SPE 165360

Flow Units: From Conventional to Tight Gas to Shale Gas to Tight Oil to Shale Oil Reservoirs

Roberto Aguilera, Schulich School of Engineering, University of Calgary

Copyright 2013, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Western Regional & AAPG Pacific Section Meeting, 2013 Joint Technical Conference held in Monterey, California, USA, 19−25 April 2013. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessar ily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohi bited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract

Core data from various North American basins with the support of limited amounts of data from other basins around the

world have shown in the past that process (or delivery) speed provides a continuum between conventional, tight and shale gas

reservoirs (Aguilera, 2010). This work extends the previous observation to tight oil and shale oil reservoirs. The link

between the various fluids is provided by the word ‘petroleum’ in ‘Total Petroleum System’ (TPS) which encompasses liquid

and gas hydrocarbons found in conventional, tight and shale reservoirs. Results of the present study lead to distinctive flow

units for each type of reservoir that can be linked empirically to gas and oil rates and under favorable conditions to

production decline. To make the work tractable the bulk of the data have been extracted from published geologic and

petroleum engineering literature. The paper introduces a new unrestricted transition flow period in tight reservoirs that is

recognized by a straight line with a slope of -0.75 on log-log coordinates. This straight line occurs as a transition between 2

linear flow periods.

Process speed is the ratio of permeability and porosity. The approximate boundary between viscous and diffusion dominated

flow in gas reservoirs is estimated with Knudsen number which can be calculated from pore throat radius (a function of

process speed). Viscous flow is present, for example, when the architecture of the rock is dominated by megaports,

macroports, mesoports and sometimes microports (port = pore throat). Diffusion flow on the other hand is observed at the

nanoport scale, which can occur in both tight and shale reservoirs.

The process speed concept has been used successfully in conventional petroleum reservoirs for several decades and in tight

and shale gas reservoirs during the past 3-4 years. The concept is extended in this paper to tight oil and shale oil reservoirs,

and hence to the complete petroleum system, with the support of core and drill-cuttings data. The approach permits

estimating volumes of petroleum-in-place, differentiating between viscous and diffusion dominated flow in gas reservoirs

and the contribution of each flow mechanism with the use of a unified diffusion-viscous flow model. This is valuable, for

example, in those cases where the formation to be developed is composed of alternating stacked layers of tight and shale

reservoirs, or where there are lateral variations due to facies changes.

It is concluded that there is significant practical potential in the use of process speed as part of the flow unit characterization

and production performance prediction in unconventional petroleum reservoirs.

Introduction

Different hydrocarbons and reservoir types can be integrated under the umbrella of a ‘Total Petroleum System’. That is the

premise for being able to integrate in this paper flow units of conventional, tight gas, shale gas, tight oil and shale oil

reservoirs and to estimate potential production rates. A previous paper (Aguilera, 2010) described flow units in tight and

shale gas reservoirs. That paper is extended in this work to the case of tight oil and shale oil.

An excellent explanation of the Petroleum System has been presented by Magoon and Beaumont (1999). “The Petroleum

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System is a unifying concept that encompasses all of the disparate elements and processes of petroleum geology including a

pod of active source rock and all genetically related oil and gas accumulations.”

The Petroleum System includes all the geologic elements and processes required for an oil and gas accumulation to exist. The

word ‘petroleum’ includes high concentrations of any of the following substances: (1) Thermal and biological hydrocarbon

gas found in conventional reservoirs as well as in unconventional reservoirs (gas hydrates, tight reservoirs, fractured shale,

and coal). (2) Condensates. (3) Crude oils. (4) Natural bitumen. The word ‘system’ describes the interdependent elements and

processes that form the functional unit that creates hydrocarbon accumulations.

Magoon and Beaumont (1999) indicate that the essential elements of a Petroleum System include the following: (1) Source

rock. (2) Reservoir rock. (3) Seal rock. (4) Overburden rock. The Petroleum System includes two processes: (1) Trap

formation. (2) Generation–migration–accumulation of hydrocarbons. These essential elements and processes must be

correctly placed in time and space so that organic matter included in a source rock can be converted into a petroleum

accumulation. A petroleum System exists wherever all these essential elements and processes are known to occur or are

thought to have a reasonable chance or probability to occur.

The segments of the Total Petroleum System described above, dealing with conventional and unconventional oil and gas

reservoirs is the primary objective of this paper. The significant paradigm shift is that tight rocks that could not produce any

petroleum in the past or were nearly impermeable ‘seals’ are now economic reservoir rocks.

Several researchers (Archie, 1950; Kwon and Pickett, 1975; MacKenzie, 1975; Chopra et al., 1987; Gunter et al., 1997;

Ebanks, 1987; Hartmann and Beaumont, 1999; Nelson, 2009; Clarkson et al., 2012) have discussed the importance of pore

and throat structure (for example size, geometry, distribution, connectivity, and composition) on flow unit and storage

capacity of porous media. Pore throat apertures have been estimated based on knowledge of process speed, i.e., the ratio of

permeability and porosity (Kolodzie, 1980; Aguilera, 2002). In turn, these pore throat apertures have been used with

reasonable success to anticipate flow rates that can be expected from given oil (Martin et al., 1997) or gas (Deng et al., 2011)

wells. In general, this type of work has been performed in the past in ‘conventional’ carbonate and siliciclastic reservoirs, and

more recently in tight gas and shale gas reservoirs. This paper shows, with the use of real data that the same concept can be

extended quantitatively to the case of tight oil and shale oil reservoirs. In order to do that, data from several conventional

reservoirs around the world; tight gas and shale gas reservoirs; and tight and oil reservoirs primarily in North America are

examined in this study. Aguilera (2010) has indicated that tight gas reservoirs are best represented by at least dual porosity

models while shale gas reservoirs are best represented by at least quadruple porosity models and more rigorously by

quintuple porosity models (Lopez and Aguilera, 2013). This observation leads to volumes of original gas in place (OGIP),

free gas in place and gas recovery that are in all probability larger than considered previously. It must be noted, however, that

smaller volumes of OGIP have also been discussed in the literature (Ambrose et al., 2010).

Figure 1 shows world gas resource pyramids including global endowment for conventional gas, tight gas, shale gas, coalbed

methane, conventional oil, tight oil, shale and oil sands reservoirs. Endowment, as used in this paper, is the summation of

cumulative gas production, reserves and undiscovered gas. The total natural gas endowment, excluding natural gas hydrates,

is gigantic, at 45,000 tcf, out of which 67% is estimated to be in tight and shale gas. Tight gas endowment in the United

States and Canada is estimated 450 and 105 tcf, respectively. These volumes represent only 7% of the original gas in place.

Shale gas endowment in the United States has been estimated preliminary at approximately 240 and 70 tcf by the GFREE

team. The endowment of natural gas, the cleanest burning fossil fuel, will supply market needs for several decades. The

pyramid shows that unconventional gas is associated with very low permeabilities. As such, successful production of

unconventional gas will include increases in production, prices, activation indices, research and time. Activation index

(Economides and Oligney, 2000, p. 83) is a measure of the total investment required to establish access to new oil or gas

expressed in dollars per unit volume per day (for example, $/barrel/day or $/Mcf/d) of stabilized production. The pyramid

also shows decreases in process (or delivery speed) and pore throat apertures, which are some of the key topics discussed in

this paper.

