Browsing by Author "Ajay Pratap Singh"

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Advancing post-stack seismic inversion through music-inspired harmony search optimization technique. A case study
(Elsevier B.V., 2025) Ravi Kant; Brijesh M.N. Kumar; Satya Prakash Maurya; Satya Narayan; Ajay Pratap Singh; Gopal Hema
A novel post-stack seismic inversion algorithm has been developed to estimate acoustic impedances using P-wave reflection seismic data, employing the music-inspired harmony search global optimization (HSO) technique. This optimization seeks to find the global minimum of the objective function, which measures the misfit between synthetic and observed post-stack seismic data. During the iterative inversion process, acoustic impedance models are randomly perturbed, and synthetic seismic data are recalculated to match observed data. To enhance stability, the algorithm uses constraints from a well-log-derived low-frequency impedance model. The proposed algorithm was tested on synthetic and real data to demonstrate its effectiveness in post-stack seismic data inversion. On synthetic test, we found high accuracy of the HSO-generated traces, with average correlations of 0.99, 0.99, 0.97, and 0.96, and RMS errors of 0.12, 0.40, 0.50, and 0.62, for noise levels of 0 %, 10 %, 20 %, and 30 %, respectively. For real data from the Blackfoot Field, Alberta, Canada, the algorithm achieved a 0.93 correlation and 0.22 RMS error, enabling seismic data inversion for acoustic impedance estimation. The inverted section identified low acoustic impedance (8000–9000 m/s∗g/cc), matching the high seismic amplitude anomaly, suggesting a sand channel reservoir between 1040 and 1065 ms two-way travel time. While, high acoustic impedance (9000–12000 m/s∗g/cc) indicating background shale facies. This study explores potential hydrocarbon reservoirs in the Blackfoot Field, Alberta, using HSO-based advanced global optimization for efficient and accurate seismic data inversion. © 2025
Assistive Support Through Technologies for Persons with Disabilities in Libraries
(Defense Scientific Information and Documentation Centre, 2022) Abhay Chaurasia; Ajay Pratap Singh
This paper aims to give a brief about the services provided by libraries to disable library users using software and hardware technologies. In this era, the development of technologies, information and communication technologies, etc., is widespread and being disseminated and published globally. Usually, it is convenient for a library professional to differentiate between individuals in need of assistance. This paper emphasises specialised equipment, technologies, and services that provide a barrier-free environment to the disabled users in libraries and information centres, leading to many technological innovations and advancements for general and disabled persons. This study will be helpful for persons with disabilities, LIS specialists, and other professional communities to provide information about the situation and the variety of assistive technologies available in libraries. © 2022, DESIDOC.
CO2 characterization using seismic inversion based on global optimization techniques for enhanced reservoir understanding: a comparative study
(Springer Science and Business Media Deutschland GmbH, 2025) Ajay Pratap Singh; Ravi Kant; Satya Prakash Maurya; Brijesh M.N. Kumar; Nitin Verma; Raghav S. Singh; Kumar Hemant Singh; Manoj Kumar Srivastava; Gopal Hema
Characterization of CO2 in subsurface reservoirs is an important aspect of ensuring the effectiveness and safety of storage operations. Seismic inversion technique, widely applied in the petroleum industry for tasks such as quantitative reservoir characterization and improved oil recovery, is now finding potential application in estimating the extension of CO2 plumes within an underground reservoir. Seismic inversion, coupled with global optimization techniques, offers a powerful approach to enhance reservoir understanding in CCS projects. This paper presents a comprehensive study on the application of a global optimization workflow to increase subsurface resolution in the CO2 storage. Global optimization techniques including simulated annealing and particle swarm optimization are employed to optimize the subsurface model and estimate the P-wave impedance. We used the Sleipner field in the Norwegian North Sea which is extracting gas with high CO2 content, and for environmental reasons, they have been injecting more than 11 million tons of CO2 into the Utsira sand saline aquifer above the hydrocarbon reserves since 1996. To monitor the spread of this CO2 plume and ensure the safety of the upper layers, a series of seven 3D seismic surveys have been conducted. Our study concentrated on vintage data from 1994 (before CO2 injection) and 1999 and 2006 (after an 8.4 Mt CO2 injection). The workflow incorporates prior information from well logs, facilitating faster convergence and detailed subsurface representations. The findings suggest that the application of global optimization techniques is advantageous for optimizing earth’s subsurface models, particularly in the context of CO2 storage initiatives. Although we faced challenges due to the absence of time-lapse well-log data in the specific area of interest, we successfully applied our inverse workflow to generate acoustic impedance data, to the best of our knowledge. These findings offer valuable insights for enhancing the understanding of CO2 dispersion within a reservoir. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences 2025.
