Shun Chiyonobu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Shun Chiyonobu has a total of 41 co-authors. Here are the top co-authors by number of shared publications:
- Hirokazu Madokoro
Faculty of Software and Information Science, Iwate Prefectural University, Takizawa 020-0693, Japan
3 shared publications - Kazuhito Sato
Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo 015-0055, Japan
3 shared publications - Stephanie Nix
Faculty of Software and Information Science, Iwate Prefectural University, Takizawa 020-0693, Japan
3 shared publications - Takeshi Nagayoshi
Faculty of Bioresource Sciences, Akita Prefectural University, Akita 010-0195, Japan
2 shared publications - Aftabuzzaman
Institute of Geology and Paleontology, Graduate School of Science, Tohoku University Sendai Japan
1 shared publication - Ahmed Mansour
Geology Department, Faculty of Science, Minia University, Minia 61519, Egypt
1 shared publication
Latest Publications
- Open Access
Weathering Intensity, Paleoclimatic, and Progressive Expansion of Bottom-Water Anoxia in the Middle Jurassic Khatatba Formation, Southern Tethys: Geochemical Perspectives
The Jurassic Period was a significant phase of variable organic matter accumulation in paleo-shelf areas of the southern Tethys (Egypt). Reconstructing the paleoredox conditions, paleoclimate, and weathering intensity, along with the role of terrigenous sediment flux and mineralogical maturity, is important for understanding basin infill history and prevalent paleoenvironmental conditions. Here, inorganic geochemical data are presented from the Middle Jurassic Khatatba Formation and two samples from the underlying Ras Qattara and the overlying Masajid formations in the Jana-1x well, Shushan Basin, Western Desert. Twenty-four (24) whole-rock samples were analyzed for their major and trace element composition and carbonate content. The Khatatba Formation represents one of the major hydrocarbon source rocks in the North Western Desert, Egypt. Redox conditions were assessed based on enrichment factors of redox-sensitive elements Mo, V, U, and Co. Results revealed that the Khatatba Formation was deposited under predominant anoxic bottom and pore water conditions, in contrast to the oxic settings that were prevalent during the deposition of the Ras Qattara and Masajid formations. Continental weathering intensity and paleoclimate were reconstructed based on several proxies, such as the chemical index of alteration (CIA), K2O/Rb, Rb/Sr, Ln(Al2O3/Na2O), and Al/K ratios, indicating that the studied succession was deposited during alternating phases between weak and moderate weathering intensity under arid and warm-humid climates, respectively. Periods of enhanced continental weathering were associated with high values of clastic ratios such as Si/Al, Ti/Al, and Zr/Al, suggesting increased terrigenous sediment supply during intensified hydrological cycling. These ratios further provided inferences about the changes in sediment grain size, such as a change from shale to coarse silt- and sand-size fractions.
Open AccessWeathering Intensity, Paleoclimatic, and Progressive Expansion of Bottom-Water Anoxia in the Middle Jurassic Khatatba Formation, Southern Tethys: Geochemical Perspectives
The Jurassic Period was a significant phase of variable organic matter accumulation in paleo-shelf areas of the southern Tethys (Egypt). Reconstructing the paleoredox conditions, paleoclimate, and weathering intensity, along with the role of terrigenous sediment flux and mineralogical maturity, is important for understanding basin infill history and prevalent paleoenvironmental conditions. Here, inorganic geochemical data are presented from the Middle Jurassic Khatatba Formation and two samples from the underlying Ras Qattara and the overlying Masajid formations in the Jana-1x well, Shushan Basin, Western Desert. Twenty-four (24) whole-rock samples were analyzed for their major and trace element composition and carbonate content. The Khatatba Formation represents one of the major hydrocarbon source rocks in the North Western Desert, Egypt. Redox conditions were assessed based on enrichment factors of redox-sensitive elements Mo, V, U, and Co. Results revealed that the Khatatba Formation was deposited under predominant anoxic bottom and pore water conditions, in contrast to the oxic settings that were prevalent during the deposition of the Ras Qattara and Masajid formations. Continental weathering intensity and paleoclimate were reconstructed based on several proxies, such as the chemical index of alteration (CIA), K2O/Rb, Rb/Sr, Ln(Al2O3/Na2O), and Al/K ratios, indicating that the studied succession was deposited during alternating phases between weak and moderate weathering intensity under arid and warm-humid climates, respectively. Periods of enhanced continental weathering were associated with high values of clastic ratios such as Si/Al, Ti/Al, and Zr/Al, suggesting increased terrigenous sediment supply during intensified hydrological cycling. These ratios further provided inferences about the changes in sediment grain size, such as a change from shale to coarse silt- and sand-size fractions.
