You must log in to edit PetroWiki. Help with editing
Content of PetroWiki is intended for personal use only and to supplement, not replace, engineering judgment. SPE disclaims any and all liability for your use of such content. More information
Hydraulic fracturing in tight gas reservoirs
The definition of a tight gas reservoir is one that must be successfully fracture treated to produce economic volumes of gas at economic flow rates. In this page, we will discuss a few basic considerations for fracture treatment design and application.
Contents
- 1 Formation mechanical properties
- 2 Post-fracture reservoir evaluation methods
- 3 Transient flow considerations
- 4 Types of models
- 5 Analyzing post-fracture production data
- 6 Post-fracture pressure transient analysis
- 7 Nomenclature
- 8 References
- 9 Noteworthy papers in OnePetro
- 10 External links
- 11 See also
- 12 Category
Formation mechanical properties
Many tight gas reservoirs are thick, layered systems that must be hydraulically fracture treated to produce at commercial gas flow rates. To optimize the completion, it is necessary to understand the mechanical properties of all the layers above, within, and below the gas pay intervals. Basic rock properties such as in-situ stress, Young’s modulus and Poisson’s ratio are needed to design a fracture treatment. The in-situ stress of each rock layer affects how much pressure is required to create and propagate a fracture within the layer. The values of Young’s modulus relate to the stiffness of the rock and help determine the width of the hydraulic fracture. The values of Poisson’s ratio relate to the lateral deformation of the rock when stressed. Poisson’s ratio is a parameter required in several fracture design formulas. The definition of these mechanical properties, the importance of these parameters, and how to determine values for each property are discussed in Hydraulic fracturing
The most important mechanical property is in-situ stress, often called the minimum compressive stress or the fracture closure pressure. When the pressure inside the fracture is greater than the in-situ stress, the fracture is open. When the pressure inside the fracture is less than the in-situ stress, the fracture is closed. We can determine values of in-situ stress using logs, cores, or injection tests. To optimize the completion, it is very important to know the values of in-situ stress in every rock layer.
Candidate selection
The success or failure of a hydraulic fracture treatment often depends on the quality of the candidate well selected for the treatment. Choosing an excellent candidate for stimulation often ensures success, while choosing a poor candidate normally results in economic failure. To select the best candidate for stimulation, the design engineer must consider many variables. The most critical parameters for hydraulic fracturing are formation permeability, the in-situ stress distribution, reservoir fluid viscosity, skin factor, reservoir pressure, reservoir depth, and the condition of the wellbore. The skin factor refers to whether the reservoir is already stimulated or, perhaps, damaged. If the skin factor is positive, the reservoir is damaged and will likely be an excellent candidate for stimulation.
The best candidate wells for hydraulic fracturing treatments in a tight gas reservoir have a substantial volume of OGIP and good barriers to vertical fracture growth above and below the net pay intervals. Such reservoirs have:
- A thick pay zone
- Medium to high pressure
- In-situ stress barriers to minimize vertical height growth
- Substantial areal extent
Tight gas reservoirs that are not good candidates for hydraulic fracturing are those with:
- A small volume of gas in place because of thin reservoirs
- Low reservoir pressure
- Small areal extent
Also, reservoirs that do not have enough clean shale above or below the pay interval to suppress vertical fracture growth are considered to be poor candidates. Reservoirs with extremely low permeability might not produce enough hydrocarbons to pay all the drilling and completion costs, even if successfully stimulated; thus, such reservoirs would not be good candidates for stimulation.
Fracture treatment optimization
The goal of every design engineer is to design the optimum fracture treatment for each and every well. Holditch et al.^{[1]}discuss the optimization of both the propped fracture length and the drainage area (well spacing) for low permeability gas reservoirs. Fig. 1 illustrates the method used to optimize the size of a fracture treatment.^{[2]}^{[3]} Fig. 1 clearly shows the following:
- As the propped length of a fracture increases, the cumulative production increased, and the revenue from hydrocarbon sales increase.
