Predictive Modeling of Energy and Emissions from Shale Gas

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Energy and the Environment

Predictive Modeling of Energy and Emissions from Shale Gas Development Evar Umeozor, and Ian Donald Gates Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b05562 • Publication Date (Web): 19 Nov 2018 Downloaded from http://pubs.acs.org on November 26, 2018

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Environmental Science & Technology

Title: Predictive Modeling of Energy and Emissions from Shale Gas Development

Authors: Evar C. Umeozor and Ian D. Gates*

Author affiliations University of Calgary, 2500 University Drive N.W., Calgary, AB, Canada T2N 1N4 *

To whom correspondence should be addressed. Email: [email protected]

Table of Contents Graphic:

Keywords: Predictive modelling; Shale gas; Preproduction; Energy; Emissions; Flowback

Supporting Information    

Modelling parameters and variables data ranges Parameter estimation model and solution methods Method of analytical modelling of drilling forces Historical drilling activities in the Montney Formation

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Abstract 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 modelling 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 modelling 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 million metric ton 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 3,400. The approach described here can be reliably extended to areas, globally, where natural gas development is becoming prominent.

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Introduction Ever since horizontal drilling with multistage hydraulic stimulation unlocked vast shale resources in many areas in North America and beyond, global natural gas production has increased tremendously resulting in abundant, cheap gas [1]. For this reason, gas-based energy technologies have become favorable for business decision reasons including desires to curtail climate effects of a growing global energy demand [2]. However, concerns about the actual environmental benefits of unconventional gas in the energy mix, particularly against coal and coupled with depleting conventional gas, have triggered a lot of scrutiny of the operational practices of natural gas producers, especially at upstream operations where both development and production activities occur [1, 3]. In combustion, it is known that natural gas – whether conventional or not – burns cleaner than other fossil fuels with up to 50% less carbon generation [3]. Moreover, between conventional and unconventional natural gas, it is primarily the difference in their development techniques, occasioned by resource deposition attributes, which may translate to disparate energy, emissions and economic impacts [4, 5, 6, 7, 8, 9]. At production, both natural gas sources can be piped into the same supply chain [9].

Shale gas is a type of unconventional resource with the depositional attribute of entrapment, or exceedingly low permeability, within pockets of petroleum reservoir rock. Shale is also deeper underground than conventional natural gas [10]. As such, relatively greater investment and energy input is required for development than that of conventional gas. Generally, this energy requirement is met by fossil fuel (often diesel) combustion at the predominantly remote locations where the resources are exploited [5]. Higher energy penalty implies more greenhouse gas (GHG) emissions, yet there is a lack of clarity on how the resource development activities distribute energy and emission intensities of the operation. This apparent lack of understanding of preproduction impacts 3

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becomes amplified when the scope of analyses is reduced to an individual gas well basis, without accounting for the annual scale of shale resource development campaigns since the shale revolution started. As of 2013, unconventional gas contributed about 64% of total U.S. natural gas production and is expected to climb to 70% by 2020 [11]. In Canada, unconventional gas accounted for 51% of total gas production in 2014 and is projected to represent 80% of all gas production by 2035 [12]. In the Canadian province of Alberta alone, a total of about two thousand gas wells were drilled in 2015 of which over one thousand were for unconventional gas [13].

Given that global GHG emission reduction policies and targets are normally designed on the basis of annual emissions to be reduced to particular baseline year values, better insights can be gained on climate impacts as more gas is consumed in global energy flows by taking a more holistic and systematic approach in the analysis of energy and environmental implications of unconventional gas development [6, 7]. The energy requirement for drilling shale gas wells depends on a number of factors: attributes of drilling machinery (e.g. efficiency), type and properties of formation being drilled, and measured depth of wellbore to be developed, among others. After drilling is completed, energy is still required for hydraulic fracturing – that is, to pump fluids, including proppant, into the reservoir to create and sustain fractures. At every stage in the development, GHG emissions are generated as energy for drilling and fracturing operations are furnished – often from fossil fuel combustion to provide the mechanical drive needed to drill or pump fluids into the formation [6, 14]. Emissions could also arise from leakages of hydrocarbons and other GHGs as the drilling operations or well completion activities expose the subsurface during development. Figure 1 breaks down shale gas preproduction activities into three steps, including drilling, hydraulic fracturing, and flowback.

