Evaluating Petrophysical Properties Using Digital Rock Physics Analysis: A CO2 Storage Feasibility Study of Lithuanian Reservoirs
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis work aims to explore the feasibility of Lithuanian deep saline aquifers, particularly Syderiai and Vaskai, for effective CO2 storage. My detailed comments in this round:
1) Quantitative descriptions can be added appropriately to the abstract.
2) Page 1 Line nos. 36-43: please complement and enrich current statement with related literature: “Dynamic Evaluation of Sealing and Site Optimization for Underground Gas Storage in Depleted Gas Reserve: A Case Study. Applied Sciences, 2024, 14(1), 298”.
3) Except for the flow of research work, the last paragraph of the Introduction section must give a brief idea about the research gap and.
4) Definitely, not all figures are required to demonstrate the work, such as Fig.5.
5) What is the significance of the Section 6? Is it necessary to retain it?
6) The authors should improve the Figure, such as Fig. 12, 13 & 14. All the legends must be corrected and the resolution should be ensured.
7) Conclusion has been explained well, but it must be briefed up. Please put enough emphasis on the points of novelty of the proposed study in your Conclusions.
Author Response
Response to Reviewers Comments
Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted in the re-submitted files.
Reviewer 1
This work aims to explore the feasibility of Lithuanian deep saline aquifers, particularly Syderiai and Vaskai, for effective CO2 storage. My detailed comments in this round:
Comment 1: Quantitative descriptions can be added appropriately to the abstract.
Response 1: Thank you for your suggestion. The abstract has been modified and quantitative description has been added to the abstract. The modified abstract is as follows:
“As global concern over greenhouse gas emissions grows, COâ‚‚ storage in deep saline aquifers and depleted reservoirs has become crucial for climate mitigation. This study evaluates the feasibility of Lithuanian deep saline aquifers, specifically Syderiai and Vaskai, for effective COâ‚‚ storage. Unlike previous theoretical analyses, it provides experimental data on static and dynamic reservoir parameters that impact COâ‚‚ injection and retention. Using Micro X-ray Computed Tomography (MXCT) and multi-resolution scanning at 8 µm and 22 µm, digital rock volumes (DRVs) from core samples were created to determine porosity and permeability. The method, validated against analogous samples, identified a representative element volume (REV) within sub-volumes, showing a homogeneous distribution of petrophysical properties in Lithuanian samples. Results show DRVs can accurately reflect pore-scale properties, achieving 90-95% agreement with lab measurements, and offer a rapid, efficient means to analyze storage potential. These insights confirm that Lithuanian aquifers are promising for COâ‚‚ sequestration, with recommendations for further long-term monitoring and application of this technique across the region.”
Comment 2: Page 1 Line nos. 36-43: please complement and enrich current statement with related literature: “Dynamic Evaluation of Sealing and Site Optimization for Underground Gas Storage in Depleted Gas Reserve: A Case Study. Applied Sciences, 2024, 14(1), 298”.
Response 2: Thank you for your suggestion. To complement the statement from line 36-43, the related literature has been cited, as reference number 2.
Comment 3: Except for the flow of research work, the last paragraph of the Introduction section must give a brief idea about the research gap.
Response 3: Thank you for your comment. The research gap has been addressed from lines 73-82 in the Introduction section.
Comment 4: Definitely, not all figures are required to demonstrate the work, such as Fig.5.
Response 4: Thank you for pointing this out. The figure 5 has been removed from the manuscript as per your suggestion.
Comment 5: What is the significance of the Section 6? Is it necessary to retain it?
Response 5: Section 6 presents an assessment of the CO2 storage capacity of Lithuanian saline aquifers, Syderiai and Vaskai, which were also used in the present study for petrophysical characterization using digital volumes. The section 6 demonstrates that these aquifers have significant potential for CO2 storage, highlighting their capability to store CO2 within a considerable capacity range. Therefore, we think it’s important to highlight the storage efficiency of the saline aquifers.
Comment 6: The authors should improve the Figure, such as Fig. 12, 13 & 14. All the legends must be corrected and the resolution should be ensured.
Response 6: Thank you for pointing this out. The Figures 12, 13 and 14 have been modified and updated in the manuscript.
Comment 7: Conclusion has been explained well, but it must be briefed up. Please put enough emphasis on the points of novelty of the proposed study in your Conclusions.