- Open Access
OutcropHyBNet: Hybrid Backbone Networks with Data Augmentation for Accurate Stratum Semantic Segmentation of Monocular Outcrop Images in Carbon Capture and Storage Applications
The rapid advancement of climate change and global warming have widespread impacts on society, including ecosystems, water security, food production, health, and infrastructure. To achieve significant global emission reductions, approximately 74% is expected to come from cutting carbon dioxide (CO) emissions in energy supply and demand. Carbon Capture and Storage (CCS) has attained global recognition as a preeminent approach for the mitigation of atmospheric carbon dioxide levels, primarily by means of capturing and storing CO emissions originating from fossil fuel systems. Currently, geological models for storage location determination in CCS rely on limited sampling data from borehole surveys, which poses accuracy challenges. To tackle this challenge, our research project focuses on analyzing exposed rock formations, known as outcrops, with the goal of identifying the most effective backbone networks for classifying various strata types in outcrop images. We leverage deep learning-based outcrop semantic segmentation techniques using hybrid backbone networks, named OutcropHyBNet, to achieve accurate and efficient lithological classification, while considering texture features and without compromising computational efficiency. We conducted accuracy comparisons using publicly available benchmark datasets, as well as an original dataset expanded through random sampling of 13 outcrop images obtained using a stationary camera, installed on the ground. Additionally, we evaluated the efficacy of data augmentation through image synthesis using Only Adversarial Supervision for Semantic Image Synthesis (OASIS). Evaluation experiments on two public benchmark datasets revealed insights into the classification characteristics of different classes. The results demonstrate the superiority of Convolutional Neural Networks (CNNs), specifically DeepLabv3, and Vision Transformers (ViTs), particularly SegFormer, under specific conditions. These findings contribute to advancing accurate lithological classification in geological studies using deep learning methodologies. In the evaluation experiments conducted on ground-level images obtained using a stationary camera and aerial images captured using a drone, we successfully demonstrated the superior performance of SegFormer across all categories.Open AccessOutcropHyBNet: Hybrid Backbone Networks with Data Augmentation for Accurate Stratum Semantic Segmentation of Monocular Outcrop Images in Carbon Capture and Storage Applications
The rapid advancement of climate change and global warming have widespread impacts on society, including ecosystems, water security, food production, health, and infrastructure. To achieve significant global emission reductions, approximately 74% is expected to come from cutting carbon dioxide (CO) emissions in energy supply and demand. Carbon Capture and Storage (CCS) has attained global recognition as a preeminent approach for the mitigation of atmospheric carbon dioxide levels, primarily by means of capturing and storing CO emissions originating from fossil fuel systems. Currently, geological models for storage location determination in CCS rely on limited sampling data from borehole surveys, which poses accuracy challenges. To tackle this challenge, our research project focuses on analyzing exposed rock formations, known as outcrops, with the goal of identifying the most effective backbone networks for classifying various strata types in outcrop images. We leverage deep learning-based outcrop semantic segmentation techniques using hybrid backbone networks, named OutcropHyBNet, to achieve accurate and efficient lithological classification, while considering texture features and without compromising computational efficiency. We conducted accuracy comparisons using publicly available benchmark datasets, as well as an original dataset expanded through random sampling of 13 outcrop images obtained using a stationary camera, installed on the ground. Additionally, we evaluated the efficacy of data augmentation through image synthesis using Only Adversarial Supervision for Semantic Image Synthesis (OASIS). Evaluation experiments on two public benchmark datasets revealed insights into the classification characteristics of different classes. The results demonstrate the superiority of Convolutional Neural Networks (CNNs), specifically DeepLabv3, and Vision Transformers (ViTs), particularly SegFormer, under specific conditions. These findings contribute to advancing accurate lithological classification in geological studies using deep learning methodologies. In the evaluation experiments conducted on ground-level images obtained using a stationary camera and aerial images captured using a drone, we successfully demonstrated the superior performance of SegFormer across all categories. - Open Access