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Drilling

Fracking

Flowback

Production

Figure 1: Preproduction operations (in dashed box) during shale gas development. Previous reports in the literature have used reported data or heuristic approaches based on assessments of primary energy feedstocks for development operations to gauge preproduction emissions [14, 15, 16, 17, 18]. These approaches lead to limitations in transferability of the results when the conditions for measurements, type of energy source, or attributes of the resource depositions differ from one development project to another which in turn creates pitfalls for applying emission factors arising from such studies. This study presents a predictive modelling approach with a strong analytical background to account for energy use and GHG emissions during shale gas development. We identify the activities and events which trigger energy-derived or direct methane emissions. Applicability of our approach is demonstrated using data from 1,403 shale gas wells in the Montney Formation in Western Canada. Figure 2 shows the Montney basin area covering developed wells within the provinces of British Columbia and Alberta. Well-level data are obtained from the HPDI and GeoScout databases [19, 20]. Detailed modelling of sources and the implementation workflow is presented to enable transferability of our method to other areas where shale gas development activity is growing.

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Montney Formation Wells British Columbia

Alberta

Figure 2: Study focus area showing the spread of Montney over British Columbia and Alberta with developed wells highlighted in red. Method We focus on energy and methane emissions from preproduction activities during shale gas development covering drilling, hydraulic fracturing, and flowback operations. Diesel is used as the primary energy source for both drilling and fracturing operations. Overall preproduction emission is computed as the combination of energy consumption emissions and potential direct releases of methane during each development operation. The principal activities requiring energy input during shale gas development include drilling, drilling mud circulation and hydraulic fracturing. The total potential preproduction emissions can be expressed as a sum of potential direct and energy emissions, expressed by:

𝑄𝐶𝑂2𝑒𝑞 = 𝐷𝑟𝑖𝑙𝑙𝑖𝑛𝑔 + 𝑀𝑢𝑑 𝑓𝑙𝑜𝑤 + 𝑀𝑢𝑑 𝑔𝑎𝑠 + 𝐻𝑦𝑑𝑟𝑎𝑢𝑙𝑖𝑐 𝑓𝑟𝑎𝑐𝑡𝑢𝑟𝑖𝑛𝑔 + 𝐹𝑙𝑜𝑤𝑏𝑎𝑐𝑘 𝑔𝑎𝑠 𝐸𝑛𝑒𝑟𝑔𝑦

𝐸𝑛𝑒𝑟𝑔𝑦

𝐷𝑖𝑟𝑒𝑐𝑡

𝐸𝑛𝑒𝑟𝑔𝑦

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𝐷𝑖𝑟𝑒𝑐𝑡

(1)

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Actual emissions depend on whether the potential direct methane releases are captured, flared or vented. There is no reason to restrict gas handling to either capturing or flaring scenarios since current regulatory requirement does not demand a strict adherence to either option [21, 22, 23]. Therefore, we estimate total preproduction emission on the basis of energy and potential preproduction methane emissions. Flowback gas is assumed to have a volumetric methane content of 78.8%; which agrees with recorded Montney Formation, air-free, natural gas methane composition. Methane density of 19 kg/Mcf is used to calculate the mass, and the CO2-equivalent emission is obtained by applying a global warming potential of 36. Model parameter values are chosen for ease of comparison of results with previous studies. However, sensitivities of emission estimates are evaluated by using up-to-date parameter values. The ranges of modelling input parameter and variable values are available in the supplementary document (SI.1). Detailed modelling of preproduction activities and events is presented individually below.

