TECHNICAL PROGRAMME | Primary Energy Supply – Future Pathways
Advances in Geoscience
Forum 5 | Technical Programme Hall 1
29
April
14:30
16:00
UTC+3
Advances in geoscience are pivotal in revolutionising energy supply, improving resource management, and addressing environmental challenges. By integrating cutting-edge technologies and innovative methods, geoscientists are paving the way for a more sustainable and efficient future in energy production and resource utilisation.
Core data has traditionally served as the foundational reference for formation evaluation by providing direct measurements of reservoir petrophysical properties. Following core retrieval, plugs intended for special core analysis (SCAL) are preserved, while routine analysis plugs must undergo extensive cleaning to remove hydrocarbons and salts, typically through Soxhlet extraction using hot toluene and methanol. This cleaning process can extend over several weeks, depending on factors such as rock permeability, pore structure complexity, and the type of hydrocarbons present. In this context, emerging digital imaging technologies, such as whole-core computed tomography (CT) scanning, have become particularly valuable by offering a rapid, nondestructive method for detailed core characterization and representative sample selection.
Whole-core CT imaging is a widely adopted technique in the oil and gas industry for assessing the internal structure of core samples. It enables quick visualization of core tubes for sample selection and provides critical geological and petrophysical insights, including the identification of fractures, facies transitions, and porosity variations. A major advantage of X-ray CT imaging lies in its ability to generate continuous, high-resolution images coupled with quantitative data essential for core evaluation. In this study, standard whole-core CT scanning was conducted at a single high-energy setting (140 kV) to primarily capture density variations along the core length, and the extracted data were utilized for porosity prediction. These continuous datasets are particularly valuable during the early phases of core analysis programs for characterizing reservoir heterogeneity and optimizing SCAL sample selection.
The primary objective of this study is to accelerate porosity estimation by integrating whole-core CT scanning, 3D virtual core plug acquisition, and quantitative CT data analysis, while also examining CT responses across different Winland r35 rock types.
The 3D virtual core plugging technique, a relatively recent innovation, involves creating digital replicas of core plugs of any desired diameter using specialized software. In this study, approximately seventy virtual plug samples were acquired from 30-meter-long sandstone and carbonate cores. Virtual plug porosity was calculated through correlations established between bulk density and CT numbers and compared with laboratory-measured helium porosity. A strong correlation was observed between the CT-derived and helium porosity values, as evidenced by a high coefficient of determination (R²).
This integrated approach not only streamlines early-stage porosity estimation but also significantly enhances SCAL sampling strategies, offering particular advantages in thinly laminated, fractured, and heterogeneous cores where physical plug acquisition can be operationally challenging.
Co-author/s:
Hasan Caglar Usdun, Senior Geologist, Turkish Petroleum Corporation.
Whole-core CT imaging is a widely adopted technique in the oil and gas industry for assessing the internal structure of core samples. It enables quick visualization of core tubes for sample selection and provides critical geological and petrophysical insights, including the identification of fractures, facies transitions, and porosity variations. A major advantage of X-ray CT imaging lies in its ability to generate continuous, high-resolution images coupled with quantitative data essential for core evaluation. In this study, standard whole-core CT scanning was conducted at a single high-energy setting (140 kV) to primarily capture density variations along the core length, and the extracted data were utilized for porosity prediction. These continuous datasets are particularly valuable during the early phases of core analysis programs for characterizing reservoir heterogeneity and optimizing SCAL sample selection.
The primary objective of this study is to accelerate porosity estimation by integrating whole-core CT scanning, 3D virtual core plug acquisition, and quantitative CT data analysis, while also examining CT responses across different Winland r35 rock types.
The 3D virtual core plugging technique, a relatively recent innovation, involves creating digital replicas of core plugs of any desired diameter using specialized software. In this study, approximately seventy virtual plug samples were acquired from 30-meter-long sandstone and carbonate cores. Virtual plug porosity was calculated through correlations established between bulk density and CT numbers and compared with laboratory-measured helium porosity. A strong correlation was observed between the CT-derived and helium porosity values, as evidenced by a high coefficient of determination (R²).
This integrated approach not only streamlines early-stage porosity estimation but also significantly enhances SCAL sampling strategies, offering particular advantages in thinly laminated, fractured, and heterogeneous cores where physical plug acquisition can be operationally challenging.
Co-author/s:
Hasan Caglar Usdun, Senior Geologist, Turkish Petroleum Corporation.