- As the fracture length increases, the incremental benefit ($ of revenue per foot of additional propped fracture length) decreases.
- As the treatment volume increases, the propped fracture length increases.
- As the fracture length increases, the incremental cost of each foot of fracture ($ of cost per foot of additional propped fracture length) increases.
- When the incremental cost of the treatment is compared to the incremental benefit of increasing the treatment volume, an optimum propped fracture length can be found for every situation.
Additional economic calculations can be made to determine the optimum fracture treatment design. However, in all cases, the design engineer must consider the effect of the fracture upon flow rates and recovery, the cost of the treatment, and the investment guidelines of the company that owns and operates the well.
Fracture treatment design considerations
The most important data for designing a fracture treatment are the:
- In-situ stress profile
- Formation permeability
- Fluid loss characteristics
- Total fluid volume pumped
- Propping agent type and amount
- Pad volume
- Fracture fluid viscosity
- Injection rate
- Formation modulus
It is very important to quantify the in-situ stress profile and the permeability profile of the zone to be stimulated, plus the layers of rock above and below the target zone that influence fracture height growth.
There is a structured method that should be followed by the engineer to design, optimize, execute, evaluate, and re-optimize the fracture treatments in any reservoir.^{[4]} The first step is always the construction of a complete and accurate data set. Table 1 lists the sources for the data required to run fracture propagation and reservoir models. Notice that the design engineer must be capable of:
- Analyzing logs
- Analyzing cores
- Analyzing production data
- Analyzing well-test data
- Reviewing well files to obtain all the information needed to design and evaluate the well that is to be hydraulically fracture treated
Design procedures
To design the optimum treatment, the engineer must determine the effect of fracture length and fracture conductivity upon the productivity and the ultimate recovery from the well. As in all engineering problems, sensitivity runs must be made to evaluate uncertainties, such as estimates of formation permeability and drainage area. The production data obtained from the reservoir model should be used in an economics model to determine the optimum fracture length and conductivity. Then, a fracture treatment must be designed using a fracture propagation model to achieve the desired length and conductivity at minimum cost. The most important concept is to design a fracture using all data and appropriate models that results in the optimum economic benefit to the operator of the well, as shown in Fig. 1. A hydraulic fracture propagation model should be run to determine what needs to be mixed and pumped into the well to achieve the optimum values of propped fracture length and fracture conductivity. The base data set should be used to make a base case run. Then, the engineer determines which variables are the most uncertain. Many times, the values of in-situ stress, Young’s modulus, permeability, and fluid loss coefficient, for example, are not known with certainty and have to be estimated. The design engineer should acknowledge these uncertainties and makes sensitivity runs with the fracture propagation model to determine the effect of these uncertainties on the design process. As databases are developed, the number and magnitude of the uncertainties will diminish.
In practice, the design engineer should simulate the fracture treatment of the well many times on his or her computer. Making these sensitivity runs leads to a better design, while also educating the design engineer on how certain variables affect both the created and the propped fracture dimensions.
Fracture fluid selection
A critical decision by the design engineer is the selection of the fracture fluid for the treatment. Economides et al.^{[5]} developed a flow chart that can be used to select the category of fracture fluid required to stimulate a gas well on the basis of factors such as:
- Reservoir temperature
- Reservoir pressure
- The expected value of fracture half-length
- A determination of whether the reservoir is water sensitive
To view chart, See Fig. 2 in Fracture treatment design
Propping agent selection
Economides et al.^{[5]} also produced a flow chart for selecting propping agents. Their flow chart is located in Fig. 3 in Fracture treatment design. The selection of the propping agent is based on the maximum effective stress that is applied to the propping agent during the life of the well. The maximum effective stress depends on the minimum value of flowing bottomhole pressure that one expects during the life of the well. If the maximum effective stress is less than 6,000 psi, sand is usually recommended as the propping agent. If the maximum effective stress is between 6,000 and 12,000 psi, one should use either resin-coated sand or intermediate strength proppant, depending on the temperature. For cases in which the maximum effective stress is greater than 12,000 psi, high-strength bauxite should be used as the propping agent.