Response 7: Thank you for your comment. The conclusion has been modified with emphasis on novelty of the study. The modified conclusion is,
“The present study explored the utility of digital rock volumes (DRVs) in evaluating a reservoir's capacity for effective CO2 storage, focusing on two pivotal parameters: porosity and permeability. Recognizing that subsurface fluid storage and flow processes occur at the pore scale, this research used DRVs to examine pore distribution and flow characteristics in Lithuanian deep saline aquifers (Syderiai and Vaskai) and similar formations. Notably, this work fills a gap in the literature by providing experimental data for a region where such information was previously unavailable. The findings show that employing a combination of algorithms for pore space segmentation achieves accuracy levels of 90-95% compared to laboratory measurements, validating reliability of DRV method. Clay-related image segmentation challenges were addressed effectively within the workflow. This novel application of DRVs provides new insights into Lithuanian reservoirs, offering valuable data for COâ‚‚ storage efficiency and long-term reservoir stability.
The study also acknowledges scale-related limitations, particularly in heterogeneous samples, suggesting future work with diverse samples and tailored segmentation algorithms. Upscaling petrophysical properties and evaluating geo-mechanical and geochemical effects are recommended to support safe, long-term COâ‚‚ storage. This research offers a methodological framework for future COâ‚‚ storage studies in the Baltic Basin and similar regions, benefiting academic and industry applications.”
Reviewer 2
Comment 1: The abstract does not provide an in-depth description and analysis of the research results on the use of Lithuanian crude oil reservoirs for CO2 storage. In addition, the author is considering whether carbonation in aquifers during CO2 storage will damage the reservoir rock and reduce its storage safety.
Response 1: Thank you for your comment. In the present study, the Lithuanian saline aquifers have been assessed and therefore the focus are only saline aquifers. When dealing with CO2 storage it is important to highlight the risks associated with the long-term storage. Therefore, a brief discussion has been done on the geochemical and geomechanical implications of long-term CO2 storage.Top of Form
Bottom of Form
Comment 2: The large-scale CO2 emission area in Figure 1 is far away from the oil field concentration area and storage area, which creates great economic pressure and safety risks for the pressurization and transportation of CO2. What are the reasons for the author to choose the geographical location of the above saline-alkali aquifer?
Response 2: Figure 1 shows the location of various CO2 emission sources and the distribution of reservoirs in the Baltic Basin region. Figure 2 highlights the location of the two main saline aquifers in Lithuania, Syderiai and Vaskai. From Figure 1 and Figure 2, it is evident that the CO2 emission sources are located relatively close to the two saline aquifers, with the largest emission source situated nearest to the Syderiai saline aquifer. Additionally, the properties of the saline aquifers—such as porosity, permeability, depth, and the presence of a sealing layer above the aquifer zone—make them suitable for CO2 storage. The storage capacity assessment of the Lithuanian reservoirs indicates that both the Syderiai and Vaskai aquifers show great potential for CO2 sequestration.
Comment 3: The author needs to add the parameter meanings and related parameter units of the many equations appearing in the original literature, or the author can make an index table at the end of the article to summarize all the parameters appearing in the equations.
Response 3: Thank you for your suggestions. The parameters along with their meaning and units have been defined for the equations in the manuscript.
Comment 4: Another sentence was added to express the "The fracturing or drilling process of hydrocarbon reservoirs also provides convenience for CO2 storage" in the introduction section, And it needs to be supported by some papers: The Carrying Behavior of Water-Based Fracturing Fluid in Shale Reservoir Fractures and Molecular Dynamics of Sand Carrying Mechanism. ---A Numerical Investigation on Kick Control with Displacement Kill Method during Well Test in Deep-water Gas Reservoir: Case Study.
Response 4: Thanks for your comment, but I am afraid this comment does not seem to be related to our manuscript.
Comment 5: What is the number of experimental tests n for the porosity error in Table 4? And why is the error of the BB model porosity in Table 4 significantly higher than that of SS and L? In addition, the permeability in Table 5 shows completely different characteristics from Table 4, while permeability and porosity should be in direct proportion.