Introduction:
The discovery of the Pre-salt province in 2006 in Santos Basin, southeast Brazil, unveiled significant hydrocarbon reserves in ultra deep-water offshore carbonate reservoirs. The Buzios field, identified by the wildcat well 2-ANP-1 and currently the largest known commercial oil field in ultra deep-waters worldwide, features a substantial column of carbonate rocks containing light oil (27-30º API), driving innovations in geology and geophysics (G&G) modeling and advanced drilling technologies. A crucial aspect of Buzios's Director Plan is maximizing recovery through a comprehensive data acquisition strategy, use of water and water-alternate-gas (WAG) injection methods and remotely operated intelligent completion valves (ICVs), as well as incorporating seismic monitoring throughout the field's lifecycle. The primary oil extraction mechanism is the solution gas drive, supplemented by secondary recovery methods using WAG injection. The drainage strategy positions producers in structural highs, with peripheral injection wells in the flanks.
Modeling 4D signatures:
Uncertainties in geophysical modeling of the complex carbonate reservoirs in Buzios emphasize the need for advanced marine acquisition technologies. The first Ocean Bottom Nodes (OBN) survey recorded in Buzios and completed in 2019, was the largest survey globally at that time. Selecting suitable long-term seismic monitoring technology requires a multivariate approach, considering rock and fluid properties, economic analyses, water depths, subsea layout complexity, and the number of scheduled monitoring surveys, to identify those that maximizes seismic data repeatability. A critical aspect is the expected 4D seismic signature, dependent on the rock-fluid system and selected recovery mechanisms. The injection program aims to enhance sweeping efficiency and compensate for pore pressure decreases due to significant oil production rates. Petroelastic modeling studies have provided synthetic seismic responses related to anticipated WAG and water injection conditions. Findings highlighted challenges in obtaining reliable 4D signatures, indicating complex interactions between injected fluids and reservoir matrix.
Monitoring Surveys and Value of Information (VoI):
To evaluate the optimal timescale for future seismic monitoring campaigns and their ability to capture rapid reservoir changes, Petrobras conducted field tests after its first Nodes monitor campaign. The VoI metric assesses the economic benefits of acquiring additional information for decision-making, comparing acquisition costs against their potential impact on reducing uncertainty. Benefits include optimizing well placement, improving production rates, identifying poorly swept zones for infill opportunities, and mitigating geomechanical risks. Successful implementation of the Life of the Field Seismic (LoFS) project in Buzios relies on high-quality seismic monitoring data, efficient processing, and rapid updates of numerical simulators.
Conclusions:
Opportunities from the LoFS project in Buzios depend on high-quality seismic monitoring data for G&G model integration. Maximizing investments requires efficient processing and swift updates of geological and numerical simulation models, enhancing well placement predictability, understanding fluid pathways, and mitigating geomechanical risks.
The discovery of the Pre-salt province in 2006 in Santos Basin, southeast Brazil, unveiled significant hydrocarbon reserves in ultra deep-water offshore carbonate reservoirs. The Buzios field, identified by the wildcat well 2-ANP-1 and currently the largest known commercial oil field in ultra deep-waters worldwide, features a substantial column of carbonate rocks containing light oil (27-30º API), driving innovations in geology and geophysics (G&G) modeling and advanced drilling technologies. A crucial aspect of Buzios's Director Plan is maximizing recovery through a comprehensive data acquisition strategy, use of water and water-alternate-gas (WAG) injection methods and remotely operated intelligent completion valves (ICVs), as well as incorporating seismic monitoring throughout the field's lifecycle. The primary oil extraction mechanism is the solution gas drive, supplemented by secondary recovery methods using WAG injection. The drainage strategy positions producers in structural highs, with peripheral injection wells in the flanks.
Modeling 4D signatures:
Uncertainties in geophysical modeling of the complex carbonate reservoirs in Buzios emphasize the need for advanced marine acquisition technologies. The first Ocean Bottom Nodes (OBN) survey recorded in Buzios and completed in 2019, was the largest survey globally at that time. Selecting suitable long-term seismic monitoring technology requires a multivariate approach, considering rock and fluid properties, economic analyses, water depths, subsea layout complexity, and the number of scheduled monitoring surveys, to identify those that maximizes seismic data repeatability. A critical aspect is the expected 4D seismic signature, dependent on the rock-fluid system and selected recovery mechanisms. The injection program aims to enhance sweeping efficiency and compensate for pore pressure decreases due to significant oil production rates. Petroelastic modeling studies have provided synthetic seismic responses related to anticipated WAG and water injection conditions. Findings highlighted challenges in obtaining reliable 4D signatures, indicating complex interactions between injected fluids and reservoir matrix.
Monitoring Surveys and Value of Information (VoI):
To evaluate the optimal timescale for future seismic monitoring campaigns and their ability to capture rapid reservoir changes, Petrobras conducted field tests after its first Nodes monitor campaign. The VoI metric assesses the economic benefits of acquiring additional information for decision-making, comparing acquisition costs against their potential impact on reducing uncertainty. Benefits include optimizing well placement, improving production rates, identifying poorly swept zones for infill opportunities, and mitigating geomechanical risks. Successful implementation of the Life of the Field Seismic (LoFS) project in Buzios relies on high-quality seismic monitoring data, efficient processing, and rapid updates of numerical simulators.