Of course, any rule of thumb should only be used as a guide, as there will be exceptions. For example, even if the maximum effective stress is less than 6,000 psi, the design engineer may choose to use resin-coated sand or other additives to "lock" the proppant in place when proppant flowback becomes an issue. Also, in high flow rate gas wells, intermediate strength proppants may be needed because of inertial flow. For fracture treatments in countries that do not mine sand for fracturing, the largest cost for the proppant is often the shipping charges. Thus, if one has to import the propping agent, one may choose to use intermediate strength proppants, even for relatively shallow wells, because the cost differential between the intermediate strength proppants and sand is not a significant factor.
Once the optimum fracture half-length has been determined and the fracture fluid and fracture propping agent have been selected, the design engineer needs to use a P3D model to determine the details of the design, such as the optimum injection rate, the optimum pad volume, the need for fluid loss additives, the proper location for the perforations, and other details. After designing the optimum treatment, the design engineer must compute the costs of the proposed treatment to be certain the costs are not too different from the costs assumed during the treatment optimization process. If the treatment costs are substantially different, the entire optimization loop (Fig. 1) should be retraced using the correct cost data.
Fracture treatment execution in the field
After the optimum fracture treatment has been designed, it must be pumped into the well successfully. A successful field operation requires planning, coordination, and cooperation of all parties. Treatment supervision and the use of quality-control measures improve the successful application of hydraulic fracturing. Safety is always the primary concern in the field. Safety begins with a thorough understanding by all parties of their duties in the field. A safety meeting is always held to review the treatment procedure, establish a chain of command, make sure everyone knows his/her job responsibilities for the day, and to establish a plan for emergencies.
The safety meeting also should be used to discuss the well completion details and the maximum allowable injection rate and pressures, as well as the maximum pressures to be held as backup in the annulus. All casing, tubing, wellheads, valves, and weak links, such as liner tops, should be thoroughly tested prior to beginning the fracturing treatment. Mechanical failures during a treatment can be costly and dangerous. All mechanical problems should be discovered during testing and repaired prior to pumping the fracture treatment.
Prior to pumping the treatment, the engineer in charge should conduct a detailed inventory of all the equipment and materials on location. The inventory should be compared to the design and the prognosis. After the treatment is concluded, the engineer should conduct another inventory of all the materials left on location. In most cases, the difference in the two inventories can be used to verify what was mixed and pumped into the wellbore and the hydrocarbon-bearing formation.
In addition to an inventory, samples of the base fracturing fluid (usually water) should be taken and analyzed. Typically, a water analysis is done on the base fluid to determine the minerals present and the type of bacteria in the water. The data from the water analysis can be used to select the additives required to mix the viscous fracture fluid required to create a wide fracture and to transport the propping agent into the fracture. In addition to testing the water, samples of the additives used during a treatment, and the fracture fluid after all additives have been added, should be taken during the job and saved in case future analyses are required.
Post-fracture reservoir evaluation methods
Analyzing post-fracture production and pressure data requires a thorough understanding of the flow patterns in the reservoir.^{[4]} The technique applied to analyze the data must be compatible with the flow regime that is occurring when the data are collected. For a well containing a finite conductivity hydraulic fracture, the flow regimes that occur consist of:
- Bilinear flow
- Linear flow
- Transitional flow
- Pseudoradial flow
These flow regimes can be defined in terms of dimensionless time. The times that encompass bilinear flow, linear flow, and transitional flow can be termed "transient flow." The pseudoradial flow data can be analyzed using semisteady-state methods. In most tight gas reservoirs containing a finite conductivity hydraulic fracture, the flow rate and pressure data measured during well tests fall somewhere in the transient flow category. Seldom can semisteady-state analyses techniques, such as the Horner analyses of PBU data, be used to successfully analyze well-test data in tight gas reservoirs containing a hydraulic fracture. As such, transient flow analyses methods should be used to analyze such data. If long-term (years) production data are available, semisteady-state methods can be used successfully to analyze the production and pressure data.