Drilling energy use and emission

Well drilling is a major activity in the development of shale gas. Unfortunately, existing lifecycle impact assessment studies have not presented a systematic and elaborate approach to quantify energy and emission impacts of the drilling operations during shale gas development. Vafi and Brandt [24] was the first attempt to shed more light in this area through careful modelling of some of the events during oil and gas well development. However, their work did not cover all sources (like mud gas and completion emissions) and generally handled some of the critical variables as time-invariant. Faezelaideh [25] used analytical modelling to investigate the forces on the drillstring during a drilling operation. This modelling approach enables understanding of the 7

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effects of changes in design and operational variables when treating different types of wells within a play or among wells in various basins. The required drilling torque can be obtained for the straight (vertical, horizontal, or inclined) and curved sections of the target wellbore design by summing the effective and lost torque components as follows:

(2)

𝑇𝑆𝑆 = ∑𝑖 ∈ 𝑆𝑆 {𝛽𝜔∆𝑙𝑟(cos 𝛼 + 𝜇sin 𝛼)}𝑖

{

(

𝑇𝐶𝑆 = ∑𝑖 ∈ 𝐶𝑆 𝛽𝜔∆𝑙𝑟

sin 𝛼𝑘 ― sin 𝛼𝑘 ― 1 𝛼𝑘 ― 𝛼𝑘 ― 1

+𝜇

)}

cos 𝛼𝑘 ― 1 ― cos 𝛼𝑘 𝛼𝑘 ― 𝛼𝑘 ― 1

(3) 𝑖

where 𝑆𝑆 and 𝐶𝑆 indicate the sections of the target wellbore being developed. To estimate total drilling energy requirement supplied by a top-drive system, if 𝑖 represents each section of the drillstring (in addition to the drill bit), 𝑗 indicates straight sections of the wellbore to be created, and 𝑘 stands for the curved parts of the wellbore, then the energy use can be expressed as:

𝐸𝑑 = ∑𝑗∑𝑖(𝛽𝑤∆𝑙𝑟𝜑)𝑖,𝑗(cos 𝛼𝑖,𝑗 + 𝜇sin 𝛼𝑖,𝑗) + ∑𝑘∑𝑖(𝛽𝑤∆𝑙𝑟𝜑)𝑖,𝑘

(

sin 𝛼𝑖,𝑘 ― sin 𝛼𝑖,𝑘 ― 1 𝛼𝑖,𝑘 ― 𝛼𝑖,𝑘 ― 1

)

cos 𝛼𝑖,𝑘 ― 1 ― cos 𝛼𝑖,𝑘

+ 𝜇𝑖,𝑘

𝛼𝑖,𝑘 ― 𝛼𝑖,𝑘 ― 1

(4)

where 𝜑 is total angular displacement of Section 𝑖 of drillstring through the 𝑗/𝑘 segment of the wellbore. This can be evaluated sequentially by following the entire path of the drill bit through the wellbore, as illustrated in Figure 3. The energy use accounts for the rotational motion of the drilling assembly as propelled solely by a top-drive system. Therefore, this value only represents

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the useful energy requirement for the drilling operation. To evaluate the actual energy input, we apply the efficiencies of the systems:

𝐸𝐷 =

𝐸𝑑

(5)

𝜂𝑑𝜂𝑝𝑚

where 𝜂𝑑 is the drilling motor efficiency and 𝜂𝑝𝑚 is the prime-mover efficiency.

Figure 3: Workflow for calculating the drilling energy requirement.

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Obtaining this result enables us to quantify the actual CO2 emissions from energy use based on carbon content of the input energy source:

(6)

𝑄𝐶𝑂2𝑒,𝑑 = 𝜒𝐶𝑂2𝐸𝐷

Mud Flow Pump Casing

Drill String Bit

Figure 4: Schematic of drilling arrangement with vertical, curved and horizontal sections, showing mud circulation (not drawn to scale). Mud circulation energy use and emission

Another aspect of the drilling operation involves pumping of drilling mud to provide balance, lubrication and cooling at the cutting edge of the driller [26]. Mud circulation has been reported as a major source of GHG emission arising from the pumping energy requirements [24]. Generally, the drilling operation is conducted in either one of underbalanced or overbalanced condition; underbalanced is where the mud pressure is lower than that of the formation and overbalanced is

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the opposite [27]. Here, we consider an overbalanced drilling operation, which is common practice.

