用于实时钻具横向运动预测的物理信息贝叶斯数据同化方法

IF 2 Q2 ENGINEERING, MECHANICAL Frontiers in Mechanical Engineering Pub Date : 2024-06-12 DOI:10.3389/fmech.2024.1410360
Fei Song, Kevin Shi, Ke Li, Amine Mahjoub, S. Ossia, Ives Loretz, Robson Serafim
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引用次数: 0

摘要

在本研究中,我们展示了一种贝叶斯数据同化方法,该方法将物理学与运动传感器数据融合在一起,通过适当的不确定性量化来推断井底组件(BHA)上相关点的动态状态。以一个 4.75 英寸-LWD(边钻边测井)工具为例,地层评估传感器的动态状态可通过运动传感器的测量值作为所需输入进行实时预测。这是由利用无香味卡尔曼滤波技术开发的传递函数实现的。利用有限元分析(FEA)模拟获得的合成数据,针对不同的 BHA 配置和钻井条件,对传递函数的稳健性进行了评估。结果发现,传递函数的预测结果与地层评估传感器的真实运动状态非常吻合。具体来说,使用所开发的传递函数可将地层评估传感器运动轨迹的相对误差降低 3 倍,并可显著提高测量质量风险分类。利用接近钻井条件的滚动测试数据对所开发的传递函数方法进行了进一步评估。结果发现,在存在反向漩涡的情况下,传递函数的预测结果始终接近地面实际情况。所开发的建模方法可能会产生更广泛的影响,如实现适合盆地的虚拟 V&V(验证和确认),以加快 LWD 工具的开发,或实现未来的钻井优化。
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A physics-informed Bayesian data assimilation approach for real-time drilling tool lateral motion prediction
In this study, a Bayesian data assimilation method that fuses physics with motion sensor data is demonstrated to infer the dynamic states at points of interest on the bottomhole assembly (BHA) with proper uncertainty quantification. A 4.75 inch-LWD (Logging-while-drilling) tool has been used as a use case, where the dynamic states at the formation evaluation sensor can be predicted in real time with the measurements at the motion sensor as the required inputs. This was achieved with a developed transfer function that utilizes unscented Kalman filtering technique. The robustness of the transfer function was evaluated with synthetic data obtained from finite element analysis (FEA) simulations for various BHA configurations and drilling conditions. It was found that the prediction by the transfer function agrees favorably well with the true states of motion at the formation evaluation sensor. Specifically, using the developed transfer function can help reduce the relative errors for the motion trajectories at the formation evaluation sensor by a factor of 3, and can significantly enhance measurement quality risk classification. The developed transfer function method was further assessed with experimental roll test data, which is considered as close to drilling conditions. The prediction by the transfer function was found consistently close to the ground truth in the presence of backward whirl. The developed modeling method can potentially have broader impacts by enabling fit-for-basin virtual V&V (Verification and Validation) to accelerate LWD tool development, or enabling future drilling optimization.
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来源期刊
Frontiers in Mechanical Engineering
Frontiers in Mechanical Engineering Engineering-Industrial and Manufacturing Engineering
CiteScore
4.40
自引率
0.00%
发文量
115
审稿时长
14 weeks
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