Successful Integration of UAV Aeromagnetic Mapping with Terrestrial Methane Emissions Surveys in Orphaned Well Remediation

Round 1

Reviewer 1 Report

This paper discusses the identification of orphaned oil and gas wells thanks to the use of UAV aeromagnetometry data. The use of drones can be a promising tool for undiscovered wells identification and prioritization for wellsite remediation which in turn can benefit the environmental effort to cut methane emissions from unattended wells.

 

The methodology is well-defined and described.

It clearly explains various sources of data and how they were obtained.

It is neat and easy to read and follow.

The authors' suggestions about best practices for UAV mission planning are valuable and correct and indeed needed for the safety and quality of data. 

In terms of experimental technique, this paper is innovative in applying UAVs for large-area magnetic surveys and preliminary identification of possible high-emitting methane oil wells.

Well-thought research and delivery

 

The paper would have benefited greatly from one figure which would show how the orphaned unlocated previously wells can be distinguished from UAV aeromagnetometry data and the surroundings. And how well it correlates spacially with ground truth from a portable methane detector.

 

Also, about the comment that PMD sensor has poor internal GPS accuracy of a few meters - have you thought about implementing a GNSS solution from a UAV shelf next to/on top of PMD which would enable either a PPK or RTK accuracy? There are plenty of lightweight solutions on the market. Or use a surveying grade GPS enabling measurements even through a tree canopy while the methane data is collected. In that way, the well would be easily found even overgrown with tall grass. It would be interesting to see how well the magnetic anomalies correlate with a survey grade well position.

 

The article proves that low-altitude UAV magnetic surveys can be the only viable solution for unlocated well identification on a mass scale in terms of costs, accuracy and environmental benefits.

 

English correction:

Line 206 - There

 

I recommend that this paper be accepted and published.

Author Response

This paper discusses the identification of orphaned oil and gas wells thanks to the use of UAV aeromagnetometry data. The use of drones can be a promising tool for undiscovered wells identification and prioritization for wellsite remediation which in turn can benefit the environmental effort to cut methane emissions from unattended wells.

 

The methodology is well-defined and described.

It clearly explains various sources of data and how they were obtained.

It is neat and easy to read and follow.

The authors' suggestions about best practices for UAV mission planning are valuable and correct and indeed needed for the safety and quality of data. 

In terms of experimental technique, this paper is innovative in applying UAVs for large-area magnetic surveys and preliminary identification of possible high-emitting methane oil wells.

Well-thought research and delivery

 

Thank you for your thorough review, it is greatly appreciated.

 

The paper would have benefited greatly from one figure which would show how the orphaned unlocated previously wells can be distinguished from UAV aeromagnetometry data and the surroundings. And how well it correlates spacially with ground truth from a portable methane detector.

 We agree and have added a figure that we believe demonstrates this.

Also, about the comment that PMD sensor has poor internal GPS accuracy of a few meters - have you thought about implementing a GNSS solution from a UAV shelf next to/on top of PMD which would enable either a PPK or RTK accuracy? There are plenty of lightweight solutions on the market. Or use a surveying grade GPS enabling measurements even through a tree canopy while the methane data is collected. In that way, the well would be easily found even overgrown with tall grass. It would be interesting to see how well the magnetic anomalies correlate with a survey grade well position.

 

Thank you for the suggestion. We think the same and did some research and are now looking to integrate Emlid Reach in future research.

 

The article proves that low-altitude UAV magnetic surveys can be the only viable solution for unlocated well identification on a mass scale in terms of costs, accuracy and environmental benefits.

 

English correction:

Line 206 – There

 

Thanks, that is our oversight.

 

I recommend that this paper be accepted and published.

Reviewer 2 Report

1.     What is the main question addressed by the research?

 

In this study, it is presented  a database of identified and ground-truthed wellsites correlated to their magnetic signatures and provide a roadmap to initial prioritization of wellsites for subsequent reediation activities that can be implemented in complex environments where other survey options are not feasible

 

2  I consider the topic original or relevant in the field of journal

 

3. Did you use ground control points fort his study. Please give a table list of GCP and coordinates.

4. Please add sensor specifications as table and add UAV and specifications.

5. The conclusions consistent with the evidence and arguments presented

and do they address the main question posed.

