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Luc Quoniam - One of the best experts on this subject based on the ideXlab platform.
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how to use big data technologies to optimize operations in upstream Petroleum Industry
arXiv: Computers and Society, 2014Co-Authors: Abdelkader Baaziz, Luc QuoniamAbstract:"Big Data is the oil of the new economy" is the most famous citation during the three last years. It has even been adopted by the World Economic Forum in 2011. In fact, Big Data is like crude! It's valuable, but if unrefined it cannot be used. It must be broken down, analyzed for it to have value. But what about Big Data generated by the Petroleum Industry and particularly its upstream segment? Upstream is no stranger to Big Data. Understanding and leveraging data in the upstream segment enables firms to remain competitive throughout planning, exploration, delineation, and field development. Oil & Gas Companies conduct advanced geophysics modeling and simulation to support operations where 2D, 3D & 4D Seismic generate significant data during exploration phases. They closely monitor the performance of their operational assets. To do this, they use thousands sensors in subsurface wells and surface facilities to provide continuous and real-time monitoring of assets and environmental conditions. Unfortunately, this information comes in various and increasingly complex forms, making it a challenge to collect, interpret, and leverage the disparate data. Big Data technologies integrate common and disparate data sets to deliver the right information at the appropriate time to the correct decision-maker. These capabilities help firms act on large volumes of data, transforming decision-making from reactive to proactive and optimizing all phases of exploration, development and production. Furthermore, Big Data offers multiple opportunities to ensure safer, more responsible operations. Another invaluable effect of that would be shared learning. The aim of this paper is to explain how to use Big Data technologies to optimize operations. How can Big Data help experts to decision-making leading the desired outcomes?
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How to use Big Data technologies to optimize operations in Upstream Petroleum Industry
International Journal of Innovation (IJI), 2013Co-Authors: Abdelkader Baaziz, Luc QuoniamAbstract:Big Data is the oil of the new economy" is the most famous citation during the three last years. It has even been adopted by the World Economic Forum in 2011. In fact, Big Data is like crude! It's valuable, but if unrefined it cannot be used. It must be broken down, analyzed for it to have value. But what about Big Data generated by the Petroleum Industry and particularly its upstream segment? Upstream is no stranger to Big Data. Understanding and leveraging data in the upstream segment enables firms to remain competitive throughout planning, exploration, delineation, and field development. Oil & Gas Companies conduct advanced geophysics modeling and simulation to support operations where 2D, 3D & 4D Seismic generate significant data during exploration phases. They closely monitor the performance of their operational assets. To do this, they use tens of thousands of data-collecting sensors in subsurface wells and surface facilities to provide continuous and real-time monitoring of assets and environmental conditions. Unfortunately, this information comes in various and increasingly complex forms, making it a challenge to collect, interpret, and leverage the disparate data. As an example, Chevron's internal IT traffic alone exceeds 1.5 terabytes a day. Big Data technologies integrate common and disparate data sets to deliver the right information at the appropriate time to the correct decision-maker. These capabilities help firms act on large volumes of data, transforming decision-making from reactive to proactive and optimizing all phases of exploration, development and production. Furthermore, Big Data offers multiple opportunities to ensure safer, more responsible operations. Another invaluable effect of that would be shared learning. The aim of this paper is to explain how to use Big Data technologies to optimize operations. How can Big Data help experts to decision-making leading the desired outcomes?
