A Type-Curve Matching Procedure For Material Balance Analysis Of Production Data From Geopressured Gas Reservoirs

1991 ◽  
Vol 30 (05) ◽  
Author(s):  
A.K. Ambastha
1994 ◽  
Author(s):  
S. L. West ◽  
P. J. R. Cochrane

Tight shallow gas reservoirs in the Western Canada Basin present a number of unique challenges in accurately determining reserves. Traditional methods such as decline analysis and material balance are inaccurate due to the formations' low permeabilities and poor pressure data. The low permeabilities cause long transient periods not easily separable from production decline using conventional decline analysis. The result is lower confidence in selecting the appropriate decline characteristics (exponential or harmonic) which significantly impacts recovery factors and remaining reserves. Limited, poor quality pressure data and commingled production from the three producing zones results in non representative pressure data and hence inaccurate material balance analysis. This paper presents the merit of two new methods of reserve evaluation which address the problems described above for tight shallow gas in the Medicine Hat field. The first method applies type curve matching which combines the analytical pressure solutions of the diffusivity equation (transient) with the empirical decline equation. The second method is an extended material balance which incorporates the gas deliverability theory to allow the selection of appropriate p/z derivatives without relying on pressure data. Excellent results were obtained by applying these two methodologies to ten properties which gather gas from 2300 wells. The two independent techniques resulted in similar production forecasts and reserves, confirming their validity. They proved to be valuable, practical tools in overcoming the various challenges of tight shallow gas and in improving the accuracy in gas reserves determination in the Medicine Hat field.


2021 ◽  
Author(s):  
Bashirul Haq

Abstract Sour gas reservoirs are vital sources for natural gas production. Sulphur deposition in the reservoir reduces a considerable amount of gas production due to permeability reduction. Consequently, well health monitoring and early prediction of Sulphur deposition are crucial for effective gas production from a sour gas reservoir. Dynamic gas material balance analysis is a useful technique in calculating gas initially in place utilizing the flowing wellhead or bottom hole pressures and rates during the well's lifetime. The approach did not apply to monitor a producing gas's health well and detect Sulphur deposition. This work aims to (i) modify dynamic gas material balance equation by adding the Sulphur deposition term, (ii) build a model to predict and validate the issue utilizing the modified equation. A unique form of the flowing material balance is developed by including Sulphur residue term. The curve fitting tool and modified flowing gas material balance are applied to predict well-expected behaviour. The variation between expected and actual performance indicates the health issue of a well. Initial, individual components of the model are tested. Then the model is validated with the known values. The workflow is applied to active gas field and correctly detected the health issue. The novel workflow can accurately predict Sulphur evidence. Besides,the workflow can notify the production engineers to take corrective measures about the subject. Keywords: Sulfur deposition, Dynamic gas material balance analysis, Workflow


2021 ◽  
Author(s):  
Helmi Pratikno ◽  
W. John Lee ◽  
Cesario K. Torres

Abstract This paper presents a method to identify switch time from end of linear flow (telf) to transition or boundary-dominated flow (BDF) by utilizing multiple diagnostic plots including a Modified Fetkovich type curve (Eleiott et al. 2019). In this study, we analyzed publicly available production data to analyze transient linear flow behavior and boundary-dominated flow from multiple unconventional reservoirs. This method applies a log-log plot of rate versus time combined with a log-log plot of rate versus material balance time (MBT). In addition to log-log plots, a specialized plot of rate versus square root of time is used to confirm telf. A plot of MBT versus actual time, t, is provided to convert material balance time to actual time, and vice versa. The Modified Fetkovich type curve is used to estimate decline parameters and reservoir properties. Applications of this method using monthly production data from Bakken and Permian Shale areas are presented in this work. Utilizing public data, our comprehensive review of approximately 800 multi-staged fractured horizontal wells (MFHW) from North American unconventional reservoirs found many of them exhibiting linear flow production characteristics. To identify end of linear flow, a log-log plot of rate versus time alone is not sufficient, especially when a well is not operated in a consistent manner. This paper shows using additional diagnostic plots such as rate versus MBT and specialized plots can assist interpreters to better identify end of linear flow. With the end of linear flow determined for these wells, the interpreter can use the telf to forecast future production and estimate reservoir properties using the modified type curve. These diagnostic plots can be added to existing production analysis tools so that engineers can analyze changes in flow regimes in a timely manner, have better understanding of how to forecast their wells, and reduce the uncertainty in estimated ultimate recoveries related to decline parameters.


Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Shijun Huang ◽  
Jiaojiao Zhang ◽  
Sidong Fang ◽  
Xifeng Wang

In shale gas reservoirs, the production data analysis method is widely used to invert reservoir and fracture parameter, and productivity prediction. Compared with numerical models and semianalytical models, which have high computational cost, the analytical model is mostly used in the production data analysis method to characterize the complex fracture network formed after fracturing. However, most of the current calculation models ignore the uneven support of fractures, and most of them use a single supported fracture model to describe the flow characteristics, which magnifies the role of supported fracture to a certain extent. Therefore, in this study, firstly, the fractures are divided into supported fractures and unsupported fractures. According to the near-well supported fractures and far-well unsupported fractures, the SRV zone is divided into outer SRV and inner SRV. The four areas are characterized by different seepage models, and the analytical solutions of the models are obtained by Laplace transform and inverse transform. Secondly, the material balance pseudotime is introduced to process the production data under the conditions of variable production and variable pressure. The double logarithmic curves of normalized production rate, rate integration, the derivative of the integration, and material balance pseudotime are established, and the parameters are interpreted by fitting the theoretical curve to the measured data. Then, the accuracy of the method is verified by comparison the parameter interpretation results with well test results, and the influence of parameters such as the half-length and permeability of supported and unsupported fractures on gas production is analyzed. Finally, the proposed method is applied to four field cases in southwest China. This paper mainly establishes an analytical method for parameter interpretation after hydraulic fracturing based on the production data analysis method considering the uneven support of fractures, which is of great significance for understanding the mechanism of fracturing stimulation, optimization of fracturing parameters, and gas production forecast.


Lithosphere ◽  
2021 ◽  
Vol 2021 (Special 1) ◽  
Author(s):  
Lixia Zhang ◽  
Yingxu He ◽  
Chunqiu Guo ◽  
Yang Yu

Abstract Determination of gas in place (GIP) is among the hotspot issues in the field of oil/gas reservoir engineering. The conventional material balance method and other relevant approaches have found widespread application in estimating GIP of a gas reservoir or well-controlled gas reserves, but they are normally not cost-effective. To calculate GIP of abnormally pressured gas reservoirs economically and accurately, this paper deduces an iteration method for GIP estimation from production data, taking into consideration the pore shrinkage of reservoir rock and the volume expansion of irreducible water, and presents a strategy for selecting an initial iteration value of GIP. The approach, termed DMBM-APGR (dynamic material balance method for abnormally pressured gas reservoirs) here, is based on two equations: dynamic material balance equation and static material balance equation for overpressured gas reservoirs. The former delineates the relationship between the quasipressure at bottomhole pressure and the one at average reservoir pressure, and the latter reflects the relationship between average reservoir pressure and cumulative gas production, both of which are rigidly demonstrated in the paper using the basic theory of gas flow through porous media and material balance principle. The method proves effective with several numerical cases under various production schedules and a field case under a variable rate/variable pressure schedule, and the calculation error of GIP does not go beyond 5% provided that the production data are credible. DMBM-APGR goes for gas reservoirs with abnormally high pressure as well as those with normal pressure in virtue of its strict theoretical foundation, which not only considers the compressibilities of rock and bound water, but also reckons with the changes in production rate and variations of gas properties as functions of pressure. The method may serve as a valuable and reliable tool in determining gas reserves.