Although process speed has been used for several decades in conventional reservoirs in the oil and gas industry, the proposed

use of this concept for distinguishing between flow units in conventional and unconventional petroleum reservoirs is new.

Comparisons of real data and theoretical simulations at the pore throat level are consistent and provide good support to the

proposed methodology. To make the results of the interpretations presented in this paper tractable the bulk of the core,

cuttings and production data used in the study have been extracted from referenced published geologic and petroleum

engineering literature.

SPE 165350 3

Process or delivery Speed

Process or delivery speed, i.e., the ratio of permeability and porosity, provides a relative indication of storage and how

quickly fluids can move through porous media. The concept has been shown to be powerful for characterizing conventional

oil and gas reservoirs in various lithologies (Chopra et al., 1987, Gunter et al., 1997), for predicting recoverable hydrocarbon

volumes (Pickett and Artus, 1970), and for determining flow units in tight gas and shale gas reservoirs (Aguilera, 2010).

The flow unit (a function of permeability and porosity) is thus a useful concept for linking geology, petrophysics and

reservoir engineering as permeability and porosity are studied in detail and used by all of these disciplines (Aguilera, 2004).

The process speed (k/ø) is an important part of the diffusivity equation:

(1)

where is fluid viscosity and ct is total compressibility. The above equation is at the heart of fluid flow calculations in porous

media by reservoir engineers. Thus it is extremely important to have knowledge of the process speed (k/) and hydraulic

diffusivity [ = ct / (k/)].

Flow Units

Process speed is related directly to flow (or hydraulic) units, a concept introduced by H. D. Winland of Amoco using data

from formations ranging in age from Ordovician to Tertiary, including Simpson, Delaware, Tensleep, Nugget, Cotton Valley,

Muddy, Mesaverde, Terry, First Wall Creek, Frontier, Montrose, Vicksburg, and Frio sandstone. Windland’s concept has

been used successfully by MacKenzie (1975) in the Cardium sandstone of Canada, Kolodzie in the Spindle field in Colorado

(1980), Pittman in sandstone reservoirs of the United States (1992), Ebanks (1987) as an aid to reservoir description for

engineering projects, Aguilera (2010) for flow unit determination in tight gas and shale gas reservoirs, and Clarkson et al.

(2012) for evaluation of the Montney formation in Canada. A flow unit is defined as a stratigraphically continuous reservoir

subdivision characterized by a similar pore type (Hartmann and Beaumont, 1999, p. 9-7). As such, the concept is powerful

for helping define optimum layering in simulation work.

Pore throat aperture (rp35) in microns can be calculated from (Aguilera, 2002, 2004):

45.0

35100

665.2

krp (2)

The equation was developed utilizing data from more than 2500 sandstone and carbonate samples from the Aux Vases,

Hoover, Dakota, Nesson, Judith River, Lodgepole, Nisku dolomite, Morrow and Keyes, Hunton, Granite wash, Venango,

Cypress, Mission Canyon, Cherokee, Bartlesville, Stony Mountain, Swift, Muddy, Tar Springs, Minnelusa, Red River,

Desmoines, Devonian, Benois, Trenton limestone, Silurian and Edwards formations. The data had been used originally by

Kwon and Pickett (1975) for creating a pore structure model and developing pore structure interrelationships.

Pore size classes are grouped on the basis of pore throat (port) apertures as megaports (rp35 > 10 microns), macroports (2.5-10

microns), mesoports (0.5 to 2.5 microns), microports (0.1 to 0.5 microns), and nanoports (0.01 to 0.1 microns) following

approximations suggested by Martin et al. (1997). Note that ports prefixes (mega, macro, meso, micro, nano) as used

customarily in the geologic literature do not correspond to the mathematical meaning of such prefixes. Figure 2A shows a

crossplot of permeability vs. porosity for various pore size classes including conventional, tight and shale petroleum

reservoirs, and potential rates that can be obtained for oil (Martin et al, 1997) and gas (Deng et al., 2011) reservoirs. The lines

of constant rp35 were developed with the use of equation 2. For comparison note that the radius of a methane molecule is

0.0002 microns, the radius of water is 0.000137 microns and the radius of oil ranges between approximately 0.00025 and

0.005 microns. Corroboration of the validity of equation 2 has been demonstrated with the use of simulation at the pore throat

level as shown in Figure 2B (Rahmanian et al., 2010).

Although the interpretation of pore size classes described above has been carried out mostly in conventional rocks in the past,

this paper shows that process or delivery speed provides a continuum between conventional, tight gas, shale gas, tight oil and

shale oil reservoirs. The surprising result, based on core data from various North American basins, leads to distinctive flow

units for each type of reservoir. Viscous flow is present when the architecture of the rock is dominated by megaports,

macroports, mesoports and sometimes microports. Diffusion flow on the other hand is observed sometimes during gas

4 SPE 165350

production at the nanoport level. The approximate boundary between viscous and diffusion dominated flow is estimated with

the dimensionless Knudsen number (Kn), which is defined as the ratio of the molecular mean gas mean free path length ()

and pore diameter (d).

Conventional Petroleum Reservoirs

Figure 2A has provided reasonable results when compared against average values of permeability and porosity for 10,481

worldwide carbonate reservoirs considered by Ehrenberg and Nadeau (2005). The comparison (Aguilera, 2006) indicates that

90% (P90) of the reservoirs in all petroleum-producing countries (except Canada as Ehrenberg and Nadeau data bank for

Canada does not include permeabilities) have pore throat apertures (rp35) with a maximum size of about 2.5 microns

(mesoports); 50% of the reservoirs have pore throat apertures with a maximum of about 5 microns (macroports), and only

10% of the reservoirs have pore throat apertures with a maximum of about 10 microns (megaports).

Figure 2A has also provided reasonable results when compared against average values of permeability and porosity for

30,122 worldwide siliciclastic reservoirs considered by Ehrenberg and Nadeau (2005). At the P50 and P90 levels the relative

drop in siliciclastics pore throat apertures is more significant compared with the carbonate case. This might be the result of a

larger amount of fracturing and microfracturing in carbonate rocks as compared with siliciclastic reservoirs (Ehrenberg and

Nadeau, 2005; Aguilera, 2006).

The results are significant as they indicate that more than 90% of the reservoirs have pore throat sizes that are smaller than

2.5 microns (as in tight gas and shale gas reservoirs). This compares well with the global resource pyramids (Figure 1) for oil

and gas that show that the size of the pore throats decrease continuously as the size of the pyramid, towards the bottom,

becomes larger. The bottom of the resource pyramid is unknown and this opens significant possibilities for the future of

unconventional petroleum resources throughout the world.

The validity of the rp35 approach is demonstrated with the use of Figure 3 that includes data published several years ago by

Sneider et al. (1983) in a classic paper where the authors developed an empirical qualitative methodology for evaluating drill

cuttings with the use of a binocular microscope at 20X magnification. The approach proved to be of significant practical

value for economic development of tight gas reservoirs in the Deep Basin of the Western Canada Sedimentary Basin

(WCSB).