Response 5: Thank you for your comment. The higher error percentage in BB is due to the presence of clay in the sample, which tends to impact the pore space and reduce the porosity. Moreover, the size of the samples presented in Table 4 and 5 are different. Table 4 presents the porosity estimated from the whole volume, while Table 5 presents the permeability values obtained for each sub-volume. Therefore, the smaller sub-volumes tend to capture the local heterogeneities and show the variability which could not be seen when whole volume is assessed.
Comment 6: The error of the 22um permeability data in Figure 13 is significantly greater than that of the 8um permeability data, but the author did not analyze the underlying reasons in detail in the article. In addition, why is the error of S3 significantly lower than that of V4?
Response 6: Thank you for pointing this out. The error in 8µm data is lower because of the high resolution of the images, which provides a detailed view of the intricacies of the rock sample. Moreover, the sub volumes were extracted from the whole scanned volume, where different volumes have different arrangement of pores and grains, leading to differences in the permeability and porosity values in each sub volume. This variation has resulted in a significantly higher error in 22µm data compared to 8µm data. The sample S3 comes from the Syderiai saline aquifer, whereas the sample V4 is from the Vaskai saline aquifer in Lithuania. Their differing mineralogical compositions also impact the MXCT scanning process, resulting in varying error percentages.
Reviewer 3
The study will be more interesting if samples from other countries will be covered, at the least three different European countries.
Comment 1: Table 1 should be removed from the introduction and add it to the supplementary information
Response 1: Thank you for suggestion. The Table 1 gives a brief review of the advancements in CCS studies and is important to be included in the Introduction section as it helps address the gap and define the novelty of the present work.
Comment 2: The same comment goes to the figure 1 & 2
Response 2: Thank you for your comment. The Figures 1 and 2 are important as they highlight the distribution and location of reservoirs in Baltic region specifically Lithuania.
Comment 3: Introduction should be one paragraph
Response 3: Thanks for your comment, I am afraid such a guideline is not provided by the journal.
Comment 4: No need to add figure 5
Response 4: Thank you for pointing this out. The figure 5 has been removed from the manuscript as per your suggestion.
Comment 5: The methodology looks too much confusing, please remove unnecessary information, and it should be one paragraph.
Response 5: Thank you for your comment. Section 3 has been updated, and a new sub-section “3.4. Methodology Adopted” had been added to describe the workflow employed for processing the images.
Comment 6: The structure of the paper needs to be reviewed
Response 6: Thank you for pointing this out. The structure of the manuscript has been thoroughly reviewed and updated. A new sub-section has been defined in section 3 to improve clarity.
Comment 7: The results discussion is not supported by the updated literature (e.g.: Modeling CO2 Adsorption in a Thin Discrete Packing)
Response 7: Thank you for your comment. The literature has been cited in the Discussion section.
Comment 8: The quality of the displayed figures is very poor (remove the grey line and use tick marks supported by the error bar).
Response 8: Thank you for pointing this out. The quality of the figures has been improved by increasing the resolution, removing the grey line and adding tick marks. The updated figures 12, 13 and 14 have been added to the manuscript.
Comment 9: Please revise the conclusion and remove unnecessary information.
Response 9: Thank you for your feedback. The conclusion has been modified as per your suggestions. The modified conclusion is as follows:
“The present study explored the utility of digital rock volumes (DRVs) in evaluating a reservoir's capacity for effective CO2 storage, focusing on two pivotal parameters: porosity and permeability. Recognizing that subsurface fluid storage and flow processes occur at the pore scale, this research used DRVs to examine pore distribution and flow characteristics in Lithuanian deep saline aquifers (Syderiai and Vaskai) and similar formations. Notably, this work fills a gap in the literature by providing experimental data for a region where such information was previously unavailable. The findings show that employing a combination of algorithms for pore space segmentation achieves accuracy levels of 90-95% compared to laboratory measurements, validating reliability of DRV method. Clay-related image segmentation challenges were addressed effectively within the workflow. This novel application of DRVs provides new insights into Lithuanian reservoirs, offering valuable data for COâ‚‚ storage efficiency and long-term reservoir stability.
The study also acknowledges scale-related limitations, particularly in heterogeneous samples, suggesting future work with diverse samples and tailored segmentation algorithms. Upscaling petrophysical properties and evaluating geo-mechanical and geochemical effects are recommended to support safe, long-term COâ‚‚ storage. This research offers a methodological framework for future COâ‚‚ storage studies in the Baltic Basin and similar regions, benefiting academic and industry applications.”
