SPE 160869

A Review of Recent Developments and Challenges in Shale Gas Recovery O. Arogundade, M. Sohrabi, SPE, Heriot Watt University

Copyright 2012, Society of Petroleum Engineers

This paper was prepared for presentation at the SPE Saudi Arabia Section Technical Symposium and Exhibition held in Al-Khobar, Saudi Arabia, 8–11 April 2012. 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, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at the SPE meetings are subject to publication review by Editorial Committee of Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. 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 where and whom the paper was presented. Write Librarian, SPE, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.

Abstract Over the past decade, there has been increased interest in shale gas plays worldwide. This is due to improved techniques in shale gas recovery from these ultra-low (in the order of hundreds of nanodarcies) permeability formations which is owed primarily to horizontal drilling, hydraulic fracturing and other technological advances. Another attraction to the exploration of shale gas is the lower inherent risk associated with its exploration when compared with exploring for conventional hydrocarbons due to its ubiquitous abundance wherever it is present. This success has indeed driven down gas prices and has culminated in the security of gas supply worldwide for decades to come. This paper is a critical literature review of shale gas that identifies and examines challenges encountered in shale gas recovery which include inadequacies in mathematical flow models applied in shale gas modelling due to non-darcy flow, uncertainties in the fracture intensity, fracture symmetry and orientation and lack of standard protocols to mention a few. It also takes a look at how hydraulic fracturing improves the economics of shale gas exploitation since it considerably increases production and also the overall recovery from the reservoir. Hydraulic fracturing has come as the primary mode of increasing recovery in shale gas reservoirs but it also comes with its own problems where desired results are easily achieved in brittle shale formations but may be even more challenging for ductile shale formations. Another progress made is being able to monitor the fracture growth within the reservoir real time to prevent the fracture growing out of control. Milestones are continually being achieved on improving the recovery of shale gas and in this paper we address progresses made and challenges encountered. Introduction Just recently, the volume of fossil fuel reserves worldwide was considered to be on the decline because of the reduced incidence of significant discoveries of reservoirs worldwide. The continuously declining nature of existent reservoirs with a substantial number of these in mature life, until techniques to economically recover reserves from unconventional reservoirs were developed. Unconventional reservoirs are reservoirs that contain fossil fuel but are uneconomical to produce (with recoveries of the order of 2%) at prevailing market rates when conventional recovery mechanisms are applied. Examples of unconventional reservoirs are coal bed methane reservoirs, tight gas reservoirs, shale gas reservoirs etc. As a consequence of significant breakthroughs in research to increase recovery from low permeability reservoirs, matrix permeability of reservoirs of interest has reduced from millidarcies in conventional reservoirs to microdarcies in tight gas reservoirs down to nanodarcies in shale gas reservoirs (Kundert et al; 2009).

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Kundart et al (2009) defined shale as a class of tightly packed fine-grained clastic sedimentary rock possessing an average grain size below 0.0025in. The small grain size and its tight packing is what results in a formation with low porosity and ultra-low permeability. As early as 1637, the Scots, Swedes and French used oil shale as a source of fuel. Oil shale is generally found at depths below 3000ft in carbonate rocks that are very rich in kerogen (K. Biglarbigi et al, 2010).Oil shales are usually younger in the geological age when compared with conventional oil which requires longer geological time and therefore deeper formations at higher temperatures (K. Biglarbigi et al, 2010). Shale Oil is hydrocarbon usually found within the source rock of the shale reservoir (similar to shale gas). It usually occurs in the form of kerogen which requires further processing by heating before being useful (Lechtenbohmer et al; 2011). Shale gas frequently occurs in tight sedimentary rock formations which are as impermeable as concrete with permeability in the range of hundreds of nanodarcies and a porosity of between 2-10%. It is found in shale formations in mature petroleum source rocks within the thermogenic gas window. In shale gas reservoirs, since no migratory path for the produced gas exists, the source rock doubles as the reservoir rock. Since the first shale gas well (a shallow 31ft deep well) was drilled in the Appalachian basin, USA in 1821, no progress was made in this area because oil and gas companies did not possess the requisite technology to economically exploit shale gas. Due to the very low permeability of shale gas reservoirs, economic production rates and recovery cannot be achieved without long horizontal wells stimulated by multi-staged hydraulic fracturing treatment, closer well spacing and other factors. Formation of Shale Gas Reservoirs The United States Geological Survey defines an unconventional reservoir as one with a very large coverage area and hydrocarbon initially in place with very low matrix permeability and a low expected final recovery with the absence of a hydrocarbon trap (Schenk, 2002). The process of formation of shale gas reservoirs is entirely different from the way conventional reservoirs are formed. Here, the shale formation acts as both the source rock and the reservoir rock where no migration path for the hydrocarbon evolved exists and the top of the reservoir lacks the presence of a trapping mechanism. Aguilera (2010) suggested ways in which gas is stored in shale, they are; (a) trapping of the gas in organic matter (adsorption) (b) trapping of the free gas in non-organic matrix porosity (c) trapping of the free gas in the micro-fracture porosity (d) hydraulic fractures as a consequence of reservoir stimulation contain stored gas (e) existent pore network within the organic matter also contains free gas. World Shale Gas Volume Over the past decade, as a consequence of improvement in the technologies for hydraulic fracturing and horizontal drilling, vast reserves of shale gas around the world have remained largely untapped and are now being exploited with even more shale gas plays to be discovered. Figure 1 gives a distribution of shale gas reserves around the world where the largest reserves are located in the North American and Asian basins with estimates of world shale gas volumes conservatively estimated at about 16,000Tcf (W. Fazelipour; 2010). Currently, there is a surge in investments worldwide by Exploration and Production companies in shale gas exploration because of the lower geological and/ commercial development risk and a decreased average decline rate when compared with conventional plays (W. Fazelipour; 2011). This is as a consequence of the presence of giant shale gas reserves in the subsurface which when discovered makes the project a very likely commercial success. Adsorption In shale gas reservoirs, the contained hydrocarbon usually exists in two states which are; free gas stored in the limited pore space and adsorbed gas stored in the organic matter (Cipolla et al; 2010). When both

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are combined, they form the total gas content. The proportion of the adsorbed gas may be a significant proportion of the total gas in place (40-50%) but with current technology, there is a limited ability to produce the adsorbed gas. The following are factors that affect the productive capacity of adsorbed gas (Cipolla et al; 2010);

• Relatively high flowing bottom hole pressure • Ultra-tight matrix rock • A desorption profile which may require reduced pressures for substantial volumes of adsorbed gas

to be produced

Desorption Biswas (2011) suggests that the flow of gas through the shale gas reservoir fracture network is a consequence of desorption and diffusion of the gas which transports it within the matrix-fracture interface. Javadpour et al (2007) showed the laboratory procedure of the canister desorption testing to produce desorption curves, a method now popular in studying shale gas desorption. Gas desorption plays a role in the overall recovery of tight shale gas reservoirs and it may amount to about 5-15% of the total produced gas volume where it usually occurs later in the life of the reservoir. Thomson et al (2011) showed that when desorption is taken into account in the production profile, it could account for about 17% of the Expected Ultimate Recovery. Cipolla et al (2010) showed that gas desorption leads to an improved final recovery. Since desorption becomes significant late in the life of the reservoir, its effect on the project economics is negligible. Factors known to affect the degree of desorption are (Cipolla et al; 2010); Fracture Spacing: The less the fracture spacing the more the effect of desorption as shown in Figure 2 where for a fracture spacing 600ft apart, the desorbed gas accounts for 8.5% of the total produced gas compared to a 15% proportion of total produced gas when the fracture spacing is 50ft. Flowing Bottom Hole Pressure (FBHP): Decreasing the FBHP does not significantly affect the production of desorbed gas, although there is an overall increase in recovery as a consequence of increase in production of free gas where the ultimate production could rise by about 12% as observed in the figure 3 (Cipolla et al; 2010). Challenges of Shale Gas Exploration Shale gas reservoirs are unconventional reservoirs in which many techniques developed for conventional reservoirs are being modified for its use but do not strictly apply to it and techniques are being sought to improve them. Some of these include but are not limited to instantaneous capillary equilibrium, determination of physical properties of shale gas reservoirs (i.e. rock and fluid properties e.g water saturation, capillary pressure, permeability etc), non-Darcy flow, predictive tools for production forecasting etc. To have an insight into how these affect the exploration for shale gas, the subsections below investigate these factors on an individual basis. Simulating Shale Gas Reservoirs Studies have shown that Darcy flow and instantaneous capillary equilibrium applied in simulators for conventional reservoirs are inadequate for reliable simulation of shale gas reservoirs (Quin, 2007; Andrade et al., 2010). With the complex nature of shale gas reservoirs, many capabilities necessary to accurately simulate these reservoirs are lacking which allows us question how representative these simulation models actually are. Andrade et al (2010) identifies areas where commercial simulators make unrealistic estimates unsuitable for shale gas reservoirs, these are; (1) the assumption of instantaneous capillary equilibrium (2) that Darcy flow gives a complete description of the flow regime (3) that relative permeability is not rate