To the author’s knowledge the data shown on Figure 3 has never been evaluated using the rp35 method. Thus it provides a

good test for the flow unit methodology presented in this paper for the case of conventional reservoirs. The graph shows a

crossplot of permeability vs. porosity for Pennsylvanian sandstones and conglomerates of the Elk City field in Oklahoma.

This is a giant conventional oil field where Sneider et al. indicate that “porosity, permeability and pore geometry are related

to grain size and sorting, cementation and compaction, consolidation and the amount of pore-filling clays.” Sneider et al.

identified 3 types of rocks: (1) Type I rocks that are capable of producing petroleum without any type of stimulation. Sneider

et al. sub-divided Type I rocks into A (k >100 md), B (10 to 100 md), C (1 to 10 md) and D (0.5 to 1md). (2) Type II rocks

are capable of producing petroleum when interbedded with Type I rocks or when affected by natural fractures and/or

hydraulic fractures. Sneider et al. indicated that Type II rocks have permeabilities larger than 0.07 md to 0.5 to 1 md. (3)

Type III rocks which are too tight to produce at commercial rate even in the presence of some natural fractures and/or

hydraulic fractures. Sneider et al. indicated that Type III rocks are characterized by permeabilities smaller than 0.07 md. Note

that generally for all rock types (for example Type IC represented by the letter C in Figure 3) there is a general tendency for

the data to display a smaller permeability as porosity decreases.

Figure 4 shows Sneider et al.’s data on the template developed for the rp35 method. The graph clearly shows that that Sneider

et al.’s rock types can be properly placed into separate flow units based on the rp35 values. In this case the rp35 template

captures properly the general tendency of permeability to decrease with porosity for each rock type. The type III rock could

not produce commercially when Sneider et al. published their paper (1983). These types of rocks, however, are now capable

of commercial production in several places in Canada and The United States thanks to technological innovations that include

horizontal drilling and multi-stage hydraulic fracturing.

Another conventional oil example is provided by the prolific Cardium sandstone in Canada with the use of data published by

MacKenzie (1975) for the Pembina oil field. As in the previous case as far as I know MacKenzie’s data has never been

evaluated using the rp35 method. Figure 5 shows MacKenzie’s data on the rp35 template for his Type I and Type II rocks.

Note that Mackenzie’s definition of Type I and II rocks is different from the one presented by Sneider et al (1983). I retain

their original definitions in this paper to maintain consistency with their work. What is important from a practical point of

view is that in both cases the rp35 values allow to distinguish clearly unique flow units in the Elk City (United States) and

Pembina (Canada) oil fields. On both Figures 4 and 5 the porosity and permeability data are presented as published by

SPE 165350 5

Sneider et al. (1983) and MacKenzie (1975) without any modifications. The Cardium data also introduce tight oil (now

commercial in many instances) as shown in the lower part of Figure 5 that is characterized by smaller values of rp35. Tight oil

is discussed later in this paper in more detail

Tight Gas and Shale Gas Reservoirs

Shales are defined in different ways by different organizations. For example the Energy Resources Conservation Board

(ERCB) of Alberta, Canada defines shale in Section 1.020(2) 27.1 of the Oil and Gas Conservation Regulations (OGCR) as a

“lithostratigraphic unit having less than 50% by weight organic matter, with: less than 10% of the sedimentary clasts having a

grain size greater than 62.5 micrometers; and more than 10% of the sedimentary clasts having a grain size less than 4

micrometers.” In some cases the definition is simpler and considers only the size of the fine-grained clastic sedimentary

particles that make up the rock; for example less than 0.0625 mm. The mineralogy of clays is quite complex (Shaw and

Weaver, 1965) and includes for example quartz (21.5%), feldspar (4.5%), clay minerals (66.9%), Iron oxides (<0.5%),

carbonates (3.6%), other mineral (<2%), and organic carbon (1%).

In the case of shale gas formations, natural gas is generated in the shale and remains within the shale. Consequently the shale

is both source rock and reservoir rock. In commercial shale reservoirs the shale is an excellent source rock. An important

characteristic of both tight gas and shale gas reservoirs is that they extend over very larger distances forming part thus of

continuous accumulations (Law, 2002). Smocker (2005) has defined a continuous petroleum accumulation as “those oil or

gas accumulations that have large spatial dimensions and indistinctly defined boundaries, and which exist more or less

independently of the water column.” Grains and pores are smaller in shales as compared with tight and conventional gas

formations. Gas is trapped and stored in shale in different ways: (1) as adsorbed and dissolved gas into the kerogen material

(Javadpour et al., 2007), (2) free gas trapped in nonorganic inter-particle (matrix) porosity, (3) free gas trapped in

microfracture porosity, (4) free gas stored in hydraulic fractures created during the stimulation of the shale reservoir, and (5)

free gas trapped in a pore network developed within the organic matter or kerogen (Ruppeil and Loucks, 2008; Wang et al.,

2009). The last one has significant practical implications that can help explain the larger than anticipated gas rates and

recoveries of natural gas from some of these formations, for example, from Devonian shales of the Appalachian Basin. The

different types of storage suggest that shale gas reservoirs should be represented at least by quadruple porosity models

(Aguilera, 2010; Andrade et al., 2011; Swami, 2013) and more rigorously by quintuple porosity models (Lopez and Aguilera,

2013).

Figure 6 is a semi-logarithmic crossplot of permeability vs. porosity that includes data from Horn River basin and soft shales

in Canada; and Fayetteville and Barnet shales in the United States. Lines for different values of rp35 (0.014, 0.025 and 0.04

microns) were developed with the use of equation 2. The lines provide a reasonable fit to the data. Thus although there is not

a clearly defined protocol for determining permeability and porosity in shales the rp35 results indicate that these values should

be determined in the laboratory along with pore and pore throat apertures. The shale gas flow units in Figure 6 are used

continuously for comparison against the tight gas, shale oil and tight oil reservoirs discussed in this paper.

In the case of tight formations, natural gas is generated somewhere else (usually in a shale) and migrates to the tight reservoir

where it is trapped and stored in inter-particle (matrix porosity), slot and microfracture porosity. This suggests that tight gas

reservoirs should be represented at least by dual porosity models and preferentially by triple porosity models. The use of a

triple porosity model that permits estimating values on intergranular, slot and/or fractures, and isolated or non-effective

porosity has been demonstrated by Deng et al, 2011.

Figure 7 reproduces the same data shown on Figure 6 but also includes cores and drill cuttings data from the tight gas

Nikanassin formation (Upper Jurassic and Lower Cretaceous) in the Western Canada Sedimentary Basin (WCSB). Clearly

the tight gas sandstone forms separate and distinctive flow units as compared with shale gas reservoirs. Permeabilities from

drill cuttings are consistently lower than in cores suggesting that some of the microfractures and slots and not preserved in

cuttings due to the action of the drilling bit on rocks. Figure 8 is a repeat Figure 7 but adding data from the Utica shale gas

in Quebec. Thus also imperfect data from shale gas reservoirs tend to form distinctive flow units for shale and tight gas

reservoirs.

The comparison is a good example of the continuum between conventional, tight gas and shale gas reservoirs presented in

this paper.