Increasing Recoverable Oil in Northern Afghanistan Kashkari Oil Field by Low-Salinity Water Flooding
In northern Afghanistan, the Kashkari oil field’s first production well was drilled in 1976, and by 1979, there were a total of ten wells drilled in the area. According to the results of surveys and calculations conducted by research institutions, the total amount of original oil in place (OOIP) in the Kashkari oil site was around 140 million barrels (MMbbls). Therefore, a method to increase the total amount of recoverable oil in the Kashkari oil field by low-salinity water flooding is presented in this study. First, the oil extraction method by low-salinity water injected into the underlying petroleum storage tank was examined by both a laboratory core flooding test and a numerical simulation model. Laboratory conditions (temperature, pressure, rock properties, and oil properties) were designed to mimic those of the Kashkari oil field. Additionally, different injection (Inj) and production patterns were considered to achieve the best results. Next, results obtained from the laboratory and computer simulations were compared. Then, the total amount of recoverable oil was calculated using the low-salinity water flooding method. Based on the findings, details of the simulated model were applied to the Kashkari reservoir model for extracting oil by injecting low-salinity water in the oil field. As a result, an amount of 10.3 MMbbls, which is about 7.5% of the field, was produced.
Open AccessIncreasing Recoverable Oil in Northern Afghanistan Kashkari Oil Field by Low-Salinity Water Flooding
In northern Afghanistan, the Kashkari oil field’s first production well was drilled in 1976, and by 1979, there were a total of ten wells drilled in the area. According to the results of surveys and calculations conducted by research institutions, the total amount of original oil in place (OOIP) in the Kashkari oil site was around 140 million barrels (MMbbls). Therefore, a method to increase the total amount of recoverable oil in the Kashkari oil field by low-salinity water flooding is presented in this study. First, the oil extraction method by low-salinity water injected into the underlying petroleum storage tank was examined by both a laboratory core flooding test and a numerical simulation model. Laboratory conditions (temperature, pressure, rock properties, and oil properties) were designed to mimic those of the Kashkari oil field. Additionally, different injection (Inj) and production patterns were considered to achieve the best results. Next, results obtained from the laboratory and computer simulations were compared. Then, the total amount of recoverable oil was calculated using the low-salinity water flooding method. Based on the findings, details of the simulated model were applied to the Kashkari reservoir model for extracting oil by injecting low-salinity water in the oil field. As a result, an amount of 10.3 MMbbls, which is about 7.5% of the field, was produced.
- Open Access
- 2 August 2022
- Published by MDPI AG in Applied Sciences
- Vol. 12 (15) , 7785
Semantic Segmentation of Agricultural Images Based on Style Transfer Using Conditional and Unconditional Generative Adversarial Networks
Classification, segmentation, and recognition techniques based on deep-learning algorithms are used for smart farming. It is an important and challenging task to reduce the time, burden, and cost of annotation procedures for collected datasets from fields and crops that are changing in a wide variety of ways according to growing, weather patterns, and seasons. This study was conducted to generate crop image datasets for semantic segmentation based on an image style transfer using generative adversarial networks (GANs). To assess data-augmented performance and calculation burdens, our proposed framework comprises contrastive unpaired translation (CUT) for a conditional GAN, pix2pixHD for an unconditional GAN, and DeepLabV3+ for semantic segmentation. Using these networks, the proposed framework provides not only image generation for data augmentation, but also automatic labeling based on distinctive feature learning among domains. The Fréchet inception distance (FID) and mean intersection over union (mIoU) were used, respectively, as evaluation metrics for GANs and semantic segmentation. We used a public benchmark dataset and two original benchmark datasets to evaluate our framework of four image-augmentation types compared with the baseline without using GANs. The experimentally obtained results showed the efficacy of using augmented images, which we evaluated using FID and mIoU. The mIoU scores for the public benchmark dataset improved by 0.03 for the training subset, while remaining similar on the test subset. For the first original benchmark dataset, the mIoU scores improved by 0.01 for the test subset, while they dropped by 0.03 for the training subset. Finally, the mIoU scores for the second original benchmark dataset improved by 0.18 for the training subset and 0.03 for the test subset.