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dependent. These assumptions makes history matching a more daunting task than it already is where it wrongly predicts the volume of water produced, poorly handles changes in gas flow rates with time (and some cases pressure) which ultimately results in poorly modelled gas production. Improving Current Simulators for Shale Gas Reservoir Simulation Most reservoir simulators were designed using the instantaneous capillary equilibrium model which is not applicable to modelling unconventional reservoirs. Andrade et al (2010) described how the instantaneous capillary equilibrium model does not apply to shale gas simulation with the use of a simplistic model. Assume we have a water wet conical tube of infinitesimal radius, and infinite water reservoir at pressure Pwr at the small conical end and an infinite gas reservoir at pressure Pgr at the large conical end as depicted in figure 4. When the pressure of the infinite water reservoir is reduced by draining water from it, the rate of flow of the water-gas interface to the left (towards the smaller conical end of the tube) is dictated by the rate at which water can flow through this small conical end. As this occurs, because of the very high gas compressibility, the gas easily expands to occupy this void and attain a new equilibrium level and capillary pressure. In this instance, instantaneous capillary pressure model stays valid. On the other hand, if the gas reservoir were to be depleted extremely fast thereby lowering its pressure the situation will be different from that explained above. In this case, a sudden drop of the pressure in the capillary tube will be experienced. However, as a consequence of its very low compressibility, water in the capillary tube does not instantaneously move to the right of the capillary tube to occupy the void created as experienced in the previous illustration. So, applying the principle of instantaneous capillary pressure, a negative pressure is encountered, which is impractical. As suggested by Barenblatt et al. (2003), fluid redistribution from one steady state to another takes place over a significant amount of time. For this reason, application of instantaneous capillary pressure to shale gas reservoir simulation should be revised in order to have more representative reservoir simulation model results. Permeability Measurement Accurately determining the permeability is a very important step in reservoir characterization. Measuring permeability for shale gas reservoirs is a very challenging process and carrying out the measurement through traditional means for conventional reservoirs will produce results that do not depict the true nature of the reservoir. Also, permeability measurements obtained from two entirely different laboratories may give results that vary from each other by a magnitude of two or three (Passey et al, 2010; Freeman, 2010). Therefore, methods to reliably quantify permeability for shale gas reservoirs have been developed and they include the pulse decay permeability method, and the steady state method. Freeman et al. (2009) noted that under the assumptions of continuum flow, Darcy’s law holds valid. But Javadpour et al. (2007) suggests that the continuum law fails to apply in very tight porous media that possess mean pore throat diameter in similar dimensions as the mean free path of the gas molecules. Aguilera (2010) proposed that viscous flow occurs in rock which contain megaports, macroports, mesoports and microports. On the other hand, nanoports (e.g. shale formations) experience diffusion flow which is a deviation from Darcy’s law and a consequence of gas slippage effect and inertial flow (Rahmanian et al.; 2010). Ignoring these non-Darcy effects can lead to significant errors in the laboratory results when determining permeability and steady state techniques have been discovered to minimize these effects since they cannot be completely eliminated. Effect of Gas Slippage Rushing et al (2004) defined gas slippage as an effect that causes the flow within the pores to deviate from viscous flow to a non-laminar flow. Usually, gas slippage takes place when the dimensions of the pores are within the range of the mean free path of gas molecules which causes the gas molecules to slip when in contact with the rock surface and therefore accelerate. Figure 5 illustrates the phenomenon of slip flow. In effect, it can be expected that a narrower dimension of the mean free path transforms to a

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greater slippage effect. The gas slippage effect was observed by Klinkenberg (1941) and he defined the slippage factor which corrects for the gas slippage effect on permeability measurements. This factor, also known as the ‘Klinkenberg Slippage Factor’ b, is a measure of the gas molecule slippage along the pore walls at reduced pressures. Mathematically,

∞ 1 …………………………………………………………………………….…………….(1) Where is the apparent permeability and ∞ is the intrinsic permeability at infinite pressure. Klinkenberg made an assumption which is still widely acknowledged that at very high pressures, gas and liquid behaviour would be similar and as a consequence of this, there will be no slippage effect. The equation 1 shows that a plot of apparent permeability against the inverse of pressure gives a straight line having an intercept equal to the intrinsic permeability and a slope of b. Effect of Inertial Flow Rushing et al (2004) suggests that inertial flow is usually experienced at high flow rates. It occurs when an increase in pressure is experienced without any increase in flow rate. The pressure rise causes the gas to travel at a faster rate within the nanopore space but decelerates when it approaches larger pore spaces. One reason the effective flow rate remains constant is because of the gas deceleration within the larger pores which also slows down approaching gas molecules. Another reason for this is within the tighter pores where a velocity gain is occurs, a viscous shearing effect may be experienced and results in energy loss through heat, thereby maintaining constant velocity. Previous experimental works carried out on inertial flow have referred to the flow equation attributed to Forchheimer (1901);

………………………………………………………………………………….…(5) The equation 5 denotes the general form of the Darcy equation. The first parameter on the right hand side of the equation represents viscous flow and dominates at low gas velocities usually in megaports, macroports, mesoports and microports. The second parameter on the right hand side of the equation is a consequence of inertial forces at work and dominates at higher velocities where viscous forces become less dominant in the rock matrix which consists of nanoports. From the equation, when 0, the equation reverts to Darcy’s law for viscous flow. Steady State Method of Estimating Permeability Rushing et al. (2004) showed that the steady state method of measuring permeability obtained more reliable results than the unsteady state method. It was observed that the unsteady state method consistently considerably overestimated Klinkenberg corrected permeability values for very tight formations by a substantial magnitude as depicted in figure 6. Before making measurements, the cores were cleaned with chloroform-methanol solution using the Dean Stark extraction process and specially dried in a humidity-controlled environment to avoid damage to the clay in the sample. Rushing et al (2004) carried out measurements with a hydrostatic-type test cell and Nitrogen used as the flowing fluid since due to the very tight nature of the samples, liquids like mercury are inappropriate for permeability measurement. Results were obtained for constant backpressures of between 0 and 200 psig with a net over-burden pressure of 800 psig relative to the core pressure all through the experiment. Figure 7 shows the corrected klinkenberg permeability for a given core at varying backpressures of 0 psi, 46.5 psig, 94.6 psig, 146.4 psig. From figure 7, at a backpressure of 0 psig (i.e. no backpressure), it can be observed that the permeability results obtained deviates from when back pressures are applied. The reason for this is a consequence of visco-inertial forces and gas slippage which both have an inverse relationship with the applied backpressure. Also plotting a graph of the slippage-corrected Darcy function

