Next Article in Journal
A Broadband Information Metasurface-Assisted Target Jamming System for Synthetic Aperture Radar
Next Article in Special Issue
Estimation of Land Deformation and Groundwater Storage Dynamics in Shijiazhuang–Baoding–Cangzhou–Hengshui Using Multi-Temporal Interferometric Synthetic Aperture Radar
Previous Article in Journal
Optimizing Optical Coastal Remote-Sensing Products: Recommendations for Regional Algorithm Calibration
Previous Article in Special Issue
Estimation of Co-Seismic Surface Deformation Induced by 24 September 2019 Mirpur, Pakistan Earthquake along an Active Blind Fault Using Sentinel-1 TOPS Interferometry
 
 
Article
Peer-Review Record

Surface Displacement Evaluation of Canto Do Amaro Onshore Oil Field, Brazil, Using Persistent Scatterer Interferometry (PSI) and Sentinel-1 Data

Remote Sens. 2024, 16(9), 1498; https://doi.org/10.3390/rs16091498
by Lenon Silva de Oliveira 1, Fabio Furlan Gama 1,*, Edison Crepani 1, José Claudio Mura 1 and Delano Menecucci Ibanez 2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Reviewer 4: Anonymous
Remote Sens. 2024, 16(9), 1498; https://doi.org/10.3390/rs16091498
Submission received: 12 March 2024 / Revised: 17 April 2024 / Accepted: 19 April 2024 / Published: 24 April 2024
(This article belongs to the Special Issue Monitoring Geohazard from Synthetic Aperture Radar Interferometry)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. The introduction of the paper lacks clarity in explaining the novelty of the work. While the authors briefly mention the implementation of quantitative analyses of deformational processes in oil and gas production fields, they fail to adequately articulate the specific gaps or challenges in the existing literature that their research addresses. Moreover, there is a notable absence of citations supporting their claim and demonstrating a comprehensive understanding of the relevant literature in this field.

2.The authors assert that their technique facilitates statistical analyses of phase errors associated with atmospheric conditions and/or other noises using a substantial image dataset. However, it is essential to note that the dataset utilized in the study consists of only 42 images spanning a relatively short period from 2020 to 2021. A larger dataset encompassing a more extended time period would provide a broader range of observations, thereby enhancing the reliability and generalizability of the analysis results.

3. In Figure 7, it is observed that the STA2 area is not delineated, while there are two regions labeled as STA1. Clarification is needed to ascertain whether one of the labeled STA1 regions corresponds to STA2 or if STA2 has been inadvertently omitted from the visualization.

4. The authors state that the deformation velocities obtained for the region exhibit a wide range, from -20.93 mm/year to 14.63 mm/year, with the maximum peaks of uplift and subsidence possibly associated with erosion and sedimentation processes along water resource margins. However, it is crucial to inquire about the specific processes responsible for such significant variations within a relatively short time frame. The observed range of deformation velocities suggests dynamic and complex geological processes at play. It would be valuable for the authors to provide further insights into the mechanisms driving these variations, especially considering the short-term nature of the study period. Factors such as tectonic activity, hydrological changes, anthropogenic influences, and geotechnical properties of the subsurface could all contribute to the observed deformation patterns. Additionally, while the hypothesis of erosion and sedimentation along water resource margins may offer one possible explanation, it may not fully account for the magnitude of deformation rates observed, particularly in the context of the semi-arid climate of the study area.

5. The authors state that the mean velocity used in their grid shows relatively low deformation rates rates compared to other studies conducted in oil fields. However, it's important to note that deriving a mean velocity over a grid of 500x500m may not provide sufficiently detailed insights, especially when considering the low density of points used to construct the grid. The use of a grid-based approach could potentially mask localized deformation patterns, particularly in areas adjacent to the oil and gas fields where severe deformations are observed. It would be prudent for the authors to consider the possibility of deformation migration resulting from fluid injection and extraction activities in these adjacent areas. This could lead to deformations occurring not only directly beneath the oil fields but also in surrounding regions due to the migration of subsurface fluids.

Author Response

1) Answer: The introduction was improved with more citations describing their results in different oil exploitation regions. Our study differs from other studies because our test site region it is semi-arid region in Brazil with a dense shrubby Caatinga, with heavy rains during the summer and autumn, in where the oil extraction is carried out in small areas of vegetation clearings. This information was added too in the last paragraph of the introduction.

