Weight Assignment Method and Application of Key Parameters in Shale Gas Resource Evaluation

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript called "Weight assignment method and application of key parameters in shale gas resource evaluation" whose authors are

Tianshu Yuan , Jinchuan Zhang, Bingsong Yu, Xuan Tang , Jialiang Niu, Menglian Sun is an excellent research from the methodological point of view as well as its realization in a specific geographical place.

I only find errors in the beginning of the references part that should be corrected.

From my point of view, after this correction the manuscript can be published.

Author Response

Dear reviewer，

I am honored that you have reviewed my manuscript. Thank you very much for providing revision suggestions for my manuscript. Your opinion is very professional and insightful. I will make modifications according to your suggestions.

Thank you for your careful and professional review.

Best wishes

Dr. Tianshu Yuan

"Weight assignment method and application of key parameters in shale gas resource evaluation" whose authors are Tianshu Yuan, Jinchuan Zhang,Bingsong Yu,Xuan Tang,Jialiang Niu, Menglian Sun is an excellent research from the methodological point of view as well as its realization in a specific geographical place.

I only find errors in the beginning of the references part that should be corrected.

From my point of view, after this correction the manuscript can be published.

Thank you for your careful and professional review. I found the issue of duplicate numbers in the references and have already corrected them all.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

 

I have reviewed the manuscript critically and have found it very interesting. The work reported by the authors is novel. In my opinion the manuscript should be accepted but after undergoing major revision. My comments are as follows:

 

1. There is a lot of grammatical and formatting errors in the paper. Check in the full paper.

2. Why evaluation methods for shale gas resources and the key parameters involved are diverse?

3. How does commercial shale gas generation take place?

4. How accuracy of common parameters affects the accuracy of resource evaluation?

5. Why there is no explanation for the figures? Please properly present the content.

6. Why are all variables for the equations not explained? Please explain them.

7. What is the difference between dispersion method, entropy method, Nemero index method?

8. What is the key contribution of this work? This is not clear and highlights the novelty properly in view of the literature and current work.

9. How does correlation coefficient act as a statistical indicator?

10. Conclusion should be more quantified. Please modify it.

Comments on the Quality of English Language

No comments

Author Response

Dear reviewer，

I am honored that you have reviewed my manuscript. Thank you very much for providing revision suggestions for my manuscript. Your opinion is very professional and insightful. I will make modifications according to your suggestions.

Thank you for your careful and professional review.

Best wishes

Dr. Tianshu Yuan

1. There is a lot of grammatical and formatting errors in the paper. Check in the full paper.

Thank you for your careful and professional review. I have checked the entire text and corrected any grammar and formatting errors.

2. Why evaluation methods for shale gas resources and the key parameters involved are diverse?

Thank you for your careful and professional review. Due to different levels of exploration in different regions and the main influencing factors of regional geological conditions, there are various methods for evaluating shale gas resources, and the key parameters are also diverse.

3. How does commercial shale gas generation take place?

Thank you for your careful and professional review. In Nie Haikuan 's 2020 publication  'Status and direction of legitimacy exhibition and development in China': The quality of organic rich shale is one of the most important factors, and deep-water shelf facies are recognized as favorable areas for shale gas enrichment; The structure and sedimentary background of shale control the distribution of organic rich shale, and deep-water areas far from the source area are usually better areas for shale reservoir development and shale gas enrichment. Shale gas content is an important part of shale gas selection evaluation, resource and reserve calculation, production capacity prediction, and gas reservoir evaluation. It is also one of the main factors determining whether shale gas reservoirs can be commercially exploited. Of course, the higher the shale gas content, the better.

4. How accuracy of common parameters affects the accuracy of resource evaluation?

Thank you for your careful and professional review. The accuracy of parameters is a basic condition for resource estimation, and common parameters need to be calculated to obtain the resource quantity. Therefore, the accuracy of parameters will directly affect the accuracy of resource estimation.

5. Why there is no explanation for the figures? Please properly present the content.

Thank you for your careful and professional review. I have provided additional explanations in the manuscript according to your feedback.

6. Why are all variables for the equations not explained? Please explain them.

Thank you for your careful and professional review. I have provided explanations in the manuscript based on your feedback.

7. What is the difference between dispersion method, ent.ropy method, Nemero index method?

Thank you for your careful and professional review. Dispersion method, entropy method, and Nemerow index method are three different mathematical methods for processing parameter values, used for different application scenarios and data analysis purposes. ‌

Dispersion method: It is related to the distribution and degree of dispersion of data, involving how to process or analyze data with different distribution characteristics, such as outlier handling, missing value handling, etc., to ensure the accuracy and reliability of data analysis.