Conclusions:
Opportunities from the LoFS project in Buzios depend on high-quality seismic monitoring data for G&G model integration. Maximizing investments requires efficient processing and swift updates of geological and numerical simulation models, enhancing well placement predictability, understanding fluid pathways, and mitigating geomechanical risks.
The oil and gas industry is undergoing a significant transformation fueled by the rapid advancements of digital technologies. The integration of advanced digitalization tools and artificial intelligence (AI) methodologies is revolutionizing the field of geoscience, supporting optimization of complex geological workflows, unlocking new insights from diverse data sources, and reactivating legacy assets. This digital transformation deepens the understanding of subsurface reservoirs and empowers more informed, efficient, and effective decision-making. By leveraging multi-scale, multimodal digital imaging and AI methods, we can analyze vast datasets and extract valuable insights from millions of geological rock samples and analytical reports. This paper highlights the potential of digital transformation to revolutionize oil and gas geoscience, with the goal of transforming exploration workflows and reservoir characterization outcomes.
The discovery of oil in Saudi Arabia in the 1930s marked the beginning of a rich legacy of geological knowledge, resulting in a vast and diverse repository of operational data and geological sample sets. However, the unstructured and variable nature of this legacy data has hindered its full potential, limiting its accessibility and integration. To overcome this challenge, we employed Generative AI (GenAI) technologies to transform the original data into a structured database, utilizing Optical Character Recognition (OCR) models and Retrieval-Augmented Generation (RAG) pipelines. This approach enabled efficient access and utilization of the information, including the application of AI-driven analytics. Concurrently, we digitized and analyzed a vast collection of subsurface rock samples to create a 'Digital Rock,' generating high-fidelity digital twins of the rock samples and predicting rock properties via simulations of physical and chemical processes at the pore scale.
Our digital transformation initiatives have significantly enhanced the efficiency of exploration and petroleum system analysis, saving thousands of man-hours in the search and retrieval of geological information. The Digital Rock has unlocked novel insights into complex petroleum system elements, including microporous, bioturbated, thin-bedded, tight sandstones, hot shales, and other challenging formations. Two exemplary case studies demonstrate the potential of digital transformation: (1) the regularization of over 90 years of biostratigraphic analysis datasets using GenAI, and (2) the assessment of flow heterogeneity in mega-porous reservoirs utilizing a multi-scale digital imaging workflow. These applications underscore the transformative potential of digital technologies in geoscience, enabling more accurate and efficient reservoir characterization.
The integration of rock sample images with corresponding interpretation reports has enabled the creation of a comprehensive and robust database, providing a solid foundation for training and validating AI models. This multidisciplinary approach has significantly enhanced our understanding of the subsurface environment. The synergistic relationship between geological data, interpretation, and AI-modeling has the potential to revolutionize the field of geoscience, enabling more informed decision-making for effective exploration and field development strategies.
Co-author/s:
Mohammed Sadah, Lead Geologist, Saudi Aramco.
Abid Bhullar, Senior Geologist Consultant, Saudi Aramco.
The discovery of oil in Saudi Arabia in the 1930s marked the beginning of a rich legacy of geological knowledge, resulting in a vast and diverse repository of operational data and geological sample sets. However, the unstructured and variable nature of this legacy data has hindered its full potential, limiting its accessibility and integration. To overcome this challenge, we employed Generative AI (GenAI) technologies to transform the original data into a structured database, utilizing Optical Character Recognition (OCR) models and Retrieval-Augmented Generation (RAG) pipelines. This approach enabled efficient access and utilization of the information, including the application of AI-driven analytics. Concurrently, we digitized and analyzed a vast collection of subsurface rock samples to create a 'Digital Rock,' generating high-fidelity digital twins of the rock samples and predicting rock properties via simulations of physical and chemical processes at the pore scale.
Our digital transformation initiatives have significantly enhanced the efficiency of exploration and petroleum system analysis, saving thousands of man-hours in the search and retrieval of geological information. The Digital Rock has unlocked novel insights into complex petroleum system elements, including microporous, bioturbated, thin-bedded, tight sandstones, hot shales, and other challenging formations. Two exemplary case studies demonstrate the potential of digital transformation: (1) the regularization of over 90 years of biostratigraphic analysis datasets using GenAI, and (2) the assessment of flow heterogeneity in mega-porous reservoirs utilizing a multi-scale digital imaging workflow. These applications underscore the transformative potential of digital technologies in geoscience, enabling more accurate and efficient reservoir characterization.
The integration of rock sample images with corresponding interpretation reports has enabled the creation of a comprehensive and robust database, providing a solid foundation for training and validating AI models. This multidisciplinary approach has significantly enhanced our understanding of the subsurface environment. The synergistic relationship between geological data, interpretation, and AI-modeling has the potential to revolutionize the field of geoscience, enabling more informed decision-making for effective exploration and field development strategies.