2) Answer: Our study analyzed two years of Sentinel-1, we agree that would be interesting to investigate a longer surveying, but is necessary take in account the oil exploitation data available. We added this information in the conclusion chapter.

3) Answer: The figure 7 (after changes it is figure 8) was corrected and the STA2 label was inserted now.

4) Answer: The paragraph was changed to be clearer, pointing out that “this behavior can be caused by erosion and sedimentation processes along water resource margins associated to rainy season as well”.

5) Answer: Due to the low density of PS and the oil exploitation and the injection influence is not punctual effect, the process affects the neighbor well too. So, we decide to use the grid to perform the analysis obtaining a synoptic view to the deformation.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

In this manuscript, the surface deformation characteristics of the Canto do Amaro coastal oilfield area were investigated using PS-InSAR technology and Sentinel-1 data. The relationship between data point density and surface coverage, the relationship between surface deformation and oil and gas production, and the impact of fault activity on the distribution of surface deformation were analyzed. The research results provide a reference for mastering the deformation characteristics of the Canto do Amaro field and understanding the influencing factors of surface deformation.

1)line 44 , it is usually using LOS as the abbreviation for 'Line of Sight'. It is recommended to correct and unify the entire text.

2)line 50,  line 58, please use "DInSAR" instead of "DinSAR", It is recommended to correct and unify the entire text.

3)1. Introduction, the purpose of this study and the problems to be solved are not clear enough.

4)Table 1. The parameters are too general, and it seems that the time period of the data and the path, frame, and other information should be introduced more.

5)Table 2. It is recommended to use a spatiotemporal baseline distribution map instead of a table for more intuitive purposes.

6)3.2. Recommend merging the three paragraphs into one.

7)line 50, Repeated introduction of 'Line of Sight'.

8)4.2.1. How is the accuracy of monitoring results evaluated? Is there external data to validate the results? For example, leveling and GNSS measurement results.

9)Figure 9. In the legend of colors, "," is used instead of "." in the numerical values. Please confirm.

Author Response

1) Answer: The Abbreviation was corrected along the article.

2) Answer: The expression DInSAR was corrected along the article

3) Answer:  The test site differs from other regions because it is semi-arid region in Brazil with a dense bush savannah, with heavy rains during the summer and autumn, in where the oil extraction is carried out in small areas of vegetation clearings. This information was added in the last paragraph of the introduction.

4) Answer: More information about the images used was added in the Table 1.

5) Answer: The spatiotemporal baseline distributions was added (Figure 06).

6) Answer: The correction was made.

7) Answer: The correction was made.

8) Answer: unfortunately, there wasn’t leveling and GNSS measurement in order to validate the numeric values, but the results showed the trends in terms of velocity of deformation. In the conclusions, we added a comment suggesting using the GNSS and levelling for future works.

9) Answer: The legend of colors was fixed.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

see attached file

Comments for author File: Comments.pdf

Author Response

1) In general, the document describes in a very detailed way the theoretical framework, facilitating the understanding and giving a clear picture of the subject matter, however, for the analysis of the results, it lacks depth. A more specific analysis should be carried out, perhaps taking some reference wells and comparing the individual deformation series with the production series of those wells.

Answer: Due to the low density of PS and the oil exploitation and the injection influence is not punctual effect, the process affect the neighbor well too. So we decide to use the grid to perform the analysis obtaining a synoptic view to the deformation.

2) page 1, line 44: Line Of Sight (LOS)

Answer: The Abbreviation was corrected along the article.

3) Page 6, line 175: a point is missing... across all images. Afterwards,

Answer: It was corrected.

4) Figure 6 shows results obtained for the SAVI, a brief introduction to the index and its estimation would be adequate.

Answer: We added a brief introduction to SAVI as recommended.

Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

Generally, this is a well-written paper, which focuses on the hot topic of monitoring surface displacement by InSAR. At present form, this paper have some improvements needed to be made before it can be accepted:

1) InSAR technique have been widely used for assessing surface displacement. What are the innovations of this study? This should be clearly clarified in the Introduction Section.

