完整的论文提出了一种新颖的方法，该方法融合了物理学、数据科学和不确定性建模的原理，旨在为实时卡钻事件的管理提供更具弹性和更精确的解决方案。该方法涵盖了多种卡钻机制，包括机械、几何、差动、键槽、岩屑封隔和地质力学因素。这些参数的独立性有助于预测导致卡钻的机制。
基于所提方法的可扩展模型，可同时监测多个钻机，如上图1所示。该图还展示了在油井监测过程中可提取的各种实时洞察，例如描述性、预测性、诊断性和规范性洞察。
The complete paper presents a novel methodology that merges principles of physics, data science, and uncertainty modeling to offer more-resilient and -precise solutions for managing real-time pipe-sticking occurrences. The methodology embraces diverse modes of pipe-sticking mechanisms, encompassing mechanical, geometrical, differential, key-seat, cuttings-packoff, and geomechanical factors. The independence of these parameters facilitates the prediction of mechanisms that contribute to pipe sticking.
The scalable model for monitoring multiple rigs at the same time based on the proposed approach is shown in Fig. 1 above. The figure also shows different real-time insights, such as descriptive, predictive, diagnostic, and prescriptive, that can be extracted as the wells are monitored.
