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Engineering    2017, Vol. 3 Issue (2) : 244 -256
Research |
Interactions between the Design and Operation of Shale Gas Networks, Including CO2 Sequestration
Sharifzadeh Mahdi(),Xingzhi Wang,Nilay Shah
Center for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London SW7 2AZ, UK

As the demand for energy continues to increase, shale gas, as an unconventional source of methane (CH4), shows great potential for commercialization. However, due to the ultra-low permeability of shale gas reservoirs, special procedures such as horizontal drilling, hydraulic fracturing, periodic well shut-in, and carbon dioxide (CO2) injection may be required in order to boost gas production, maximize economic benefits, and ensure safe and environmentally sound operation. Although intensive research is devoted to this emerging technology, many researchers have studied shale gas design and operational decisions only in isolation. In fact, these decisions are highly interactive and should be considered simultaneously. Therefore, the research question addressed in this study includes interactions between design and operational decisions. In this paper, we first establish a full-physics model for a shale gas reservoir. Next, we conduct a sensitivity analysis of important design and operational decisions such as well length, well arrangement, number of fractures, fracture distance, CO2 injection rate, and shut-in scheduling in order to gain in-depth insights into the complex behavior of shale gas networks. The results suggest that the case with the highest shale gas production may not necessarily be the most profitable design; and that drilling, fracturing, and CO2 injection have great impacts on the economic viability of this technology. In particular, due to the high costs, enhanced gas recovery (EGR) using CO2 does not appear to be commercially competitive, unless tax abatements or subsidies are available for CO2 sequestration. It was also found that the interactions between design and operational decisions are significant and that these decisions should be optimized simultaneously.

Keywords Shale gas      Hydraulic fracturing      Scheduling      Well shut-in      CO2 sequestration      Simultaneous optimization     
Corresponding Authors: Sharifzadeh Mahdi   
Just Accepted Date: 16 March 2017   Online First Date: 21 April 2017    Issue Date: 27 April 2017
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Sharifzadeh Mahdi
Xingzhi Wang
Nilay Shah
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Sharifzadeh Mahdi,Xingzhi Wang,Nilay Shah. Interactions between the Design and Operation of Shale Gas Networks, Including CO2 Sequestration[J]. Engineering, 2017, 3(2): 244 -256 .
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1   Sharifzadeh M. Integration of process design and control: A review. Chem Eng Res Des 2013;91(12):2515–49
doi: 10.1016/j.cherd.2013.05.007
2   Sharifzadeh M, Thornhill NF. Integrated design and control using a dynamic inversely controlled process model. Comput Chem Eng 2013;48:121–34
doi: 10.1016/j.compchemeng.2012.08.009
3   Sharifzadeh M, Meghdari M, Rashtchian D. Multi-objective design and operation of solid oxide fuel cell (SOFC) triple combined-cycle power generation systems: Integrating energy efficiency and operational safety. Appl Energy 2017;185(Part 1):345–61
doi: 10.1016/j.apenergy.2016.11.010
4   Ran B, Kelkar M. Fracture stages optimization in Bakken shale formation. In: Proceedings of the 3rd Unconventional Resources Technology Conference; 2015 Jul 20–22; San Antonio, USA. San Antonio: URTeC; 2015.
5   Balan HO, Gupta A, Georgi DT, Al-Shawaf AM. Optimization of well and hydraulic fracture spacing for tight/shale gas reservoirs. In: Proceedings of the 4rd Unconventional Resources Technology Conference; 2016 Aug 1–3 ; San Antonio, USA. San Antonio: URTeC; 2016
doi: 10.15530/urtec-2016-2435369
6   Whitson CH, Rahmawati SD, Juell A. Cyclic shut-in eliminates liquid-loading in gas wells. In: Proceedings of the SPE/EAGE European Unconventional Resources Conference and Exhibition; 2012 Mar 20–22; Vienna, Austria. Richardson:Society of Petroleum Engineers; 2012
doi: 10.2118/153073-MS
7   Knudsen BR. Production optimization in shale gas reservoirs [dissertation]. Trondheim: Norwegian University of Science and Technology; 2010.
8   Knudsen BR, Foss B, Whitson CH, Conn AR. Target-rate tracking for shale-gas multi-well pads by scheduled shut-ins. IFAC Proceedings Volumes 2012;45(15):107–13
doi: 10.3182/20120710-4-SG-2026.00063
9   Knudsen BR, Foss B. Shut-in based production optimization of shale-gas systems. Comput Chem Eng 2013;58:54–67
doi: 10.1016/j.compchemeng.2013.05.022
10   Knudsen BR, Grossmann IE, Foss B, Conn AR. Lagrangian relaxation based decomposition for well scheduling in shale-gas systems. Comput Chem Eng 2014;63:234–49
doi: 10.1016/j.compchemeng.2014.02.005
11   Vermylen JP. Geomechanical studies of the Barnett shale [dissertation]. California: Stanford University; 2011.
12   Eshkalak MO, Al-Shalabi EW, Sanaei A, Aybar U, Sepehrnoori K. Simulation study on the CO2-driven enhanced gas recovery with sequestration versus the re-fracturing treatment of horizontal wells in the U.S. unconventional shale reservoirs. J Nat Gas Sci Eng 2014;21:1015–24
doi: 10.1016/j.jngse.2014.10.013
13   Kulga B, Dilmore R, Wyatt C, Ertekin T. Investigation of CO2 storage and enhanced gas recovery in depleted shale gas formations using a dual-porosity/dual-permeability, multiphase reservoir simulator [Internet]. Morgantown: US Department of Energy, National Energy Technology Laboratory; 2014 Sep 25 [cited 2017 Mar 10]. Available from: Library/Research/onsite research/publications/NETL-TRS-4-2014_CO2-Storage-and-Enhanced-Gas-Recovery_20140925.pdf.