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against the mass flow rate as depicted in figures 8-10, the upward deviation of the points on the graph is a result of non-Darcy effects and this deviation reduces as the backpressure is increased. At 146.4 psig, it was observed that the visco-inertial forces were substantially reduced as seen in figure 10. It should be acknowledged that when a gas phase is used for permeability measurement of tight rock samples, the effect of the visco-inertial forces due to non-Darcy flow can reduced to a minimum (by the application of a backpressure) but in the practical sense, cannot be entirely eliminated which is another challenge in characterizing shale gas reservoirs. Other methods were used to determine the intrinsic permeability which are beyond the scope of this paper. Pulse Decay Permeability The pulse decay method was originally developed for measuring permeability in tight rocks and synthetic materials. In this method, permeability data for a large number of samples is compiled to give a frequency distribution. A histogram is plotted from the frequency distribution which gives an insight into the permeability distribution of the reservoir. A clearer picture of the permeability distribution may be obtained by also plotting a cumulative frequency curve. Javadpour et al. (2007) obtained permeability data from 9 reservoirs totalling 152 samples. Figure 11a shows the permeability distribution on a frequency vs permeability plot while Figure 11b shows a cumulative frequency distribution of the measured permeability of the 152 measured samples. From the cumulative frequency curve, we can infer that 90% of the measured permeability data is below 150 nanoDarcies. Water Saturation In characterizing either conventional or unconventional reservoirs, the water saturation is a very important parameter which has to be determined. Estimating the water saturation for an unconventional reservoir could be quite challenging and prone to errors. The Dean-Stark extraction and retort methods are popular methods for estimating the water saturation for conventional and unconventional reservoirs. The Dean-Stark method is a procedure that consists of raising the temperature of a solvent (the solvent may be miscible or immiscible with water) to the boiling point of water in an attempt to separate the water from the sample by evaporation. The evaporated water is condensed and measured. Two methods of the Dean-Stark extraction exist and they are the high temperature and low temperature methods, but they are known to obtain contrasting results possibly because of a variation in properties since both methods require the use of different solvents. For best results, the high and low temperature measurements of the water saturation should be carried and the obtained results compared with outliers carefully determined. The high temperature method has the merit of no difficulty in the estimation of the water yield since water and toluene are immiscible but has a major drawback where the water saturation could seem higher than it actually is because of clay dehydration. Primary sources of error in this method are during core recovery and preservation, where between coring and preservation, some water saturation may be lost (Clarkson et al; 2011). The retort method makes use of crushed core samples and heated to up to about 650oC to evaporate the liquids presents (water and possibly oil). The evaporated fluid is condensed and measured the same way as the Dean-Stark method. Other smaller samples from the core are examined to estimate the gas saturation by high pressure mercury injection (up to 1000psi) where the mercury occupies the pores where the gas previously occupied. The summation of the volume occupied by the fluids is the total pore volume. In this method, errors may occur when different samples are used for mercury injection and retort, this is because the assumption that the different samples being used are assumed to be entirely the same which may not be the case (Clarkson et al; 2011). Currently, there is no standard method of measuring water saturation for shale gas reservoirs where compared water saturation for shale gas reservoirs from the above methods have been found to show significant variations (Clarkson et al; 2011, Sondergeld et al; 2010a) and poor reproducibility of results. Another method that is currently being developed is the Lab base NMR which has been successfully used to estimate water saturation in coal and shale. Results obtained here are promising and it is expected

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replace the above methods for estimating the water saturation in the future (Clarkson et al; 2011). Capillary Pressure Currently, a gray area still exists in the area of capillary pressure for shale gas reservoirs where at this time, a lot of research is dedicated into studying the subject of capillary pressure for unconventional reservoirs. The tighter the formation, the higher the capillary pressure should be. In unconventional reservoirs the capillary pressure could rise to hundreds or thousands of psi (Holditch, 1979; Cheng, 2010). Fractures created within the reservoir possess very high permeability values (to the order of tens of thousands of md) and therefore have very low capillary pressures where it is practical to assume the capillary pressure of the fractures as zero. Conventional methods of capillary pressure analysis are impractical because of the very low connate water saturation and high capillary pressure obtained in unconventional reservoirs. It is usually recommended to combine more than one method in order to reliably estimate the capillary pressure curves over a range of water saturation when analysing shale gas reservoirs. One approach of capillary pressure measurement involves applying both the high pressure porous plate method and the centrifuge method (which both have an upper limit of 1000psi) with the vapour desorption technique (Clarkson et al; 2011). Methods of determining capillary pressure in shale gas reservoirs are briefly explained below. The Porous Plate Method: This method requires a permeable material with wetting characteristics and a uniform pore size distribution that can withstand high pressures e.g. ceramic or plastic (allows higher displacement pressures). In this method, the specimen is not required to be cleaned before testing giving the advantage of more representative results with intrinsic wettability and other reservoir properties remaining unaltered. Another advantage of this method is it effectively prevents evaporation and therefore maintains constant water saturation, thereby giving more accurate measurements. The primary limitations of this method are that the highest capillary pressure is determined by the smallest pores present where it requires quite some time to reach equilibrium saturation levels (Newsham et al; 2004). The Centrifuge Method: This method forces the mobile sample out of the specimen with the use of a rotational force at graduated speeds. It is a faster way of obtaining the capillary pressure and can also operate at reservoir temperature and pressure. It has a capillary pressure limitation of about 1000 psi and also the problem of liquid evaporation which could result in lower values of computed water saturation (Newsham et al; 2004). The Vapour Desorption Method: Here, the following principles are applied: that the capillary pressure is a function of the vapour pressure and the vapour pressure above a liquid volume is a function of the liquid surface curvature. So, the capillary pressure can be calculated by controlling the relative humidity of the rocks, thereby lowering the vapour pressure. This is achieved by applying humidity chambers where the relative humidity (and saturation) of the sample is controlled with the use of different salt concentrations in a liquid solution. This method has the advantage of achieving very high capillary pressures well above 10,000 psi at water saturations below 5%. At high water saturations above 95%, the reliability of this method subsequently decreases (Newsham et al; 2004). Relative Permeability The relative permeability of shale gas reservoirs is usually affected by the injected water during the hydraulic fracturing process with the invaded zone (fractures) having a different set of relative permeability curves from the matrix as shown in Figure 12. Initially at the start of production after a hydraulic fracturing process, the produced water has a high salinity but this quickly tapers down during the production process, which denotes that the saline formation fluid remains immobile while the injected water during hydraulic fracturing possesses a higher mobility (Alex Novlesky et al; 2011). The mobility of the gas phase is affected by the wetting phase (water) saturation and this is obtained through relative