Development and changing paradigm of LIS education
(Defence Scientific Information and Documentation Centre, 2017) Ajay Pratap Singh
Libraries are one of the oldest human institutions. Librarianship too has been in practice for a long time and across cultures, this practice being an expression of the social practices of these cultures. The development of librarianship was closely associated with the recording of messages and information on manuscripts or papers and consequently with the collection of records in individual or public interest. Majority of the activities associated with contemporary librarianship were a part of day-to-day work culture. Later on however, with the popularisation of information sources and the rapid growth of their collection, librarianship came to be recognised as an independent profession. Subsequently, the need for professional training was identified for providing best support to its user community. And over time, specialised issues and settings have translated into academic programmes of professional schools in the higher education system. © 2017, DESIDOC.
Enhancing porosity prediction: Integrating seismic inversion utilizing sparse layer reflectivity, and particle swarm optimization with radial basis function neural networks
(John Wiley and Sons Inc, 2025) Ravi Kant; Brijesh M.N. Kumar; Ajay Pratap Singh; Gopal Hema; Satya Prakash Maurya; Raghav S. Singh; Kumar Hemant Singh; Piyush Sarkar
Seismic inversion, a crucial process in reservoir characterization, gains prominence in overcoming challenges associated with traditional methods, particularly in exploring deeper reservoirs. In this present study, we propose an inversion approach based on modern techniques like sparse layer reflectivity and particle swarm optimization to obtain inverted impedance. The proposed sparse layer reflectivity and particle swarm optimization techniques effectively minimize the error between recorded seismic reflection data and synthetic seismic data. This reduction in error facilitates accurate prediction of subsurface parameters, enabling comprehensive reservoir characterization. The inverted impedance obtained from both methods serves as a foundation for predicting porosity, utilizing a radial basis function neural network across the entire seismic volume. The study identifies a significant porosity zone (>20%) with a lower acoustic impedance of 6000–8500 m/s g cm3, interpreted as a sand channel or reservoir zone. This anomaly, between 1045 and 1065 ms two-way travel time, provides high-resolution insights into the subsurface. The particle swarm optimization algorithm shows higher correlation results, with 0.98 for impedance and 0.73 for porosity, compared to sparse layer reflectivity's 0.81 for impedance and 0.65 for porosity at well locations. Additionally, particle swarm optimization provides high-resolution subsurface insights near well location and across a broader spatial range. This suggests particle swarm optimization's superior potential for delivering higher resolution outcomes compared to sparse layer reflectivity. © 2024 European Association of Geoscientists & Engineers.