Co-author/s:
Mohammed Sadah, Lead Geologist, Saudi Aramco.
Abid Bhullar, Senior Geologist Consultant, Saudi Aramco.
In Japan, large-scale Carbon Capture and Storage (CCS) initiatives are currently on going, with several designated storage sites located in coastal regions. These environments present unique challenges for CCS monitoring, particularly in the application of geophysical methods. For instance, seismic methods for conformance monitoring must be adapted to shallow marine and transition zone settings, where data acquisition is often both technically demanding and costly. Additionally, potential impacts on local fisheries must be thoroughly evaluated and appropriately mitigated.
Tanase et al. (2021) showed the technical feasibility of monitoring in coastal environments for the Tomakomai CCS demonstration project. However, as Japan moves toward larger-scale, long-term practical CCS operations there is a growing need for more optimized and cost-effective monitoring strategies.
One promising solution for coastal CCS monitoring is Distributed Acoustic Sensing with Vertical Seismic Profiling (DAS-VSP). This technique enables imaging within the shoreline-adjacent transition zone and may reduce or even eliminate reliance on conventional Ocean Bottom Cables (OBCs). While permanently installed fiber, either behind casing or along tubing, is ideal for long-term surveillance, wireline DAS-VSP offers a practical alternative, allowing repeated surveys through existing wells. In 2022 and 2023, we conducted time-lapse wireline DAS-VSP experiments in wells completed over 50 years ago, successfully confirming the technical feasibility of this method for time-lapse monitoring. As such, this approach may serve as an effective optional or supplementary monitoring technique.
Another cost-effective approach involves 3D seismic surveying using Ocean Bottom Nodes (OBNs). Unlike OBC systems, OBNs eliminate the need for extensive cabling, thereby inherently reducing costs. To further enhance efficiency, we employed a parallel geometry for air-gun shooting. The results validated the effectiveness of this configuration, suggesting it as a valuable cost-saving solution, particularly when operating with a limited number of OBNs.
Given the substantial variability in site-specific conditions across coastal CCS projects, a flexible, multi-modal monitoring strategy is essential. Our research introduces alternative approaches that depart from conventional practices and demonstrates their technical feasibility. These findings expand the toolkit of cost-effective monitoring options available for coastal CCS deployment.
Reference:
Tanase, D., Saito, H., Niiro, R., Honda, T., Mori, A., Wada, Y., Higuchi, K., and Tanaka, J. (2021): Progress of CO2 injection and monitoring of the Tomakomai CCS Demonstration Project, Proceedings of the 15th International Conference on Greenhouse Gas Control Technologies, GHGT-15.
Tanase et al. (2021) showed the technical feasibility of monitoring in coastal environments for the Tomakomai CCS demonstration project. However, as Japan moves toward larger-scale, long-term practical CCS operations there is a growing need for more optimized and cost-effective monitoring strategies.
One promising solution for coastal CCS monitoring is Distributed Acoustic Sensing with Vertical Seismic Profiling (DAS-VSP). This technique enables imaging within the shoreline-adjacent transition zone and may reduce or even eliminate reliance on conventional Ocean Bottom Cables (OBCs). While permanently installed fiber, either behind casing or along tubing, is ideal for long-term surveillance, wireline DAS-VSP offers a practical alternative, allowing repeated surveys through existing wells. In 2022 and 2023, we conducted time-lapse wireline DAS-VSP experiments in wells completed over 50 years ago, successfully confirming the technical feasibility of this method for time-lapse monitoring. As such, this approach may serve as an effective optional or supplementary monitoring technique.
Another cost-effective approach involves 3D seismic surveying using Ocean Bottom Nodes (OBNs). Unlike OBC systems, OBNs eliminate the need for extensive cabling, thereby inherently reducing costs. To further enhance efficiency, we employed a parallel geometry for air-gun shooting. The results validated the effectiveness of this configuration, suggesting it as a valuable cost-saving solution, particularly when operating with a limited number of OBNs.
Given the substantial variability in site-specific conditions across coastal CCS projects, a flexible, multi-modal monitoring strategy is essential. Our research introduces alternative approaches that depart from conventional practices and demonstrates their technical feasibility. These findings expand the toolkit of cost-effective monitoring options available for coastal CCS deployment.
Reference:
Tanase, D., Saito, H., Niiro, R., Honda, T., Mori, A., Wada, Y., Higuchi, K., and Tanaka, J. (2021): Progress of CO2 injection and monitoring of the Tomakomai CCS Demonstration Project, Proceedings of the 15th International Conference on Greenhouse Gas Control Technologies, GHGT-15.
