Partitioning model study of the traction coefficient in a droplet model
in a wellbore
- jianxun jiang,
- Ziying Chen,
- jingguo du,
- kaijun Li,
- YInhua Liu,
- long li
jingguo du
North China University of Science and Technology
Author ProfileYInhua Liu
CNPC Research Institute of Engineering Technology
Author Profilelong li
PetroChina Southwest Oil and Gas Field Company Exploration and Development Research Institute
Author ProfileAbstract
At present, the main way to deal with the gas well effusion is to use
the over-effusion prediction model to calculate the critical fluid
carrying velocity and other factors, which provides data support and
theoretical basis for the drainage process, so as to achieve the effect
of bringing the effusion out of the wellbore. When the prediction
results of the hydrops prediction model are biased, hydrops will be
generated at the bottom of the wellbore, resulting in a decrease in gas
well productivity. Aiming at the problem that the drag coefficient of
the wellbore droplet movement model changes greatly in the process of
natural gas production, which leads to the error of the wellbore
effusion prediction, the commonly used droplet models and the common
drag coefficient models are analyzed and evaluated. Considering that the
fitting method of the commonly used drag model has different
applicability for each Reynolds number region, the literature review,
calculation and verification methods are used. The area with the highest
fitting accuracy of each method is divided and sorted, and the model is
selected. Compared with the model obtained by the partition and the
existing drag model and the experimental value, it is found that the
model can effectively reduce the average error rate between the
calculated results and the experimental value, and can be better applied
to the turbulent area and the highly turbulent area, and is more
consistent with the actual working condition.13 Jul 2023Submitted to Engineering Reports 20 Jul 2023Submission Checks Completed
20 Jul 2023Assigned to Editor
20 Jul 2023Review(s) Completed, Editorial Evaluation Pending
24 Jul 2023Reviewer(s) Assigned
28 Sep 2023Editorial Decision: Revise Major
13 Oct 2023Submission Checks Completed
13 Oct 2023Assigned to Editor
13 Oct 2023Review(s) Completed, Editorial Evaluation Pending
16 Oct 2023Reviewer(s) Assigned
02 Nov 2023Editorial Decision: Revise Minor
13 Nov 20232nd Revision Received
14 Nov 2023Submission Checks Completed
14 Nov 2023Assigned to Editor
14 Nov 2023Review(s) Completed, Editorial Evaluation Pending
17 Nov 2023Editorial Decision: Accept