Evaluating Elastic Parameters of a CO2 Plume Using Model-Based and Sparse Layer Reflectivity Inversion of Time-Lapse Seismic Data: A Case Study
(John Wiley and Sons Inc, 2025) Gopal Hema; Satya Prakash Maurya; Nitin Verma; Ravi Kant; Ajay Pratap Singh; Brijesh Kumar; Raghav S. Singh; Kumar Hemant Singh
The objective of this research is to estimate the elastic properties of the CO2 plume in the Sleipner field and perform a comparative analysis of model-based inversion (MBI) and sparse layer reflectivity (SLR) inversion techniques. MBI is relatively old method, whereas SLR is relatively new method for seismic inversion. Model-based seismic inversion is a well-established deterministic inversion technique that iteratively minimizes the misfit between observed and modelled seismic data. In contrast, SLR inversion is designed to identify and analyse the reflectivity of thin subsurface layers by emphasizing sparsity in the reflectivity sequence. This study utilizes a set of time-lapse seismic angle stack data from the Sleipner field, comprising a 1994 pre-injection baseline and a 1999 post-injection monitor survey, following the injection of 2.35 million tons of CO2. These angle stacks were used to generate P-wave and S-wave reflectivity using the two-term Fatti amplitude versus offset (AVO) equation, which was then further utilized in the inversion process to estimate the elastic parameters. Acoustic and shear impedance (SI) were derived using MBI and SLR to evaluate their strengths, limitations, computational efficiency and adaptability to geological changes. In the CO2-injected zone, acoustic impedance values were observed between 2000 and 2400 m/s g/cm3, whereas SI values ranged from 100 to 400 m/s g/cm3. Our findings suggest that overall, MBI produces sharper and more reliable imaging across the entire seismic section. For P-impedance, MBI yielded correlation values of 0.980 with an error of 0.137 in 1994 and 0.989 with an error of 0.141 in 1999 datasets, whereas SLR showed higher correlation at the well location 0.997 with an error of 0.073 in 1994 and 0.998 with an error of 0.061 in 1999. For S-impedance, MBI achieved correlation values of 0.860 with an error of 0.650 in 1994 and 0.974 with an error of 0.265 in 1999 datasets. In comparison, SLR produced a correlation of 0.995 with an error of 0.072 in 1994 and 0.951 with an error of 0.370 in 1999 datasets at the well location. However, similar to the P-impedance case, whereas SLR performed well at the well location, its application to the full seismic volume resulted in reduced performance, characterized by noisier results and longer processing time. A comparative evaluation of MBI and SLR indicates that MBI offers greater efficiency, simpler implementation and faster computational performance. As a result, the impedance outputs obtained from MBI were subsequently converted into density, P-wave velocity and S-wave velocity using empirical relationships derived from well log data. In the seismic volumes, a significant change in the reservoir's elastic properties was observed in the CO2-saturated zone, compared to the Utsira Formation, which serves as the reservoir into which CO2 has been injected. Density decreased from 1.75 to 1.35 g/cm3 (∼23%), P-wave velocity from 2000 to 1820 m/s (∼9%) and S-wave velocity from 1150 to 638 m/s (∼45%). These changes reflect the effects of CO2 replacing brine in the pore space, leading to a reduction in bulk density and stiffness and indicating overall reservoir softening due to gas injection. Integrating these inversion methods with multi-parameter elastic estimation enables effective CO2 plume monitoring and reservoir characterization, highlighting the role of seismic inversion in detecting fluid-induced changes and supporting improved monitoring strategies in carbon capture and storage (CCS) operations. © 2025 European Association of Geoscientists & Engineers.
Impact of coronavirus disease 2019 lockdown on catheterization laboratory: An Indian perspective
(Wolters Kluwer, 2020) Ajay Pratap Singh; Ranjit Kumar Nath; Ajay Raj; Neeraj Pandit; Puneet Aggarwal; Ashok Kumar Thakur; Rajeev Bharadwaj; Vinod Kumar; Kriti Singh
Aims: This study aims to study the impact of coronavirus disease 2019 (COVID‑19) lockdown on catheterization laboratory (Cath Lab) utilization for cardiac patients. Subjects and Methods: In this retrospective observational study, a total number of procedures in Cath Lab during COVID‑19 lockdown were compared with pre‑COVID‑19 lockdown time to see the impact of the pandemic on cardiac patients undergoing interventions. Results: A total of 1982 procedures (1788 in prelockdown vs. 194 in lockdown; P < 0.001) were performed in the catheterization laboratory during the 6 months’ time frame of this study. There was an alarming drop in procedures by 89.1% in the lockdown period with the maximum reduction seen in diagnostic coronary angiography (96.6%), elective angioplasty decreased by 96.4%, and primary angioplasty by 82.08%. There was an increase in rescue angioplasty by 80% (P < 0.001) during the lockdown phase. There was a fall of 83.9% in admissions of acute coronary syndrome and 62.76% reduction in heart failure admissions during the lockdown period. During the study period, there were a total of 2111 admissions in the cardiac care unit (1882 in pre vs. 229 in lockdown; P < 0.001), which showed an 87.14% reduction when compared to the prelockdown group. Conclusions: We report an alarming reduction in total admissions and catheterization laboratory procedures as an impact of COVID‑19‑related lockdown. This represents a serious problem regarding the handling of this pandemic by the health‑care system and can be used to devise proper strategies for the recovery phase of the COVID‑19 pandemic. © 2020 Heart India | Published by Wolters Kluwer - Medknow.