- 2 August 2022
- Published by MDPI AG in Applied Sciences
- Vol. 12 (15) , 7785
Open AccessSemantic Segmentation of Agricultural Images Based on Style Transfer Using Conditional and Unconditional Generative Adversarial Networks
Classification, segmentation, and recognition techniques based on deep-learning algorithms are used for smart farming. It is an important and challenging task to reduce the time, burden, and cost of annotation procedures for collected datasets from fields and crops that are changing in a wide variety of ways according to growing, weather patterns, and seasons. This study was conducted to generate crop image datasets for semantic segmentation based on an image style transfer using generative adversarial networks (GANs). To assess data-augmented performance and calculation burdens, our proposed framework comprises contrastive unpaired translation (CUT) for a conditional GAN, pix2pixHD for an unconditional GAN, and DeepLabV3+ for semantic segmentation. Using these networks, the proposed framework provides not only image generation for data augmentation, but also automatic labeling based on distinctive feature learning among domains. The Fréchet inception distance (FID) and mean intersection over union (mIoU) were used, respectively, as evaluation metrics for GANs and semantic segmentation. We used a public benchmark dataset and two original benchmark datasets to evaluate our framework of four image-augmentation types compared with the baseline without using GANs. The experimentally obtained results showed the efficacy of using augmented images, which we evaluated using FID and mIoU. The mIoU scores for the public benchmark dataset improved by 0.03 for the training subset, while remaining similar on the test subset. For the first original benchmark dataset, the mIoU scores improved by 0.01 for the test subset, while they dropped by 0.03 for the training subset. Finally, the mIoU scores for the second original benchmark dataset improved by 0.18 for the training subset and 0.03 for the test subset.
- Open Access
Development of Drone-Mounted Multiple Sensing System with Advanced Mobility for In Situ Atmospheric Measurement: A Case Study Focusing on PM2.5 Local Distribution
This study was conducted using a drone with advanced mobility to develop a unified sensor and communication system as a new platform for in situ atmospheric measurements. As a major cause of air pollution, particulate matter (PM) has been attracting attention globally. We developed a small, lightweight, simple, and cost-effective multi-sensor system for multiple measurements of atmospheric phenomena and related environmental information. For in situ local area measurements, we used a long-range wireless communication module with real-time monitoring and visualizing software applications. Moreover, we developed four prototype brackets with optimal assignment of sensors, devices, and a camera for mounting on a drone as a unified system platform. Results of calibration experiments, when compared to data from two upper-grade PM sensors, demonstrated that our sensor system followed the overall tendencies and changes. We obtained original datasets after conducting flight measurement experiments at three sites with differing surrounding environments. The experimentally obtained prediction results matched regional PM trends obtained using long short-term memory (LSTM) networks trained using the respective datasets.Open AccessDevelopment of Drone-Mounted Multiple Sensing System with Advanced Mobility for In Situ Atmospheric Measurement: A Case Study Focusing on PM2.5 Local Distribution
This study was conducted using a drone with advanced mobility to develop a unified sensor and communication system as a new platform for in situ atmospheric measurements. As a major cause of air pollution, particulate matter (PM) has been attracting attention globally. We developed a small, lightweight, simple, and cost-effective multi-sensor system for multiple measurements of atmospheric phenomena and related environmental information. For in situ local area measurements, we used a long-range wireless communication module with real-time monitoring and visualizing software applications. Moreover, we developed four prototype brackets with optimal assignment of sensors, devices, and a camera for mounting on a drone as a unified system platform. Results of calibration experiments, when compared to data from two upper-grade PM sensors, demonstrated that our sensor system followed the overall tendencies and changes. We obtained original datasets after conducting flight measurement experiments at three sites with differing surrounding environments. The experimentally obtained prediction results matched regional PM trends obtained using long short-term memory (LSTM) networks trained using the respective datasets. - Open Access