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permeability measurement. Usually, in shale gas reservoirs, measuring relative permeability also comes with its challenges where steady-state and non steady-state techniques have been developed but they also have their setbacks (Clarkson et al; 2011). Rushing et al (2003) suggested that primary challenges encountered during relative permeability measurements for shale gas reservoirs include effects of non-Darcy flow which should be taken note of and correcting for this effect is quite a difficult task where errors may be avoided by paying close attention to the temperature and saturation. Clarkson et al (2011) experimentally showed that in high permeability cores, gas permeability is strongly affected by water saturation in comparison to low permeability samples which may lead to adverse effects on the gas permeability especially after a hydraulic fracture in the form of a water block. Advancememts in Shale Gas Exploration Although the exploration for shale gas has gained popularity among E&P companies, various challenges still exist which have been previously discussed. To economically exploit shale gas reservoirs, major progress has been achieved which include hydraulic fracturing and micro-seismic mapping. The subjects of hydraulic fracturing and micro-seismic mapping have been widely discussed in literature and these technologies have led to considerable improvements in shale gas exploration and exploitation. Hydraulic Fracturing For economic exploitation of ultra-low permeability shale gas reservoirs, multi-fractured horizontal wells have become the standard practice. This is usually achieved by pumping proppant with a conveying fluid into the formation usually at a high pressure until the formation fracture pressure is exceeded. A fracture is thus created which is roughly perpendicular to the horizontal wellbore and it is practical to assume the fracture is equal on opposite sides of the wellbore (which is not usually the case). The length of the fracture on one side of the wellbore is usually referred to as the fracture half length, figure 13 shows a schematic of a hydraulic fracture. Usually, in ductile shale formations, the encountered fracturing pressure is usually extremely high because the shale formation usually deforms before ultimately fracturing and this may result in the creation of an inefficient fracture network. On the other hand, in brittle shale formations, very huge pressures are not usually required before very efficient fracture networks are created, and these formations are usually preferred. The reason for this is the Poisson Ratio which is an indicator of the quartz-clay ratio, where a high Poisson Ratio (low quartz-clay ratio) indicates a ductile formation and a low PR indicates a brittle formation. A high quartz-clay ratio is an indication of a higher porosity and lower fracture pressures (Norton et al, 2010, Miller et al, 2007). The technology of hydraulic fracturing has successfully proven to be a valid way of converting previously thought uneconomical shale gas reservoirs to highly economical projects where permeabilities in the order of thousands of millidarcies can be achieved from reservoirs as impermeable as concrete. Also, hydraulic fracturing may reactivate existent natural fractures within the reservoir to further improve production where the size of the fracture programme is proportional to the quantity of proppant used. The tonnage of the proppant has to be optimized because an extremely large hydraulic fracture may be detrimental to the project economics where the law of diminishing returns begins to set-in aside from considering the possibility of larger hydraulic fractures breaking into the water zone of the reservoir. As a result of this and other factors, a large number of smaller hydraulic fractures are preferred to simply a few large ones. Shale gas reservoirs are usually clay rich and when they are hydraulically fractured, the possibility of formation damage by clay particle migration, clay swelling and fluid retention exists where the gas relative permeability may be reduced when conventional water-based fracturing fluids are used. Figure 14 shows how the gas relative permeability is adversely affected by a rise in the water saturation beyond the connate water saturation. The very high capillary forces which is a characteristic of shale gas reservoirs cause a substantial volume of the fracturing fluid to be retained as a result of capillary imbibition. This causes a region of high water

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saturation to be created around the fracture with a direct effect on gas mobility which may result in a water block as observed in the figure above. Problems of capillary fluid retention and clay swelling can be reduced by the use of CO2 fluids for fracturing the reservoir (Gupta; 2009, Mazza; 1997). The CO2 foam minimizes fluid retention by substantially reducing the interfacial tension of water which greatly improves the ability of the formation to return to treatment fluid to the surface. Figure 15 shows how the interfacial tension of water is substantially reduced by the addition of CO2. To minimize clay swelling, additives (e.g methanol) could be added to the CO2 foam fracturing fluid (Friehauf et al; 2009). Also, a faster clean-up of the well can be achieved when CO2 fluids are used in fracturing the reservoir (Slatter et al; 1986). Therefore, the current methods of creating hydraulic fractures in shale gas reservoirs can be improved by the use of slick water combined with 30% CO2 as fracture fluids which will result in improved recovery of treatment fluid and thereby results in improved production. Micro-seismic for the Study of Hydraulic Fractures When shale gas reservoirs are stimulated, the hydraulic fractures created in the subsurface may be difficult to predict and there are usually very huge challenges and uncertainties in characterizing such reservoirs with these fractures present. The application of micro-seismic fracture mapping to shale gas reservoirs has gone a long way to improve our understanding of hydraulic fracture propagation in the subsurface (Cipolla et al, 2010). Without a reliable knowledge of the extent and height of the hydraulic fracture, it would be a daunting task to obtain a reliable history match. To minimize these uncertainties, the application of micro-seismic in hydraulic fracture characterization has proven to be an invaluable tool since a surprising variation usually exists in fracture growth which can range from comparatively simple fractures to very complex fracture networks. Figure 16 shows an illustration of different fracture geometries and a complex fracture is seen on the micro-seismic map. Micro-seismic plays a very important role in hydraulic fracturing processes where it is applied in real-time fracture monitoring during proppant injection, it comes of use where the treatment can be monitored and stopped to prevent the fracture growing into the water zone. Also, the synthesis of reservoir simulation with micro-seismic data helps remarkably improve hydraulic fracture treatment designs which helps optimize the fracture network size and complexity. The principle of micro-seismic is discussed elsewhere in literature in Cipolla et al (2010). Micro-seismic mapping is a technology that derives its method from earthquake seismological principles and a detailed procedure that comprises of sensing, locating and processing of infinitesimal seismic events induced by the fracture process (Cipolla et al, 2010; Albright et al, 1982). Figure 17 shows an illustration of how micro-seismic mapping is achieved. The distance of the fracture is determined by determining the difference in the arrival times of the P-wave and S-wave of a micro-seismic event while the depth of each event is obtained by determining the time the waves arrive on multiple sensors as seen in the figure below. The orientation of the each seismic event is obtained by the polarization of the wave. Usually, a vertical offset well is drilled between two wells to undergo hydraulic fracturing at an approximate distance of 1000-3000ft from each well. Evaluating the performance of conventional reservoirs is the main objective of exploration and appraisal wells while the appraisal of unconventional reservoirs is based on completion effectiveness and hydraulic fracture performance, the ability to quickly gain knowledge in this area is very important for the commercial success of the project (Cipolla et al; 2010). In shale gas plays where micro-seismic mapping is applied, fewer wells are required to be drilled for the appraisal of the field because of the substantially reliable data obtained unlike plays where it is absent and this substantially reduces capital expenditure. Also, the knowledge gained from the micro-seismic data about the performance of the hydraulic fracture will help improve further fracture treatment design e.g. modification of pump pressure, pump rate etc (Fazelipour, 2011). The technology of micro-seismic mapping is very popular in North America (where the technology is readily available) but is often over-looked in other continents because of the impression that it is very expensive ignoring the fact that well productivity can be ramped up 5- to 10- fold (Cipolla

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et al; 2010). The increased productivity easily offsets the costs incurred as a consequence of the application of micro-seismic mapping technology which also minimizes the uncertainty in fracture modelling, reducing the time required to obtain a more reliable history match and production forecast. Also, it is imperative to know that increased utility can be obtained from microseismic data when it is combined with geological and 3D seismic data, logs, geomechanical modelling, etc (Cipolla et al; 2010). Figure 18 illustrates how the use of microseismic mapping in the field study can help substantially improve the learning curve, where the inclusion of microseismic early in a field study could increase the potential gas production and subsequently revenue by a factor of 2. Micro-seismic mapping has many applications in the exploration of unconventional reservoirs and these include;

• Determining the length, height and orientation of fractures, • Estimating the location of the fractures, • Determining the complexity of the fracture network, • Real time analysis of fracture growth during a hydraulic fracturing process.

