A review of the technical and economic evaluation techniques for shale gas development

Yuan, Jiehui; Luo, Dongkun; Feng, Lianyong

doi:10.1016/j.apenergy.2015.03.040

Cited by 194 publications

(87 citation statements)

References 87 publications

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“…It is worth noting that the proposed modeling framework is flexible enough to account for seasonal variations in the demand if we consider a short‐time horizon, for example, 1 year. The related data, including economic data, and technological data, used in this work are based on the existing literature …”

Section: Case Studymentioning

confidence: 99%

Data‐driven distributionally robust optimization of shale gas supply chains under uncertainty

2018

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This article aims to leverage the big data in shale gas industry for better decision making in optimal design and operations of shale gas supply chains under uncertainty. We propose a two‐stage distributionally robust optimization model, where uncertainties associated with both the upstream shale well estimated ultimate recovery and downstream market demand are simultaneously considered. In this model, decisions are classified into first‐stage design decisions, which are related to drilling schedule, pipeline installment, and processing plant construction, as well as second‐stage operational decisions associated with shale gas production, processing, transportation, and distribution. A data‐driven approach is applied to construct the ambiguity set based on principal component analysis and first‐order deviation functions. By taking advantage of affine decision rules, a tractable mixed‐integer linear programming formulation can be obtained. The applicability of the proposed modeling framework is demonstrated through a small‐scale illustrative example and a case study of Marcellus shale gas supply chain. Comparisons with alternative optimization models, including the deterministic and stochastic programming counterparts, are investigated as well. © 2018 American Institute of Chemical Engineers AIChE J, 65: 947–963, 2019

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Section: Case Studymentioning

confidence: 99%

Data‐driven distributionally robust optimization of shale gas supply chains under uncertainty

2018

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“…Shale gas, due to its clean‐burning and efficient nature, is becoming an increasingly promising alternative energy resource . Understanding gas transport in shale media poses a long‐standing challenge to scientists and engineers.…”

Section: Introductionmentioning

confidence: 99%

An analytical model for real gas flow in shale nanopores with non‐circular cross‐section

Ren

Tian

et al. 2016

AIChE Journal

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An analytical model for gas transport in shale media is proposed on the basis of the linear superposition of convective flow and Knudsen diffusion, which is free of tangential momentum accommodation coefficient. The present model takes into the effect of pore shape and real gas, and is successfully validated against experimental data and Lattice-Boltzmann simulation results. Gas flow in noncircular nanopores can be accounted by a dimensionless geometry correction factor. In continuum-flow regime, pore shape has a relatively minor impact on gas transport capacity; the effect of pore shape on gas transport capacity enhances significantly with increasing rarefaction. Additionally, gas transport capacity is strongly dependent of average pore size and streamline tortuosity. We also show that the present model without using weighted factor can describe the variable contribution of convective flow and Knudsen diffusion to the total flow. As pressure and pore radius decrease, the number of molecule-wall collisions gradually predominates over the number of intermolecule collisions, and thus Knudsen diffusion contributes more to the total flow. The parameters in the present model can be determined from independent laboratory experiments. We have the confidence that the present model can provide some theoretical support in numerical simulation of shale gas production.Where a is the geometry correction factor, dimensionless, with a 5 1 for a circular; r e is equivalent pore radius, m.

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“…Kinnaman [18], Wang et al [17] and Yuan et al [19] provide informative reviews of these studies. To be more specific, Bonakdarpour et al [20] suggests that the shale gas industry contributed more than 600,000 jobs in 2010 and is likely to increase to around 870,000 by 2015 and more than 1.6 million by 2035.…”

Section: Literature Reviewmentioning

confidence: 99%

The US Shale Gas Revolution and Its Externality on Crude Oil Prices: A Counterfactual Analysis

Liu¹,

Li²

2018

Sustainability

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Abstract:The expansion of shale gas production since the mid-2000s which is commonly referred to as "shale gas revolution" has had large impacts on global energy outlook. The impact is particularly substantial when it comes to the oil market because natural gas and oil are substitutes in consumption and complements and rivals in production. This paper investigates the price externality of shale gas revolution on crude oil. Applying a structural vector autoregressive model (VAR) model, the effect of natural gas production on real oil price is identified in particular, and then based on the identification, counterfactuals of oil price without shale gas revolution are constructed. We find that after the expansion of shale gas production, the real West Texas Intermediate (WTI) oil price is depressed by 10.22 USD/barrel on average from 2007 to 2017, and the magnitude seems to increase with time. In addition, the period before shale gas revolution is used as a "thought experiment" for placebo study. The results support the hypothesis that real WTI oil price can be reasonably reproduced by our models, and the estimated gap for oil price during 2007-2017 can be attributed to shale gas revolution. The methodology and framework can be applied to evaluate the economic impacts of other programs or policies.

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A review of the technical and economic evaluation techniques for shale gas development

Cited by 194 publications

References 87 publications

Data‐driven distributionally robust optimization of shale gas supply chains under uncertainty

Data‐driven distributionally robust optimization of shale gas supply chains under uncertainty

An analytical model for real gas flow in shale nanopores with non‐circular cross‐section

The US Shale Gas Revolution and Its Externality on Crude Oil Prices: A Counterfactual Analysis

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