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首页> 外文期刊>Journal of offshore mechanics and arctic engineering >Comparison of Two Models for Prediction of Seismic Streamer State Using the Ensemble Kalman Filter
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Comparison of Two Models for Prediction of Seismic Streamer State Using the Ensemble Kalman Filter

机译：集成卡尔曼滤波的两种预测流线状态的模型比较

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摘要

Towed marine seismic streamers are extensively utilized for petroleum exploration. With the increasing demand for efficiency, leading to longer and more densely spaced streamers, as well as four-dimensional (4D) surveys and more complicated survey configurations, the demand for optimal streamer steering has increased significantly. Accurate streamer state prediction is one important aspect of efficient streamer steering. In the present study, the ensemble Kalman filter (EnKF) has been used with two different models for data assimilation including parameter estimation followed by position prediction. The data used are processed position data for a seismic streamer at the very start of a survey line with particularly large cable movements due to currents. The first model is a partial differential equation (PDE) model reduced to two-dimensional (2D), solved using a finite difference method (FDM). The second model is based on a path-in-the-water (PIW) model and includes a drift angle. Prediction results using various settings are presented for both models. A variant of the PIW method gives the overall best results for the present data.
机译：拖曳的海上地震拖缆被广泛用于石油勘探。随着对效率的需求不断增加，导致拖缆的长度和密度越来越高，以及四维（4D）测量和更复杂的测量配置，对最优拖缆转向的需求已大大增加。准确的拖缆状态预测是有效的拖缆转向的重要方面之一。在本研究中，集成卡尔曼滤波器（EnKF）已与两个不同的模型用于数据同化，包括参数估计和位置预测。所使用的数据是勘测拖缆在勘测线刚开始时的处理过的位置数据，由于电流，电缆的移动特别大。第一个模型是简化为二维（2D）的偏微分方程（PDE）模型，使用有限差分法（FDM）求解。第二个模型基于水上路径（PIW）模型，并包含一个漂移角。两种模型都显示了使用各种设置的预测结果。 PIW方法的一种变体为当前数据提供了总体最佳结果。

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  • 来源
    《Journal of offshore mechanics and arctic engineering》 |2018年第6期|061101.1-061101.9|共9页
  • 作者

    Grindheim Jan Vidar; Revhaug Inge; Pedersen Egil; Solheim Peder;

  • 作者单位

    GEOGRAF AS, Strandgt 5, NO-4307 Sandnes, Norway;

    Norwegian Univ Life Sci NMBU, Fac Sci & Technol IMT, POB 5003, NO-1432 As, Norway;

    Arctic Univ Norway UiT, Dept Engn Sci & Safety, Veg 18, NO-9037 Tromso, Norway;

    GEOGRAF AS, Strandgt 5, NO-4307 Sandnes, Norway;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
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  • 正文语种 eng
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