稠油油田基准:一种识别总成本和生产优化机会的工具

J. L. Ortiz-volcan, W. Al-Khamees, K. Ahmed
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引用次数: 0

摘要

本文提出了一种对稠油油田进行基准测试的实用方法,作为识别总成本和生产优化机会的工具。该方法结合了典型稠油油田的实际数据,定义了油藏、油井和地面复杂性指数,用于对主题油田进行分类,并建立了总成本分解模型,以映射可能导致总成本增加、潜在项目/过程延迟和生产性能不佳的潜在风险。基准测试过程包括四个步骤:1)使用前端加载(FEL)和复杂性指标对主题领域进行分类,这些指标包括:a)储层构造、地层、岩石、流体、能量、静态和动态复杂性,b)井复杂性和c)地面过程复杂性;2)选取指标范围内的模拟场;3)使用因果图来识别影响资本支出(CAPEX)、运营支出(OPEX)、生产损失和周期时间的不确定性和风险的原因;4)总成本随机模型用于生成图形,提供主题领域与类似物的位置。总未贴现成本分解结构提供了最关键的成本驱动因素的信息,其中重大影响对应于运营成本。因果图描述了地表和地下的典型总成本驱动因素。对七个最重要的风险组进行建模,以可视化对成本、生产损失、周期时间以及健康、安全和环境的影响,并根据成本效益对建议的缓解行动进行排名。该数据库提供了来自委内瑞拉、加拿大、美国和中东等著名稠油产区的冷采和热采稠油油田的生产成本(Capex、Opex)信息。采用热采技术的稠油油田的典型运营成本范围为2 ~ 22美元/桶,总成本范围为10 ~ 40美元/桶。一个关键的观察结果是,燃料和电力成本是热增强采收率最大的单一运营成本,约占50%。严重的生产损失与腐蚀和井喷引起的故障有关,这是最大的HSE风险。提出的方法有助于对稠油油田的总成本进行基准测试,这是一项需要从技术论文、监管机构和石油行业中研究可用可靠资源的任务。了解稠油油田每桶高成本的原因及其与不确定性和风险的关系,是多学科成本优化的强大工具,因为它提供了所有相关学科都能理解的共同语言。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Benchmarking Of Heavy Oil Fields: A Tool for Identification of Opportunities for Total Cost and Production Optimization
This paper presents a practical method for benchmarking heavy oil fields as a tool for identification of opportunities for total cost and production optimization. The method combines actual data from typical heavy oil fields to define reservoir, well and surface complexity indices, for categorizing a subject field and a total cost breakdown model to map potential risks that could cause total cost to increase, potential project/process delay and poor production performance. The benchmarking process consists of four steps: 1) classification of a subject field using Front End Loading (FEL) and complexity indices that account for: a) reservoir structural, stratigraphic, rock, fluid, energy, static and dynamic complexity, b) well complexity and c) surface processes complexity; 2) selection of analog fields within the range of indices; 3) use of causal maps to identify causes of uncertainty and risks that impact capital expenditures (CAPEX), operational expenditures (OPEX), production losses and cycle time; and 4) a total cost stochastic model is used to generate graphs providing the position of the subject field vs. analogs. A total undiscounted cost breakdown structure provided information on the most critical cost drivers, where significant impact corresponded to OPEX. Causal maps described typical total cost drivers for surface and subsurface. Seven most significant groups of risks are modeled to visualize the impact on cost, production losses, cycle time and health, safety and environment with recommended mitigation actions ranked by cost benefit. A database provides information about cost of production (Capex, Opex) from heavy oil fields undergoing cold production and thermal enhanced oil Recovery well-known heavy oil production areas from Venezuela, Canada, USA and Middle East. Heavy oil fields undergoing thermal enhanced oil recovery indicated typical ranges for Opex from 2 to 22 USD/bbl and Total Cost ranges from 10 to a maximum of 40 $/bbl. A key observation is that cost of fuel and power is the largest single OPEX cost for thermal enhanced recovery accounting for about 50%. Significant production losses are associated to failures due to corrosion and blowouts is the most significant HSE risk. The proposed method helps benchmarking total costs in heavy oil fields, which is a task that requires lot of efforts in researching available reliable sources from technical papers, regulatory agencies, and oil industry. Understanding causes of high cost per barrel and their relationship with uncertainties and risks for heavy oil field, is a formidable tool for multidisciplinary cost optimization as it provides a common language that understood by all disciplines involved.
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