Reviewer 2 Report
Comments and Suggestions for Authors1: The abstract does not provide an in-depth description and analysis of the research results on the use of Lithuanian crude oil reservoirs for CO2 storage. In addition, the author is considering whether carbonation in aquifers during CO2 storage will damage the reservoir rock and reduce its storage safety.
2: The large-scale CO2 emission area in Figure 1 is far away from the oil field concentration area and storage area, which creates great economic pressure and safety risks for the pressurization and transportation of CO2. What are the reasons for the author to choose the geographical location of the above saline-alkali aquifer?
3: The author needs to add the parameter meanings and related parameter units of the many equations appearing in the original literature, or the author can make an index table at the end of the article to summarize all the parameters appearing in the equations.
4: Another sentence was added to express the "The fracturing or drilling process of hydrocarbon reservoirs also provides convenience for CO2 storage"in the introduction section, And It needs to be supported by some papers: The Carrying Behavior of Water-Based Fracturing Fluid in Shale Reservoir Fractures and Molecular Dynamics of Sand-Carrying Mechanism. ---A Numerical Investigation on Kick Control with Displacement Kill Method during Well Test in Deep-water Gas Reservoir: Case Study.
5: What is the number of experimental tests n for the porosity error in Table 4? And why is the error of the BB model porosity in Table 4 significantly higher than that of SS and L? In addition, the permeability in Table 5 shows completely different characteristics from Table 4, while permeability and porosity should be in direct proportion.
6: The error of the 22um permeability data in Figure 13 is significantly greater than that of the 8um permeability data, but the author did not analyze the underlying reasons in detail in the article. In addition, why is the error of S3 significantly lower than that of V4?
Author Response
Reviewer 2
Comment 1: The abstract does not provide an in-depth description and analysis of the research results on the use of Lithuanian crude oil reservoirs for CO2 storage. In addition, the author is considering whether carbonation in aquifers during CO2 storage will damage the reservoir rock and reduce its storage safety.
Response 1: Thank you for your comment. In the present study, the Lithuanian saline aquifers have been assessed and therefore the focus are only saline aquifers. When dealing with CO2 storage it is important to highlight the risks associated with the long-term storage. Therefore, a brief discussion has been done on the geochemical and geomechanical implications of long-term CO2 storage.Top of Form
Bottom of Form
Comment 2: The large-scale CO2 emission area in Figure 1 is far away from the oil field concentration area and storage area, which creates great economic pressure and safety risks for the pressurization and transportation of CO2. What are the reasons for the author to choose the geographical location of the above saline-alkali aquifer?
Response 2: Figure 1 shows the location of various CO2 emission sources and the distribution of reservoirs in the Baltic Basin region. Figure 2 highlights the location of the two main saline aquifers in Lithuania, Syderiai and Vaskai. From Figure 1 and Figure 2, it is evident that the CO2 emission sources are located relatively close to the two saline aquifers, with the largest emission source situated nearest to the Syderiai saline aquifer. Additionally, the properties of the saline aquifers—such as porosity, permeability, depth, and the presence of a sealing layer above the aquifer zone—make them suitable for CO2 storage. The storage capacity assessment of the Lithuanian reservoirs indicates that both the Syderiai and Vaskai aquifers show great potential for CO2 sequestration.
Comment 3: The author needs to add the parameter meanings and related parameter units of the many equations appearing in the original literature, or the author can make an index table at the end of the article to summarize all the parameters appearing in the equations.
Response 3: Thank you for your suggestions. The parameters along with their meaning and units have been defined for the equations in the manuscript.
Comment 4: Another sentence was added to express the "The fracturing or drilling process of hydrocarbon reservoirs also provides convenience for CO2 storage" in the introduction section, And it needs to be supported by some papers: The Carrying Behavior of Water-Based Fracturing Fluid in Shale Reservoir Fractures and Molecular Dynamics of Sand Carrying Mechanism. ---A Numerical Investigation on Kick Control with Displacement Kill Method during Well Test in Deep-water Gas Reservoir: Case Study.
Response 4: Thanks for your comment, but I am afraid this comment does not seem to be related to our manuscript.