Tight Oil and Shale Oil Reservoirs

As in the case of tight gas and shale gas; tight oil and shale oil also form part of continuous accumulations. In the case of

tight oil the oil is generated somewhere else and migrates into the tight formation. In the case of shale oil, the oil is generated

6 SPE 165350

in the shale and remains within the shale. Thus in this respect the famous Bakken (United States) although generally called a

‘shale oil’ reservoir (DOE, 2012) is in reality a tight oil reservoir. In fact, oil is generated in the lower and/or upper Bakken

shales and migrates into the middle Bakken which has proved very prolific particularly in North Dakota although it is also

found as a continuous accumulation in South Dakota and Montana (United States), and Saskatchewan and Manitoba

(Canada).

In the case of the Canadian Bakken some of the oil might have been generated in the general areas where it is found but it is

likely that a significant amount of the oil might have been generated deep in the basin in the North Dakota area and might

have migrated north to the Shallower Bakken in Canada. This is suggested by the maturity levels of Bakken total petroleum

system presented in the W-E schematic cross-section shown Figure 9.

In general the Bakken is considered as a naturally fractured tight oil reservoir in North Dakota (Sonnenberg, 2011). The host

permeability can be enhanced by natural fractures and slot porosity stemming from dolomitization. This is the case of the

Elm Coulee, Parshall, and Sanish pools in North Dakota. However, the evidence of natural fractures is not as clear in the

shallower Bakken present north of the border in Saskatchewan and Manitoba, Canada.

Figure 10 introduces a crossplot of permeability vs. porosity on the rp35 template for the Bakken tight oil reservoir in the

United States and Canada. The data for Bakken Foghorn, Brutus and Jackson Rowdy was extracted from (Almanza, 2011).

The big red triangle highlights ‘sweet spot’ properties (permeability = 0.15 md, porosity = 6%) in the Bakken as established

by Sarg, Sonnenberg et al. (2011). In this case porosity and permeability can be much larger due to dolimitization, natural

fractures and slot porosity. Note also that porosities and permeabilities tend to be larger in the shallower Saskatchewan

Bakken in Canada. However because of the lack of natural fractures the productivity of the Bakken Saskatchewan wells is

generally smaller than the productivity of the Bakken North Dakota wells. For comparison Figure 10 also includes data from

Horn River (HR) and soft shales in Canada; and Fayetteville (F) and Barnett (B) in the United States included previously in

Figure 6. Different pore throat apertures (rp35) are clearly delineated.

Figure 11 shows a crossplot of permeability vs. porosity for Cardium conventional oil reservoirs of Type I (CT I) and Type

II (CT II) in Canada compared to Cardium tight oil reservoir (CT T). The data for the Type I and Type II rocks was published

originally by Mackenzie (1975) and was also highlighted in Figure 5. The Cardium conventional reservoir has been one of

the most prolific in Canada. Most recently the tight oil Cardium has been coming of age. Figure 11 highlights differences in

pore throat apertures between the Cardium and shale gas reservoirs. Each rock type corresponds clearly to different flow

units. This is probably responsible for the different production profiles discussed later in this paper. The data for the shale gas

reservoirs, shown initially in Figure 6, include the Horn River (HR) in Canada; Fayetteville (F) and Barnett (B) in the United

States.

Figure 12 includes permeability and porosity data from the Monterey shale in California. Some of the data was published by

Freeman and Eller (2010) and was sourced from Venoco and Occidental. The Monterey ‘shale’ is composed of fractured

chert and siliceous shales (and a very complex lithology that goes from Opal A, i.e., unaltered diatomite; to Opal CT, i.e.,

cristobalite tridymiteat larger depths) of Upper Miocene Age (Regan, 1953). There are clearly different flow units for the

shale gas and shale oil reservoirs in Figure 12. The shale gas samples show pore throat radii (rp35) varying between 0.014 and

0.004 microns. On the other hand 62.5% of the Monterey samples show rp35 ranging between 0.55 and 2.2 microns, 31.3%

between 0.15 and 0.25 microns and 6.2% between 0.04 and 0.15 microns. Liquids require larger pore throat apertures for

commercial production due to the larger viscosity of oil as compared to natural gas. And the more viscous the oil, the larger

must the pore throat apertures required to attain commercial production. In the case of the Monterey the API gravity ranges

between less than 6 and more than 30. For comparison purposes Figure 12 also includes the same data shown on Figure 6

for Horn River basin in Canada; and Fayetteville and Barnet shale gas in the United States.

Figure 13 shows permeability and porosity data developed by Walls et al. (2011) for the Eagleford shale in Texas using an

integrated Digital Rock Physics (DRP) process for analyzing rock properties of shales and other unconventional reservoirs.

Data from Gas Research Institute (GRI) crushed sample analysis tends to show lower permeability than the DRP results in

the lower porosity range. Walls et al. indicate that the difference in porosity-perm trends between the two methods will be the

subject of further study. There is also a data point for the Eagleford shale (a green triangle followed by question mark) taken

from Freeman and Eller (2010). The question mark stems from the fact that the author is not sure as to the validity of the data

point. If the data point is correct, comparison with other tight oil reservoirs discussed in this paper would suggest very rapid

production declines for those wells with this poroperm characteristic even if the wells are drilled horizontally and

hydraulically fractured in multiple stages. As there are wells that perform much better it is likely that there are areas with

better rock characteristics as indicated by Walls et al. (2011). The Eagleford shale and the Austin chalk are considered as a

total petroleum system (Martin et al., 2011) where the Eagleford shale is the source for the naturally fractured Austin chalk.

Figure 13 also includes the same data shown on Figure 6 for Horn River basin in Canada; and Fayetteville and Barnet shale

SPE 165350 7

gas in the United States.

Sleeping Giants

When compared with the other flow units in shale and tight oil reservoirs discussed in this paper (Figure 14); pore throat

apertures (rp35), porosities and permeabilities suggest that the Monterey is in all probability a sleeping giant. This assertion is

increased when the Monterey area (about 1650 square miles) and thickness (1000 to 3000 ft) are taken into account. Under

these circumstances it is reasonable to anticipate that with the proper management of externalities and development this

combination of area, thickness, porosity, permeability, pore throat apertures, large API gravities in some areas and innovative

technology will most likely lead to a gigantic recovery of ‘unconventional’ Monterey oil.

As for natural gas, the flow units of the Utica shale in Quebec presented in Figures 8 and 14 suggest rock quality

comparable to other prolific shale gas reservoirs. This shale extends to the U.S. where it has an area than is larger than the

Marcellus and a thickness that is also larger the Marcellus (Figure 15). Notice in Figure 14 that the pore throat apertures

(rp35) of the Marcellus (red squares) and the upper pattern of the Utica (yellow circles) compare reasonably well. Furthermore

note that the Utica in The U.S. side is underlain by basement rock. Based on my experience there is potential in the

basement, if naturally fractured, as the formation of natural fractures creates dilatancy and a vacuum that tends to suck the

fluids (natural gas and oil) present in the surroundings. As in the case of the Monterey, it is reasonable to anticipate that with

the proper management of externalities and development this combination of area, thickness, porosity, permeability, pore

throat apertures and innovative technology will most likely lead the Utica shale to a gigantic recovery of ‘unconventional’

petroleum (oil and gas).