6. I would like to recommend some updated papers about your study

Candan, L. & Kaçar, E. (2023). Methodology of real-time 3D point cloud mapping with UAV lidar . International Journal of Engineering and Geosciences , 8 (3) , 301-309 . DOI: 10.26833/ijeg.1178260

Erdal, K. & Makineci, H. B. (2023). Adaptation analysis of produced 3D models from UAV-SLAM and UAV-TLS data combinations . Mersin Photogrammetry Journal , 5 (1) , 18-23 . DOI: 10.53093/mephoj.1269630

Akay, S. S. , Ozcan, O. , Balık Şanlı, F. , Bayram, B. & Görüm, T. (2021). Assessing the spatial accuracy of UAV-derived products based on variation of flight altitudes . Turkish Journal of Engineering , 5 (1) , 35-40 . DOI: 10.31127/tuje.653631

Doğan, Y. & Yakar, M. (2018). GIS and three-dimensional modeling for cultural heritages . International Journal of Engineering and Geosciences , 3 (2) , 50-55 . DOI: 10.26833/ijeg.378257

Kaya, E., & Güngör, M. (2022). Numerical data generation using unmanned aerial vehicle: a case study of Aksaray Güzelyurt District. Advanced UAV, 1(1), 34–39. Retrieved from https://publish.mersin.edu.tr/index.php/uav/article/view/154

Author Response

What is the main question addressed by the research? 

In this study, it is presented  a database of identified and ground-truthed wellsites correlated to their magnetic signatures and provide a roadmap to initial prioritization of wellsites for subsequent reediation activities that can be implemented in complex environments where other survey options are not feasible

2  I consider the topic original or relevant in the field of journal

3. Did you use ground control points fort his study. Please give a table list of GCP and coordinates.

We did not use ground control points in this study.

4. Please add sensor specifications as table and add UAV and specifications.

We note the sensor specification on line 138-139. We have added the UAV specifications on line 133. We think a Table is not necessary as the important specifications can be briefly described in the text.

5. The conclusions consistent with the evidence and arguments presented

and do they address the main question posed.

6. I would like to recommend some updated papers about your study

Thank you for your comprehensive review, we have added these papers to the reference section and called them out in the text on line 105.

Candan, L. & Kaçar, E. (2023). Methodology of real-time 3D point cloud mapping with UAV lidar . International Journal of Engineering and Geosciences , 8 (3) , 301-309 . DOI: 10.26833/ijeg.1178260

Erdal, K. & Makineci, H. B. (2023). Adaptation analysis of produced 3D models from UAV-SLAM and UAV-TLS data combinations . Mersin Photogrammetry Journal , 5 (1) , 18-23 . DOI: 10.53093/mephoj.1269630

Akay, S. S. , Ozcan, O. , Balık Şanlı, F. , Bayram, B. & Görüm, T. (2021). Assessing the spatial accuracy of UAV-derived products based on variation of flight altitudes . Turkish Journal of Engineering , 5 (1) , 35-40 . DOI: 10.31127/tuje.653631

Doğan, Y. & Yakar, M. (2018). GIS and three-dimensional modeling for cultural heritages . International Journal of Engineering and Geosciences , 3 (2) , 50-55 . DOI: 10.26833/ijeg.378257

Kaya, E., & Güngör, M. (2022). Numerical data generation using unmanned aerial vehicle: a case study of Aksaray Güzelyurt District. Advanced UAV, 1(1), 34–39. Retrieved from https://publish.mersin.edu.tr/index.php/uav/article/view/154

Reviewer 3 Report

Comments for author File: Comments.pdf

Author Response

Orphaned oil and gas wells represent an important environmental and economic development concern in areas and Its detection is a very worthwhile research problem. In this manuscript, the authors adopted the magnetic anomaly detection method to identify them and present a database of identified and ground-truthed wellsites correlated to their magnetic signatures and provide a roadmap to initial prioritization of wellsites for subsequent remediation activities that can be implemented in complex environments where other survey options are not feasible. This work is very valuable and it can be accepted after making several revisions.

Thank you for your kind comments and thorough review. We appreciate the constructive comments below that help to materially improve the manuscript.

• The authors used the hybrid UAV with magnetometer to make magnetic field survey, it may be more beneficial for readers to understand the magnetic detection effect, if the author can describe the performance index of the UAV and magnetometer used.

Thank you for this comment. We agree and are currently preparing a manuscript on exactly this to the journal Drones.

• It cannot clearly see the whole process to find and identify the Orphaned oil and gas wells, it will be to outline the whole process, including how to measure the magnetic data, process magnetic data, and identify the target’s signal.

Thank you for this comment. We have added to the methods and outline the magnetometers specifications, data acquisition, processing, and target identification in lines 129-146.