Energy-environmental implications of shale gas extraction with considering a stochastic decentralized structure

Multi-criteria design of shale-gas-water supply chains and production systems towards optimal life cycle economics and greenhouse gas emissions under uncertainty

Contributions of individual preproduction activities to overall energy use and greenhouse gas (GHG) emissions during shale gas development are not well understood nor quantified. This paper uses predictive modeling combining the physics of reservoir development operations with depositional attributes of shale gas basins to account for energy requirements and GHG emissions during shale gas well development. We focus on shale gas development from the Montney basin in Canada and account for the energy use during drilling and fluid pumping for reservoir stimulation, in addition to preproduction emissions arising from energy use and potential gas releases during operations. Detailed modeling of activities and events that take place during each stage of development is described. Relative to the hydraulic fracturing activity, we observe significantly higher energy intensity for the well drilling and mud circulation activities. Well completion flowback gas is found to be the predominant potential source of GHG emission. When these results are expressed on an annual basis, consistent with the convention of most climate policy goals and directives, environmental impacts of our growing natural gas economy are better appreciated. Estimated likely GHG emission from new development wells in 2017 in the Montney Formation alone is 2.68 Mt CO2e. However, on a preproduction requirements basis and dependent on mean estimated ultimate recovery (EUR), energy return on invested energy for shale gas from the Montney Formation in Canada is estimated to be about 3400. The approach described here can be reliably extended to areas, globally, where natural gas development is becoming prominent.

Quantification and control of the greenhouse gas emissions from a dairy cow system

The optimal design and operations of shale gas supply chains under uncertainty of estimated ultimate recovery (EUR) is addressed. A two‐stage stochastic mixed‐integer linear fractional programming (SMILFP) model is developed to optimize the levelized cost of energy generated from shale gas. In this model, both design and planning decisions are considered with respect to shale well drilling, shale gas production, processing, multiple end‐uses, and transportation. To reduce the model size and number of scenarios, we apply a sample average approximation method to generate scenarios based on the real‐world EUR data. In addition, a novel solution algorithm integrating the parametric approach and the L‐shaped method is proposed for solving the resulting SMILFP problem within a reasonable computational time. The proposed model and algorithm are illustrated through a case study based on the Marcellus shale play, and a deterministic model is considered for comparison. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3739–3755, 2015

In this paper, we propose the first stochastic model addressing the optimal design and operations of the comprehensive shale gas supply chain, where uncertainties of estimated ultimate recovery (EUR) in each shale well are considered. The resulting mixed-integer linear programming (MILP) model covers the well-to-wire life cycle of shale gas, which consists of a number of stages including freshwater acquisition, shale well drilling, fracking, and completion, shale gas production, wastewater management, shale gas processing, electricity generation as well as transportation and storage. In order to reduce the model size and the number of scenarios, we use a sample average approximation approach to generate scenarios based on the EUR distribution derived from actual historical data. To demonstrate the proposed stochastic model and solution approach, we present a case study based on Marcellus shale play to maximize the total expected profit of this shale gas supply chain network.

This article addresses the optimal design of a non‐cooperative shale gas supply chain based on a game theory approach. Instead of assuming a single stakeholder as in centralized models, we consider different stakeholders, including the upstream shale gas producer and the midstream shale gas processor. Following the Stackelberg game, the shale gas producer is identified as the leader, whose objectives include maximizing its net present value (NPV) and minimizing the life cycle greenhouse gas (GHG) emissions. The shale gas processor is identified as the follower that takes actions after the leader to maximize its own NPV. The resulting problem is a multiobjective mixed‐integer bilevel linear programming problem, which cannot be solved directly using any off‐the‐shelf optimization solvers. Therefore, an efficient projection‐based reformulation and decomposition algorithm is further presented. Based on a case study of the Marcellus shale play, the non‐cooperative model not only captures the interactions between stakeholders but also provides more realistic solutions. © 2017 American Institute of Chemical Engineers AIChE J, 63: 2671–2693, 2017

A three-level framework for balancing the tradeoffs among the energy, water, and air-emission implications within the life-cycle shale gas supply chains

In recent decades, large-scale production of shale gas has been considered as a major issue in the U.S. energy industry. In accordance with its great economic potential and environmental concerns, shale gas process and supply chain optimization has become one of the most popular research areas. In this chapter, we provide a comprehensive overview of the supply chain management and process design problems in shale gas industry. We summarize four major research challenge areas, namely the design and planning of shale gas supply chain, water management in hydraulic fracturing, sustainability concerns in shale gas industry, and design and optimization in shale gas processing system. We further provide review and discussions of the major publications corresponding to each of the aforementioned topics. Potential opportunities in the shale gas system are presented as well to illuminate the future research.

Techno-economic integration evaluation in shale gas development based on ensemble learning

Game-based analysis of energy-water nexus for identifying environmental impacts during Shale gas operations under stochastic input

We present results of a life cycle assessment (LCA) of Marcellus shale gas used for power generation. The analysis employs the most extensive data set of any LCA of shale gas to date, encompassing data from actual gas production and power generation operations. Results indicate that a typical Marcellus gas life cycle yields 466 kg CO2eq/MWh (80% confidence interval: 450-567 kg CO2eq/MWh) of greenhouse gas (GHG) emissions and 224 gal/MWh (80% CI: 185-305 gal/MWh) of freshwater consumption. Operations associated with hydraulic fracturing constitute only 1.2% of the life cycle GHG emissions, and 6.2% of the life cycle freshwater consumption. These results are influenced most strongly by the estimated ultimate recovery (EUR) of the well and the power plant efficiency: increase in either quantity will reduce both life cycle freshwater consumption and GHG emissions relative to power generated at the plant. We conclude by comparing the life cycle impacts of Marcellus gas and U.S. coal: The carbon footprint of Marcellus gas is 53% (80% CI: 44-61%) lower than coal, and its freshwater consumption is about 50% of coal. We conclude that substantial GHG reductions and freshwater savings may result from the replacement of coal-fired power generation with gas-fired power generation.

Life cycle greenhouse gas emissions of China shale gas

Plastics and climate change—Breaking carbon lock-ins through three mitigation pathways

In this work, the life cycle economic and environmental optimization of shale gas supply chain network design and operations is addressed. The proposed model covers the well-to-wire life cycle of electricity generated from shale gas, consisting of a number of stages including freshwater acquisition, shale well drilling, hydraulic fracturing and completion, shale gas production, wastewater management, shale gas processing, electricity generation as well as transportation and storage. A functional-unit based life cycle optimization problem for a cooperative shale gas supply chain is formulated as a multiobjective nonconvex mixed-integer nonlinear programming (MINLP) problem. The resulting Pareto-optimal frontier reveals the trade-off between the economic and environmental objectives. A case study based on Marcellus shale play shows that the greenhouse gas emission of electricity generated from shale gas ranges from 433 to 499 kg CO2e/MWh, and the levelized cost of electricity ranges from $69 to $91/MWh. A g...

A Leader-Follower Game-Based Life Cycle Optimization Framework and Application