Intelligent Stuck Pipe Type Recognition Using Digital Twins and Knowledge Graph Model
Round 1
Reviewer 1 Report
The article is written at a very good level and supported by objective research. English should have small corrections because they are long and hard to understand. ( do it more simply) row 434 -440, row 511-518, row 494 - 498.
Author Response
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Reviewer 2 Report
The paper provides an overview of intelligent Stuck-Pipe type recognition This paper should be of various researchers’ interest. The summary is inadequate to the content of the article. Moreover, the title does not correlate with the content of the whole.
In terms of the methods used, they are of a high standard.Author doesn’t indicate the purpose of the article. The key words are well written. The quality of the language is appropriate, however, the author sometimes uses expressions in informal style and a few sentences are unclear to the reader. What I suggest it to change the title of a paper. The review of the literature is no fairly up-to-date. Unfortunately, the conclusion is so poorand clear. Autors should change a conclusion and will write a recommendation. The paper is of appropriate length and suggestions are well-written.
The organization of sections is satisfactory (Introducton, research background, purpose of the article, Methodology/methods, outcome). What I suggest it to change the abstract and title of a paper. The review of the literature is no fairly up-to-date.
In the theoretical section, the author don't explores the notion of health education, intervention. References section is ok, but conclusion must be correct. The paper is of acceptable scientific quality, but the author must address the comments and suggestions. The paper requires revision.
Author Response
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Reviewer 3 Report
This work is interesting and meaningful. In this paper, the identification of sticking degree was studied based on physical model and particle swarm optimization algorithm. Also, the recognition system of stuck drill type based on knowledge graph was established. The efficiency of model recognition could be improved by dual drive of digital twin and knowledge graph used in this paper. However, it is not well written. There are some incorrect or strange using of the phases in the paper, which makes the paper difficult to be understood. There are some other comments.
1. The Abstract should be rewritten since it is not clearly what is the contribution of this paper to the researches in the related field.
2.In the Introduction section, the author should write clearly what is the knowledge gap in the field, so as to give a more clear and convincing interpretation of the objective of the paper.
Author Response
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Reviewer 4 Report
Dear Authors,
I carefully read this very interesting manuscript related to the recognition of stuck-pipe type using the Digital Twins and the Knowledge Graph Model. To improve the quality of this manuscript, I have added more comments as follows:
- The abstract: there is no mention of the method/technique to recognize the pipe sticking type
- Line 19 -> 21: this sentence may be rewritten to highlight the idea of the authors.
- Lines 30 ->34; 249-> 329: give the citation
- Use the appropriate glossary: e.g: ‘drill pipe’ instead of ‘pit shaft’, ‘heavy weight drill pipe’ instead of ‘weighted drill pipe’
- Ref 15 is mentioned in the list of references, without being cited in the work
- The content from lines 77 to 90, the author should mention the advantages of the knowledge graph in recognition of pipe sticking type when compared to other methods.
- Line 452: correct the name of the well used to analyze.
Kind regards,
Reviewer
Author Response
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Round 2
Reviewer 3 Report
The manuscript has been revised, however, there still exist some problems should to be corrected.
1.There are some writing mistakes, especially incorrect use of punctuations, for example, in Line 71 there exist an extra space; in Line 142 there is lack of a space. The similar problem exist in some other lines. The author should re-check the use of punctuations carefully.
2.The first letter of the table header is not capitalized for Table 2, table 3. The similar problem exist in some other lines. The author should re-check it carefully.
3.In Line 474, Table 1, 2 and 3 appear again, while they should be renumbered as table 8,9 and 10. The same problem exist for some figure number. The author should re-check the numbers carefully.
4. Please go over the manuscript thoroughly before submission.
Author Response
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