以井眼轨迹优化为重点的智能井眼规划算法与模型

E. Wiktorski, D. Sui
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引用次数: 0

摘要

井规划是一项耗时的工作,需要综合各个领域专业人员的知识和经验,如钻井工程师、管材制造商、钻井泥浆专家、地质学家等。根据OG21的报告(1),规划一口井的平均时间为2-3个月。钻井工程师必须以最小的成本设计井,并在任何时候保持井眼完整性。井眼还应允许油藏最大产量和最小弯曲度,以确保成功下入和完井套管。幸运的是,在勘探充分的地质区域,地层序列和相应的地压是已知的,主要目标可以缩小到最佳轨迹设计。最佳井眼轨迹至少考虑三个标准:最短路径、避免碰撞和与油藏接触时间最长。由于涉及到大量的模块,因此井的规划需要一个整体的方法。同时,由于模块和各自的物理模型之间的复杂交互,该任务要求高精度。本文介绍了一种内部井计划模拟器的开发,该模拟器以一种智能的方式集成了所有必要的井计划模块。模拟器的中心部分由轨迹规划和优化模块表示,该模块基于最小化井筒长度和狗腿严重程度。还包括与防碰撞有关的约束。井眼轨迹智能优化技术的引入为工程师提供了多种选择,从而节省了时间和精力,满足了上述限制条件。我们的最终目标是通过为井眼规划模拟器中的其他重要模块开发智能优化器,最大程度地实现井眼规划的自动化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithms and Models for Smart Well Planning With Emphasis on Trajectory Optimization
Well planning is a time-demanding procedure, which integrates knowledge and experience of various field professionals, as drilling engineers, pipe manufacturers, drilling mud specialists, geologists, etc. According to OG21 report (1), time spent for planning a well is on average 2–3 months. Drilling engineers have to design a well at minimum costs maintaining wellbore integrity at any time. The wellbore should also allow for maximum production from the reservoir and minimum tortuosity for successful casing running and completion. Fortunately, in the well-explored geological areas, where stratigraphic sequences and corresponding geopressures are known, the main objective can be narrowed down to optimal trajectory design. Optimal wellbore trajectory considers at least three criteria: shortest possible path, collision avoidance and longest possible contact with reservoir. Due to large number of modules involved, well planning requires a holistic approach. At the same time, due to complex interaction between the modules and respective physical models, this task implicates a high level of precision. This paper presents a development of an in-house well planning simulator, which integrates all essential well planning modules in a smart way. Central part of the simulator is represented by a trajectory planning and optimization module, which is based on minimization of wellbore length and dogleg severity. Constraints related to anticollision are also included. Introduction of smart optimization techniques for wellbore trajectory has a real potential of saving time and efforts by providing engineers with multiple options, which satisfy the aforementioned constraints. Our ultimate goal is to automate wellbore planning to the largest possible extent by developing smart optimizers for other vital modules within the well planning simulator.
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