Case History I: Integrating MicroSeismic Mapping with Geological and Geophysical Data As depicted in figure 19, the horizontal lateral was drilled in the direction of the minimum horizontal stress (σ ), and this allows transverse hydraulic fractures where four fracture treatments each consisting of 25,000 bbls of slickwater and 430,000 lbs of sand. As shown on the microseismic map, from the advanced sonic log, the difference between the maximum and minimum horizontal stress is estimated to be largest at the toe of the lateral which leads to a substantial difference in fracture stages 3 and 4 where complex fractures were created in contrast to stages 1 and 2 which are planar fractures (Cipolla et al, 2010c). Integrating microseismic data with 3D seismic and geophysical data provided deeper insights into the structure of the Barnett shale. 3D seismic data showed that the natural fracture orientation in the heel section is perpendicular to the hydraulic fracture propagation while the natural fractures in the toe section are parallel to the hydraulic fractures and therefore, a significant difference is observed in the hydraulic fractures towards the toes and closer to the heel. Case History II: The Application of Real-Time Microseismic Mapping to Avoid Geo-Hazards and Improve Stimulation Effectiveness in a Barnett Shale Horizontal Well. Cipolla et al (2010c) documented how geo-hazards can be avoided during hydraulic fracturing. The most common geo-hazards during hydraulic fracturing are faults which can be identified with their magnitude and location on a microseismic map for different North American basins as depicted in figure 20 where the largest magnitudes depict fault activation. An illustration of how fault activation is seen on a microseismic map is shown in the figure 21. The figure contains a horizontal well with four hydraulic fractures, the size of each microseismic event is proportional to its magnitude as shown. Stages 3 and 4 (light blue and red events) are located within the reservoir and do not encounter any fault. While the microseismic events in the first two stages (dark blue and yellow events) possess large magnitudes which led to a fault activation as shown in the figure. In this example, the real-time microseismic was not applied to prevent the hydraulic fracture from causing fault activation, the subsequent case history from Waters et al. (2009b) and Cipolla et al. (2010c) give a field example of this scenario. Using real-time microseismic mapping, the pump rate, pressure, proppant concentration and other parameters can be altered at any time during the hydraulic fracturing process to enable complete control of the hydraulic fracture. As depicted in figure 22(a), geophones are used to capture microseismic events in real-time. Software which integrates multi-disciplinary data is used along with visualization software for viewing the fracture propagation in the sub-surface which gives complete control of the hydraulic fracture process. Preferential points for locating stages for the hydraulic fracture are picked using a

SPE 160869 11

‘sonic-derived, anisotropic mechanical properties stress model’ which improves the possibility of creating a complex hydraulic fracture model. After the first stage of the hydraulic fracture process (Figure 22(a), depicted by yellow events), it can be observed on the microseismic map that the fractures propagated towards the fault. In this case, the pump rate was kept very low to avoid creating a fault of great magnitude in height which could break into the water bearing formation. The microseismic activity was visualized on a three-Dimensional software to ensure the height of the fracture conformed to the design with increased confidence while the job continued. At the commencement of Stage 2 of the hydraulic fracture process (depicted by the light purple events in Figure 22(b)), the fracture was propagating into the geo-hazard with the size of each event proportional to its magnitude. With the data gathered, the microseismic events had to be diverted back to the reservoir rock away from the potential geo-hazard with the use of ‘fibre diversion packages’ included in the pump programme. This fibre diversion package bridges the fractures that have connected to fractures created during the stage 1 hydraulic fracture program, concentrating the newly created fracture within the reservoir zone thereby preventing the fractures from extending into the fault zone (depicted by the dark purple events). For the third stage of the hydraulic fracture programme (depicted in bluish-green events in figure 23), it can be deduced that a lower stress regime exists here which results in a very complex fracture network being created, entirely different from the induced fractures in the previous two stages. Production Forecasting Many E&P companies find it challenging to reliably estimate the ultimate recovery from the stimulated reservoir volume and the economic production life of shale gas wells which has become a subject of interest in recent times. Obtaining these estimates through reservoir simulation is one approach but due to the inherent uncertainties that exist within the reservoir itself, another method has to be sought to confirm the result from actual production data. The application of the decline curve analysis is a widely accepted approach in studying conventional reservoirs but still undergoing rigorous development in unconventional reservoirs. In unconventional reservoirs, with the available production data, decline curve analysis is used to estimate the production life on a well by well basis and also obtain the recoverable reserves from the stimulated reservoir volume as opposed to conventional reservoirs where it can be carried out on both a well scale and a field scale (Strickland et al; 2011). As seen in figure 24, the flow in hydraulically fractured shale gas wells are usually in three dominant flow regimes, they are;

• An early time flow period where the flow is from the hydraulic fractures; • An intermediate time period when the flow is from the matrix and the fractures; • A late time period when the flow is predominantly from the matrix.

Arps (or hyperbolic) decline curve analysis is readily available in commercial software and can be used to analyse production data for shale gas reservoirs but this has to be done with caution. This is because of the ultra-low permeability of shale gas reservoirs and so, results in a very long transient flow period (up to a few years in many cases). If the Arps equation is used in the transient flow period, there is a possibility of over-estimating the reserves by a factor of 2 or 3 due to a high b factor greater than 1 as opposed to a hyperbolic exponent of between 0.0 and 1.0 for boundary dominated flow (Strickland et al, 2010; Arps, 1945). Lee and Sidle (2010) also pointed out that due to problems associated with the Arps equation, the United States Securities and Exchange Commission does not identify it as a ‘’sufficiently reliable technology’’ for the reporting of reserves. This does not in any way discountenance results obtained by the Arps equation when the flow is boundary dominated period where obtained forecasts are usually reliable. Also, a recent development in decline curve analysis which is beginning to gain wide acceptance is the

12 SPE 160869

Power law exponential method also called the stretched exponential method. Though, it is yet to be deployed in commercial software, it has been show that it performs better and requires less data than the hyperbolic analysis (Strickland et al; 2011). The Arps Hyperbolic Equation It has been shown that when the decline rate reduces, the Arps equation can be used to reliably forecast the production from a shale gas reservoir. The Arps’ rate-time relations are outlined below (Arps 1945); Arps hyperbolic equation (0<b<1): ..……………………………...……….(6)

Where Di and qi denote the initial decline rate and initial production rate respectively and b represents the decline exponent. The value of the decline exponent determines which form the Arps equation takes with each form having a different shape on Cartesian and Semi-log graphs. The Arps hyperbolic equation is the general form of the Arps equation where the other forms of the equation can be obtained from it as stated below; Arps exponential equation (b=0): exp ……………………………………………(7) Arps harmonic equation (b=1):

..…………………………...……………...(8)

The Arps equation makes the following assumptions (Rushing et al, 2007; Lee et al, 1996; Tarek et al, 2005) (reference on page 6 of SPE 109625);

• The extrapolation of the best-fit curve for the current or historical production is accurate for future production trends;

• No major alteration in the current operating conditions or field development that might affect the curve fit and the future forecast;

• The bottom hole flowing pressure of the well is constant; • The well is in a boundary dominated flow. • The well is flowing at or near capacity

As earlier stated, the use of the Arps equation is only valid in the study of unconventional reservoirs after the reservoir has reached the boundary dominated flow period. The Power-Law Exponential Function A detailed examination of the Power-Law exponential function for production forecasting was substantially discussed by Ilk et al (2008a, 2008b). The fundamentals of the power-law exponential function are the ‘loss-ratio’ and the ‘loss-ratio derivative’ defined below;

/

(The Loss-Ratio) .…………………………………………………………………….…. (9)

/

(The Loss-Ratio Derivative) .………..………………………………...…. (10) Studies carried out have indicated that the D-parameter for a hydraulic fractured ultra-low permeability is best defined by the power-law function, given as;

∞ …..…………………………………………………………………………….. (11) From equation 10, it can be observed that the b-parameter is a function of the D-parameter, this leads us to believe that the b-parameter is also a function of time, substituting Eq. 11 into Eq. 10, we get;

SPE 160869 13

∞

……………………………..……………………………… (12) The equation above gives us the mathematical relation of how the b-parameter varies with time. Now, substituting Eq. 11 in Eq. 10, the power-law exponential equation is obtained below;

∞ …………………………………………..………………………………...(13) The power-law exponential equation can also be written in the form (Ilk et al; 2008a);

exp ∞ ……………………...………………….……………………………….(14) The Stretched Exponential Function The stretched exponential function is another approach to production forecasting, a derivative from the power-law function. Here, the decline constant at infinite time, ∞ is assumed to be zero and after mathematical manipulation, the D-parameter and flow rate at a given time reduces to the form given below (Ilk et al; 2010);

.………………………………………………………..…………………………….... (15)

exp ………………………………………………….…………………………...…(16) Case History I: A Small Waterfrac Gas Well I This case history is adapted from Ilk et al. (2008). The hydraulically fractured well was completed with 20/40 proppant size. This study concentrates on applying the hyperbolic rate decline relation and the power-law exponential to forecast future gas production. In figure 25, it can be observed that the unstable rates are most likely affected by liquid loading towards the end of the data set. Again, increasing rates at the early time can be deduced as a consequence of well clean-up. The figure shows a ‘q-D-b’ plot where boundary dominated flow begins to occur at about 800 days. To perform a production forecast, the harmonic form (b=1) of the hyperbolic equation is used and the results obtained does not follow the data trend at early time and is shown to be very optimistic. The D-parameter (when ∞ 0 and ∞ 0 in eq. 11&14) was obtained for the stretched exponential function and the power-law exponential funtion respectively. The result obtained showed that the power law exponential model ( ∞ 0) gave a reasonable match thereby, giving a closer relationship with the rate data.