Vasily Bogoyavlensky
Vice Chair
Deputy Director
Oil and Gas Research Institute of the Russian Academy of Sciences
Susan Nash
Vice Chair
Director of Innovation and Emerging Science/Technology
American Association of Petroleum Geologists
Introduction:
The discovery of the Pre-salt province in 2006 in Santos Basin, southeast Brazil, unveiled significant hydrocarbon reserves in ultra deep-water offshore carbonate reservoirs. The Buzios field, identified by the wildcat well 2-ANP-1 and currently the largest known commercial oil field in ultra deep-waters worldwide, features a substantial column of carbonate rocks containing light oil (27-30º API), driving innovations in geology and geophysics (G&G) modeling and advanced drilling technologies. A crucial aspect of Buzios's Director Plan is maximizing recovery through a comprehensive data acquisition strategy, use of water and water-alternate-gas (WAG) injection methods and remotely operated intelligent completion valves (ICVs), as well as incorporating seismic monitoring throughout the field's lifecycle. The primary oil extraction mechanism is the solution gas drive, supplemented by secondary recovery methods using WAG injection. The drainage strategy positions producers in structural highs, with peripheral injection wells in the flanks.
Modeling 4D signatures:
Uncertainties in geophysical modeling of the complex carbonate reservoirs in Buzios emphasize the need for advanced marine acquisition technologies. The first Ocean Bottom Nodes (OBN) survey recorded in Buzios and completed in 2019, was the largest survey globally at that time. Selecting suitable long-term seismic monitoring technology requires a multivariate approach, considering rock and fluid properties, economic analyses, water depths, subsea layout complexity, and the number of scheduled monitoring surveys, to identify those that maximizes seismic data repeatability. A critical aspect is the expected 4D seismic signature, dependent on the rock-fluid system and selected recovery mechanisms. The injection program aims to enhance sweeping efficiency and compensate for pore pressure decreases due to significant oil production rates. Petroelastic modeling studies have provided synthetic seismic responses related to anticipated WAG and water injection conditions. Findings highlighted challenges in obtaining reliable 4D signatures, indicating complex interactions between injected fluids and reservoir matrix.
Monitoring Surveys and Value of Information (VoI):
To evaluate the optimal timescale for future seismic monitoring campaigns and their ability to capture rapid reservoir changes, Petrobras conducted field tests after its first Nodes monitor campaign. The VoI metric assesses the economic benefits of acquiring additional information for decision-making, comparing acquisition costs against their potential impact on reducing uncertainty. Benefits include optimizing well placement, improving production rates, identifying poorly swept zones for infill opportunities, and mitigating geomechanical risks. Successful implementation of the Life of the Field Seismic (LoFS) project in Buzios relies on high-quality seismic monitoring data, efficient processing, and rapid updates of numerical simulators.
Conclusions:
Opportunities from the LoFS project in Buzios depend on high-quality seismic monitoring data for G&G model integration. Maximizing investments requires efficient processing and swift updates of geological and numerical simulation models, enhancing well placement predictability, understanding fluid pathways, and mitigating geomechanical risks.
The discovery of the Pre-salt province in 2006 in Santos Basin, southeast Brazil, unveiled significant hydrocarbon reserves in ultra deep-water offshore carbonate reservoirs. The Buzios field, identified by the wildcat well 2-ANP-1 and currently the largest known commercial oil field in ultra deep-waters worldwide, features a substantial column of carbonate rocks containing light oil (27-30º API), driving innovations in geology and geophysics (G&G) modeling and advanced drilling technologies. A crucial aspect of Buzios's Director Plan is maximizing recovery through a comprehensive data acquisition strategy, use of water and water-alternate-gas (WAG) injection methods and remotely operated intelligent completion valves (ICVs), as well as incorporating seismic monitoring throughout the field's lifecycle. The primary oil extraction mechanism is the solution gas drive, supplemented by secondary recovery methods using WAG injection. The drainage strategy positions producers in structural highs, with peripheral injection wells in the flanks.
Modeling 4D signatures:
Uncertainties in geophysical modeling of the complex carbonate reservoirs in Buzios emphasize the need for advanced marine acquisition technologies. The first Ocean Bottom Nodes (OBN) survey recorded in Buzios and completed in 2019, was the largest survey globally at that time. Selecting suitable long-term seismic monitoring technology requires a multivariate approach, considering rock and fluid properties, economic analyses, water depths, subsea layout complexity, and the number of scheduled monitoring surveys, to identify those that maximizes seismic data repeatability. A critical aspect is the expected 4D seismic signature, dependent on the rock-fluid system and selected recovery mechanisms. The injection program aims to enhance sweeping efficiency and compensate for pore pressure decreases due to significant oil production rates. Petroelastic modeling studies have provided synthetic seismic responses related to anticipated WAG and water injection conditions. Findings highlighted challenges in obtaining reliable 4D signatures, indicating complex interactions between injected fluids and reservoir matrix.