Implementing 4D seismic inversion based on Linear Programming techniques for CO2 monitoring at the Sleipner field CCS site in the North Sea, Norway
(Springer Science and Business Media Deutschland GmbH, 2025) Ajay Pratap Singh; Satya Prakash Maurya; Ravi Kant; Kumar Hemant Singh; Raghav S. Singh; Manoj Kumar Srivastava; Gopal Hema; Nitin Verma
This article provides a comprehensive analysis of CO2 injection monitoring in the Sleipner Field. Ensuring the safe storage and containment of CO2 in geological formations or assigned storage sites, especially in the carbon capture and storage (CCS) projects. In this study, a seismic inversion method incorporating linear programming sparse spike inversion was employed to observe and analyze the CO2 plume in the Sleipner field, Norway. This approach enhances the understanding of the dynamics and behavior of the CO2 injection, providing valuable insights into the monitoring and assessment of CCS operations in the Sleipner field. The foundational dataset includes 3D post-stack seismic data from the year 1994, with special emphasis on the monitoring data collected in 1999, following four years of CO2 sequestration. The analysis utilized synthetic data to investigate alterations in seismic amplitude, highlighting that amplitude variations were more prominent compared to variations in velocity and density. The findings highlight noticeable shifts in P-wave velocity, signifying a significant 29% reduction, with the most substantial decrease occurring within the 0 to 30% CO2 saturation range. Correspondingly, density changes align with trace variations, demonstrating only a 2–3% reduction in density as gas saturation increases from 0 to 30%. Beyond 30% saturation, density exhibits a further decrease of 30%. The traces collectively reveal a consistent trend, showcasing a 32% reduction in impedance as CO2 saturation levels rise. Through the cross-equalization process, it was observed that the initial data repeatability was low, indicated by a normalized root mean square (NRMS) value of 0.6508. However, significant improvement was achieved, bringing the NRMS value to a more satisfactory level of 0.5581. This improvement underscored the alignment of features both above and below the reservoir, underscoring the efficacy of the cross-equalization technique. The outcomes of the 4D inversion provided insights into the distribution of CO2 within the reservoir, revealing upward migration. Importantly, the results confirmed the secure storage of CO2 within the reservoir, affirming the integrity of the overlying cap layer. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences 2024.