Transient flow considerations
In the 1950s and 1960s, several papers were published containing semisteady-state analysis methods to analyze wells containing hydraulic fractures.^{[6]}^{[7]}^{[8]} During the time those papers were published, most wells that were hydraulically fracture treated were moderate to high permeability wells that had been damaged during drilling or production. The fracture treatments were designed to be short and only break through the near-wellbore damaged zone. For such situations, the wells would reach semisteady-state flow in a matter of days or weeks, and the semisteady-state analysis methods of Horner, Prats, or McGuire and Sikora could be used successfully to analyze the production and pressure data. However, in low permeability gas reservoirs containing long hydraulic fractures, months or years of production must occur before the well approaches pseudoradial flow.
The flow regimes of a vertical well containing a finite conductivity vertical fracture can be defined using the dimensionless time equation.
In a paper by Lee and Holditch,^{[9]} it was shown that linear flow occurs between dimensionless times of 0.0225 and 0.1156. Pseudo-radial flow of a well containing a finite conductivity hydraulic fracture does not begin until a dimensionless time of 2 to 5, depending on the value of dimensionless fracture conductivity. Prior to reaching linear flow, the flow is often characterized as bilinear flow. Between the end of linear flow and the beginning of pseudo-radial flow, the regime is often called transitional flow. The data in Table 2 illustrate the actual times required to reach linear flow and pseudo-radial flow for typical reservoir situations.
Notice that for gas reservoirs with permeabilities of 1.0 md containing short hydraulic fractures, linear and pseudoradial flow techniques can be used to analyze data during the first month of production. However, as the permeability decreases below the value of 0.1 md, long, hydraulic fractures are required to produce the well at commercial flow rates, and years worth of data are required to use linear and pseudoradial flow analysis procedures.
So how do we analyze early time data from low permeability gas reservoirs containing finite conductivity fractures? The answer is that we must use analytical or numerical solutions of Darcy’s law to properly analyze data in the transient flow period, which is all the pressure and flow-rate data prior to reaching pseudoradial flow. Many analytical transient-flow solutions for hydraulically fractured wells have been derived and published. In fact, there are too many to list in the references, but the first and most important analytical solutions were published by Russell and Truitt,^{[10]} Gringarten et al.,^{[11]} Cinco et al.,^{[12]} and Agarwal.^{[13]}
In addition to the analytical solutions, Lee and Holditch^{[9]} showed that finite difference modeling could be used to analyze data from tight gas reservoirs containing a finite conductivity hydraulic fracture. Actually, the ideal solution is to first use the analytical models to analyze the data to determine first-order estimates of formation permeability, fracture half-length, and fracture conductivity, and then take those values and use them as input into a realistic finite difference model. The finite difference model can be used to determine the final estimates of the formation and fracture properties, taking into account effects such as non-Darcy flow, fracture closure, and formation compaction. The key is to use transient-flow models to analyze transient-flow data. If one tries to analyze data in linear flow with a pseudoradial flow model (such as the Horner graph), one gets incorrect estimates of formation and fracture properties.
Types of models
There are several types of models that can be used to analyze flow and pressure data from a tight-gas-well containing a finite conductivity hydraulic fracture.