Monitoring Surveys and Value of Information (VoI):
To evaluate the optimal timescale for future seismic monitoring campaigns and their ability to capture rapid reservoir changes, Petrobras conducted field tests after its first Nodes monitor campaign. The VoI metric assesses the economic benefits of acquiring additional information for decision-making, comparing acquisition costs against their potential impact on reducing uncertainty. Benefits include optimizing well placement, improving production rates, identifying poorly swept zones for infill opportunities, and mitigating geomechanical risks. Successful implementation of the Life of the Field Seismic (LoFS) project in Buzios relies on high-quality seismic monitoring data, efficient processing, and rapid updates of numerical simulators.
Conclusions:
Opportunities from the LoFS project in Buzios depend on high-quality seismic monitoring data for G&G model integration. Maximizing investments requires efficient processing and swift updates of geological and numerical simulation models, enhancing well placement predictability, understanding fluid pathways, and mitigating geomechanical risks.
Ivan Deshenenkov
Speaker
Geological Consultant - Digital Transformation Lead
Saudi Aramco
The oil and gas industry is undergoing a significant transformation fueled by the rapid advancements of digital technologies. The integration of advanced digitalization tools and artificial intelligence (AI) methodologies is revolutionizing the field of geoscience, supporting optimization of complex geological workflows, unlocking new insights from diverse data sources, and reactivating legacy assets. This digital transformation deepens the understanding of subsurface reservoirs and empowers more informed, efficient, and effective decision-making. By leveraging multi-scale, multimodal digital imaging and AI methods, we can analyze vast datasets and extract valuable insights from millions of geological rock samples and analytical reports. This paper highlights the potential of digital transformation to revolutionize oil and gas geoscience, with the goal of transforming exploration workflows and reservoir characterization outcomes.
The discovery of oil in Saudi Arabia in the 1930s marked the beginning of a rich legacy of geological knowledge, resulting in a vast and diverse repository of operational data and geological sample sets. However, the unstructured and variable nature of this legacy data has hindered its full potential, limiting its accessibility and integration. To overcome this challenge, we employed Generative AI (GenAI) technologies to transform the original data into a structured database, utilizing Optical Character Recognition (OCR) models and Retrieval-Augmented Generation (RAG) pipelines. This approach enabled efficient access and utilization of the information, including the application of AI-driven analytics. Concurrently, we digitized and analyzed a vast collection of subsurface rock samples to create a 'Digital Rock,' generating high-fidelity digital twins of the rock samples and predicting rock properties via simulations of physical and chemical processes at the pore scale.
Our digital transformation initiatives have significantly enhanced the efficiency of exploration and petroleum system analysis, saving thousands of man-hours in the search and retrieval of geological information. The Digital Rock has unlocked novel insights into complex petroleum system elements, including microporous, bioturbated, thin-bedded, tight sandstones, hot shales, and other challenging formations. Two exemplary case studies demonstrate the potential of digital transformation: (1) the regularization of over 90 years of biostratigraphic analysis datasets using GenAI, and (2) the assessment of flow heterogeneity in mega-porous reservoirs utilizing a multi-scale digital imaging workflow. These applications underscore the transformative potential of digital technologies in geoscience, enabling more accurate and efficient reservoir characterization.
The integration of rock sample images with corresponding interpretation reports has enabled the creation of a comprehensive and robust database, providing a solid foundation for training and validating AI models. This multidisciplinary approach has significantly enhanced our understanding of the subsurface environment. The synergistic relationship between geological data, interpretation, and AI-modeling has the potential to revolutionize the field of geoscience, enabling more informed decision-making for effective exploration and field development strategies.
Co-author/s:
Mohammed Sadah, Lead Geologist, Saudi Aramco.
Abid Bhullar, Senior Geologist Consultant, Saudi Aramco.
The discovery of oil in Saudi Arabia in the 1930s marked the beginning of a rich legacy of geological knowledge, resulting in a vast and diverse repository of operational data and geological sample sets. However, the unstructured and variable nature of this legacy data has hindered its full potential, limiting its accessibility and integration. To overcome this challenge, we employed Generative AI (GenAI) technologies to transform the original data into a structured database, utilizing Optical Character Recognition (OCR) models and Retrieval-Augmented Generation (RAG) pipelines. This approach enabled efficient access and utilization of the information, including the application of AI-driven analytics. Concurrently, we digitized and analyzed a vast collection of subsurface rock samples to create a 'Digital Rock,' generating high-fidelity digital twins of the rock samples and predicting rock properties via simulations of physical and chemical processes at the pore scale.