Cumulative Production Distribution

Although shales are very heterogeneous and have multiple porosities (Aguilera, 2010; Andrade et al., 2011, Swami, 2013;

Lopez and Aguilera, 2013) the cumulative production of shale gas reservoirs is significantly and surprisingly more

homogeneous than the cumulative gas production distribution of tight gas and conventional gas and oil reservoirs. Figure 16

shows a production variability plot of fractional cumulative gas vs. fractional cumulative number of production wells for the

Barnett shale gas reservoir. The six curves represent different operating companies. If the shales were completely

homogeneous all the curves would fall in the dashed 45-degree straight line. The six curves separate from the dashed straight

line indicating a certain amount of heterogeneity. Figure 17 is a production variability plot for the Nikanassin tight gas

formation in six different areas of the Deep Basin (Western Canada Sedimentary Basin). The data show that as the fracture

density decreases the curvature and thus the level of heterogeneity increases. The separation from the 45-degree dashed

straight line is more significant in Figure 17 than in Figure 16 indicating a larger degree of heterogeneity in tight gas

reservoirs as compared with shale reservoirs. The result is surprising but corroborated by actual production data. At this time

there is not enough production data from tight and shale oil reservoirs to reach a conclusion with respects to the distribution

of their cumulative oil production.

Production Rates

The original attempt to correlate production rates and pore throat apertures was published by Martin et al. (1997). Pore size

classes were grouped by Martin et al. on the basis of pore throat (port) apertures as megaports (r35 > 10 microns), macroports

(2.5-10 microns), mesoports (0.5 to 2.5 microns), microports (0.1 to 0.5 microns), and nanoports (0.01 to 0.1 microns).

Martin et al. indicated that comparatively megaports can reach medium gravity oil production rates of 10s of thousands of

barrels per day if “zonal thickness and other factors are constant” and without mechanical constraints, macroports can reach

thousands of barrels per day, and mesoports hundreds of barrels per day. Microports can produce few to tens of barrels per

day on pump. However, Martin et al. state that “microport flow units are decidedly non-reservoir in this comparative

completion of moderate thickness and medium gravity oil without mechanical constraints. These flow units are of far more

interest as potential seals for higher quality reservoir downdip.” Since Martin et al.’s publication microports and nanoport

reservoirs have become economic in many instances. Subsequently, Deng et al. (2011) associated possible gas rates in

conventional reservoirs with pore throat apertures. Oil and gas rates from these efforts are presented in the upper right hand

side of Figure 2A. Martin et al. (1997) and Deng et al. (2011) estimates were for vertical wells. Figure 2A adds some

estimates of oil and gas rates for multistage hydraulically fractured horizontal wells.

This paper examines production rates and flow periods for some ‘unconventional’ petroleum reservoirs and makes a

comparison with the corresponding pore throat apertures. As early as the 1970s, Aguilera (1980, p. 403) demonstrated the

presence of linear flow in wells producing from Devonian shales in an infinite-acting reservoir (Figure 18). The start of the

data went back to the 1950s and flow rates extended over a 25-year period without reaching the boundary dominated flow.

The connectivity was interpreted to occur through natural fractures. This led to the development of approximate solutions for

8 SPE 165350

linear flow in dual porosity reservoirs (Aguilera, 1986).

The linear flow observation has also been made more recently with data from wells drilled during the last few years,

particularly in wells that have been drilled horizontally and stimulated in multiple stages. Many rigorous solutions have been

developed to handle the linear flow observations in shale and tight gas reservoirs (Wattenbarger et al., 1997; El Banbi, 1998;

El Banbi and Wattenbarger, 1998; Arevalo-Villagran, 2006; Moghadam, 2010; Brohi et al., 2011) as well as approximate

solutions (Aguilera, 1986; Leguizamon and Aguilera, 2011). There have been also many useful and practical empirical

models based on actual recordings of production rates in unconventional oil and gas reservoirs (Reynolds et al., 2010; Baihly

et al., 2010 and 2011; Martin et al., 2011; Hamm and Struyk, 2011). As in the case of permeabilities and porosities used for

estimating pore throat apertures (rp35), the petroleum rates published in some of the above mentioned studies are used in this

paper to make the proposed interpretations tractable.

Gas Rates.- Production data for the Barnett, Fayetteville, Woodford and Haynesville shale published by Baihly et al. (2010,

2011) are presented in the upper graph of Figures 19, 20, 21 and 22, respectively. The authors considered 1,957 horizontal

wells in their study and shifted the production data to the day of first production (DOFP). They grouped the wells according

to the year in which the wells started production. The middle graphs in Figures 19, 20, 21 and 22 present my interpretation

of the data as a crossplot of rate vs. time on log-log coordinates (these graphs were not presented in the Baihly et al.’s study).

For the Barnett, Fayetteville and Woodford there are linear trends with a slope of -0.5 indicating an average linear flow. The

possible beginning of boundary dominated flow is also observed for some Barnett wells particularly in the group that started

production in the year 2003. For the Haynesville the data production data falls below the straight line with a slope of -0.5

indicated a possible lack of linear flow.

The lower graphs in Figures 19, 20, 21 and 22 present my interpretation of the data as a crossplot of 1.0 divided by rate (1/q)

vs. the square root of time on Cartesian coordinates (these graphs were not presented in the Baihly et al.’s study). There are

indications of linear flow in the Barnett, Fayetteville and Woodford shales; and in all these cases the linear trend extrapolates

to the origin at zero time, a clear indication the there is no damage around the wellbore. For the Barnett (Figure 19) some

wells have clearly reached boundary dominated flow. The Fayetteville does not reach boundary dominated flow and the

Woodford might have reached it for the wells that started production in 2006. The Haynesville response is different. As

indicated previously the log-log crossplot of rate vs. time yielded a production trend that fell below the -0.5 straight line.

There could be linear flow, however, as the 1/q vs. square root of time shows a linear trend that extrapolates to a negative

value of 1/q. This is indicative of improved conditions around the wellbore that probably stem from the over-pressured

condition of the reservoir. The negative effect, however, is that permeability and porosity decrease as the net stress on the

fractures become larger.

Thus the type of flow observed in Barnett, Fayetteville, Woodford and Haynesville horizontal gas wells is not too dissimilar

from the linear flow observed in hydraulically fractured vertical Devonian shale wells starting in the 1950s (Figure 18). As

such the data can be generally interpreted with methods available in the literature for handling linear (and bilinear) flow

(Aguilera, 1986: Wattenbarger et al., 1997; El Banbi, 1998; El Banbi and Wattenbarger, 1998; Arevalo-Villagran, 2006;

Moghadam, 2010; Brohi et al., 2011; Leguizamon and Aguilera, 2011). The flow behavior of tight oil wells, however, can be

different as discussed next.