Semisteady-State models
Early models by Horner,^{[8]} Prats,^{[7]} and McGuire and Sikora,^{[6]} or simply the semisteady-state flow equation, can be used successfully to analyze data from wells that actually reach pseudoradial flow. In the 1950s and 1960s, very few wells with permeabilities less than 1.0 md were completed because of the low gas prices at the time. As illustrated in Table 2, the time required to reach pseudoradial flow in reservoirs of 1.0 md or greater was short enough so that semisteady-state models could be used successfully to analyze the data
Semianalytical models
Analytical and semianalytical models^{[10]}^{[11]}^{[12]}^{[13]} published in the 1960s and 1970s allowed the engineer to analyze both production and pressure data during the transient flow period. Originally, these semianalytical solutions were presented in the form of type curves. To analyze the field data, the data had to be plotted on a log/log graph, made of transparent paper, and then the field data would be placed on top of the type curve and shifted horizontally and vertically until the "shape of the field data" could be matched with the "shape of one of the type curves." At the time, even though the solution method was time consuming, type curves revolutionized pressure transient analyses by allowing engineers to analyze transient-flow data from wells containing a finite conductivity hydraulic fracture. A complete discussion on how to use type curves to analyze data from wells containing a hydraulic fracture is found in Ref. 54^{[4]}.
Even though the use of type curves has proven to be very useful, type curves (semianalytical solutions) do have their limitations. For example, most semianalytical solutions were derived using the following assumptions:
- There is single-phase Darcy flow.
- There is a single-layer, horizontal, homogeneous, isotropic reservoir.
- The reservoir is under pressure depletion drive and no water drive or water influx is included.
- The reservoir permeability is constant with time.
- The hydraulic fracture conductivity is constant with both time and distance.
These assumptions do fit many reservoir situations; hence, the engineer analyzing the data must realize these limitations. In most cases, the semianalytical solutions can be used to analyze transient-flow data and derive first-order estimates of:
- Formation permeability
- Fracture half-length
- Fracture conductivity
Finite difference models
Finite difference or numerical models can also be used to analyze transient-flow data from a well containing a finite conductivity hydraulic fracture.^{[9]} Finite difference models can be used to overcome many of the limitations that accompany the semianalytical solutions. For example, if a finite difference reservoir model is used, we can model:
- Multiphase flow
- Water influx
- Multiple layers^{[14]}
- Anisotropic reservoir properties
In addition, the finite difference reservoir model can be used to simulate non-Darcy flow^{[15]} and fracture closure because of the crushing and embedment of the propping agent. Other factors can also be investigated, such as:
- Water blocking caused by the fracture fluid^{[16]}
- The effects of fracture fluid on the cleanup behavior of the reservoir after the fracture treatment^{[17]}
Finite difference reservoir models are more difficult to use and more time consuming than the semianalytical models, especially if multiphase flow and multilayered reservoirs are going to be simulated. However, when these properties are important, the extra time and effort to use a finite difference reservoir model results in a better understanding of the reservoir and better estimates of the reservoir and fracture properties. The best solution technique is normally to use the semianalytical reservoir models to obtain a first-order estimate of the formation and fracture properties and then use those values as input to the finite difference reservoir model. The finite difference model can then be used to determine the final answers.
Analyzing post-fracture production data
In many cases, after a well is fracture treated (especially in the early days of fracturing), the well is produced to a pit until the fracture fluid is cleaned up sufficiently to turn the well to sales. After the well quits making proppant and fracture fluid, a test separator is installed to measure the gas flow rate. The gas flow rate and flowing pressures are subsequently analyzed using transient-flow models to estimate values of the reservoir and fracture properties. If lucky, the engineer talks management into shutting in the well to run a pressure buildup test.
In the 1980s, we found that we could better analyze the hydraulic fracture and the reservoir if all of the pressure and flow-rate data were measured from the time the well is opened for cleanup. The Gas Research Inst. (GRI) sponsored a multiyear research project to learn how to evaluate fracture treatments in tight gas reservoirs. The research was focused on four staged field experiments (SFE) in which four wells named SFE Nos. 1, 2, 3, and 4 were drilled^{[18]}^{[19]}^{[20]}^{[21]} and tested extensively. During the GRI tight-gas-sands research project, it was learned that we need to measure all flow rates (gas, water, and condensate) and the flowing pressures from the time the well is opened for cleanup. Especially in SFE No. 1,^{[18]} it was found that the only acceptable match of the pressure transient data could be obtained by modeling multiphase flow and fracture fluid cleanup in a multilayer reservoir. Such a complicated analysis can only be done using a finite difference reservoir simulator.