Comment 5: What is the number of experimental tests n for the porosity error in Table 4? And why is the error of the BB model porosity in Table 4 significantly higher than that of SS and L? In addition, the permeability in Table 5 shows completely different characteristics from Table 4, while permeability and porosity should be in direct proportion.
Response 5: Thank you for your comment. The higher error percentage in BB is due to the presence of clay in the sample, which tends to impact the pore space and reduce the porosity. Moreover, the size of the samples presented in Table 4 and 5 are different. Table 4 presents the porosity estimated from the whole volume, while Table 5 presents the permeability values obtained for each sub-volume. Therefore, the smaller sub-volumes tend to capture the local heterogeneities and show the variability which could not be seen when whole volume is assessed.
Comment 6: The error of the 22um permeability data in Figure 13 is significantly greater than that of the 8um permeability data, but the author did not analyze the underlying reasons in detail in the article. In addition, why is the error of S3 significantly lower than that of V4?
Response 6: Thank you for pointing this out. The error in 8µm data is lower because of the high resolution of the images, which provides a detailed view of the intricacies of the rock sample. Moreover, the sub volumes were extracted from the whole scanned volume, where different volumes have different arrangement of pores and grains, leading to differences in the permeability and porosity values in each sub volume. This variation has resulted in a significantly higher error in 22µm data compared to 8µm data. The sample S3 comes from the Syderiai saline aquifer, whereas the sample V4 is from the Vaskai saline aquifer in Lithuania. Their differing mineralogical compositions also impact the MXCT scanning process, resulting in varying error percentages.
Reviewer 3
The study will be more interesting if samples from other countries will be covered, at the least three different European countries.
Comment 1: Table 1 should be removed from the introduction and add it to the supplementary information
Response 1: Thank you for suggestion. The Table 1 gives a brief review of the advancements in CCS studies and is important to be included in the Introduction section as it helps address the gap and define the novelty of the present work.
Comment 2: The same comment goes to the figure 1 & 2
Response 2: Thank you for your comment. The Figures 1 and 2 are important as they highlight the distribution and location of reservoirs in Baltic region specifically Lithuania.
Comment 3: Introduction should be one paragraph
Response 3: Thanks for your comment, I am afraid such a guideline is not provided by the journal.
Comment 4: No need to add figure 5
Response 4: Thank you for pointing this out. The figure 5 has been removed from the manuscript as per your suggestion.
Comment 5: The methodology looks too much confusing, please remove unnecessary information, and it should be one paragraph.
Response 5: Thank you for your comment. Section 3 has been updated, and a new sub-section “3.4. Methodology Adopted” had been added to describe the workflow employed for processing the images.
Comment 6: The structure of the paper needs to be reviewed
Response 6: Thank you for pointing this out. The structure of the manuscript has been thoroughly reviewed and updated. A new sub-section has been defined in section 3 to improve clarity.
Comment 7: The results discussion is not supported by the updated literature (e.g.: Modeling CO2 Adsorption in a Thin Discrete Packing)
Response 7: Thank you for your comment. The literature has been cited in the Discussion section.
Comment 8: The quality of the displayed figures is very poor (remove the grey line and use tick marks supported by the error bar).
Response 8: Thank you for pointing this out. The quality of the figures has been improved by increasing the resolution, removing the grey line and adding tick marks. The updated figures 12, 13 and 14 have been added to the manuscript.
Comment 9: Please revise the conclusion and remove unnecessary information.
Response 9: Thank you for your feedback. The conclusion has been modified as per your suggestions. The modified conclusion is as follows:
“The present study explored the utility of digital rock volumes (DRVs) in evaluating a reservoir's capacity for effective CO2 storage, focusing on two pivotal parameters: porosity and permeability. Recognizing that subsurface fluid storage and flow processes occur at the pore scale, this research used DRVs to examine pore distribution and flow characteristics in Lithuanian deep saline aquifers (Syderiai and Vaskai) and similar formations. Notably, this work fills a gap in the literature by providing experimental data for a region where such information was previously unavailable. The findings show that employing a combination of algorithms for pore space segmentation achieves accuracy levels of 90-95% compared to laboratory measurements, validating reliability of DRV method. Clay-related image segmentation challenges were addressed effectively within the workflow. This novel application of DRVs provides new insights into Lithuanian reservoirs, offering valuable data for COâ‚‚ storage efficiency and long-term reservoir stability.