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how to use big data technologies to optimize operations in upstream Petroleum Industry
International Journal of Innovation, 2013Co-Authors: Abdelkader Baaziz, Luc QuoniamAbstract:“ Big Data is the oil of the new economy ” is the most famous citation during the three last years. It has even been adopted by the World Economic Forum in 2011. In fact, Big Data is like crude! It’s valuable, but if unrefined it cannot be used. It must be broken down, analyzed for it to have value. But what about Big Data generated by the Petroleum Industry and particularly its upstream segment? Upstream is no stranger to Big Data . Understanding and leveraging data in the upstream segment enables firms to remain competitive throughout planning, exploration, delineation, and field development. Oil & Gas Companies conduct advanced geophysics modeling and simulation to support operations where 2D, 3D & 4D Seismic generate significant data during exploration phases. They closely monitor the performance of their operational assets. To do this, they use tens of thousands of data-collecting sensors in subsurface wells and surface facilities to provide continuous and real-time monitoring of assets and environmental conditions. Unfortunately, this information comes in various and increasingly complex forms, making it a challenge to collect, interpret, and leverage the disparate data. As an example, Chevron’s internal IT traffic alone exceeds 1.5 terabytes a day. Big Data technologies integrate common and disparate data sets to deliver the right information at the appropriate time to the correct decision-maker. These capabilities help firms act on large volumes of data, transforming decision-making from reactive to proactive and optimizing all phases of exploration, development and production. Furthermore, Big Data offers multiple opportunities to ensure safer, more responsible operations. Another invaluable effect of that would be shared learning. The aim of this paper is to explain how to use Big Data technologies to optimize operations. How can Big Data help experts to decision-making leading the desired outcomes? Keywords: Big Data; Analytics; Upstream Petroleum Industry; Knowledge Management; KM; Business Intelligence; BI; Innovation; Decision-making under Uncertainty
Abdelkader Baaziz - One of the best experts on this subject based on the ideXlab platform.
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how to use big data technologies to optimize operations in upstream Petroleum Industry
arXiv: Computers and Society, 2014Co-Authors: Abdelkader Baaziz, Luc QuoniamAbstract:"Big Data is the oil of the new economy" is the most famous citation during the three last years. It has even been adopted by the World Economic Forum in 2011. In fact, Big Data is like crude! It's valuable, but if unrefined it cannot be used. It must be broken down, analyzed for it to have value. But what about Big Data generated by the Petroleum Industry and particularly its upstream segment? Upstream is no stranger to Big Data. Understanding and leveraging data in the upstream segment enables firms to remain competitive throughout planning, exploration, delineation, and field development. Oil & Gas Companies conduct advanced geophysics modeling and simulation to support operations where 2D, 3D & 4D Seismic generate significant data during exploration phases. They closely monitor the performance of their operational assets. To do this, they use thousands sensors in subsurface wells and surface facilities to provide continuous and real-time monitoring of assets and environmental conditions. Unfortunately, this information comes in various and increasingly complex forms, making it a challenge to collect, interpret, and leverage the disparate data. Big Data technologies integrate common and disparate data sets to deliver the right information at the appropriate time to the correct decision-maker. These capabilities help firms act on large volumes of data, transforming decision-making from reactive to proactive and optimizing all phases of exploration, development and production. Furthermore, Big Data offers multiple opportunities to ensure safer, more responsible operations. Another invaluable effect of that would be shared learning. The aim of this paper is to explain how to use Big Data technologies to optimize operations. How can Big Data help experts to decision-making leading the desired outcomes?
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How to use Big Data technologies to optimize operations in Upstream Petroleum Industry
International Journal of Innovation (IJI), 2013Co-Authors: Abdelkader Baaziz, Luc QuoniamAbstract:Big Data is the oil of the new economy" is the most famous citation during the three last years. It has even been adopted by the World Economic Forum in 2011. In fact, Big Data is like crude! It's valuable, but if unrefined it cannot be used. It must be broken down, analyzed for it to have value. But what about Big Data generated by the Petroleum Industry and particularly its upstream segment? Upstream is no stranger to Big Data. Understanding and leveraging data in the upstream segment enables firms to remain competitive throughout planning, exploration, delineation, and field development. Oil & Gas Companies conduct advanced geophysics modeling and simulation to support operations where 2D, 3D & 4D Seismic generate significant data during exploration phases. They closely monitor the performance of their operational assets. To do this, they use tens of thousands of data-collecting sensors in subsurface wells and surface facilities to provide continuous and real-time monitoring of assets and environmental conditions. Unfortunately, this information comes in various and increasingly complex forms, making it a challenge to collect, interpret, and leverage the disparate data. As an example, Chevron's internal IT traffic alone exceeds 1.5 terabytes a day. Big Data technologies integrate common and disparate data sets to deliver the right information at the appropriate time to the correct decision-maker. These capabilities help firms act on large volumes of data, transforming decision-making from reactive to proactive and optimizing all phases of exploration, development and production. Furthermore, Big Data offers multiple opportunities to ensure safer, more responsible operations. Another invaluable effect of that would be shared learning. The aim of this paper is to explain how to use Big Data technologies to optimize operations. How can Big Data help experts to decision-making leading the desired outcomes?