Implementing 4D seismic inversion based on Linear Programming techniques for CO2 monitoring at the Sleipner field CCS site in the North Sea, Norway
(Springer Science and Business Media Deutschland GmbH, 2024) Ajay Pratap Singh; Satya Prakash Maurya; Ravi Kant; Kumar Hemant Singh; Raghav Singh; Manoj Kumar Srivastava; Gopal Hema; Nitin Verma
This article provides a comprehensive analysis of CO2 injection monitoring in the Sleipner Field. Ensuring the safe storage and containment of CO2 in geological formations or assigned storage sites, especially in the carbon capture and storage (CCS) projects. In this study, a seismic inversion method incorporating linear programming sparse spike inversion was employed to observe and analyze the CO2 plume in the Sleipner field, Norway. This approach enhances the understanding of the dynamics and behavior of the CO2 injection, providing valuable insights into the monitoring and assessment of CCS operations in the Sleipner field. The foundational dataset includes 3D post-stack seismic data from the year 1994, with special emphasis on the monitoring data collected in 1999, following four years of CO2 sequestration. The analysis utilized synthetic data to investigate alterations in seismic amplitude, highlighting that amplitude variations were more prominent compared to variations in velocity and density. The findings highlight noticeable shifts in P-wave velocity, signifying a significant 29% reduction, with the most substantial decrease occurring within the 0 to 30% CO2 saturation range. Correspondingly, density changes align with trace variations, demonstrating only a 2–3% reduction in density as gas saturation increases from 0 to 30%. Beyond 30% saturation, density exhibits a further decrease of 30%. The traces collectively reveal a consistent trend, showcasing a 32% reduction in impedance as CO2 saturation levels rise. Through the cross-equalization process, it was observed that the initial data repeatability was low, indicated by a normalized root mean square (NRMS) value of 0.6508. However, significant improvement was achieved, bringing the NRMS value to a more satisfactory level of 0.5581. This improvement underscored the alignment of features both above and below the reservoir, underscoring the efficacy of the cross-equalization technique. The outcomes of the 4D inversion provided insights into the distribution of CO2 within the reservoir, revealing upward migration. Importantly, the results confirmed the secure storage of CO2 within the reservoir, affirming the integrity of the overlying cap layer. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences 2024.
Machine learning-based comparative assessment of seismic inversion approaches for porosity estimation
(Springer, 2025) Brijesh M.N. Kumar; Ravi Kant; Shushant Singh; Nitin Verma; Satya Prakash Maurya; Ajay Pratap Singh; Gopal Hema; Sanjay K. Sharma
Seismic inversion is a fundamental technique for extracting quantitative subsurface properties from seismic data. This study confidently presents a thorough comparative assessment of five seismic inversion methods: Coloured Inversion (CI), Band-Limited Inversion (BLI), Model-Based Inversion (MBI), Maximum Likelihood Inversion (MLI), and Sparse Layer Reflectivity (SLR), all enhanced by a Probabilistic Neural Network (PNN) for porosity estimation. Using seismic data from the Blackfoot field in Canada, we rigorously evaluate the effectiveness of these techniques in delineating reservoir zones and accurately predicting porosity. Our compelling results demonstrate that MBI, BLI, and CI significantly outperform the other methods in identifying reservoir boundaries and aligning closely with well-log data. When integrated with PNN, MBI and BLI excel in mapping reservoir porosity, providing reliable predictions ranging from 5 to 20% and impedance values between 7000 and 18,000 m/s*g/cc. These integrated approaches deliver an unparalleled understanding of reservoir characteristics, far surpassing the precision and reliability of traditional methods. This research underscores the immense potential of combining advanced seismic inversion techniques with neural network models to revolutionize reservoir characterization. Our findings firmly establish the effectiveness of MBI and BLI, particularly when paired with PNN, in delivering accurate and high-resolution insights into subsurface porosity and reservoir boundaries. © Indian Academy of Sciences 2025.
Monitoring long-term storage of CO2 in a gas and condensate field in the North Sea off the coast of Norway using seismic methods
(Society of Exploration Geophysicists, 2025) Ajay Pratap Singh; Satya Prakash Maurya; Ravi Kant; Brijesh M.N. Kumar; Gopal Hema; Manoj Kumar Srivastava; Abhay Kumar; Anjali; Shoharat; Rohit Chaurasia; Anupama Sharma; Ankita Devi; Swarnima Pandey
The rising concentration of CO2 in the atmosphere drives climate change, prompting the development of various mitigation strategies. One approach involves injecting CO2 into hydrocarbon reservoirs for long-term storage. For long-term storage, one needs to monitor the injected CO2 to see the CO2 storage location and detect any leakage. This study focuses on the monitoring of injected CO2 in the Utsira Formation from a gas and condensate field in the Sleipner Field off the coast of Norway. The monitoring of injected CO2 is carried out using seismic inversion techniques of time-lapse data acquired over the injected zone at different time intervals. Seismic inversion techniques transform seismic reflection data into quantitative acoustic impedance models of the subsurface. The objective of the present study is to compare model-based inversion, band-limited inversion (BLI), maximum likelihood inversion, linear programming inversion (LPI) and sparse layer reflectivity inversion (SLRI) approaches to monitor CO2. All inversion techniques show consistent results, with low impedance values ranging from 2115 to 5275 m/s*g/cm3 in the Utsira Formation. Among these techniques, SLRI and LPI outperform traditional methods by offering high-resolution imaging of CO2 migration pathways, making them particularly effective for early leak detection and reducing uncertainties in reservoir modeling. By enhancing storage security and predictive modeling, these methodologies significantly contribute to the scalability and reliability of carbon capture and storage as a critical tool in combating climate change. This research not only strengthens the scientific foundation of seismic monitoring techniques but also provides practical recommendations for optimizing subsurface CO2 storage assessment methods. © 2025 Society of Exploration Geophysicists. All rights reserved.