Our digital transformation initiatives have significantly enhanced the efficiency of exploration and petroleum system analysis, saving thousands of man-hours in the search and retrieval of geological information. The Digital Rock has unlocked novel insights into complex petroleum system elements, including microporous, bioturbated, thin-bedded, tight sandstones, hot shales, and other challenging formations. Two exemplary case studies demonstrate the potential of digital transformation: (1) the regularization of over 90 years of biostratigraphic analysis datasets using GenAI, and (2) the assessment of flow heterogeneity in mega-porous reservoirs utilizing a multi-scale digital imaging workflow. These applications underscore the transformative potential of digital technologies in geoscience, enabling more accurate and efficient reservoir characterization.
The integration of rock sample images with corresponding interpretation reports has enabled the creation of a comprehensive and robust database, providing a solid foundation for training and validating AI models. This multidisciplinary approach has significantly enhanced our understanding of the subsurface environment. The synergistic relationship between geological data, interpretation, and AI-modeling has the potential to revolutionize the field of geoscience, enabling more informed decision-making for effective exploration and field development strategies.
Co-author/s:
Mohammed Sadah, Lead Geologist, Saudi Aramco.
Abid Bhullar, Senior Geologist Consultant, Saudi Aramco.
In Japan, large-scale Carbon Capture and Storage (CCS) initiatives are currently on going, with several designated storage sites located in coastal regions. These environments present unique challenges for CCS monitoring, particularly in the application of geophysical methods. For instance, seismic methods for conformance monitoring must be adapted to shallow marine and transition zone settings, where data acquisition is often both technically demanding and costly. Additionally, potential impacts on local fisheries must be thoroughly evaluated and appropriately mitigated.
Tanase et al. (2021) showed the technical feasibility of monitoring in coastal environments for the Tomakomai CCS demonstration project. However, as Japan moves toward larger-scale, long-term practical CCS operations there is a growing need for more optimized and cost-effective monitoring strategies.
One promising solution for coastal CCS monitoring is Distributed Acoustic Sensing with Vertical Seismic Profiling (DAS-VSP). This technique enables imaging within the shoreline-adjacent transition zone and may reduce or even eliminate reliance on conventional Ocean Bottom Cables (OBCs). While permanently installed fiber, either behind casing or along tubing, is ideal for long-term surveillance, wireline DAS-VSP offers a practical alternative, allowing repeated surveys through existing wells. In 2022 and 2023, we conducted time-lapse wireline DAS-VSP experiments in wells completed over 50 years ago, successfully confirming the technical feasibility of this method for time-lapse monitoring. As such, this approach may serve as an effective optional or supplementary monitoring technique.
Another cost-effective approach involves 3D seismic surveying using Ocean Bottom Nodes (OBNs). Unlike OBC systems, OBNs eliminate the need for extensive cabling, thereby inherently reducing costs. To further enhance efficiency, we employed a parallel geometry for air-gun shooting. The results validated the effectiveness of this configuration, suggesting it as a valuable cost-saving solution, particularly when operating with a limited number of OBNs.
Given the substantial variability in site-specific conditions across coastal CCS projects, a flexible, multi-modal monitoring strategy is essential. Our research introduces alternative approaches that depart from conventional practices and demonstrates their technical feasibility. These findings expand the toolkit of cost-effective monitoring options available for coastal CCS deployment.
Reference:
Tanase, D., Saito, H., Niiro, R., Honda, T., Mori, A., Wada, Y., Higuchi, K., and Tanaka, J. (2021): Progress of CO2 injection and monitoring of the Tomakomai CCS Demonstration Project, Proceedings of the 15th International Conference on Greenhouse Gas Control Technologies, GHGT-15.
Tanase et al. (2021) showed the technical feasibility of monitoring in coastal environments for the Tomakomai CCS demonstration project. However, as Japan moves toward larger-scale, long-term practical CCS operations there is a growing need for more optimized and cost-effective monitoring strategies.
One promising solution for coastal CCS monitoring is Distributed Acoustic Sensing with Vertical Seismic Profiling (DAS-VSP). This technique enables imaging within the shoreline-adjacent transition zone and may reduce or even eliminate reliance on conventional Ocean Bottom Cables (OBCs). While permanently installed fiber, either behind casing or along tubing, is ideal for long-term surveillance, wireline DAS-VSP offers a practical alternative, allowing repeated surveys through existing wells. In 2022 and 2023, we conducted time-lapse wireline DAS-VSP experiments in wells completed over 50 years ago, successfully confirming the technical feasibility of this method for time-lapse monitoring. As such, this approach may serve as an effective optional or supplementary monitoring technique.
Another cost-effective approach involves 3D seismic surveying using Ocean Bottom Nodes (OBNs). Unlike OBC systems, OBNs eliminate the need for extensive cabling, thereby inherently reducing costs. To further enhance efficiency, we employed a parallel geometry for air-gun shooting. The results validated the effectiveness of this configuration, suggesting it as a valuable cost-saving solution, particularly when operating with a limited number of OBNs.