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how to use big data technologies to optimize operations in upstream Petroleum Industry
International Journal of Innovation, 2013Co-Authors: Abdelkader Baaziz, Luc QuoniamAbstract:“ Big Data is the oil of the new economy ” is the most famous citation during the three last years. It has even been adopted by the World Economic Forum in 2011. In fact, Big Data is like crude! It’s valuable, but if unrefined it cannot be used. It must be broken down, analyzed for it to have value. But what about Big Data generated by the Petroleum Industry and particularly its upstream segment? Upstream is no stranger to Big Data . Understanding and leveraging data in the upstream segment enables firms to remain competitive throughout planning, exploration, delineation, and field development. Oil & Gas Companies conduct advanced geophysics modeling and simulation to support operations where 2D, 3D & 4D Seismic generate significant data during exploration phases. They closely monitor the performance of their operational assets. To do this, they use tens of thousands of data-collecting sensors in subsurface wells and surface facilities to provide continuous and real-time monitoring of assets and environmental conditions. Unfortunately, this information comes in various and increasingly complex forms, making it a challenge to collect, interpret, and leverage the disparate data. As an example, Chevron’s internal IT traffic alone exceeds 1.5 terabytes a day. Big Data technologies integrate common and disparate data sets to deliver the right information at the appropriate time to the correct decision-maker. These capabilities help firms act on large volumes of data, transforming decision-making from reactive to proactive and optimizing all phases of exploration, development and production. Furthermore, Big Data offers multiple opportunities to ensure safer, more responsible operations. Another invaluable effect of that would be shared learning. The aim of this paper is to explain how to use Big Data technologies to optimize operations. How can Big Data help experts to decision-making leading the desired outcomes? Keywords: Big Data; Analytics; Upstream Petroleum Industry; Knowledge Management; KM; Business Intelligence; BI; Innovation; Decision-making under Uncertainty
James L Coleman - One of the best experts on this subject based on the ideXlab platform.
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the american whale oil Industry a look back to the future of the american Petroleum Industry
Nonrenewable Resources, 1995Co-Authors: James L ColemanAbstract:The American whaling Industry rose from humble beginnings off Long island to become an international giant. In its peak year, 1846, 735 ships and 70,000 people served the Industry. As whale stocks and reserves decreased, whalers were forced to go farther and farther from their New England home ports. Voyages became longer, and risks on required return-on-investment became higher. The “easy money” of Atlantic and Pacific whaling was no more: the only remaining profitable ventures were to Arctic and Antarctic waters. Many ships returned empty, if at all. in 1871, most of the Arctic whaling fleet was crushed by early winter ice and lost. This calamity, in conjunction with the long-term diminishing whale stocks, the diversion of investment capital to more profitable ventures, and the discovery, development, and refinement of abundant Petroleum crude oil, struck the death blow to the American whaling Industry. By 1890, only 200 whaling vessels were at work, and by 1971, no American commercial whaling ship sailed the world's oceans. It is apparent that no single event caused the final, rapid decline. However, a single calamity, in an already stressed Industry, that was self-insured and commercially interlinked, precipitated the end. Today's American Petroleum Industry, although adopting some principles of the American whaling Industry, also has embraced other activities such as work process reengineering and customer alliances, which may preempt, or postpone, a similar catastrophic demise.