Figure 4 illustrates mud circulation in a simplified drilling setup. Vafi and Brandt [24] gave an elaborate discussion on drilling mud circulation dynamics in terms of mud differential pressure; considering frictional, dynamic, discharge, and hydrostatic elements of the overall pressure drop. However, their model did not demonstrate the dynamics of the differential pressures as drilling progresses through the various segments of the wellbore being developed. Given that the hydrostatic component in the model is zero, and without a downhole motor in the drilling assembly, the pressure differential can be expressed in terms of frictional and dynamic losses [24]:

(7)

∆𝑃𝑝𝑢𝑚𝑝 = ∆𝑃𝑓𝑟𝑖𝑐𝑡𝑖𝑜𝑛 +∆𝑃𝑑𝑦𝑛𝑎𝑚𝑖𝑐

The total losses occurring over the course of the drilling operations can be computed consecutively following segments of the drilling assembly through the wellbore. Frictional losses are computed for each drillstring segment as it penetrates through the subsurface, covering both flows of the mud within the pipe and through the annular area between the pipe and wellbore contact. Dynamic losses at the drill bit is computed for each bit used and through its coverage of measured depth of the wellbore. Consequently, the total energy required for mud circulation is then:

(8)

𝐸𝑚 = ∑𝑗∑𝑖∆𝑃𝑖𝑗𝑄𝑖𝑗∆𝑡𝑖𝑗

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where 𝑖 and 𝑗 are indexes for sections of the drillstring and wellbore segments, respectively. To calculate the actual primary energy input, we apply efficiencies of pump and prime-mover, and the energy emission is calculated by multiplying with carbon content of fuel:

𝐸𝑚

𝐸𝑀 = 𝜂𝑝𝜂𝑝𝑚

(9)

𝑄𝐶𝑂2𝑒,𝑚 = 𝜒𝐶𝑂2𝐸𝑀

(10)

Apart from energy used for drilling mud circulation, mud gas is released whenever a gas bearing zone is encroached. As drilling cuts through reservoir pay zone, entrapped gas and cuttings are entrained to the surface by the mud. Emission at this stage is primarily from released mud gas which gets vented. This mud gas volume (𝑉𝑚) can be estimated from the relationship:

𝑉𝑚 =

𝜋𝑑2𝑏𝐿𝑝𝑧𝜙(1 ― 𝑆𝑙)

(11)

4𝐵𝑔

where 𝐿𝑝𝑧 is well length within the pay zone, 𝜙 is reservoir porosity, 𝑆𝑙 is liquid saturation, and 𝐵𝑔is the gas formation volume factor. The HPDI database contains information on gas-to-oil and water-to-oil ratios from which the liquid saturation can be calculated from:

𝑤𝑜𝑟 + 1

(12)

𝑆𝑙 = 𝑔𝑜𝑟 + 𝑤𝑜𝑟 + 1

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At this point, we can define GHG content of formation gas based on formation gas compositions for individual wells or shale basins. Considering GHG components of the raw gas (𝑎), potential GHG emissions can be estimated from:

(13)

𝑄𝐶𝑂2𝑒,𝑚 = ∑𝑎𝐺𝑊𝑃𝑎𝜉𝑎𝜌𝑉𝑚

where 𝜉𝑎 is the composition of GHG component 𝑎 in the gas and 𝜌 is the gas density. For our analysis, only methane content of the gas is accounted for using an average methane content of 78.8% and global warming potential of 36 in line with updated IPCC methane climate warming potency. We further bracket these estimates in the sensitivity analyses using reported ranges of shale gas methane content of 45-95% and published range of methane GWP of 21-36 to enable comparison with past studies [22].