Navigating the Narrative: Unveiling the Journey of Public Libraries in India Through Challenges and Opportunities
(Routledge, 2024) Abhay Chaurasia; Ajay Pratap Singh
This article dives into a captivating journey, unraveling the intricate tapestry of challenges, opportunities, and Governmental strides shaping the vibrant realm of Public Libraries in India. Not just that, it delves into the fascinating history, dissecting the state of these libraries before and after independence. Venturing beyond the surface, this exploration delves into the heart of matters. It exposes the pivotal role the Government plays in nurturing these havens of intellect, sparking a deeper appreciation for their contribution. Going beyond surface-level observations, this discourse penetrates the core of the subject and highlights the indispensable role of government in nurturing these bastions of intelligence. The article does not end here; Instead, it serves as a repository of solutions, addressing urgent needs for financial support, essential resources and innovative strategies that highlight a visionary path forward. With its interesting, practical and forward-looking approach, this article serves as a guiding compass, taking us through the complex labyrinth of library development. Intriguing, insightful, and forward-looking, this article is a compass guiding us through the intricate maze of library development. It promises to captivate your mind and ignite your curiosity, leaving you with a newfound respect for the past, present, and the limitless potential of Public Libraries in India. © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.
PAST AND PRESENT FACTORS OF THE DIFFICULTIES AND GOVERNMENT INITIATIVES IN INDIAN PUBLIC LIBRARIES
(University of Idaho Library, 2020) Abhay Chaurasia; Ajay Pratap Singh
Purpose: The purpose of this paper is to analyse the overall reasons for the difficulties in India’s contemporary library institutions. This difficulty is complicated by the historical origins of the general public libraries in India and, more broadly, by the difficult relationship between the Indian culture, government initiatives and today’s world. Methodology: A theoretical discussion on the role of Indian public libraries with government initiatives to achieve the role of Indian public libraries. Findings: The problems faced by the public libraries of India have been listed. There are a total of 28 states and 8 union territories in India, out of which only 19 states have library legislation in force and only five of them have a provision for library cess or levy. It has also been observed that there is no library legislation in a state with a low literacy rate. The lack of political consensus and goodwill, as well as the legislative process and legal issues involved in policymaking, have severely hampered of public libraries for the people of India. This paper needs to be considered in recent times to make the current national acts and the state library law in tune with the changing times and reflects the important phases of the IFLA's campaign, It is inclusive of government policies to include universal or public access to information literacy, information and communication and cultural heritage. The paper finds that the continuing acquisition of government initiatives, the development of a form of politics in the country suspended between centralised government and the claims of the local self-governments are all factors that have influenced the establishment of the public libraries in India. Originality/Value: Conjecturing the circumstances of the questionable origins of the public libraries in India can be of cooperating when determining which model to use in the future. A proper model for this system must not ignore but, in contrast, must improve the role of the library as a social institution of the history of a particular community. © 2020, Library Philosophy and Practice (e-journal). All Rights Reserved.