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a speculative look at the future of the american Petroleum Industry based on a full cycle analysis of the american whale oil Industry abstract
AAPG Bulletin, 1995Co-Authors: James L ColemanAbstract:A full-cycle, Industry-scale look at the American whaling Industry of the 19th century suggests a number of comparisons with the American Petroleum Industry of the 20th century. Using the King Hubbert production profile for extraction industries as a guide, both industries show a similar business life span. An understanding of the history of American whaling will, perhaps, gives us a more complete understanding of the history of the American Petroleum Industry. The rise of the American whaling Industry to the premier investment opportunity of its day is little known to most in today`s oil and gas Industry. Yet, we all know that abundant and inexpensive crude oil was a key factor in its demise. From a careful study of the history of the American whaling Industry a set of factors (or stages of transition), common to similar extraction industries, can be developed, which may help investors and workers determine the state of health of our Industry: (1) defection of highly skilled personnel to other, comparable, technical industries; (2) discovery and initial development of a replacement commodity; (3) major calamity, which adversely affects the Industry in terms of significant loss of working capital and/or resources; (4) loss of sufficient investment capitalmore » to continue resource addition; (5) rapid development of a replacement commodity with attendant decrease in per unit price to a position lower than the primary commodity; (6) significant loss of market share by the primary commodity; and (7) end of the primary commodity as a major economic force.« less
Stephanie G Adams - One of the best experts on this subject based on the ideXlab platform.
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corporate social responsibility benchmarking and organizational performance in the Petroleum Industry a quality management perspective
International Journal of Production Economics, 2012Co-Authors: Mahour Mellat Parast, Stephanie G AdamsAbstract:Abstract The purpose of this paper is to investigate the effect of corporate social responsibility and benchmarking on organizational performance in the Petroleum Industry. We find that top management support for quality is the main driver of practices associated with corporate social responsibility. Corporate social responsibility appears to have a significant impact on internal quality results (operational performance) but it does not have a significant effect on external quality results (firm performance). We did not find a very strong relationship between benchmarking and internal/external quality results. Our findings suggest that the implementation of corporate social responsibility in the Petroleum Industry is economically driven. Recommendations for managers and future research have been outlined.
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improving operational and business performance in the Petroleum Industry through quality management
International Journal of Quality & Reliability Management, 2011Co-Authors: Mahour Mellat Parast, Stephanie G Adams, Erick C JonesAbstract:Purpose – The purpose of this paper is to investigate empirically the effects of quality management practices on operational and business performance.Design/methodology/approach – A reliable and valid survey instrument was used for data gathering from managers in the Petroleum Industry. A multiple regression analysis was conducted to determine the effect of quality management practices on operational and business performance.Findings – The results indicate that top management support, employee training, and employee involvement are significant variables explaining the variability of operational performance. Furthermore, a multiple regression analysis on business performance indicated the significance of top management support on business performance. The study also shows that customer orientation is not a significant predictor of business performance in the Petroleum Industry. In addition, focus on practices associated with human resource management (employee training and employee involvement) is critical...
Mahour Mellat Parast - One of the best experts on this subject based on the ideXlab platform.
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corporate social responsibility benchmarking and organizational performance in the Petroleum Industry a quality management perspective
International Journal of Production Economics, 2012Co-Authors: Mahour Mellat Parast, Stephanie G AdamsAbstract:Abstract The purpose of this paper is to investigate the effect of corporate social responsibility and benchmarking on organizational performance in the Petroleum Industry. We find that top management support for quality is the main driver of practices associated with corporate social responsibility. Corporate social responsibility appears to have a significant impact on internal quality results (operational performance) but it does not have a significant effect on external quality results (firm performance). We did not find a very strong relationship between benchmarking and internal/external quality results. Our findings suggest that the implementation of corporate social responsibility in the Petroleum Industry is economically driven. Recommendations for managers and future research have been outlined.
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improving operational and business performance in the Petroleum Industry through quality management
International Journal of Quality & Reliability Management, 2011Co-Authors: Mahour Mellat Parast, Stephanie G Adams, Erick C JonesAbstract:Purpose – The purpose of this paper is to investigate empirically the effects of quality management practices on operational and business performance.Design/methodology/approach – A reliable and valid survey instrument was used for data gathering from managers in the Petroleum Industry. A multiple regression analysis was conducted to determine the effect of quality management practices on operational and business performance.Findings – The results indicate that top management support, employee training, and employee involvement are significant variables explaining the variability of operational performance. Furthermore, a multiple regression analysis on business performance indicated the significance of top management support on business performance. The study also shows that customer orientation is not a significant predictor of business performance in the Petroleum Industry. In addition, focus on practices associated with human resource management (employee training and employee involvement) is critical...