2) How large is the area of the study area? Is image mosaic needed to cover the study area?

3) latitude and longitude labels in Fig. 1 are not correct.

4) In Abstract, "......with a dataset comprising 42 Sentinel-1 images, from July 23, 2020, to December 21, 2021."  but, in Table 2, the time and the number of images are not consistent with that in Abstract.

5) Figure 6, how was the vegetation cover information obtained? By classification using Sentinel-1 images or using optical images or other dataset? 

6) No surface displacement maps covered the whole study area are provided, and the authors only displayed the displacement on some points. Considering providing surface displacement maps in some different periods.

7) Can we use some methods or other data sources to validate the reliability of surface displacement assessment results.

Author Response

1) InSAR techniques have been widely used for assessing surface displacement. What are the innovations of this study? This should be clearly clarified in the Introduction Section.

Answer: This test site differs from other regions because it is semi-arid region in Brazil with a dense bush savannah, with heavy rains during the summer and autumn, in where the oil extraction is carried out in small areas of vegetation clearings. This information was added in the last paragraph of the introduction.

2) How large is the area of the study area? Is image mosaic needed to cover the study area?

Answer: The interest area (oil wells) was covered by the Sentinel-1A swath, without be necessary to do a mosaic, only the deburst pre-processing. This information was added in the Chapter 3 in the first paragraph.

3) Latitude and longitude labels in Fig. 1 are not correct.

Answer: The coordinates were changed to geographic form.

4) In Abstract, "......with a dataset comprising 42 Sentinel-1images, from July 23, 2020, to December 21, 2021." but, in Table 2, the time and the number of images are not consistent with that in Abstract.

Answer: The table 2 was removed and a spatiotemporal baseline distribution was added (Figure 5).

5) Figure 6, how was the vegetation cover information obtained? By classification using Sentinel-1 images or using optical images or other dataset?

Answer: It was used Sentinel-2 for the SAVI analysis, this information was added in the third paragraph of chapter 4.1.

6) No surface displacement maps covered the whole study area are provided, and the authors only displayed the displacement on some points. Considering providing surface displacement maps in some different periods.

Answer: Due the low interferometric coherence in the study area caused by the Caatinga vegetation (Figure 7. Multitemporal analysis of vegetation change in Canto do Amaro site), and the rain during the period of analysis, the number of PS decreased and in most part of the area disappeared.

7)Can we use some methods or other data sources to validate the reliability of surface displacement assessment results?

Answer: The use of GNSS data could be an interesting for numeric validation of the deformation number. Unfortunately, there isn’t this equipment installed in the test site. We added this suggestion on the final conclusions.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you for your revised manuscript and for addressing all the concerns raised during the review process. I believe that your responses and adjustments have improved the manuscript's clarity and overall quality.

I did not identify any further issues.

Author Response

We express our sincere appreciation for all your suggestions, as we firmly believe that our work has been significantly enhanced by your contributions. Thank you very much.

Reviewer 2 Report

Comments and Suggestions for Authors

The issues I am concerned about have been addressed in the revised manuscript, and the quality and readability of the manuscript have been significantly improved.

1) On page 8, 3.2, please briefly supplement the frequency and accuracy of data collection.

2) Please explain in the text what the SAVI values of 1 and -1 in Figure 7 represent, respectively?

Author Response

1) On page 8, 3.2, please briefly supplement the frequency and accuracy of data collection.

Answer: Alterations have been made to this section to facilitate the interpretation of the frequency and origin of the production data collection utilized in the analysis.

2) Please explain in the text what the SAVI values of 1 and -1 in Figure 7 represent, respectively?

Answer: We have added an explanation for the SAVI values ranging from -1 to 1 (Line 283 to 285).

We express our gratitude for all the suggestions provided and hope that the current modifications have improved the clarity of the text. Thank you very much.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors made suggestions and clarified the analysis performed.

Author Response

We express our sincere appreciation for all your suggestions, as we firmly believe that our work has been significantly enhanced by your contributions. Thank you very much.

Reviewer 4 Report

Comments and Suggestions for Authors

The authors have well addressed my questions. No more questions.

Author Response

We express our sincere appreciation for all your suggestions, as we firmly believe that our work has been significantly enhanced by your contributions. Thank you very much.

Back to TopTop