Reservoir characterization using simultaneous inversion of pre-stack seismic data based on traditional conjugate gradient methods and particle swarm optimization: A comparative case study
(Springer Science and Business Media Deutschland GmbH, 2025) Brijesh M.N. Kumar; Ravi Kant; Satya Prakash Maurya; Ajay Pratap Singh; Gopal Hema; Raghav S. Singh; Piyush Sarkar; Kumar Hemant Singh; Sanjay K. Sharma
Seismic inversion is a geophysical method that converts seismic reflection data into a quantitative representation of a reservoir's geological properties. These parameters are crucial for predicting reservoir rocks and the fluids present in the subsurface. Seismic inversion has been categorized into two ways: post-stack and pre-stack inversion. Pre-stack seismic inversion provides more detailed properties of the subsurface as compared to post-stack inversion. This study focuses on pre-stack seismic inversion using the traditional conjugate gradient methods and a novel methodology based on particle swarm optimization (PSO) techniques. Pre-stack inversion inherently utilizes amplitude variation with offset (AVO), which provides critical information about the elastic properties of the subsurface. The conjugate gradient method is a local optimization technique that can converge at local optima, potentially leading to false solutions to the inverse problem. To overcome these drawbacks, PSO, a global optimization technique with a tendency to converge at global optima, was employed. These methods were employed in the Penobscot field in Canada in two phases. Initially, the composite trace was inverted and then compared to the original well-log data. The full seismic volume was then inverted to calculate P-velocity, S-velocity, and density. The inverted results from both methods provided high-resolution subsurface information, but the PSO-based seismic inversion showed significantly better results compared to traditional methods. The conjugate gradient method attained a correlation of 0.89 with a RMS error of 0.33, while the PSO-based inversion attained a correlation of 0.95 with RMS error of 0.23. Additional statistical parameters also demonstrated that the PSO-based seismic inversion offered more detailed and higher-resolution subsurface information compared to the traditional pre-stack seismic inversion utilizing conjugate gradient methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.
Seismic inversion based on principal component analysis and probabilistic neural network for prediction of porosity from post-stack seismic data
(Springer Science and Business Media Deutschland GmbH, 2025) Nitin Verma; Ravi Kant; Satya Prakash Maurya; Brijesh M.N. Kumar; Ajay Pratap Singh; Gopal Hema; Raghav S. Singh; Kumar Hemant Singh; Piyush Sarkar
This research delves into the utilization of Principal Component Analysis (PCA) and Probabilistic Neural Network (PNN) techniques for predicting porosity values based on seismic inversion data, which provides crucial insights into subsurface properties essential for reservoir characterization. The study integrates Principal Component Analysis (PCA) with Probabilistic Neural Networks (PNN), to streamline the interpretation of seismic data by condensing numerous attributes into a smaller set with a probabilistic classification approach. This integration provides a novel methodology for processing and interpreting complex seismic data. Additionally, model-based inversion is conducted to obtain extra attributes (inverted impedance 7000–18000 m/s*g/cc) for use in training the PNN model. Subsequently, the PNN model is utilized to make accurate porosity predictions by leveraging the reduced-dimensional seismic features. The study aims to compare PNN performance with single attributes against PNN with Principal Component(PC), highlighting their differences and similarities for the data from the Blackfoot field in Canada.Initially, various single attributes are generated and then subjected to PCA techniques to convert them into three principal components. Both PNN models, one with single attributes and the other with PC, are trained and validated to reveal detailed subsurface information. The inverted results show a strong correlation with well-log parameters, with an average correlation coefficient of 0.84 for PNN using single attributes and 0.78 for PNN using PC.It was observed that PNN with single attributes performed better on the training data set but Performs below expectations on validation dataset compared to PNN with PC.Furthermore, these algorithms are applied to whole seismic data to predict porosity within the inter-well region. The inverted volumes depict consistent porosity ranging from 5 to 11% across the region for PNN with PC. Furthermore, the interpretation of the inverted results for PNN with PC highlights anomalous zones characterized by low impedance and high porosity. These zones closely match well-log data and are identified as likely sand channels. The combination of PCA and PNN represents an advancement in machine learning techniques applied to geoscience. This research contributes to the growing field of machine learning in geoscience by exploring new methodologies and their applications. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Seismic inversion for CO2 volume monitoring and comprehensive evaluation of pore fluid properties: a case study