Model or qi (MSCFD)

or Di (D-1)

∞ (D-1)

n (dimensionless)

Gp,max (BSCF)

Power-Law Exponential ( ∞ 0)

1.7x104 0.33 3.0x10-5 0.3 5.4

Stretched Exponential ( ∞ 0)

1.7x104 0.33 0 0.3 6.1

Hyperbolic (b=1)

6000 4.0x10-3 N/A N/A 26.0

Table 1: Power-Law Exponential and the Hyperbolic Model Estimate of the Ultimate Recovery.

From table 1, it can be observed that the hyperbolic function substantially over-estimates the final recovery. Case History II: A Small Waterfrac Well II This case history is adapted from Ilk et al. (2008). The well in this case is different from the well in the previous example where a 40/70 proppant size was used in the hydraulic fracture of this well. Figure 26

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shows a ‘q-D-b’ plot where liquid loading can be observed in the gas rate data. From the rate data trend, a power-law trend can easily be observed. First, the hyperbolic decline extrapolation is obtained applying the harmonic relation (b=1) and also using an estimate of the D-parameter. As observed in this case, the early part of the rate data is not matched by the hyperbolic decline curve where it also gives very optimistic production forecast when compared to the Power-law exponential function as shown in table 2. From the figure, the stretched exponential function (where ∞ 0) and the power law exponential function (where ∞ 0) represent a good match with the rate data from the early time. The stretched exponential function gives a higher estimate of the ultimate gas produced where the only difference between both methods is the deviation in production forecast at the end of the available rate data unlike the hyperbolic function which does not correlate with the rate data at the early time.

Model or qi (MSCFD)

or Di (D-1)

∞ (D-1)

n (dimensionless)

Gp,max (BSCF)

Power-Law Exponential ( ∞ 0)

3.2x104 1.24 1.5x10-4 0.17 2.3

Stretched Exponential ( ∞ 0)

3.2x104 1.24 0 0.17 3.8

Hyperbolic (b=1)

3600 6.0x10-3 N/A N/A 10.0

Table 2: Power-Law Exponential and the Hyperbolic Model Estimate of the Ultimate Recovery.

Discussion The exploration of shale gas reservoirs is still in its infancy when compared with conventional reservoirs therefore, so many challenges still remain to be overcome. No standard procedure exists for a number of the current measurement techniques used in practice to determine physical reservoir parameters for shale gas reservoirs e.g. permeability, water saturation etc where techniques used in conventional reservoirs are applied. Therefore, results obtained using one approach may significantly vary when another method is used which raises the question of the reliability of these methods. As experienced is gained in the subject of shale gas reservoirs, reliable techniques in determining these parameters will be developed and possibly adopted as industry standard. Commercial simulation software (e.g. Eclipse and CMG) now have dedicated modules for simulating shale gas and this improves the accuracy in modelling shale gas reservoirs. Substantial development has occurred in modelling shale gas reservoirs but some challenges are still being encountered most especially in the subject of instantaneous capillary pressure where negative pressures may be encountered in the numerical simulation of shale gas reservoirs which is impractical. Also, significant progress has been made in hydraulic fracturing where thousands of horizontal wells are drilled and fractured on an annual basis. This has subsequently helped boost production and recovery in shale gas reservoirs now make exploring for shale gas an economical project. The productive capacity of hydraulic fractures could be improved by creating the fractures with high concentration CO2 foam as treatment fluid which results in improved recovery of treatment fluid. This could turn out to be very expensive since several fractures will be created which significantly increases the project cost. The possibility of using slick water with lower CO2 concentration comes as a valid economic alternative. The subject of reliably understanding the subsurface dynamics and quantifying the fracture distribution as a result of hydraulic fracturing is still being studied with the help of micro-seismic mapping where substantial progress has been achieved with this technology. Though, carrying out micro-seismic mapping is currently a very expensive project where the cost of drilling an offset well substantially increases this cost. Cipolla et al (2010) discussed how E&P companies that intend to apply this

SPE 160869 15

technology can substantially reduce its cost of implementation without having to drill an offset well, though, it should be pointed out that this method is quite subjective. Predictive techniques for production forecasting of shale gas reservoirs involves the application of decline curve analysis which is another challenging area. This is because the methods used for conventional reservoirs have been shown to be inadequate for shale gas reservoirs and new techniques are currently been developed and tested to reliably predict the future production profile of these reservoirs (e.g the power-law exponential and the stretched exponential functions). Since we have a couple of years of production data for shale gas reservoirs which is used to forecast production for up to 50 years or more, current results have been promising but the oil and gas industry may have to wait a for a few more years to ascertain the accuracy and reliability of these newly developed and subsequent production forecasting models. Conclusion and Recommendation

• The application of instantaneous capillary pressure in reservoir simulation software is only valid in conventional reservoirs and should be revised in the simulation of unconventional reservoirs since we have seen how inadequate it is for the numerical simulation of shale gas reservoirs.

• In the determination of the physical properties of shale gas reservoirs, to obtain the capillary pressure, a combination of more than one technique will continuously be used due to the low pressure limitations of existing methods (e.g centrifuge method, porous plate method) until a reliable method for measuring over a reasonably wide spectrum of capillary pressures is developed. Also, in estimating the water saturation of shale gas reservoirs, the current existent methods (i.e. Dean-Stark and retort methods) give conflicting results when compared. But currently, research is in place in the use of laboratory based NMR in determining the water saturation for unconventional reservoirs and so far, the results have been promising.

• Determining the permeability of shale gas reservoirs using the unsteady state techniques consistently over-estimates the permeability values unlike the steady state technique. While determining the permeability using a gas phase, non-Darcy effects can be minimized by the application of a backpressure and this improves the accuracy of the permeability results.

• Slick water with about 30% CO2 concentration may be applied as treatment fluid and this reduces the cost of CO2 fracture treatment and also improves the ability of the formation to return treatment water to the surface thereby improving productivity.

• The use of micro-seismic mapping is very important in gaining insightful knowledge of the induced fracture network. It also helps reduce the simulation time in trying to ascertain the fracture distribution during the history matching process and also from previous works carried out, improvements could be implemented in further hydraulic fracture programmes to be carried out from knowledge gained here which could help increase production. In essence, micro-seismic mapping can help accelerate the learning curve in the field study of an unconventional reservoir. It is recommended that more E&P companies worldwide should adopt this technology for subsurface monitoring when carrying out hydraulic fracturing.

• The predictive models for forecasting production for conventional reservoirs (i.e. Arps equation) may over-estimate the reserves for shale gas reservoirs if improperly used. The stretched exponential function and the power law exponential function give a better match to the rate data and therefore a better production forecast. From the case studies, in forecasting production for shale gas reservoirs, the power-law exponential function gives the most reliable match.

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Acknowledgement The authors will like express their profound gratitude to Heriot-Watt University and the SPE data library for providing the necessary materials for the successful completion of this paper.