The study also acknowledges scale-related limitations, particularly in heterogeneous samples, suggesting future work with diverse samples and tailored segmentation algorithms. Upscaling petrophysical properties and evaluating geo-mechanical and geochemical effects are recommended to support safe, long-term COâ‚‚ storage. This research offers a methodological framework for future COâ‚‚ storage studies in the Baltic Basin and similar regions, benefiting academic and industry applications.”
Reviewer 3 Report
Comments and Suggestions for AuthorsThe study will be more interesting if samples from other countries will be covered, at the least three different European countries. My comments are below:
1- Table 1 should be removed from the introduction and add it to the supplementary information
2- The same comment goes to the figure 1 & 2
3- Introduction should be one paragraph
4- No need to add figure 5
5- The methodology looks too much confusing, please remove unnecessary information, and it should be one paragraph.
6- The structure of the paper needs to be reviewed
7- The results discussion is not supported by the updated literature (e.g.: Modeling CO2 Adsorption in a Thin Discrete Packing)
8- The quality of the displayed figures is very poor (remove the grey line and use tick marks supported by the error bar).
9- Please revise the conclusion and remove unnecessary information.
Author Response
Reviewer 2
Comment 1: The abstract does not provide an in-depth description and analysis of the research results on the use of Lithuanian crude oil reservoirs for CO2 storage. In addition, the author is considering whether carbonation in aquifers during CO2 storage will damage the reservoir rock and reduce its storage safety.
Response 1: Thank you for your comment. In the present study, the Lithuanian saline aquifers have been assessed and therefore the focus are only saline aquifers. When dealing with CO2 storage it is important to highlight the risks associated with the long-term storage. Therefore, a brief discussion has been done on the geochemical and geomechanical implications of long-term CO2 storage.Top of Form
Bottom of Form
Comment 2: The large-scale CO2 emission area in Figure 1 is far away from the oil field concentration area and storage area, which creates great economic pressure and safety risks for the pressurization and transportation of CO2. What are the reasons for the author to choose the geographical location of the above saline-alkali aquifer?
Response 2: Figure 1 shows the location of various CO2 emission sources and the distribution of reservoirs in the Baltic Basin region. Figure 2 highlights the location of the two main saline aquifers in Lithuania, Syderiai and Vaskai. From Figure 1 and Figure 2, it is evident that the CO2 emission sources are located relatively close to the two saline aquifers, with the largest emission source situated nearest to the Syderiai saline aquifer. Additionally, the properties of the saline aquifers—such as porosity, permeability, depth, and the presence of a sealing layer above the aquifer zone—make them suitable for CO2 storage. The storage capacity assessment of the Lithuanian reservoirs indicates that both the Syderiai and Vaskai aquifers show great potential for CO2 sequestration.
Comment 3: The author needs to add the parameter meanings and related parameter units of the many equations appearing in the original literature, or the author can make an index table at the end of the article to summarize all the parameters appearing in the equations.
Response 3: Thank you for your suggestions. The parameters along with their meaning and units have been defined for the equations in the manuscript.
Comment 4: Another sentence was added to express the "The fracturing or drilling process of hydrocarbon reservoirs also provides convenience for CO2 storage" in the introduction section, And it needs to be supported by some papers: The Carrying Behavior of Water-Based Fracturing Fluid in Shale Reservoir Fractures and Molecular Dynamics of Sand Carrying Mechanism. ---A Numerical Investigation on Kick Control with Displacement Kill Method during Well Test in Deep-water Gas Reservoir: Case Study.
Response 4: Thanks for your comment, but I am afraid this comment does not seem to be related to our manuscript.
Comment 5: What is the number of experimental tests n for the porosity error in Table 4? And why is the error of the BB model porosity in Table 4 significantly higher than that of SS and L? In addition, the permeability in Table 5 shows completely different characteristics from Table 4, while permeability and porosity should be in direct proportion.
Response 5: Thank you for your comment. The higher error percentage in BB is due to the presence of clay in the sample, which tends to impact the pore space and reduce the porosity. Moreover, the size of the samples presented in Table 4 and 5 are different. Table 4 presents the porosity estimated from the whole volume, while Table 5 presents the permeability values obtained for each sub-volume. Therefore, the smaller sub-volumes tend to capture the local heterogeneities and show the variability which could not be seen when whole volume is assessed.