Hydraulic fracturing energy use and emission

Energy is required to pump fluids into the reservoir to create fractures. The fractures enhance hydrocarbon flow in the formation by connecting the reservoir and the wellbore [10]. Energy emission is the primary emission source at this stage, and it depends on the type of energy source being used. The field profile of the typical reservoir stimulation operation indicates that the fracturing fluid is injected from the surface at a specific rate via perforations in the well casing and then into the formation [10]. The reservoir pressure builds up to the formation breakdown pressure at which the targeted shale rocks start to break. Hydraulic fracturing is a complex process influenced by a number of factors, including: injection rate, fracturing fluid, wellbore dimensions,

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state of stress, and reservoir rock properties, among others [28]. The pressure needed for hydraulic fracturing derives from the bottomhole pressure, given as [24]:

(14)

𝑃𝑓𝑟𝑎𝑐 = 𝑃𝑠𝑢𝑟𝑓𝑎𝑐𝑒 + 𝑃ℎ𝑒𝑎𝑑 ― 𝑃𝑓𝑟𝑖𝑐𝑡𝑖𝑜𝑛

where 𝑃𝑠𝑢𝑟𝑓𝑎𝑐𝑒 is fracturing treatment pressure applied at the surface by the pump system, 𝑃ℎ𝑒𝑎𝑑is the hydrostatic pressure due to the fluid column in the wellbore, and 𝑃𝑓𝑟𝑖𝑐𝑡𝑖𝑜𝑛 account for all frictional losses [10, 28]. After rock breakdown is achieved or in residence of natural fractures in the formation, the net fracturing pressure, which is responsible for propagating fractures in the reservoir rock can be expressed as the bottomhole pressure less of the closure stress (or fracture reopening pressure) [10, 28]:

(15)

𝑃𝑓𝑟𝑎𝑐 = 𝑃𝑠𝑢𝑟𝑓𝑎𝑐𝑒 + 𝑃ℎ𝑒𝑎𝑑 ― 𝑃𝑓𝑟𝑖𝑐𝑡𝑖𝑜𝑛 ― 𝑃𝑐𝑙𝑜𝑠𝑢𝑟𝑒

Analysis of fracturing pressure demonstrates that it follows a power dependence with treatment time, as reported by [29, 30]:

𝑃𝑓𝑟𝑎𝑐 = 𝑐(𝑡 ― 𝑡𝑖)𝑛

(16)

The pump work needed to achieve this can be determined based on thermodynamic relations:

∆𝐻 = ∆𝑈 + 𝑉∆𝑃 + 𝑃∆𝑉

(17)

∆𝑈 = 𝑄 ― 𝑊

(18)

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Considering ∆𝑉 is relatively unchanged for an incompressible fracturing fluid and only the flow work is provided by the pump (i.e. ∆𝐻 and 𝑄 are zero), the input rate of pumping energy which supplies the flow work needed for hydraulic fracturing becomes:

𝑑𝐸𝑓𝑟𝑎𝑐 𝑑𝑡

(19)

= 𝑞∆𝑃

where 𝑞 is the volumetric injection rate and ∆𝑃 is defined with respect to the reference pressure by:

∆𝑃 = 𝑃𝑓𝑟𝑎𝑐 ― 𝑃𝑟𝑒𝑓

(20)

𝑃𝑟𝑒𝑓 = 𝑃ℎ𝑒𝑎𝑑

(21)

For a given injection rate, the energy use for fracturing operations can be obtained from the integral of the input rate of pumping energy given by:

𝑞𝑐

𝐸𝑓𝑟𝑎𝑐 = 𝑛 + 1(𝑡 ― 𝑡𝑖)𝑛 + 1 ―𝑞𝑃𝑟𝑒𝑓(𝑡 ― 𝑡𝑖)

(22)

However, the flow of fracturing fluid through the well suffers frictional losses which must be included and thus, the total energy requirement is the sum of the fracturing energy input and losses:

(23)

𝐸ℎ = 𝐸𝑓𝑟𝑎𝑐 + 𝐸𝑓𝑟𝑖𝑐

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where 𝐸𝑓𝑟𝑖𝑐 is the frictional losses as fracturing fluid pressure drops along the well. Determination of frictional pressure losses for Newtonian and non-Newtonian fluids are elaborately treated for different flow regimes by [26]. Our model incorporates the equations for both laminar and turbulent flow regimes. To evaluate total energy losses, the number of fracturing stages have to be accounted for in the model – given that each stage is located at a unique measured depth – as follows:

(24)

𝐸𝑓𝑟𝑖𝑐 = ∑𝑗𝑞𝑗∆𝑃𝑗∆𝑡𝑗

where 𝑗 represents each fracturing stage along the horizontal section of the well. Given that 𝐸ℎ represents the ideal energy requirement, the actual energy input considering pumping and primemover efficiencies (𝜂𝑝,𝜂𝑝𝑚), depending on the type of energy source, is then:

𝐸𝐻 =

𝐸ℎ

(25)

𝜂𝑝𝜂𝑝𝑚

Then, the emissions for the fracturing operation is obtained by using the emission intensity of the input fuel: (26)

𝑄𝐶𝑂2𝑒,ℎ = 𝜒𝐶𝑂2𝐸𝐻

Flowback emission

Methane leakage during flowback operations occur as fracturing fluid is cleared from a shale gas reservoir to the surface in the absence of an arrangement to capture the flowback gas [31]. Reduced

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emission completion (REC) technologies, otherwise called green completions, are used by some operators to recover flowback gas for use or sales. Although not all injected fluid is recovered in most cases due to leak-off, the flowback regime covers the period from initiation until all fracturing fluid has been removed or the production of liquid levels off [4]. Umeozor et al. [4] used field data and flowback analysis to describe the three regimes of the lifetime of a shale gas well. Based on the observed flowback profile, we propose that the flowback rate from a well can be represented by the equation:

𝑞𝑓𝑏 = 𝑞𝑔,𝑝𝑒𝑎𝑘(1 ― 𝑒 ―𝜆 ― 𝜆𝑒 ―𝜆)

(27)

where 𝑞𝑔,𝑝𝑒𝑎𝑘 is the peak gas rate from the well and 𝜆 is a parameter that characterizes the shape of the flowback profile of the gas well. Therefore, 𝜆 can be related to the flowback duration and peak gas value, and takes values between 0 and 1. To evaluate potential emissions from flowback (𝑄𝑓𝑏), we integrate the equation over the flowback regime to obtain: 𝑄𝑓𝑏 = 𝑞𝑔,𝑝𝑒𝑎𝑘[(𝜆 ― 2) + (𝜆 + 2)𝑒 ―𝜆]

(28)

Relative initial production (IP) based models, peak gas production data is easily available and the historical range of its values within a basin or play can be used to bracket potential emissions from new well developments. IP based models also require more data inputs which may introduce more uncertainty in estimation results [4]. Peak gas data for North American shale plays can be found in the Drilling Info database [19]. The parameter 𝜆 can be calibrated for a given shale gas well due to differences in the attributes of each shale gas reservoir/basin. Further details on the parameter estimation can be found in the supplementary material (SI.2). Calibrated values for individual shale

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basins range from 0.6 to 1. However, for the generality of wells considered in this study, a representative value of parameter 𝜆 is equal to 0.75.

