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Productivity Prediction Model for Stimulated Reservoir Volume Fracturing in Tight Glutenite Reservoir Considering Fluid-Solid Coupling

Overview of attention for article published in Frontiers in Energy Research, November 2020
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1 X user

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6 Mendeley
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Title
Productivity Prediction Model for Stimulated Reservoir Volume Fracturing in Tight Glutenite Reservoir Considering Fluid-Solid Coupling
Published in
Frontiers in Energy Research, November 2020
DOI 10.3389/fenrg.2020.573817
Authors

Leng Tian, Xiaolong Chai, Peng Wang, Hengli Wang

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 17%
Researcher 1 17%
Lecturer > Senior Lecturer 1 17%
Unknown 3 50%
Readers by discipline Count As %
Energy 2 33%
Business, Management and Accounting 1 17%
Unknown 3 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 November 2020.
All research outputs
#20,666,963
of 23,262,131 outputs
Outputs from Frontiers in Energy Research
#1,319
of 3,424 outputs
Outputs of similar age
#353,903
of 414,162 outputs
Outputs of similar age from Frontiers in Energy Research
#37
of 111 outputs
Altmetric has tracked 23,262,131 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,424 research outputs from this source. They receive a mean Attention Score of 1.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 414,162 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.