Comment 6: The error of the 22um permeability data in Figure 13 is significantly greater than that of the 8um permeability data, but the author did not analyze the underlying reasons in detail in the article. In addition, why is the error of S3 significantly lower than that of V4?
Response 6: Thank you for pointing this out. The error in 8µm data is lower because of the high resolution of the images, which provides a detailed view of the intricacies of the rock sample. Moreover, the sub volumes were extracted from the whole scanned volume, where different volumes have different arrangement of pores and grains, leading to differences in the permeability and porosity values in each sub volume. This variation has resulted in a significantly higher error in 22µm data compared to 8µm data. The sample S3 comes from the Syderiai saline aquifer, whereas the sample V4 is from the Vaskai saline aquifer in Lithuania. Their differing mineralogical compositions also impact the MXCT scanning process, resulting in varying error percentages.
Reviewer 3
The study will be more interesting if samples from other countries will be covered, at the least three different European countries.
Comment 1: Table 1 should be removed from the introduction and add it to the supplementary information
Response 1: Thank you for suggestion. The Table 1 gives a brief review of the advancements in CCS studies and is important to be included in the Introduction section as it helps address the gap and define the novelty of the present work.
Comment 2: The same comment goes to the figure 1 & 2
Response 2: Thank you for your comment. The Figures 1 and 2 are important as they highlight the distribution and location of reservoirs in Baltic region specifically Lithuania.
Comment 3: Introduction should be one paragraph
Response 3: Thanks for your comment, I am afraid such a guideline is not provided by the journal.
Comment 4: No need to add figure 5
Response 4: Thank you for pointing this out. The figure 5 has been removed from the manuscript as per your suggestion.
Comment 5: The methodology looks too much confusing, please remove unnecessary information, and it should be one paragraph.
Response 5: Thank you for your comment. Section 3 has been updated, and a new sub-section “3.4. Methodology Adopted” had been added to describe the workflow employed for processing the images.
Comment 6: The structure of the paper needs to be reviewed
Response 6: Thank you for pointing this out. The structure of the manuscript has been thoroughly reviewed and updated. A new sub-section has been defined in section 3 to improve clarity.
Comment 7: The results discussion is not supported by the updated literature (e.g.: Modeling CO2 Adsorption in a Thin Discrete Packing)
Response 7: Thank you for your comment. The literature has been cited in the Discussion section.
Comment 8: The quality of the displayed figures is very poor (remove the grey line and use tick marks supported by the error bar).
Response 8: Thank you for pointing this out. The quality of the figures has been improved by increasing the resolution, removing the grey line and adding tick marks. The updated figures 12, 13 and 14 have been added to the manuscript.
Comment 9: Please revise the conclusion and remove unnecessary information.
Response 9: Thank you for your feedback. The conclusion has been modified as per your suggestions. The modified conclusion is as follows:
“The present study explored the utility of digital rock volumes (DRVs) in evaluating a reservoir's capacity for effective CO2 storage, focusing on two pivotal parameters: porosity and permeability. Recognizing that subsurface fluid storage and flow processes occur at the pore scale, this research used DRVs to examine pore distribution and flow characteristics in Lithuanian deep saline aquifers (Syderiai and Vaskai) and similar formations. Notably, this work fills a gap in the literature by providing experimental data for a region where such information was previously unavailable. The findings show that employing a combination of algorithms for pore space segmentation achieves accuracy levels of 90-95% compared to laboratory measurements, validating reliability of DRV method. Clay-related image segmentation challenges were addressed effectively within the workflow. This novel application of DRVs provides new insights into Lithuanian reservoirs, offering valuable data for COâ‚‚ storage efficiency and long-term reservoir stability.
The study also acknowledges scale-related limitations, particularly in heterogeneous samples, suggesting future work with diverse samples and tailored segmentation algorithms. Upscaling petrophysical properties and evaluating geo-mechanical and geochemical effects are recommended to support safe, long-term COâ‚‚ storage. This research offers a methodological framework for future COâ‚‚ storage studies in the Baltic Basin and similar regions, benefiting academic and industry applications.”
Round 2
Reviewer 2 Report
Comments and Suggestions for Authorsaccepted
Reviewer 3 Report
Comments and Suggestions for AuthorsThe paper looks good and is ready to be published.