Results

Figure 4-5 compares modeled flowback gas estimate to actual field measurement data. The mean value of estimated potential emission is 4810 Mg CO2e (± 190 Mg CO2e at 95% CI), which is within 95% confidence limits of actual field measurements of potential flowback emissions. Table 1 lists descriptive statistics of the model along with those of measurement data. The results indicate good agreement and capability of the model to capture the range of variability in measured potential emissions. High standard deviations in both results reflect discrepancies in the emissions from a few high-emitters and a majority of wells which do not release as much emissions. To further explore predictiveness of the model, the data and model estimates are visualized on a parity plot in Figure 6 and uncertainty is evaluated based on the relative error to be 5.2%. An important use of the flowback model is that it requires only one variable input; which is the anticipated peak gas production from the well. Therefore, information on the range of historical peak gas volume at any shale gas basin can be used to bracket estimates of potential methane emissions during development. Such knowledge would be useful for decision making on the gas handling scenario to deploy for either economic or regulatory reasons.

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Figure 5: Comparison of proposed flowback gas model results with actual field measurements.

Table 1: Descriptive statistics comparison for model and measured completions flowback potential methane emissions.

Method Estimated (Mg CO2e) Measured (Mg CO2e)

Mean

Median

Std

Min

Max

P25

P75

4,810

4,070

3,530

3

32,970

2,100

6,490

4,400

1,610

7,650

7

37,270

230

4,490

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Figure 6: Comparison of modeled emission estimates to the data, with an inset parity line.

To understand the contribution of each preproduction activity and event to overall development potential emissions, a breakdown of direct and energy emissions is presented in Figure 7. As can be observed from the results, completions flowback gas is a major potential source of preproduction GHG emissions, accounting for 4,810 Mg CO2e per well. It must be mentioned that this represents the potential emission which can be avoided, reduced, or released; depending on the jurisdictional regulatory requirements or the gas handling decisions of the operator. The next main source of emissions is the well drilling activity. We have subdivided the entire drilling operations into circulation of drilling mud and the actual rotary drilling activity powered by a top-

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drive system. Both the mud pump and rotary driver are assumed to be powered by diesel prime mover. A diesel energy content (LHV) of 42.8 MJ per kg and emission factor of 69.4 kg CO2 per GJ (i.e., 2.97 kg CO2/kg diesel) is applied in the model. Although dependent on the borehole dimensions and well design, most of the CO2 emitted during the drilling stage arise from energy used for circulating drilling mud. This stems from pressure losses as mud is pumped into the bottom through the drillstring to drill bit, and up again to the surface via the annulus. In this operation, the mud also clears drill cuttings to the surface. For a 5 inch lateral casing in a 6.125 inch open hole, this accounts for about 91% of the total preproduction energy requirements.

Flowback

4811.97

Mud Gas

0.04

Hydraulic Fracturing

13.45

Mud Circulation

628.92

Well Drilling

49.95

0

1,000

2,000

3,000

4,000

5,000

Emission (Mg CO2e) Figure 7: Breakdown of preproduction energy and direct emissions by activity.

Well drilling energy requirement captures the rotational energy needed by a top-drive system to develop the borehole considering just rotational motion as the drilling assembly makes its way into

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the shale gas reservoir. Additionally, mud gas is released when the drilling operation encounters a gas-bearing zone. For our model, we have estimated the amount of mud gas from drill cuttings through the lateral section of the wellbore. Since our method assumes an over-balanced drilling operation, it should be expected that this approach determines the lower bound of the potential mud gas emission. The mud gas emission is estimated as 0.04 Mg CO2e per well. Total CO2 emissions for all activities during the drilling stage is estimated as 678.87 Mg per well. For the same lateral casing design, hydraulic fracturing energy use represents about 2% of the total; amounting energy-derived CO2 emission of 13.45 Mg per well. This includes frictional losses as fracturing fluid is pumped for each stage of fracturing job and the energy needed breakdown reservoir rock and propagate fractures into the rock. As expressed in equation (14), energy input for hydraulic stimulation derives from the pump work (which is based on 𝑃𝑠𝑢𝑟𝑓𝑎𝑐𝑒); therefore, the hydrostatic head contribution to the fracturing pressure is not assigned to the pump.

Figure 8: Energy requirements for shale gas well development with lateral casing sizes corresponding to 6 1/8, 7 1/2, and 8 3/4 inches lateral borehole diameters, respectively.