Entropy method: Entropy method is a mathematical method used to determine the degree of dispersion of a certain indicator. The entropy method is generally used to determine the weights of each indicator. The greater the degree of dispersion, the greater the impact of this indicator on comprehensive evaluation.

Nemerow Index Method: Nemerow Index Method is a comprehensive evaluation score obtained by synthesizing the evaluation scores of each individual component.

In summary, although dispersion method, entropy method, and Nemerow index method are all methods used for data analysis or evaluation, their application scenarios, purposes, and calculation methods are different. The dispersion method focuses more on data processing and outlier handling, the entropy method is used to determine the weights of indicators for comprehensive evaluation, and the Nemerow index method is used to comprehensively evaluate and classify multiple individual indicators.

8. What is the key contribution of this work? This is not clear and highlights the novelty properly in view of the literature and current work.

Thank you for your careful and professional review. This article quantitatively analyzes the credibility of resource evaluation by assessing the impact of different parameters on resource assessment. The errors caused by parameters are re evaluated according to the degree of impact, improving the accuracy of resource estimation. The case study in this article proves the correctness of the method proposed in this article.

9. How does correlation coefficient act as a statistical indicator?

Thank you for your careful and professional review. The partial correlation coefficient in the correlation coefficient can represent the degree of influence of a single independent variable on the dependent variable among numerous independent variables. Therefore, this article uses partial correlation coefficient to measure the degree of influence of different variables on the estimation results of resource quantity.

10. Conclusion should be more quantified. Please modify it.

Thank you for your careful and professional review. I have added a fourth quantified conclusion as per your suggestion, in lines 379-384.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors,

The article is interesting and deserves to be published after minor revisions. The following corrections are suggested:

1. An analysis of the English language is necessary. There are errors, such as:

• Line 176: "The correlation coefficient is a statistical indicator used to reflect the degree of correlation between variables, usually represented by the letter r. Due to different research subjects and purposes, there are multiple correlation coefficients in the field of statistics." Here, the verb "is" should be "are" to agree with "coefficients." Moreover, the verb "are" should agree with "coefficients," so the sentence should be "the correlation coefficients are statistical indicators."
• Line 186: "partial regression coefficient" should be "partial correlation coefficient" to be consistent with the appropriate technical context.

My suggestion: the article should be reviewed by a native English speaker.

2. Different font styles are observed in the article—this might be a PDF error. The numbers in the matrices have different fonts from those used in the text.

3. Shouldn't there be measurement errors along with the calculated values?

4. In the case application, you cite data from 2019 and 2020. Are there no more recent data available?

5. Which computational methods (software) can be used to perform the calculations?

6. The email and contact information of the lead author – head of research – are missing.

Best wishes,

Comments on the Quality of English Language

A minor revision of the English language is necessary. There are errors in agreement and plurality.

Author Response

Dear reviewer，

I am honored that you have reviewed my manuscript. Thank you very much for providing revision suggestions for my manuscript. Your opinion is very professional and insightful. I will make modifications according to your suggestions.

Thank you for your careful and professional review.

Best wishes

Dr. Tianshu Yuan

1. An analysis of the English language is necessary. There are errors, such as:

Line 176:"The correlation coefficient is a statistical indicator used to reflect the degree of correlation between variables, usually represented by the letter r. Due to different research subjects and purposes, there are multiple correlation coefficients in the field of statistics." Here, the verb "is" should be "are" to agree with "coefficients." Moreover, the verb "are" should agree with "coefficients," so the sentence should be "the correlation coefficients are statistical indicators."

Line 186: "partial regression coefficient" should be "partial correlation coefficient" to be consistent with the appropriate technical context.

My suggestion: the article should be reviewed by a native English speaker.

Thank you for your careful and professional review. The 176th and 186th lines have been modified.

2. Different font styles are observed in the article--this might be a PDF error. The numbers in the matrices have different fonts from those used in the text.

Thank you for your careful and professional review. I have checked and standardized the font format in the text.

3. Shouldn't there be measurement errors along with the calculated values?

Thank you for your careful and professional review. Measurement error is an inevitable error.

My research is to evaluate the importance of different parameters and use the weight coefficient method to reduce the error caused by the importance of parameters in the calculation process, thereby improving the credibility of resource evaluation results.

4. In the case application, you cite data from 2019and 2020. Are there no more recent data available?

Thank you for your careful and professional review. Due to project reasons, the new data is still confidential and cannot be used for public release.

Author Response File: Author Response.pdf