Oil rates.- Hamm and Struyk (2011) have presented a very complete data set for multi-stage hydraulically fractured

horizontal wells in the Western Canada Sedimentary Basin (WCSB). Based on the actual production data they have

developed empirical type curves for various reservoirs with varying types of rock quality. To generate their average type

curves they shift the production data of all wells to the same starting point. The upper graph in Figure 23 shows oil

production rates vs. time for the tight oil Cardium formation as published by Hamm et al. (2011). Their graph also includes a

curve for a Type Well developed from actual Cardium production. The graph in the middle shows a log-log crossplot of oil

rate vs. time that result in an approximate straight line with a slope of -0.75 between 2 linear flow periods. To the author’s

best knowledge there are not references in the literature that explains the -0.75 slope. As a consequence an approximation is

presented in this paper to try to explain this behavior. The conclusion is reached that the -0.75 straight line is the result of a

transient unrestricted transition between 2 linear flow periods. The bottom graph shows a Cartesian crossplot of 1/q vs. time

^0.75 with straight lines bracketing the tight oil Cardium data. The explanation for the -0.75 slope has been developed with

the use of the following equation for a triple porosity model dominated by linear flow in an infinite-acting reservoir

(Leguizamon and Aguilera, 2011):

√

(3)

The functions for the case of restricted (pseudo steady state) inter linear flow the function is given by (1991):

SPE 165350 9

( ) (

) ( ) (

) (4)

where cc’s are empirical ‘commingled completion’ exponents for the dual and triple porosity reservoirs, and Dd and Dt are

the approximate beginnings of the straight lines for the dual and triple porosity responses, respectively. For the case of

unrestricted (transient) inter linear flow the functions are given by an extension of Najurieta (1980) and Aguilera (1986,

1991):

( ) √

√

(

) √

√

(5)

d and t are storativity ratios given by:

(6)

The fracture storage (Sf) is the product (cth) for the fractures, Smd is the product (cth) for one matrix (or media) and Smt is

the product (cth) for the other matrix (or media) in the triple porosity reservoir. The dimensionless hydraulic diffusivity for

the dual and triple porosity media are given by Dd and Dt. In the case of gas reservoirs the storages are calculated at initial

pressure. The upper and lower graphs in Figure 24 show examples of results using the model described in this paper for the

case of restricted inter linear flow based on the following data: d = 0.1, t = 0.1, Dd = 10000, Dt = 0.05 and ccd = cct = 1,

Dd = 1000, Dt =1000. The log-log crossplots result in 3 parallel straight lines with slopes equal to -0.5 indicating linear

flow. The upper graph assumes restricted (pseudo steady state) inter linear flow. The transition periods result in very large

slopes. This is what has been assumed so far in the literature for the analysis of multi-stage hydraulically fractured horizontal

wells. The lower graph assumes unrestricted (transient) inter linear flow. This is the new transition flow period introduced in

this paper that is recognized by a straight line with a slope equal to -0.75. This is the flow period observed in the tight oil

Cardium formation as shown by the real production decline data presented in Figure 23. Based on this interpretation is likely

that the rates will revert to linear flow behavior in the future. It is likely that the same approach can be used for the case of

shale oil reservoirs with a unified model that take into account viscous and diffusion-like flow (Rahmanian et al., 2013).

Conclusions

1. Process (or delivery) speed, i.e., the ratio of permeability and porosity, provides a continuum between conventional,

tight gas, shale gas, tight oil and shale oil reservoirs.

2. There are distinctive flow units for each type of reservoir penetrated by vertical and horizontal multi-stage

hydraulically fractured wells that can be linked empirically to gas and oil rates and under favorable conditions to the

type of production decline.

3. A new unrestricted transition flow period in tight oil reservoirs has been recognized by considering a triple porosity

model that leads to a straight line with a slope of -0.75 on log-log coordinates. This straight line occurs as a

transition between 2 linear flow periods.

4. To make the work tractable the bulk of the data have been extracted from published geologic and petroleum

engineering literature.

Acknowledgements Parts of this work were funded by the Natural Sciences and Engineering Research Council of Canada (NSERC agreement

347825-06), ConocoPhillips (agreement 4204638), Alberta Innovates Energy and Environment Solutions (AERI agreement

1711), the Schulich School of Engineering at the University of Calgary and Servipetrol Ltd. The laboratory work with

cuttings was carried out using Darcylog equipment provided to the GFREE research team by Dr. Roland Lenormand of

Cydarex in Paris, France. Their contributions are gratefully acknowledged. I extend my gratitude to my students in the

Schulich School of Engineering, particularly Bukola Olusola, Peng Wu and John Freddy Ramirez for their help during

preparation of this paper.

Nomenclature

cc = Empirical commingled completion exponent, dimensionless

f = Function

10 SPE 165350

h = Net pay, m

hf = Fracture width, m

k = Permeability, md

k2 = Fracture permeability attached to the net pay, md

mf = Porosity exponent (cementation factor) of the natural fractures

pD = Dimensionless pressure

r35 = Winland pore throat radius at 35% cumulative pore volume, microns

rp35 = Pore throat radius at 35% cumulative pore volume, microns

St = Storage of the second matrix in the triple porosity system (cth), m/kPa

ST = Total storage of the composite system

t = Time

tD = Dimensionless time

Tf = Transmissibility, md.m/mPa.sec

wf = Fracture width, m

xf = Fracture half length, m Greek Symbols

Total porosity, fraction

Porosity of natural fractures (PHI2) scaled relative to the bulk volume of the composite system, fraction

b Matrix block porosity scaled relative to the bulk volume of the matrix system, fraction

eff Effective porosity, fraction

m Matrix block porosity scaled relative to the bulk volume of the composite system, fraction

Dd Approximate beginning of the of the last straight line in the dual porosity reservoir, h

Dt Approximate beginning of the of the last straight line in the triple porosity reservoir, h

Storativity ratio

d Storativity ratio in the dual porosity reservoir

t Storativity ratio in triple porosity

Subscripts

d = Dual porosity

D = Dimensionless

f = Fracture

g = Gas

m = Matrix

o = Oil

t = Triple porosity

Acronyms

ERCB = Energy Resources Conservation Board (Alberta, Canada)

GFREE = integrated geoscience, formation evaluation, reservoir drilling, completion and stimulation, reservoir engineering,

economics and externalities, a tight gas research program at the University of Calgary, Canada

Port = pore throat radius

WCSB = Western Canadian Sedimentary Basin

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SPE 165350 15

Figure 1. Estimates of global natural gas and oil endowment.

Reservoir Rock1000 md

10 md

0.1 md

Unconventional Gas

Tight Gas CBM

Shales Gas Gas Hydrates

Bottom of Resource Pyramid Unknown

Increasing:

ProductionCosts andPrices

ActivationIndexes

Research

Time

Decreasing:

DeliverySpeed(k / Ø)

PoreThroatApertures

Futu

re

P

rese

nt

WORLD GAS RESOURCE PYRAMID

Endowment

Aguilera et al., WPC, 2008,SPE 132845, SPE 162717

Gravity45 API

30 API

15 API

Unconventional Oil

Heavy Oil

Oil sands Tight Oil(bituminous sands)

Oil Shale

Bottom of Resource Pyramid Unknown

Increasing:

ProductionCosts andPrices

ActivationIndexes

Research

Time

Decreasing:

Oil Mobility(k / )

Futu

re

P

rese

nt

WORLD OIL RESOURCE PYRAMID

Endowment

16 SPE 165350

Figure 2A. Flow units as a function of pore throat apertures (rp35), porosities and permeabilities; and possible ranges of oil

(thousands of bopd) for vertical wells published by Martin et al. (1997) and gas flow rates (millions of scfd) for vertical wells

published by Deng et al. (2011). Graph includes possible ranges of rates for multistage hydraulically fractured (MSHF)

horizontal wells. Knudsen number allows distinguishing between viscous and diffusion-like flow.