If a finite difference reservoir simulator is used to analyze field data or just to do parametric studies, it is clear that the production and pressure transient data, if measured accurately, can lead to a much better characterization of the reservoir and the hydraulic fracture.^{[9]}^{[18]}^{[19]}^{[20]}^{[21]}The very early flow-rate data are mostly affected by the fracture conductivity, often called bilinear flow. Later, during linear flow, the flow-rate data are most affected by the fracture half-length. If pseudoradial flow is reached, the flow-rate data are most affected by the formation permeability. As such, if the early time flow-rate and pressure data, during the first few days and weeks, are not measured accurately, it is possible that one may not truly understand the properties of the hydraulic fracture.
Post-fracture production data can be analyzed with decline curves, type curves, semianalytical reservoir models, or finite difference reservoir models. When analyzing the production data, the analyst tries to determine the values of formation permeability, fracture half-length, and fracture conductivity. Experience has shown^{[4]}^{[9]} that it is best to measure the formation permeability using prefracture well testing. Then, when analyzing the post-fracture data, one is only trying to determine the properties of the hydraulic fracture.
Experience has also shown that the analysis of post-fracture production data only provides estimates of the length of the fracture that "has cleaned up."^{[17]}^{[22]}^{[23]} After the fracture treatment has been pumped, the hydraulic fracture is filled with fluid. The fracture fluid either flows into the wellbore, imbibes into the formation, or stays in the fracture.^{[16]} If the fracture fluid stays in the fracture, that part of the fracture does not allow gas to flow into the fracture from the formation. Consequently, only the part of the fracture near the wellbore that has been cleaned up is seen by the analysis of production or pressure transient data. In essence, there are three fracture lengths:
- The created fracture length
- The propped fracture length
- The effective fracture length
The propped fracture length is the part of the created fracture that contains propping agent at the end of the treatment. The effective fracture length is that part of the propped fracture length that has cleaned up enough to allow gas flow. When we analyze production and pressure transient data, we only obtain estimates of the effective fracture length.
Post-fracture pressure transient analysis
Lee and Holditch^{[9]} presented discussions concerning how to analyze post-fracture pressure transient data. In most cases, the analysis of post-fracture pressure buildup data, along with the analysis of the post-fracture production data, leads to accurate descriptions of the formation and the hydraulic fracture only if the correct portion of the data are analyzed with the correct model. For example, the analyst must be sure to use only the linear-flow data when analyzing the transient test using a linear-flow model. It might be possible, when one is analyzing data from moderate permeability reservoirs containing short fractures, that linear flow or pseudoradial flow methods can be used to correctly analyze the pressure buildup data. However, in most cases involving tight gas reservoirs containing long hydraulic fractures, transient-flow methods, such as type curves, semianalytical reservoir models, or finite difference reservoir models, must be used to correctly analyze the post-fracture pressure buildup data. To account for factors such as multiphase flow, multilayered reservoirs, non-Darcy flow, and fracture closure effects, the analyst should use a finite difference reservoir model that is capable of modeling a finite conductivity fracture, plus the other features previously listed.
Nomenclature
c | = | compressibility, 1/psi |
k | = | permeability, md |
L | = | fracture half length, ft |
t | = | time, hours or days |
φ | = | porosity, fraction |
μ | = | gas viscosity, cp |
Subscripts
D | = | dimensionless |
f | = | fluid or fracture |
t | = | true (for conductivity); total (for compressibility) |
References
- ↑ Holditch, S.A., Jennings, J.W., Neuse, S.H. et al. 1978. The Optimization of Well Spacing and Fracture Length in Low Permeability Gas Reservoirs. Presented at the SPE Annual Fall Technical Conference and Exhibition, Houston, Texas, 1-3 October 1978. SPE-7496-MS. http://dx.doi.org/10.2118/7496-MS.
