Modeling the estimation of petroleum resources in the United States

Sterman, John D.; Richardson, George P.; Davidsen, Pål I.

doi:10.1016/0040-1625(88)90015-7

Cited by 41 publications

(20 citation statements)

References 21 publications

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“…Hybrids of curvefitting and econometrics offer promise, but can also have the disadvantages of both [56,57]. Systems dynamic models [58,59] reproduce the physical and economic mechanisms that govern oil production, but can also be overcomplicated and unstable and frequently lack both empirical validation and sufficient data for parametrization. Perhaps the most promising approach is to model the production of individual fields and projects and to construct regional forecasts by aggregating this bottom-up information [60].…”

Section: Box 2 Methods Of Forecasting Oil Supplymentioning

confidence: 99%

The future of oil supply

Miller

Sorrell

2014

Phil. Trans. R. Soc. A.

115

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Abundant supplies of oil form the foundation of modern industrial economies, but the capacity to maintain and grow global supply is attracting increasing concern. Some commentators forecast a peak in the near future and a subsequent terminal decline in global oil production, while others highlight the recent growth in ‘tight oil’ production and the scope for developing unconventional resources. There are disagreements over the size, cost and recoverability of different resources, the technical and economic potential of different technologies, the contribution of different factors to market trends and the economic implications of reduced supply. Few debates are more important, more contentious, more wide-ranging or more confused. This paper summarizes the main concepts, terms, issues and evidence that are necessary to understand the ‘peak oil’ debate. These include: the origin, nature and classification of oil resources; the trends in oil production and discoveries; the typical production profiles of oil fields, basins and producing regions; the mechanisms underlying those profiles; the extent of depletion of conventional oil; the risk of an approaching peak in global production; and the potential of various mitigation options. The aim is to introduce the subject to non-specialist readers and provide a basis for the subsequent papers in this Theme Issue.

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Section: Box 2 Methods Of Forecasting Oil Supplymentioning

confidence: 99%

The future of oil supply

Miller

Sorrell

2014

Phil. Trans. R. Soc. A.

115

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“…For instance, when protocols for estimation of total resources via the Hubbert model and the USGS geologic analogy approach, using actual US data, it turns out that the Hubbert model overestimated based on experience through the 1930s, but underestimated from 1940 on, becoming increasingly accurate as production passed its peak in 1970. By contrast, the USGS model underestimated at the beginning, but overestimated dramatically from 1945 until well beyond the peak year and only approaches the right answer (from above) towards the end (Sterman et al 1988). It seems likely that the USGS-2000 methodology still suffers from the same weakness.…”

Section: Even the Most Optimistic Assessment Of Future Exergy Availabmentioning

confidence: 94%

“…Natural gas is the fashionable alternative to liquid petroleum for the middle of the twenty-first century. However, it is interesting to note that the estimates of producible domestic gas that were made by energy companies and the US Geological Survey in the 1960s and 70s have undergone substantial reduction, probably due to the faulty estimation methodology noted above (Sterman et al 1988). Gas reserves have declined since the 1970s.…”

Section: Even the Most Optimistic Assessment Of Future Exergy Availabmentioning

confidence: 99%

On the practical limits to substitution

Ayres

2007

Ecological Economics

193

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“…Its application in case studies can be seen in areas such as defence Cooper, ( 1980)social sciences Richardson (1991), medical science Homer (1987), ecology Sterman, Richardson, et Davidsen, (1998) Gary, Kunc, et Morecroft, 2009, management Roberts (1978, knowledge sharing Luna-Reyes et al, 2008, resource allocation Lee, Ford, et Joglekar, 2007, disruptions (Williams, Ackermann, et Eden, 2003 or supply networks Ashayeri, Keij, et Bröker (1998) Campuzano, Mula, et Peidro (2010).…”

Section: System Dynamicsmentioning

confidence: 99%

A Review of Approaches and Tools for Collaborative Networks Simulation

Andrés

Poler

2016

Braz. J. of Operations & Production Manag.

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Collaborative networks (CN) are characterised by being complex systems, highlighting the need of considering simulation approaches to support the resolution of CN models. Simulation approaches are seen as a supporting tool to analyse the formal model of a supply network. Three relevant simulation approaches are identified for its application in the context of CN models: Discrete Events Simulation, System Dynamics and Agent Based Simulation. Each simulation approach is briefly described and compared with each other, according to a group of relevant features, with the main aim of aiding the modellers in the task of selecting the most appropriate simulation approach to address the modelling process in the context of CN. Besides, a group of commercial and academic tools are listed for each simulation approach.

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Modeling the estimation of petroleum resources in the United States

Cited by 41 publications

References 21 publications

The future of oil supply

The future of oil supply

On the practical limits to substitution

A Review of Approaches and Tools for Collaborative Networks Simulation

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