Mb

op

d

MM

scfd

10’s

1’s

0.1’s

0.01’s

100’s

10’s

1’s

1.0’s

Vertical W

ellsM

SHF H

orizo

ntal

100’s+

1’s

10’s

0.1’s

SPE 165350 17

Figure 2B. There is consistency between porosities and permeabilities from core analysis for conventional, tight gas and

shale gas reservoirs (see Figure 1); and porosities and permeabilities calculated from pore scale modeling (this study). The

empirical flow units represented by rp35 lines (Kolodzie, 1980; Aguilera, 2010) are supported by pore scale modeling

calculations for pore throats (rt) ranging between 1-4, 0.1-1.5, 0.005-0.5 and 0.009-0.1 microns.

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

10

100

1000

10000

0 5 10 15 20 25 30

Perm

eabi

lity,

km

ax (

mD

)

Porosity (%)

CHART FOR ESTIMATING PORE THROAT APERTURE (Adapted from Aguilera, CSEG Recorder, Feb 2003)

r t : 1 - 4 micro metersr t : 0.1 - 1.5 micro metersr t : 0.05 - 0.5 micro metersr t : 0.009 - 0.1 micro meters

rp35

20

10

4

2

1

0.5

0.2

megaports

macroports

mesoports

microports

nanoports

0.04

0.025

0.014

0.1

18 SPE 165350

Figure 3. Poroperm crossplot showing pore types of Pennsylvanian sandstones and conglomerates, Elk City oil field,

Oklahoma (Source: Sneider et al., 1983).

Figure 4. Poroperm crossplot showing different rp35 flow units of Pennsylvanian sandstones and conglomerates, Elk City oil

field, Oklahoma. Data points are the same as presented in Figure 3.

0.001

0.01

0.1

1

10

100

1000

10000

0 5 10 15 20 25 30

Perm

eabi

lity

(mD)

Porosity (%)

© Servipetrol, 2003

rp35

15

6

2.3

2

1

0.5

0.05

megaports

macro

ports

mesoports

mic

roports

SPE 165350 19

Figure 5. Poroperm crossplot showing different rp35 flow units of Cardium sandstones, Pembina oil field, Canada. Data points

for Rock of Types I and II were tabulated originally by MacKenzie (1975). The dotted ellipse in the lower part of the graph

corresponds to tight oil Cardium.

Figure 6. Permeability vs. porosity crossplot including data from Horn River and soft shales in Canada, and Fayetteville and

Barnet shales in the United States. Symbols of Fayetteville data, including blue triangles, correspond to individual wells.

Green diamonds and black dots correspond to the Horn River (Muskwa formation) basin and soft shales, respectively (. et al,

2008), brown dots correspond to the Barnett formation (Source: Aguilera, 2010).

0.001

0.01

0.1

1

10

100

1000

10000

0 5 10 15 20 25 30

Perm

eabi

lity

(mD

)

Porosity (%)

CHART FOR ESTIMATING PORE THROAT APERTURE (Template Source: Aguilera, CSEG Recorder, Feb 2003)

rp35

10

4

1.7

0.8

0.42

0.2

0.1

me

ga

po

rtm

acro

po

rtsm

eso

po

rtsm

icro

po

rts

1.0E-05

1.0E-04

1.0E-03

1.0E-02

0 2 4 6 8 10 12 14 16

PER

MEA

BILI

TY (M

D)

POROSITY

FAYETTVILLE

HORN RIVERBARNETT

SOFT SHALES

0.04

0.025

0.014

rp35microns

20 SPE 165350

Figure 7. Permeability vs. porosity crossplot including shale data from Horn River (HR) and soft shales in Canada;

Fayetteville (F) and Barnett (B) in the United States, also shown on Figure 6. The red dots in the upper part of the graph

represent core data from the Nikanassin tight gas formation in Canada. The black squares with red crosses in the middle, and

the red triangles are data from Nikanassin drill cuttings (Solano, 2010; Ortega and Aguilera, 2013).

Figure 8. Permeability vs. porosity crossplot including shale data from Horn River (HR) and soft shales in Canada;

Fayetteville (F) and Barnett (B) in the United States, also shown on Figure 6. The red dots in the upper part of the graph

represent core data from the Nikanassin tight gas formation in Canada. The black squares with red crosses in the middle, and

the red triangles are data from Nikanassin drill cuttings (Solano, 2010; Ortega and Aguilera, 2013). The yellow circles

represent data from the Utica shale in Quebec (Lavoie et al., 2010).

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

0 2 4 6 8 10 12 14 16

PER

MEA

BIL

ITY

(MD

)

POROSITY

F

HR, B

SOFT SHALES

0.04

0.025

0.014

rp35microns

0.55

NIKANASSIN CORE

0.15

UTICA

NIKANASSIN CUTTINGS

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

0 2 4 6 8 10 12 14 16

PER

MEA

BIL

ITY

(MD

)

POROSITY

F

HR, B

SOFT SHALES

0.04

0.025

0.014

rp35microns

0.55

NIKANASSIN CORE

0.15

UTICA

NIKANASSIN CUTTINGS

UTICA

SPE 165350 21

Figure 9. Cross section of the Bakken petroleum system showing approximate maturity levels (Source: Sonnenberg, 2011). It

is likely that some of the oil generated in the Bakken in North Dakota migrated north (perpendicular to this page) to the

Canadian Bakken.

Figure 10. Permeability vs. porosity crossplot for the Bakken tight oil reservoir in the United States and Canada. The big red

triangle highlights ‘sweet spot’ properties in the Bakken as established by Sarg, Sonnenberg et al. (2011). In this case

porosity and permeability can be larger due to dolimitization as in the Elm Coulee, Parshall, and Sanish pools. The graph also

includes for comparison shale data from Horn River (HR) in Canada; Fayetteville (F) and Barnett (B) in the United States,

also shown on Figure 6.

Bakken Petroleum System

Reservoirs:

Middle Bakken & Three Forks

Source Beds:

Upper & Lower Bakken Shales

“what was made in the Bakken, stayed in the Bakken PS”

1.0E-06

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

1.0E+02

0 3 6 9 12 15 18 21 24 27 30

PER

MEA

BIL

ITY

(MD

)

POROSITY

F

HR, B

0.04

0.025

0.014

rp35microns

1.8

0.09

0.004

1

4.5

JACKSON

BRUTUSFOGHORN

0.55

SASK

22 SPE 165350

Figure 11. Permeability vs. porosity crossplot for Cardium conventional oil reservoirs of Type I (CT I) and Type II C(T II) in

Canada compared to Cardium tight oil reservoir (CT T) highlights differences in pore throat apertures. Each rock type

corresponds clearly to different flow units. The graph also includes for comparison shale data from Horn River (HR) in

Canada; Fayetteville (F) and Barnett (B) in the United States, also shown on Figure 6.

Figure 12. Permeability vs. porosity crossplot for the Monterey shale in California. Possible Eagleford information is

included. The graph also shows for comparison shale data from Horn River (HR) in Canada; Fayetteville (F) and Barnett (B)

in the United States, also shown on Figure 6.