Given the substantial variability in site-specific conditions across coastal CCS projects, a flexible, multi-modal monitoring strategy is essential. Our research introduces alternative approaches that depart from conventional practices and demonstrates their technical feasibility. These findings expand the toolkit of cost-effective monitoring options available for coastal CCS deployment.
Reference:
Tanase, D., Saito, H., Niiro, R., Honda, T., Mori, A., Wada, Y., Higuchi, K., and Tanaka, J. (2021): Progress of CO2 injection and monitoring of the Tomakomai CCS Demonstration Project, Proceedings of the 15th International Conference on Greenhouse Gas Control Technologies, GHGT-15.
Ibrahim Olgun Ugurlu
Speaker
Senior Sedimentologist&Whole-Core CT Rock Imaging Lead
Turkish Petroleum Corporation
Core data has traditionally served as the foundational reference for formation evaluation by providing direct measurements of reservoir petrophysical properties. Following core retrieval, plugs intended for special core analysis (SCAL) are preserved, while routine analysis plugs must undergo extensive cleaning to remove hydrocarbons and salts, typically through Soxhlet extraction using hot toluene and methanol. This cleaning process can extend over several weeks, depending on factors such as rock permeability, pore structure complexity, and the type of hydrocarbons present. In this context, emerging digital imaging technologies, such as whole-core computed tomography (CT) scanning, have become particularly valuable by offering a rapid, nondestructive method for detailed core characterization and representative sample selection.
Whole-core CT imaging is a widely adopted technique in the oil and gas industry for assessing the internal structure of core samples. It enables quick visualization of core tubes for sample selection and provides critical geological and petrophysical insights, including the identification of fractures, facies transitions, and porosity variations. A major advantage of X-ray CT imaging lies in its ability to generate continuous, high-resolution images coupled with quantitative data essential for core evaluation. In this study, standard whole-core CT scanning was conducted at a single high-energy setting (140 kV) to primarily capture density variations along the core length, and the extracted data were utilized for porosity prediction. These continuous datasets are particularly valuable during the early phases of core analysis programs for characterizing reservoir heterogeneity and optimizing SCAL sample selection.
The primary objective of this study is to accelerate porosity estimation by integrating whole-core CT scanning, 3D virtual core plug acquisition, and quantitative CT data analysis, while also examining CT responses across different Winland r35 rock types.
The 3D virtual core plugging technique, a relatively recent innovation, involves creating digital replicas of core plugs of any desired diameter using specialized software. In this study, approximately seventy virtual plug samples were acquired from 30-meter-long sandstone and carbonate cores. Virtual plug porosity was calculated through correlations established between bulk density and CT numbers and compared with laboratory-measured helium porosity. A strong correlation was observed between the CT-derived and helium porosity values, as evidenced by a high coefficient of determination (R²).
This integrated approach not only streamlines early-stage porosity estimation but also significantly enhances SCAL sampling strategies, offering particular advantages in thinly laminated, fractured, and heterogeneous cores where physical plug acquisition can be operationally challenging.
Co-author/s:
Hasan Caglar Usdun, Senior Geologist, Turkish Petroleum Corporation.
Whole-core CT imaging is a widely adopted technique in the oil and gas industry for assessing the internal structure of core samples. It enables quick visualization of core tubes for sample selection and provides critical geological and petrophysical insights, including the identification of fractures, facies transitions, and porosity variations. A major advantage of X-ray CT imaging lies in its ability to generate continuous, high-resolution images coupled with quantitative data essential for core evaluation. In this study, standard whole-core CT scanning was conducted at a single high-energy setting (140 kV) to primarily capture density variations along the core length, and the extracted data were utilized for porosity prediction. These continuous datasets are particularly valuable during the early phases of core analysis programs for characterizing reservoir heterogeneity and optimizing SCAL sample selection.
The primary objective of this study is to accelerate porosity estimation by integrating whole-core CT scanning, 3D virtual core plug acquisition, and quantitative CT data analysis, while also examining CT responses across different Winland r35 rock types.
The 3D virtual core plugging technique, a relatively recent innovation, involves creating digital replicas of core plugs of any desired diameter using specialized software. In this study, approximately seventy virtual plug samples were acquired from 30-meter-long sandstone and carbonate cores. Virtual plug porosity was calculated through correlations established between bulk density and CT numbers and compared with laboratory-measured helium porosity. A strong correlation was observed between the CT-derived and helium porosity values, as evidenced by a high coefficient of determination (R²).
This integrated approach not only streamlines early-stage porosity estimation but also significantly enhances SCAL sampling strategies, offering particular advantages in thinly laminated, fractured, and heterogeneous cores where physical plug acquisition can be operationally challenging.
Co-author/s:
Hasan Caglar Usdun, Senior Geologist, Turkish Petroleum Corporation.
