数字化建井规划工具在井概念阶段的应用

Costeno Hugo, Kandasamy Rajeswary, Telles Jose, Camacho Jacob, Medina Diego, Gori Freddy, Garcia Hector, Vilchez Omar
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引用次数: 0

摘要

如今,数字造井工具在井设计规划中得到了越来越广泛的考虑,可以在单一解决方案下实现自动化工程和团队同时协作。本文展示了在项目概念规划阶段使用数字井建设规划解决方案的结果。该方法通过应用智能引擎快速准确地对项目批准所需的特定井类型进行关键偏移分析,缩短了估算钻井时间和风险概况所需的时间。利用该解决方案,邻井分析(OWA)过程可以根据计划井的位置、轨迹和井结构自动完成。邻近井的各种信息和报告(地下和地面数据)存储在云解决方案中,无论是大规模还是小规模的数据存储,都可以轻松访问和提高数据可靠性。该软件选择最相关的邻井,显示风险分析并生成柱状图。对于概念设计,由于地面和地下潜在的未知风险,可以手动设置更高的风险级别,这些风险可以在以后进行细化。对井设计的快速验证使工程师能够更快、更有效地设计出概念性钻井方案。该解决方案最大限度地减少了执行概率时间和风险估计的时间。它减少了由于人工输入和设计而导致的有偏见的决策风险。这允许在项目可行性、利益相关者的一致性、提高设计可靠性以及减少在OWA上投入的时间和资源方面做出更明智的决策。本文介绍的工作旨在分享在概念项目阶段应用数字井建设规划解决方案的经验,并讨论它在井设计过程中所增加的价值。
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Application of Digital Well Construction Planning Tool During Well Conceptualization Phase
Digital well construction tools are becoming more widely considered today for well design planning, enabling automated engineering and simultaneous team collaboration under a single solution. This paper shows the results of using a digital well construction planning solution during a project’s conceptual planning stage. This method shortens the time needed to estimate the well times and risk profile for a drilling campaign by applying smart engines to quickly and accurately perform critical offset analysis for defined well types that is required for project sanction. With this solution, the Offset Well Analysis (OWA) process is done automatically based on the location of the planned well, trajectory and well architecture. Various information and reports (both subsurface and surface data) from neighboring wells is stored in cloud solutions, enabling ease of access and data reliability for both large or smaller scale data storage. The software selects the most relevant offset wells, displays the risk analysis and generates the stick chart. For a conceptual design, the risk levels can be manually set higher due to potential unknowns in surface and subsurface risks which can later be refined. Quick validation of the well design allows the engineer to design a conceptual drilling campaign quickly and more efficiently. The solution minimizes the time to perform probabilistic time and risk estimations. It reduces the risk of biased decision making due to manual input and design. This allows for better-informed decisions on project feasibility, alignment of stakeholders, increased design reliability as well as reducing the amount of time and resources invested in OWA. The work presented here is aimed at sharing the experience of applying a digital well construction planning solution specifically on the conceptual project stage and discuss the value it adds to the well design process.
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