自动三维岩屑和崩落测量传感器的现场测试

S. Prez, Santiago Callerio, Abraham C. Montes, Çinar Turhan, P. Ashok, E. van Oort, R. Pruitt, T. Thetford, T. Peroyea, M. Behounek
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引用次数: 0

摘要

观察岩屑和崩落是发现井眼清洁和井筒失稳问题的重要早期指标。然而,这一关键监控过程的自动化仍处于起步阶段。本文重点介绍了一种新型自动钻落监测传感器系统的开发和初步现场测试。介绍了在早期现场测试中发现的最初挑战,以及将其纳入新工作现场原型的解决方案。为原型选择的成像传感器,包括3D激光轮廓扫描仪和机器视觉相机,在最初的现场试验中使用,以评估构建可在恶劣现场环境中运行的原型的可行性。在最初的现场试验的基础上,建立了原型机,并在现场进行了初步的室外测试,以验证其性能。随后,在德克萨斯州西部的一个活跃钻井现场进行了第二次现场试验,以评估原型在现场的实施和性能。在第一次现场试验中确定的关键挑战的实用解决方案在新的原型中成功实施,并在第二次现场试验中验证了其现场性能,将原型集成到现役钻机的固控系统中,成功地收集了钻井作业期间的数据。该系统准确测量了岩屑的体积返回,测试证明了该系统能够确定岩屑尺寸分布并检测异常尺寸的崩落。研究结果可直接用于现场作业中改善井眼清洁管理和避免卡钻。本文介绍了3d成像岩屑监测系统的第一个工作原型,该系统可用于量化表面岩屑的体积返回,并提供有关岩屑和崩落的大小和形状的信息。这种岩屑传感器的开发是钻井自动化领域的一个重要里程碑,使该行业更接近实现全自动井眼清洗和卡钻预防系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Field Testing of an Automated 3D Cuttings and Cavings Measurement Sensor
Observation of cuttings and cavings serves as an important early indicator for hole cleaning and wellbore instability problems. Automation of this critical monitoring process is, however, still in its infancy. This paper highlights the development and initial field testing of a new automated cuttings and cavings monitoring sensor system. Initial challenges identified in an earlier field test, and their solutions that have been incorporated into this new working field prototype, are presented. The imaging sensors selected for the prototype, including a 3D laser profile scanner and a machine vision camera, were used in an initial field trial to assess the feasibility of building a prototype that can operate in a harsh field environment. Based on that initial field trial, the prototype was built, and preliminary outdoor tests were conducted offsite to validate its performance. Following that, a second field trial at an active drilling site in West Texas was conducted to assess the implementation and performance of the prototype in the field. Practical solutions to key challenges identified in the first field trial were successfully implemented in the new prototype, and its field performance was validated in the second field trial where the prototype was integrated into the solids control system of an active drilling rig, successfully collecting data for during drilling operations. The system accurately measured the volumetric return of cuttings, and the tests demonstrate the ability to determine the cuttings size distribution and detect anomalous-sized cavings. The results can be used directly for improved hole cleaning management and stuck pipe avoidance in field operations. This paper introduces the first working prototype of a 3D-imaging cuttings monitoring system that could be taken into production for quantifying the volumetric return of cuttings on surface and providing information about the size and shape of cuttings and cavings. The development of this cuttings sensor is a major milestone in the field of drilling automation, bringing the industry closer to achieving a fully automated hole cleaning and stuck pipe prevention system.
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