2007 ◽  
Vol 10 (03) ◽  
pp. 312-331 ◽  
Author(s):  
Christopher R. Clarkson ◽  
R. Marc Bustin ◽  
John P. Seidle

Summary Coalbed-methane (CBM) reservoirs commonly exhibit two-phase-flow (gas plus water) characteristics; however, commercial CBM production is possible from single-phase (gas) coal reservoirs, as demonstrated by the recent development of the Horseshoe Canyon coals of western Canada. Commercial single-phase CBM production also occurs in some areas of the low-productivity Fruitland Coal, south-southwest of the high-productivity Fruitland Coal Fairway in the San Juan basin, and in other CBM-producing basins of the continental United States. Production data of single-phase coal reservoirs may be analyzed with techniques commonly applied to conventional reservoirs. Complicating application, however, is the unique nature of CBM reservoirs; coal gas-storage and -transport mechanisms differ substantially from conventional reservoirs. Single-phase CBM reservoirs may also display complex reservoir behavior such as multilayer characteristics, dual-porosity effects, and permeability anisotropy. The current work illustrates how single-well production-data-analysis (PDA) techniques, such as type curve, flowing material balance (FMB), and pressure-transient (PT) analysis, may be altered to analyze single-phase CBM wells. Examples of how reservoir inputs to the PDA techniques and subsequent calculations are modified to account for CBM-reservoir behavior are given. This paper demonstrates, by simulated and field examples, that reasonable reservoir and stimulation estimates can be obtained from PDA of CBM reservoirs only if appropriate reservoir inputs (i.e., desorption compressibility, fracture porosity) are used in the analysis. As the field examples demonstrate, type-curve, FMB, and PT analysis methods for PDA are not used in isolation for reservoir-property estimation, but rather as a starting point for single-well and multiwell reservoir simulation, which is then used to history match and forecast CBM-well production (e.g., for reserves assignment). CBM reservoirs have the potential for permeability anisotropy because of their naturally fractured nature, which may complicate PDA. To study the effects of permeability anisotropy upon production, a 2D, single-phase, numerical CBM-reservoir simulator was constructed to simulate single-well production assuming various permeability-anisotropy ratios. Only large permeability ratios (>16:1) appear to have a significant effect upon single-well production characteristics. Multilayer reservoir characteristics may also be observed with CBM reservoirs because of vertical heterogeneity, or in cases where the coals are commingled with conventional (sandstone) reservoirs. In these cases, the type-curve, FMB, and PT analysis techniques are difficult to apply with confidence. Methods and tools for analyzing multilayer CBM (plus sand) reservoirs are presented. Using simulated and field examples, it is demonstrated that unique reservoir properties may be assigned to individual layers from commingled (multilayer) production in the simple two-layer case. Introduction Commercial single-phase (gas) CBM production has been demonstrated recently in the Horseshoe Canyon coals of western Canada (Bastian et al. 2005) and previously in various basins in the US; there is currently a need for advanced PDA techniques to assist with evaluation of these reservoirs. Over the past several decades, significant advances have been made in PDA of conventional oil and gas reservoirs [select references include Fetkovich (1980), Fetkovich et al. (1987), Carter (1985), Fraim and Wattenbarger (1987), Blasingame et al. (1989, 1991), Palacio and Blasingame (1993), Fetkovich et al. (1996), Agarwal et al. (1999), and Mattar and Anderson (2003)]. These modern methods have greatly enhanced the engineers' ability to obtain quantitative information about reservoir properties and stimulation/damage from data that are gathered routinely during the producing life of a well, such as production data and, in some instances, flowing pressure information. The information that may be obtained from detailed PDA includes oil or gas in place (GIP), permeability-thickness product (kh), and skin (s), and this can be used to supplement information obtained from other sources such as PT analysis, material balance, and reservoir simulation.


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