14   Li X, Elsworth D. Geomechanics of CO2 enhanced shale gas recovery. J Nat Gas Sci Eng 2015;26:1607–19
doi: 10.1016/j.jngse.2014.08.010
15   Koederitz LF. Lecture notes on applied reservoir simulation. Singapore: World Scientific; 2005
doi: 10.1142/5775
16   Soeder DJ. Petrophysical characterization of the Marcellus & other gas shales [Internet]. 2011 Sep 28 [cited 2017 Feb 4]. Available from:
17   Wang C, Wu Y. Characterizing hydraulic fractures in shale gas reservoirs using transient pressure tests. Petroleum 2015;1(2):133–8
doi: 10.1016/j.petlm.2015.05.002
18   Swami V, Clarkson CR, Settari A. Non-Darcy flow in shale nanopores: Do we have a final answer? In: Proceedings of the SPE Canadian Unconventional Resources Conference; 2012 Oct 30–Nov 1; Calgary, Canada. Richardson: Society of Petroleum Engineers; 2012
doi: 10.2118/162665-MS
19   Aguilera R. Incorporating capillary pressure, pore throat aperture radii, height above free-water table, and Winland r35 values on Pickett plots. Am Assoc Pet Geol Bull 2002;86(4):605–24.
20   Liu J, Qiu Z, Huang W, Luo Y, Song D. Nano-pore structure characterization of shales using gas adsorption and mercury intrusion techniques. J Chem Pharm Res 2014;6(4):850–7.
21   Cho Y, Ozkan E, Apaydin OG. Pressure-dependent natural-fracture permeability in shale and its effect on shale-gas well production. SPE Reserv Eval Eng 2013;16(2):216–28
doi: 10.2118/159801-PA
22   Ozkan E, Brown ML, Raghavan RS, Kazemi H. Comparison of fractured horizontal-well performance in conventional and unconventional reservoirs. Dermatol Surg 2009;27(8):703–8
doi: 10.2118/121290-ms
23   Queipo NV, Verde AJ, Canelón J, Pintos S. Efficient global optimization for hydraulic fracturing treatment design. J Petrol Sci Eng 2002;35(3–4):151–66
doi: 10.1016/S0920-4105(02)00237-1
24   Houzé O Tauzin E, Artus V, Larsen L. The analysis of dynamic data in shale gas reservoirs—Part 1 [Internet]. 2010 Dec [cited 2017 Mar 10]. Available from: The Analysis of Dynamic Data in Shale Gas Reservoirs 1.pdf.
25   Houzé O, Trin S, Tauzin E. The analysis of dynamic data in shale gas reservoirs—Part 2 [Internet]. 2010 Dec [cited 2017 Mar 10]. Available from: The Analysis of Dynamic Data in Shale Gas Reservoirs 2.pdf.
26   Houzé O, Trin S, Tauzin E. The analysis of dynamic data in shale gas reservoirs—Part 3 [Internet]. 2010 Dec [cited 2017 Mar 10]. Available from: The Analysis of Dynamic Data in Shale Gas Reservoirs 3.pdf.
27   Cipolla CL, Lolon EP, Erdle JC, Rubin B. Reservoir modeling in shale-gas reservoirs. SPE Reserv Eval Eng 2010;13(4):638–53
doi: 10.2118/125530-PA
28   Wang L, Torres A, Xiang L, Fei X, Naido A, Wu W. A technical review on shale gas production and unconventional reservoirs modeling. Nat Resour 2015;6(3):141–51
doi: 10.4236/nr.2015.63013
29   Schlumberger. E CLIPSE technical description. Paris: Schlumberger; 2014.
30   Wilson K. Optimization of shale resource development using reduced-physics surrogate models [dissertation]. California: Stanford University; 2012.
31   Lake LW, Martin J, Ramsey JD, Titman S. A primer on the economics of shale gas production just how cheap is shale gas? J Appl Corp Finance 2013;25(4):87–96
doi: 10.1111/jacf.12045
32   Wilson K, Durlofsky LJ. C omputational optimization of shale resource development using reduced-physics surrogate models. In: Proceedings of the SPE Western Regional Meeting; 2012 Mar 21–23; Bakersfield, USA. Richardson :Society of Petroleum Engineers; 2012
doi: 10.2118/152946-MS
33   Allinson G, Cinar Y, Hou W, Neal PR. The costs of CO2 transport and injection in Australia [Internet]. Canberra: Department of Resources, Energy and Tourism; 2009 Sep [cited 2017 Mar 10]. Available from: Costs of CO2 Transport and Injection in Australia.pdf.
34   Williams-Kovacs J, Clarkson CR. Using stochastic simulation to quantify risk and uncertainty in shale gas prospecting and development. In: Proceedings of the Canadian Unconventional Resources Conference; 2011 Nov 15–17; Calgary, Canada. Richardson: Society of Petroleum Engineers; 2011
doi: 10.2118/148867-MS
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