1.0E-06

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

1.0E+02

0 3 6 9 12 15 18 21 24 27 30

PERM

EABI

LITY

(MD)

POROSITY

F

HR, B

0.04

0.025

0.014

rp35microns

1.8

0.18

0.004

1

4.5

CT T

CT I

CT II 0.8

1.0E-06

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

1.0E+02

0 3 6 9 12 15 18 21 24 27 30

PER

MEA

BIL

ITY

(MD

)

POROSITY

F

HR, B

0.04

0.025

0.014

rp35microns

0.55

0.09

0.004

12

5

1.8

MONTEREY

VENOCO C

UPPER OXY

VENOCO A VENOCO B LOWER OXY

EAGLEFORD?

4.5

SPE 165350 23

Figure 13. Permeability vs. porosity crossplot for the Eagleford shale (Wells A-DRP, A-GRI-DS and B-GRI-AR-AR).

Possible Eagleford information is also included (green triangle). The graph also shows for comparison shale data from Horn

River (HR) in Canada; Fayetteville (F) and Barnett (B) in the United States, also shown on Figure 6.

Figure 14. Composite of permeability vs. porosity crossplot for tight oil and shale oil reservoirs suggests pore throat apertures

(rp35) ranging between approximately 0.09 and 4.5 microns. The graph includes data from the Shengli field (China), Cardium

(CT I, CT II, CT T), Monterey, Bakken in Saskatchewan (BSASK), Bakken in the U.S. (Foghorn, Brutus, Jackson), Viking

in Canada (VSK, VRW). Also included are the Marcellus (red squares) and the Utica (2 different patterns of yellow circles).

The lower part of the graph presets for comparison shale data from Horn River (HR) in Canada; Fayetteville (F) and Barnett

(B) in the United States, also shown on Figure 6. At the bottom of the graph data for the Upper and Lower Bakken (B).

1.0E-06

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

1.0E+02

1.0E+03

0 3 6 9 12 15 18 21 24 27 30

PER

MEA

BIL

ITY

(MD

)

POROSITY

F

HR, B

0.040.025

0.014

rp35microns

0.55

0.09

0.004

5

1.8

WELL A-GRI-DS

EAGLEFORD ?

4.5

10.0WELL B-GRI-AR-AR WELL A-DRP

1.0E-06

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

1.0E+02

0 3 6 9 12 15 18 21 24 27 30

PER

MEA

BIL

ITY

(MD

)

POROSITY

F

HR, B

0.04

0.025

0.014

rp35microns

0.55SHENGLI

0.09

EAGLEFORD(?)

BSASK3

0.004

12

4

5

14

BSASK2

BSASK1

1.8

MONTEREY

BAKKENSWEET SPOT

UPPER & LOWER B

SMCP

VP

VRW

VSKSSK

CT I

CT II

4.5

FOGHORN

BRUTUS JACKSON

CT T

MARCELLUS

UTICA

UTICA

24 SPE 165350

Figure 15. Areal extension and cross section covering the Marcellus and Utica shales in the United States. Based on the

author’s experience there is also potential in the basement, if naturally fractured, as the formation of natural fractures creates

a vacuum that tends to suck the fluids (in this case oil and natural gas) present in the surroundings. (Source of maps:

Geology.com, 2011).

Figure 16. Fractional production variability plot for the Barnett fractured shale in Texas for various operating companies

(Source: Aguilera, 2010).

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

% WELLS

% C

UM

ULA

TIVE

GA

S

BASE

Devon

Burlington

Encana

XTO

Chief

SPE 165350 25

Figure 17. Fractional production variability plot for six Nikanassin tight gas areas the Deep Basin of Canada (Source:

Gonzalez and Aguilera, 2013).

Figure 18. Drawdown linear flow for wells producing from Devonian shales connected natural fractures in an infinite-acting

reservoir. The flow rates extend over a 25-year period without reaching the boundary dominated flow (Aguilera, 1980,

p.403).

0

10

20

30

40

50

60

70

80

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

1 /

q (

1E-6

/ s

cf)

Time ̂ 1/2 (Years ̂ 1/2)

> 300 Mscfd

200_300Mscfd

100-200 Mscfd

< 100 Mscfd

Linear (< 100 Mscfd)

26 SPE 165350

Figure 19. Production history of the Barnet shale normalized to the first day of production (FDOP) is shown on the upper

graph. The presence of linear flow is shown in the log-log middle graph (slope = -0.5) and the lower graph (1/q vs. square

root of time). It is likely that some groups of wells start showing boundary effects at t^0.5 equal to 6 to 8 months^0.5 or 36 to

64 months (Source of data: Baihly et al., 2010, 2011).

SPE 165350 27

Figure 20. Production history of the Fayetteville shale normalized to the first day of production (FDOP) is shown on the

upper graph. The presence of linear flow is shown in the log-log middle graph (slope = -0.5) and the lower graph (1/q vs.

square root of time). No boundary effects are noticeable (Source of data: Baihly et al., 2010, 2011).

0.000

0.002

0.004

0.006

0.008

0.010

0 1 2 3 4 5 6 7 8

1/q

(1

/Mcf

d)

Time ^0.5 (months ^0.5)

FAYETTEVILLE

DOFP_YEAR_2005 8 WELLS

DOFP_YEAR_2006 53 WELLS

DOFP_YEAR_2007 118 WELLS

DOFP_YEAR_2008 173 WELLS

DOFP_YEAR_2009 115 WELLS

LINEAR

28 SPE 165350

Figure 21. Production history of the Woodford shale normalized to the first day of production (FDOP) is shown on the upper

graph. The presence of linear flow is shown in the log-log middle graph (slope = -0.5) and the lower graph (1/q vs. square

root of time). It is likely that the upper two groups of wells start showing boundary effects at t^0.5 equal to 5 to 6 months^0.5

or 25 to 36months (Source of data: Baihly et al., 2010, 2011).

SPE 165350 29

Figure 22. Production history of the Woodford shale normalized to the first day of production (FDOP) is shown on the upper

graph. There is absence of linear flow is shown in the log-log middle graph (slope ≠ -0.5). If there is linear flow the lower

graph (1/q vs. square root of time) would indicate improved conditions around the wellbore that would tend to disappear as

the reservoir is depleted (Source of data: Baihly et al., 2010, 2011).

30 SPE 165350

Figure 23. The upper graph shows oil production rates vs. time for the tight oil Cardium formation as published by Hamm

and Struik. (2011). Their graph also includes a curve for a Type Well developed from actual Cardium production. The graph

in the middle shows a log-log crossplot of oil rate vs. time suggesting a new unrestricted transition flow period with a slope

of -0.75 between 2 linear flow periods. The bottom graph shows a Cartesian crossplot of 1/q vs. time ^0.75 with straight lines

representing the unrestricted transition bracketing the tight oil Cardium data.

SPE 165350 31

Figure 24. The upper graph shows dimensionless rate vs. dimensionless time for a triple porosity model with restricted inter-

linear flow. The transition between the 2 linear flow periods generates an approximate straight line with a negative slope

much bigger than 0.75. The lower graph shows unrestricted inter-linear flow. The transition between the 2 linear flow periods

generates an approximate straight line with a negative slope equal to 0.75.

1.E-06

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

1.E+01

1.E+02

1.E+03

qD

tD

Decline Rate, Unrestricted Inter-Linear Transition FlowTriple Porosity Model Dominated by Linear Flow

Linear Flow (slope = -0.5)

Unrestricted Transition (slope = -0.75)

Linear

Transition

Linear