SPE 160869 17

Nomenclature - Arps hyperbolic decline exponent

- Loss Ratio

- Decline constant at ‘infinite time’ at 1 time unit [i.e., 1

∞ Decline constant at ‘infinite time’ [i.e., ∞

Decline constant [i.e.,

- Effective decline rate %/year

- Pore Diameter

- Knudsen Number

- Boltzmann’s constant

- Time ‘exponent’

- Pressure

- Permeability

PR – Poisson Ratio

- Initial fluid rate

- Fluid rate at a given time.

- Time

- Temperature (K)

- Fluid velocity

Greek Symbols

- Inertial Resistance Coefficient

- Collision Diameter

- Mean free path of molecule

- Fluid Viscosity

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References Albright, J.N., Pearson, C.F. 1982. Acoustic Emissions as a Tool for Hydraulic Fracture Location: Experience at the Fenton Hill Hot Dry Rock Site. SPEJ, Vol. 22, pp. 523-530, August 2008. Arps, J.J. 1945. Analysis of Decline curves. Trans. AIME 160: 228-247 Aguilera, R., 2010. Flow Units: From Conventional to Tight Gas to Shale Gas Reservoirs. SPE Paper No. 132845. Presented at the Trinidad and Tobago Energy Resources Conference held in Port of Spain, Trinidad, 27-30 June 2010. Andrade, J., Civan, F., Devegowda, D., Sigal, R., 2010. Accurate Simulation of Shale Gas Reservoirs. SPE Paper No. 135564. Presented at the SPE Annual Technical Conference and Exhibition held in Florence, Italy, 19-22 September 2010. Barenblatt, G.I., Patzek, T.W., Silin, D.B. 2003. The Mathematical Model of Non-Equilibrium Effects in Water-Oil Displacement. SPEJ, Vol. 8, No. 4: pp 409-416. SPE Paper No. 87329-PA. Biglarbigi, K., Crawford, P., Carolus, M., and Dean, C., 2010. Rethinking World Oil-Shale Resource Estimates. SPE Paper No. 135433. Presented at the SPE Annual Technical Conference and Exhibition held in Florence, Italy, 19-22 September 2010. Biswas, D., 2011. Shale Gas Predictive Model (SGPM) – An Alternative Approach to Predict Shale Gas Production. SPE Paper No. 148491. Presented at the Eastern Regional Meeting held in Columbus, Ohio, USA, 17-19 August 2011. Cheng, Y., 2010. Impact of Water Dynamics in Fractures on the Performance of Hydraulically Fractured Wells in Gas Shale Reservoirs. SPE Paper No. 127863. Presented at the SPE International Symposium and Exhibition on Formation Damage Control held in Lafayette, Louisiana, USA, 10-12 February 2010. Cipolla, C.L., Lolon, E.P., 2010. Reservoir Modelling in Shale Gas Reservoirs. SPE Paper No. 125530. Presented at the SPE Eastern Regional meeting, Charleston, West Virginia, USA, 23-25 September 2009, Peer approved 1 March, 2010. Cipolla, C., Mack, C., Maxwell, S., 2010. Reducing Exploration and Appraisal Risk in Low-Permeability Reservoirs Using Microseismic Fracture Mapping. SPE Paper No. 137437. Presented at the Canadian Unconventional Resources & International Petroleum Conference held in Calgary, Alberta, Canada, 19-21 October 2010. Cipolla, C., Mack, M., Maxwell, S. 2010. Reducing Exploration and Appraisal Risk in Low-Permeability Reservoirs Using Microseismic Fracture Mapping – Part 2. SPE Paper 138103. Presented at the SPE Latin American & Caribbean Petroleum Engineering Conference held in Lima, Peru, 1-3 December 2010. Clarkson, C.R., Jensen, J.L., Blasingame, T.A. 2011. Reservoir Engineering for Unconventional Reservoirs: What Do We Have to Consider. SPE Paper No. 145080. Presented at the SPE North American Unconventional Gas Conference and Exhibition held in The Woodlands, Texas, USA, 14-16 June 2011. Fazelipour, W., 2010. Innovative Simulation Techniques to History Match Horizontal Wells in Shale Gas Reservoirs. SPE Paper No. 139114. Presented at the SPE Eastern Regional Conference held in Morgantown, West Virginia, USAs, 12-14 October 2010. Fazelipour, W., 2011. Innovative Reservoir Modelling and Simulation of Unconventional Shale Gas Reservoirs Powered by Microseismic Data. SPE Paper No. 141877. Presented at the SPE Middle East Unconventional Gas Conference and Exhibition held in Muscat, Oman, 31 January – 2 February 2011. Freeman, C.M., Moridis, G., Ilk, D., Blasingame, T.A. 2009. A Numerical Study of Performance for

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Tight Gas and Shale Gas Reservoir Systems. SPE 124961. Presented at the 2009 SPE Annual Technical Conference and Exhibition held in New Orleans, Louisiana, USA, 4-7 October 2009. Freeman, C.M., 2010. A Numerical Study of Microscale Flow Behavior in Tight Gas and Shale Gas Reservoir Systems. SPE 141125-STU. Presented at the SPE International Student Paper Contest at the SPE Annual Technical Conference and Exhibition held in Florence, Italy, 19-22 September 2010. Friehauf, K.E., Sharma, M.M. 2009. Fluid Selection for Energized Hydraulic Fractures. Presented at the 2009 SPE Annual Technical Conference and Exhibition held in New Orleans, Louisiana, USA, 4-7 October. Gupta D.V.S. 2009. Presented at the 2009 SPE Hydraulic Fracturing Technology Conference held in The Woodlands, Texas, USA, 19-21 January 2009. Holditch, S.A. 1979. Factors Affecting Water Blocking and gas Flow from Hydraulically Fractured Gas Wells. JPT 31 (12): 1515-1524. Ilk, D., Rushing, J.A., Blasingame, T.A. 2008a. Estimating Reserves Using the Arps Hyperbolic Rate-Time Relation – Theory, Practice, Pitfalls. Paper CIM 2008-108 Presented at the 59th Annual Technical Meeting of the Petroleum Society, Calgary, Alberta, Canada, 17-19 June. Ilk, D., Perego, A.D., Rushing, J.A., and Blasingame, T.A. 2008b. Exponential vs Hyperbolic Decline in Tight Gas Sands – Understanding the Origin and Implications for Reserve Estimates Using Arps’ Decline Curves. SPE Paper No. 116731. Presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado, 21-24 September 2008. Javadpour, F., Fisher, D., Unsworth, M., 2007. Nanoscale Gas Flow in Shale Gas Sediments. Journal of Canadian Petroleum Technology, October 2007, Volume 46, No. 10. Klinkenberg, L.J. 1941. The Permeability of Porous Media To Liquids And Gases. API, 1941. Kundert, D., Mullen, M. 2009. Proper Evaluation of Shale Gas Reserves Leads to a More Effective Hydraulic Fracture Stimulation. SPE Paper No. 123586. Presented at the SPE Rocky Mountain petroleum Technology Conference held in Dever, Colorado, USA 14-16 April 2009. Lechtenbohmer, S., Altmann, M., Capito, S., Matra, Z., Weindrorf, W., Zittel, W. 2011. Impacts of shale gas and shale oil extraction on the environment and on human health. Lee, J., Sidle, R. 2010. Gas-Reserves Estimation in Resource Plays. SPE Paper No. 130102. Vol. 2, No. 2. October 2010. Lee, W.J., and Wattenbarger, R.A. Decline Curve Analysis of Gas Wells, Chap. 9, in Gas Reservoir Engineering, vol. 5, SPE Textbook Series, Society of Petroleum Engineering, Dallas, TX (1996), pp 214-225. Mazzer, R.L. 1997. Liquid CO2 Improves Fracturing, Hart’s Oil and Gas World. 22 February, 1997. Miller, C., Lewis, R., Bartenhagen, K. 2007. Design and Execution of Horizontal Wells in Gas Shales Using Borehole Images and Geochemical data: AAPG SW Section Convention. SEG Denver 2010 Annual Meeting. Newsham, K.E., Rushing, J.A., Lasswell, P.M., Cox, J.C., Blasingame, T.A., 2004. A Comparative Study of Laboratory Techniques for Measuring Capillary Pressures in Tight Gas Sands. Presented at the SPE Annual Technical Conference and Exhibition held in Houston, Texas, 26-29 September 2004. Norton, M., Hovdebo, W., Cho, D., Maxwell, S. 2010. Surface Seismic to Microseismic: An Integrated Case Study from Exploration to Completion in the Montney Shale of NE British Columbia, Canada. Novlesky, A., Kumar, A., Merkle, S. 2011. Shale Gas Modelling Workflow: From Microseismic to Simulation – A Horn River Case Study. CSUG/SPE Paper No. 148710. Presented at the Canadian

