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HSE Integrated Risk Assessment For A Steamflood Pilot Program

机译:HSE综合风险评估为SteamFlood试点计划

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This paper describes an HSE integrated risk assessment performed by a multidisciplinary team for a Steamflood pilot program in a shallow geologically complex multi layered super-giant heavy oil green field in Kuwait, undergoing first phase of development using field tested Cyclic Steam Stimulation (CSS) during first few years then followed by Steamflood (SF). In the first step of HSE integrated risk assessment methodology, the team stablished the most likely production scenarios during CSS and SF for selected well pattern types and sizes, components of surface infrastructure and production operation modes. To determine the safe distance between wells during drilling operations under current conditions, the team performed a consequence analysis. For each scenario the team defined ranges (minimum and maximum) for well production and injection rates, fluid composition, wellhead temperature, gas oil ratios and other key parameters using data and information from reservoir model, pilots and well designs. To account for the lack of data typical in a green field, the team reviewed well blowout failure modes and frequencies from analog heavy oil fields worldwide. Through internal workshops and using data from analogs, the team did the identification, classification, analysis and ranking of hazards and risks, ending up with a risk breakdown structure (RBS) and a risk assessment matrix (RAM). To identify root causes and their mitigation actions the team prepared cause and effect relationships maps and loss causation models for those risks related to HSE. The outcomes of the assessment are a risk register, quantitative risk assessment, detailed reports and guidelines for the Steamflood pilot program as support to prepare HSE procedures. The team identified 66 risks; classified and ranked them using a risk breakdown structure (RBS) and a risk assessment matrix (RAM) and then selected 28 risks with cause and effect relationships with HSE. The cause and effect relationships maps helped defining the 7 most significant groups of risks (likelihood and impact) in the short, medium and long term: 1) Well blowouts, 2) H2S & CO2, 3) Pattern Type & Size, 4) Heat Management, 5) Non Wanted Fluids & Solids, 6) Reservoir Description and 7) Human Factors. By using loss causation models for each of the seven group of risks, the team established the root causes and risk mitigation options. From the consequence analysis, the conclusion was that 45 meters is the minimum safe distance required between heavy oil wells considering three event scenarios of potential failure cases and the consequences. Finally, to account for the need of critical data related to the most critical HSE risks, the team visualized a Steamflood field test using a small pattern area to reach quickly steam breakthrough and gather a minimum of the needed data in less than 1 year. The HSE integrated risk asssessment methodology presented in this paper is applicable to similar heavy oil green fields to identify potential failure modes associated with well blowouts and other hazards during all phases of thermal operations using data from the subject field or from analogs.
机译:本文介绍了一支由多学科团队进行的HSE综合风险评估,以在科威特的浅层地质复杂多层超巨型大型油绿地中的浅层地质复杂的多层超大型油绿地进行,经历了使用田间测试的循环蒸汽刺激(CSS)的第一阶段开发阶段前几年然后是Steamflood(SF)。在HSE综合风险评估方法的第一步中,团队在CSS和SF期间驻扎了最可能的生产方案,用于所选井图案类型和尺寸,表面基础设施的组件和生产操作模式。为了在当前条件下确定钻井操作期间井间井之间的安全距离,该团队进行了后果分析。对于每个场景,使用储层模型,飞行员和井设计的井生产和注射速率,流体组成,井口温度,燃气氧化物,燃气量和其他关键参数定义了范围(最小和最大值),流体组成,井口温度,燃气油比和其他关键参数。为了考虑绿色领域缺乏数据,团队审查了全球模拟重油场的井喷失效模式和频率。通过内部研讨会和使用模拟数据,该团队对危险和风险的识别,分类,分析和排名进行了识别,分类,分析和排名,以风险击穿结构(RB)和风险评估矩阵(RAM)。为了识别根本原因及其缓解行动,团队为与HSE相关的风险的风险做好了成因和效果关系地图和损失因果模型。评估结果是风险登记,定量风险评估,石油飞行员计划的详细报告和准则,作为准备HSE程序的支持。该团队确定了66个风险;使用风险击穿结构(RB)和风险评估矩阵(RAM)进行分类和排名,然后选择28个风险,并与HSE效果关系。原因和效果关系地图有助于在短,中长期和长期:1)井喷室,2)H2S&CO2,3)图案类型和尺寸,4)热量中有助于定义最重要的风险(可能性和冲击)。管理,5)非通缉流体和固体,6)储层描述和7)人类因素。通过使用七组风险中的每一个的损失因果模型,团队建立了根本原因和风险缓解方案。从后果分析中,结论是,考虑到潜在故障案件的三种事件情景和后果,重油井之间需要的最低安全距离是45米。最后,为了考虑有关与最关键的HSE风险相关的关键数据,该团队使用小型图案区域可视化SteamFlood现场测试,以快速蒸汽突破,并在不到1年内收集最少所需的数据。本文提出的HSE综合风险算法方法适用于类似的重油绿地,以识别使用来自主题领域或类似物的数据的热操作阶段的井喷和其他危害相关的潜在失效模式。

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