gas projects receive a fixed long-term gas price with infrequent ability to renegotiate the gas price. The fixed gas price is established by the regulator with intent to provide the producer with a fixed rate of return. However, for liquids rich gas projects, the project return is never truly fixed given significant exposure to market pricing for these secondary products, amongst other factors. Hence it is essential to understand the probabilistic nature of the BEP. Given significant capital requirements for necessary upstream and midstream infrastructure, once an investment decision has been made, a continuous drilling campaign must be sustained to ensure full use of this fixed infrastructure. Once the primary build-out of this infrastructure is complete and given relatively certain drilling and rigless costs, the primary uncertainty becomes pricing and revenues from secondary products. This model supports decision making by providing visibility on the expected BEP and probable range of the BEP. The model results also established a clear relationship between gas BEP and pricing for secondary products. In contrast to traditional stochastic economic analysis focused on project NPV, the focus of this analysis is on the implied after-tax BEP. Given thousands of iterations are required to perform stochastic analysis, use of the common excel-based goal-seek function to identify the BEP is impractical. Instead, a formulaic approach to estimate the after-tax BEP was employed, enabling the concurrent calculation of the after-tax project BEP during each iteration of the stochastic simulation.
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