Volume 38 Issue 4
Jul.  2021
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ZHU Jinzhi, REN Lingling, LU Haiying, et al.A new method of predicting the bridging lost circulation materials and their particle size distribution[J]. Drilling Fluid & Completion Fluid，2021, 38（4）：474-478 doi: 10.3969/j.issn.1001-5620.2021.04.012
Citation: ZHU Jinzhi, REN Lingling, LU Haiying, et al.A new method of predicting the bridging lost circulation materials and their particle size distribution[J]. Drilling Fluid & Completion Fluid，2021, 38（4）：474-478 doi: 10.3969/j.issn.1001-5620.2021.04.012
shu

A New Method of Predicting the Bridging Lost Circulation Materials and Their Particle Size Distribution

doi: 10.3969/j.issn.1001-5620.2021.04.012
  • 1.

    Petrochina Tarim Oilfield Company, Korla，Xinjiang 841000

  • 2.

    Southwest Petroleum University ,Petroleum Engineering School , Chengdu，Sichuan 610500

  • Received Date: 2021-02-25
    Available Online: 2023-11-09
  • Publish Date: 2021-07-31
    Abstract
  • Accurate and rapid prediction of the types of lost circulation materials (LCMs) and their particle size distribution (PSD) plays a key role in the digital and intelligent design of bridging lost circulation material slurry. A new method of characterizing and rapid predicting the bridging lost circulation materials and the PSD thereof is presented based on the PCHIP method in an effort to overcome the deficiencies existed in the methods presently in use. Using the data obtained in the experiments on the PSD of a single bridging LCM, the applicability of the new method and the commonly used particle size distribution function methods in characterizing the PSD of LCMs was compared and analyzed. The new method was used to predict the PSDs of different LCM compositions, and the data collected in the measurement were used to verify the reliability of the new method. It was demonstrated that, compared with the commonly used PSD function methods, the new method can be used to more accurately characterize the PSDs of bridging LCM compositions. The cumulative PSD curve predicted with the new method is highly consistent with the measured data. Without the need of pre-setting a PSD function, the new method is suitable for predicting the PSD of particle matters with multiple peaks. The new method can be used to predict the PSDs of mixtures with different ratios of particle sizes.

     

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