- ↑ Veatch Jr., R.W. 1983. Overview of Current Hydraulic Fracturing Design and Treatment Technology--Part 1. J Pet Technol 35 (4): 677-687. SPE-10039-PA. http://dx.doi.org/10.2118/10039-PA.
- ↑ Britt, L.K. 1985. Optimized Oilwell Fracturing of Moderate-Permeability Reservoirs. Presented at the SPE Annual Technical Conference and Exhibition, Las Vegas, Nevada, USA, 22–26 September. SPE-14371-MS. http://dx.doi.org/10.2118/14371-MS.
- ↑ ^{4.0} ^{4.1} ^{4.2} ^{4.3} Gidley, J.L., Holditch, S.A., Nierode, D.E. et al. 1989. Recent Advances in Hydraulic Fracturing, 12, 317. Richardson, Texas: Monograph Series, SPE.
- ↑ ^{5.0} ^{5.1} Economides, M.J. and Nolte, K.G. 2000. Reservoir Stimulation, third edition. West Sussex, England: John Wiley & Sons, Ltd.
- ↑ ^{6.0} ^{6.1} McGuire, W.J. and Sikora, V.J. 1960. The Effect of Vertical Fractures on Well Productivity. Trans., AIME 219: 401.
- ↑ ^{7.0} ^{7.1} Prats, M. 1961. Effect of Vertical Fractures on Reservoir Behavior—Incompressible Fluid Case. SPE J. 1 (2). SPE-1575-G. http://dx.doi.org/10.2118/1575-G. Cite error: Invalid
<ref>
tag; name "r7" defined multiple times with different content - ↑ ^{8.0} ^{8.1} Horner, D.R. 1951. Pressure Build-Up in Wells. Proc., Third World Petroleum Congress, Leiden, Sec. II, 503.
- ↑ ^{9.0} ^{9.1} ^{9.2} ^{9.3} ^{9.4} ^{9.5} Lee, W.J. and Holditch, S.A. 1981. Fracture Evaluation With Pressure Transient Testing in Low-Permeability Gas Reservoirs. J Pet Technol 33 (9): 1776–1792. SPE-9975-PA. http://dx.doi.org/10.2118/9975-PA.
- ↑ ^{10.0} ^{10.1} Russell, D.G. and Truitt, N.E. 1964. Transient Pressure Behavior in Vertically Fractured Reservoirs. J Pet Technol 16 (10): 1159–1170. SPE-967-PA. http://dx.doi.org/10.2118/967-PA.
- ↑ ^{11.0} ^{11.1} Gringarten, A.C., Henry J. Ramey, J., and Raghavan, R. 1974. Unsteady-State Pressure Distributions Created by a Well With a Single Infinite-Conductivity Vertical Fracture. SPE J 14 (4): 347-360. SPE-4051-PA. http://dx.doi.org/10.2118/4051-PA.
- ↑ ^{12.0} ^{12.1} Cinco-Ley, H., Samaniego-V., F., and A.N., D. 1978. Transient Pressure Behavior for a Well With a Finite-Conductivity Vertical Fracture. SPE J. 18 (4): 253–264. SPE-6014-PA. http://dx.doi.org/10.2118/6014-PA.
- ↑ ^{13.0} ^{13.1} Agarwal, R.G., Carter, R.D., and Pollock, C.B. 1979. Evaluation and Performance Prediction of Low-Permeability Gas Wells Stimulated by Massive Hydraulic Fracturing. J Pet Technol 31 (3): 362–372. SPE-6838-PA. http://dx.doi.org/10.2118-6838-PA.