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Figure 8 shows the effect of different well dimensions and lateral casing designs on both the overall preproduction energy requirement and that of each development activity. It is observed that for smallest lateral diameters investigated, energy use for mud circulation dominates the total inputs. For the other lateral casing design sizes, total energy input can be significantly lower but dominated more by rotational energy for drilling with the top-driver. Consequently, variabilities in well trajectory, well casing design, formation type and resource deposition attributes are important when considering individual development project performance in terms of energy use and GHG emissions. This awareness is also essential for optimizing well development activities by tailoring decision parameters to specific formations/plays to minimize energy intensity and GHG emission impacts. For the Montney Formation wells considered, the average overall preproduction potential GHG emission is estimated as 5,300 Mg CO2e per well, corresponding to an average total energy use of 4,083 GJ per well. On the basis of preproduction requirements, energy return on invested energy (EROI) for Montney shale gas is estimated as 3,400. Furthermore, if the entire shale gas development projects in the Montney Formation during 2017 of 505 wells is sampled [20, 32], this amounts to an aggregate potential GHG emission impact of about 2.68 Mt CO2e from unconventional gas Montney Formation operations alone.

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Figure 9: Sensitivity of preproduction emission estimates to well design and estimation parameters. Figure 9 illustrates the sensitivity of preproduction emission estimates to modelling parameters and other resource deposition attributes. To calculate these sensitivities, a baseline GWP of 28 is applied to methane from all sources, so that sensitivity of results to GWP is computed over a range of 21 to 36. It can be observed that the completion flowback gas is a potential source major variability in well-level preproduction GHG emission. Nevertheless, individual well-level emission estimates might vary according to differences in parameter values and development practices as shale gas projects are initiated across many parts of the world. For instance, Vafi and Brandt [24] estimated GHG emissions from drilling and hydraulic fracturing in two U.S. shale basins (Bakken and Eagle Ford) and obtained values of 417 and 510 Mg of CO2e per well, respectively. For the same activities, our model estimated 692 Mg of CO2e per well for the Montney Formation. Taken together, at the global scale, understanding impacts of preproduction 24

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emissions on collective capacity to achieve climate targets deserves more attention than is currently accorded, and predictive modelling can serve as an essential tool to extend current knowledge future impacts of impending developments in the natural gas supply chain. Consequently, as more gas is increasingly tapped from various shale plays worldwide, regulatory controls can be designed to accelerate implementation of mitigative development strategies that help to curtail environmental impacts of more gas in the global energy pool. Already, technologies such as green completions have been proposed to control flowback gas emissions from unconventional oil and gas projects.

Shale gas is a type of unconventional gas found in pockets within a petroleum reservoir rock. Energy use and emissions during well development is the main differentiator of conventional and unconventional gas. We propose predictive modelling as an approach to quantify preproduction energy requirements and the attendant energy and direct GHG emissions. Detailed modelling workflow is presented indicating the main activities and events contributing the overall impacts of new shale gas development. Proposed model is applied to 1,403 wells in the Montney Formation in Western Canada. Our results suggest that the distribution of energy and emission impacts among the development operations might differ from how it is normally perceived. Depending on well trajectory and dimensions, energy use for mud circulation can predominate those of the other activities including the rotational energy requirement for a top-drive drilling system and the pump work utilized for hydraulic stimulation. Average preproduction energy need is estimated at 4083 GJ per well. Nevertheless, as more gas reservoirs are developed, occasioned by increasing gas demand, proper appreciation of the implications on climate change mitigation efforts can be better grasped on the basis of overall annual preproduction emissions, in accordance with the design of

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climate policy directives and targets. From this viewpoint, annual potential preproduction GHG emission from unconventional gas wells in the Montney Formation in 2017 is estimated to be 2.68 Mt CO2e.

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Acknowledgements The authors acknowledge financial support from the Natural Science and Engineering Research Council (NSERC) of Canada and the University of Calgary.

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