- 1 January 2021
- Published by Japanese Association for Petroleum Engineers in Journal of the Japanese Association for Petroleum Technology
- Vol. 86 (6) , 483-491
Fraccability of the Miocene Onnagawa Formation and its relationship with microfacies analysis
The Onnagawa shale is a middle Miocene deposit that extends along the Akita coastal area. This formation contains organic carbon enriched siliceous mudstones deposited in the basins during the early stages of the Japanese sea opening. Some researchers in petroleum geochemistry have demonstrated that these organically enriched rocks possess attributes common to oil source rocks. JOGMEC has previously perfomed shale oil reservoir characterization of the Onnagawa shale, pilot hydraulic fracturing tests, and coring through the Onngawa shales sequence. The main goal of this paper is to use methods to estimate rock properties characterized by porosity and permeability to develop an understanding of fraccability based on lithofacies and mineral composition and their distribution in the Onnagawa Formation. Core sample from the Onnagawa shale were drilled at the Unosaki coast in the Oga peninsula. Rock property, mineral composition, and lithofacies were analyzed by CMS-300, QEMSCAN, and FIB-SEM in JOGMEC-TRC. The study results identify successes or fail parts of hydraulic fracturing depending on lithofacies and mineral compositions and indicate that 1)the lihofacies of the Onnagawa shale are dark gray to light gray colored massive, bedded, and laminated. 2)the porosity and permeability values in the light gray colored facies are relatively higher than dark gray colored facies. 3)the QEMSCAN shows the Onnagawa Formation is characterized by layered carbonate concretions with dolomite and calcite and consists chiefly of quartz with clay minerals and framboidal pyrite. 4)hydraulic fracturing tests succeeded in dolomite and calcite composed carbonate concretion layers.
- 1 January 2021
- Published by Japanese Association for Petroleum Engineers in Journal of the Japanese Association for Petroleum Technology
- Vol. 86 (6) , 483-491
Open AccessFraccability of the Miocene Onnagawa Formation and its relationship with microfacies analysis
The Onnagawa shale is a middle Miocene deposit that extends along the Akita coastal area. This formation contains organic carbon enriched siliceous mudstones deposited in the basins during the early stages of the Japanese sea opening. Some researchers in petroleum geochemistry have demonstrated that these organically enriched rocks possess attributes common to oil source rocks. JOGMEC has previously perfomed shale oil reservoir characterization of the Onnagawa shale, pilot hydraulic fracturing tests, and coring through the Onngawa shales sequence. The main goal of this paper is to use methods to estimate rock properties characterized by porosity and permeability to develop an understanding of fraccability based on lithofacies and mineral composition and their distribution in the Onnagawa Formation. Core sample from the Onnagawa shale were drilled at the Unosaki coast in the Oga peninsula. Rock property, mineral composition, and lithofacies were analyzed by CMS-300, QEMSCAN, and FIB-SEM in JOGMEC-TRC. The study results identify successes or fail parts of hydraulic fracturing depending on lithofacies and mineral compositions and indicate that 1)the lihofacies of the Onnagawa shale are dark gray to light gray colored massive, bedded, and laminated. 2)the porosity and permeability values in the light gray colored facies are relatively higher than dark gray colored facies. 3)the QEMSCAN shows the Onnagawa Formation is characterized by layered carbonate concretions with dolomite and calcite and consists chiefly of quartz with clay minerals and framboidal pyrite. 4)hydraulic fracturing tests succeeded in dolomite and calcite composed carbonate concretion layers.