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Unconventional Conference held in Calgary, Alberta, Canada, 15-17 November 2011. Passey, Q.R., Bohacs, K.M., Esch, W.L., Klimentidis, R., and Sinha, S. 2010. From Oil-Prone Source Rock to Gas-Producing Shale Reservoir – Geologic and Petrophysical Characterization of Unconventional Shale-Gas Reservoirs. SPE Paper 131350. Presented at the CPS/SPE International Oil & Gas Conference and Exhibition held in Beijing, China, 8-10 June, 2010. Quin, B., 2007. Numerical Study of Recovery Mechanisms in Tight Gas Recovery. M.S. thesis, The University of Oklahoma, Norman, Oklahoma, USA. Rahmanian, M., Solano, N., Aguilera, R. 2010. Storage and Output Flow From Shale and Tight Gas Reservoirs. SPE Paper 133611. Presented at the SPE Western Regional Meeting held in Anaheim, California, USA, 27-29 May 2010. Rushing, J.A., Newsham, K.E., Fraassen, K.C. 2003. Measurement of the Two-Phase Gas Slippage Phenomenon and its Effect on Gas Relative Permeability in Tight Gas Sands. SPE Paper No. 84297. Presented at the SPE Annual Technical Conference and Exhibition held in Denver, Colorado, USA, 5-8 October 2003. Rushing, J.A., Newsham, K.E., Lasswell, P.M., Cox, J.C., Blasingame, T.A. 2004. Presented at the SPE Annual Technical Conference and Exhibition held in Houston, Texas, USA, 26-29 September 2004. Rushing, J.A., Perego, A.D., Sullivan, R.B., Blasingame, T.A. 2007. Estimating Reserves in Tight Gas Sands at HP/HT Reservoir Conditions: Use and Misuse of an Arps Decline Curve Methodology. SPE Paper No. 109625. Presented at the 2007 SPE Annual Technical Conference and Exhibition held in Anaheim, California, USA, 11-14 November 2007. Slatter, T.D., Rucker, J.R., Crisp, E.L. 1986. Presented at the Unconventional Gas Technology Symposium of the Society of Petroleum Engineers held in Louisville, Kentucky, USA, 18-21 May, 1986. Sondergeld, C.H., Newsham, K.E., Comisky, J.T., Rice, M.C., Rai, C.S. 2010a. Petrophysical Considerations in Evaluating and Producing Shale Gas Resources. SPE Paper No. 131768. Presented at the SPE Unconventional Gas Conference, Pittsburgh, Pennsylvania, 23-25 February 2010. Strickland, R., Purvis, D., Blasingame, T. 2011. Practical Aspects of Reserve Determinations for Shale Gas. SPE Paper No. 144357. Presented at the SPE North American Unconventional Gas Conference and Exhibition held in The Woodlands, Texas, USA, 12-16 June 2011. Tarek, A., McKinney, P.D., 2005. A Textbook on Advanced Reservoir Engineering. Chap. 3, p 3/238. Thomson, J.M, M’Angha, V.O, Anderson, D.M. 2011. Advancements in Shale Gas Production Forecasting – A Marcellus Case Study. SPE Paper No. 144436. Presented at the 2011 SPE Americas Unconventional Gas Conference and Exhibition held in The Woodlands, TX, USA, 14-16 June 2011. Warpinski, N.R. 2009. Integrating Microseismic Monitoring With Well Completions, Reservoir Behaviour, and Rock Mechanics. SPE Paper No. 125239. Presented at the Tight Gas Completions Conference, held in San Antonio, Texas, 15-17 June, 2009.

SPE 160869 21

Figure 1: World Shale Gas Map (Courtesy of NOHOTAIR)

Figure 2: Figure Showing the Impact of Desorbed Gas on Final Production (SPE 125530)

22 SPE 160869

Figure 3: Figure Showing Impact of FBHP on Production of Desorbed Gas (SPE 125530)

Figure 4: Illustration of the Instantaneous Capillary Pressure Problem (SPE 135564)

Figure 5: Figure Showing Gas Flow in Nanopores Where there is Slip Flow (Javadpour et al; 2007)

SPE 160869 23

Figure 6: Figure showing a comparison of Steady State (SS) and Unsteady State (USS)

Klinkenberg-Corrected Permeabilities at Various BackPressures (SPE 89867)

Figure 7: Figure Showing a Comparison of Klinkenberg Plots at Various BackPressures (SPE

89867)

Figure 8: Figure Depicting Slippage-Corrected Darcy Functions Showing Effects of Backpressure

at Backpressure of 0 psig (SPE 89867)

24 SPE 160869

Figure 9: Figure Depicting Slippage-Corrected Darcy Functions Showing Effects of Backpressure

at Backpressure of 46.5 psig (SPE 89867)

Figure 10: Figure Depicting Slippage-Corrected Darcy Functions Showing Effects of Backpressure

at Backpressure of 146.4 psig (SPE 89867)

Figure 11: Frequency Distribution for 152 Shale Gas Permeability Samples for Nine Reservoirs (a) Permeability Distribution (b) Cumulative Frequency Distribution (Javadpour et al; 2007)

SPE 160869 25

Figure 12: Figure Showing Two Sets of Relative Permeability Curves for a Fracture and Matrix System (SPE 127863)

Figure 13: Figure Showing A Hydraulic Fracture Perpendicular to the Horizontal Well-bore; xf is the fracture half-length, ye is the distance between the fracture and the boundary (SPE 140519)

26 SPE 160869

Figure 14: Consequence on Water Imbition on Gas Relative Permeability (SPE 119424)

Figure 15: A Plot Illustrating the Variation of Interfacial Tension in a Water-CO2 System at Varying Temperatures (SPE 15238)

SPE 160869 27

Figure 16: (a) Illustration of Different Fracture Geometries (b) Figure Showing the Complex

Fracture Geometry of the Barnett Shale (SPE 145080)

Figure 17: Figure Showing the Principle of Micro-Seismic Mapping (SPE 137437)

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Figure 18: Illustration of how Microseismic Mapping can Accelerate the Learning Curve in a

Hypothetical Shale-Gas Model (SPE 137437)

Figure 19: Microseismic Events for a Case History (SPE 138103)

Figure 20: Illustration of Fault Activation Using Microseismic Event and Magnitude (Warpinski,

2009)

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Figure 21: An Illustration of Fault Activation (SPE 138103).

Figure 22: (a) Microseismic activity from Well 1, Stage 1 depicting hydraulic fracture Treatment

growth Towards a Fault, (b) Well 1, Stages 1 &2 Microseismic Activity Showing the Effect of Microseismic Monitoring (SPE 138103).

Figure 23: Figure Showing Microseismic events for Stages 1, 2, and 3. Along the wellbore, the red

to blue contrasts implies a low to high formation stress (SPE 138103).

ba

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Figure 24: Matching Parameter of Horizontal Wells (SPE 144357)

Figure 25- Case Study 1: A Log-Log Plot of the Small Waterfrac Gas Well (SPE 116947)

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Figure 26- Case Study II: Log-Log Plot of the Small Waterfracs Well II (SPE 116731)