(Springer Science and Business Media Deutschland GmbH, 2025) Gopal Hema; Satya Prakash Maurya; Ravi Kant; Ajay Pratap Singh; Nitin Verma; Brijesh M.N. Kumar; Raghav S. Singh; Kumar Hemant Singh
A comprehensive evaluation of pore fluid properties, involves detailed analysis of various characteristics and behaviours relevant to its storage and management in subsurface reservoirs. The assessment includes variations in CO2 density, bulk modulus, temperature, pressure, velocities, and interactions with reservoir fluids and rocks. The seismic response of porous rocks hosting pore fluids is influenced by these physical properties, crucial for understanding CO2 behaviour in carbon capture and storage (CCS) initiatives. In this study, we first utilize the Batzle–Wang model to predict the behavior of common pore fluids, such as brine and gas, which are key to understanding the seismic response of the reservoir. This initial analysis provides the foundation for the next step: monitoring the behavior of injected CO2 at the Sleipner field in Norway. To accurately track changes in the subsurface related to CO2 injection, we employ seismic inversion using the simulated annealing (SA) technique. This global optimization approach offers significant advantages over traditional local optimization methods, yielding more reliable and near-optimal solutions for estimating the changes in acoustic impedance caused by CO2 saturation. The study examines five sets of time-lapse seismic data from the Sleipner field, from 1994 to 2006. Acoustic impedances are computed for the pre-injection period and post-injection years, revealing a low impedance zone spanning from 2000 to 2500 m/s/g/cc. This inversion result predicts the injected CO2 volume by calculating the CO2 area from the uppermost time slice of different years, based on acoustic impedance seismic sections. To address inherent non-uniqueness in time-lapse analysis, the estimated volume is compared with the original production volume. The results indicate that the estimated volume closely resembles the original injected volume for different time-lapse seismic data. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.
The role of Professional Development on Job Satisfaction of the LIS professionals
(University of Nebraska-Lincoln, 2021) Latika Singh; Ajay Pratap Singh
Professional development (PD) implies the overall and systematic development of employees. It is a method to procure current knowledge and skills. In this digital environment, it becomes more crucial that LIS professionals should be professionally developed. Professional development is one of the elements which affects job satisfaction of employees. It is imperative for LIS professionals as it increases their level of satisfaction and improves their performance. LIS professionals must participate in professional development activities that have a positive impact on job satisfaction. Professionally developed and satisfied LIS professionals can deliver better service to their users. © 2021. Library Philosophy and Practice. All rights reserved.
Two acyl sucroses from Petunia nyctaginiflora
(Elsevier Ltd, 2003) Ajay Pratap Singh; Ajit Kumar Singh; A. Sajeli Begum; Mahendra Sahai
Two new acyl sucroses were isolated from the epigeal parts of Petunia nyctaginiflora Juss. (Solanaceae). Their structures were determined to be 2, 3, 4-tri (5- methylhexanoyl)-α-D-glucopyranosyl-β-D-fructofuranoside (2) and 2, 3, 4-tri (6-methylheptanoyl)-α-D-glucopyranosyl-β-D-fructofuranoside (4) on the basis of chemical and spectroscopic evidence. © 2003 Elsevier Science Ltd. All rights reserved.
Two novel acyl sucroses from Petunia nyctaginiflora
(2005) A. Sajeli Begum; Ajay Pratap Singh; Mahendra Sahai; Subhra Singh; Yoshinori Fujimoto
Two acyl sucroses, isolated from Petunia nyctaginiflora Jussieu (Solanaceae) have been characterized chemically as 2,3,4-tri(5-methylhexanoyl)- α-D-glucopyranosyl-β-D-6-acetyl fructo-furanoside 4 and 2,3,4-tri(6-methylheptanoyl)-α-D-glucopyranosyl-β-D-6-acetyl fructofuranoside 6, on the basis of chemical and spectroscopic evidence.