- ↑ Rahim, Z., Holditch, S.A., Zuber, M.D. et al. 1998. Evaluation of Fracture Treatments Using a Layered-Reservoir Description: Field Examples. SPE Prod & Oper 13 (1): 21-28. SPE-26187-PA. http://dx.doi.org/10.2118/26187-PA.
- ↑ Holditch, S.A. and Morse, R.A. 1976. The Effects of Non-Darcy Flow on the Behavior of Hydraulically Fractured Gas Wells. J Pet Technol 28 (10): 1169–1179. SPE-5586-PA. http://dx.doi.org/10.2118/5586-PA.
- ↑ ^{16.0} ^{16.1} Holditch, S.A. 1979. Factors Affecting Water Blocking and Gas Flow From Hydraulically Fractured Gas Wells. J Pet Technol 31 (12): 1515–1524. SPE-7561-PA. http://dx.doi.org/10.2118/7561-PA.
- ↑ ^{17.0} ^{17.1} Voneiff, G.W., Robinson, B.M., and Holditch, S.A. 1996. The Effects of Unbroken Fracture Fluid on Gaswell Performance. SPE Prod & Oper 11 (4): 223-229. SPE-26664-PA. http://dx.doi.org/10.2118/26664-PA.
- ↑ ^{18.0} ^{18.1} ^{18.2} Holditch, S.A., Robinson, B.M., Whitehead, W.S. et al. 1988. The GRI Staged Field Experiment. SPE Form Eval 3 (3): 519-533. SPE-16429-PA. http://dx.doi.org/10.2118/16429-PA.
- ↑ ^{19.0} ^{19.1} Robinson, B.M., Holditch, S.A., and Peterson, R.E. 1991. The Gas Research Institute's Second Staged Field Experiment: A Study of Hydraulic Fracturing. Presented at the SPE Gas Technology Symposium, Houston, Texas, 22-24 January 1991. SPE-21495-MS. http://dx.doi.org/10.2118/21495-MS.
- ↑ ^{20.0} ^{20.1} Robinson, B.M., Holditch, S.A., Whitehead, W.S. et al. 1992. Hydraulic Fracturing Research in East Texas: Third GRI Staged Field Experiment. J Pet Technol 44 (1): 78-87. SPE-22878-PA. http://dx.doi.org/10.2118/22878-PA.
- ↑ ^{21.0} ^{21.1} Saunders, B.F., Robinson, B.M., Holditch, S.A. et al. 1992. Hydraulic Fracturing Research in the Frontier Formation Through the Gas Research Institute's Fourth Staged Field Experiment. Presented at the SPE Annual Technical Conference and Exhibition, Washington, D.C., 4-7 October 1992. SPE-24854-MS. http://dx.doi.org/10.2118/24854-MS.
- ↑ Montgomery, K.T., Holditch, S.A., and Berthelot, J.M. 1990. Effects of Fracture Fluid Invasion on Cleanup Behavior and Pressure Buildup Analysis. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, 23–26 September. SPE-20643-MS. http://dx.doi.org/10.2118/20643-MS.
- ↑ Sherman, J.B. and Holditch, S.A. 1991. Effect of Injected Fracture Fluids and Operating Procedures on Ultimate Gas Recovery. Presented at the SPE Gas Technology Symposium, Houston, Texas, 22-24 January 1991. SPE-21496-MS. http://dx.doi.org/10.2118/21496-MS.
Noteworthy papers in OnePetro
Use this section to list papers in OnePetro that a reader who wants to learn more should definitely read
External links
Use this section to provide links to relevant material on websites other than PetroWiki and OnePetro
See also
Tight gas reservoirs4.1.2 Separation and Treating;3.2.3 Hydraulic Fracturing Design, Implementation and Optimisation
Statistical data correlations in tight gas reservoirs
Reserves estimation in tight gas reservoirs
Permeability estimation in tight gas reservoirs
Tight gas drilling and completion
Log analyses in tight gas reservoirs
Core analyses in tight gas reservoirs