- 1 January 2021
- Published by Wiley in Island Arc
- Vol. 30 (1) , e12400
Multi‐approach characterization of shallow‐water carbonates off Minamitorishima and their depositional settings/history
Sedimentological, geochemical, and chronological analyses were carried out on 18 carbonate rock samples collected at depths of 938, 1085, and 3354 m on the western slope of Minamitorishima (Marcus Island), which is located near the western margin of the Pacific Plate. Four groups of carbonate rocks were distinguished: a mollusk‐rich limestone, a coral‐rich dolomite, a foraminiferal‐nannofossil packstone, and a phosphatized mudstone/wackestone. The mollusk‐rich limestone is characterized by the dominance of bivalves (including rudists) and gastropod shells. Strontium isotope ratios (87Sr/86Sr) and Mesorbitolina ex gr. texana (a large benthic foraminifer) indicate that the shallow‐water carbonates were deposited during the late Aptian–early Albian (ca. 123–111 Ma). The coral‐rich dolomite is characterized by abundant scleractinian corals and nongeniculate coralline algae associated with encrusting acervulinid foraminifers. The biotic composition is similar to that of the Oligocene–Pleistocene carbonates reported from other seamounts in the northwestern Pacific. Geochemical data show that the coral‐rich carbonates were dolomitized at 9.5–6.8 Ma (Tortonian–Messinian) and that normal seawater was the most likely parent fluid. The foraminiferal‐nannofossil packstone is a semi‐consolidated foraminiferal‐nannofossil ooze and was deposited during the Pleistocene (0.99–0.45 Ma). The phosphatized mudstone/wackestone is marked by the absence of macrofossils and the presence of traces of planktic foraminifers. Although its depositional age is not constrained, the Sr isotope ratios indicate that the phosphatization occurred at 33.2–28.9 Ma. After the deposition of the Cretaceous shallow‐water carbonates, including the mollusk‐rich limestone, Minamitorishima was drowned and its top was covered with a pelagic cap, represented by the mudstone/wackestone. The late Eocene–early Oligocene volcanism (40.2–33.2 Ma) caused episodic uplift and returned the top of Minamitorishima to a shallow‐water environment. After the early Oligocene phosphatization of the pelagic cap, coral reefs flourished on the top of this island. The reef limestone was dolomitized during the Tortonian–Messinian.
- 1 January 2021
- Published by Wiley in Island Arc
- Vol. 30 (1) , e12400
Multi‐approach characterization of shallow‐water carbonates off Minamitorishima and their depositional settings/history
Sedimentological, geochemical, and chronological analyses were carried out on 18 carbonate rock samples collected at depths of 938, 1085, and 3354 m on the western slope of Minamitorishima (Marcus Island), which is located near the western margin of the Pacific Plate. Four groups of carbonate rocks were distinguished: a mollusk‐rich limestone, a coral‐rich dolomite, a foraminiferal‐nannofossil packstone, and a phosphatized mudstone/wackestone. The mollusk‐rich limestone is characterized by the dominance of bivalves (including rudists) and gastropod shells. Strontium isotope ratios (87Sr/86Sr) and Mesorbitolina ex gr. texana (a large benthic foraminifer) indicate that the shallow‐water carbonates were deposited during the late Aptian–early Albian (ca. 123–111 Ma). The coral‐rich dolomite is characterized by abundant scleractinian corals and nongeniculate coralline algae associated with encrusting acervulinid foraminifers. The biotic composition is similar to that of the Oligocene–Pleistocene carbonates reported from other seamounts in the northwestern Pacific. Geochemical data show that the coral‐rich carbonates were dolomitized at 9.5–6.8 Ma (Tortonian–Messinian) and that normal seawater was the most likely parent fluid. The foraminiferal‐nannofossil packstone is a semi‐consolidated foraminiferal‐nannofossil ooze and was deposited during the Pleistocene (0.99–0.45 Ma). The phosphatized mudstone/wackestone is marked by the absence of macrofossils and the presence of traces of planktic foraminifers. Although its depositional age is not constrained, the Sr isotope ratios indicate that the phosphatization occurred at 33.2–28.9 Ma. After the deposition of the Cretaceous shallow‐water carbonates, including the mollusk‐rich limestone, Minamitorishima was drowned and its top was covered with a pelagic cap, represented by the mudstone/wackestone. The late Eocene–early Oligocene volcanism (40.2–33.2 Ma) caused episodic uplift and returned the top of Minamitorishima to a shallow‐water environment. After the early Oligocene phosphatization of the pelagic cap, coral reefs flourished on the top of this island. The reef limestone was dolomitized during the Tortonian–Messinian.