|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
Summary This research presents a new method to analyze production- and well-test data: the superposition rate. The method was developed from the well-accepted superposition principle. It is presented in a generalized form and is applicable to data in transient flow (including radial, linear, and bilinear), as well as in boundary-dominated flow (BDF). The superposition-rate method is validated by synthetic data generated from reservoir modeling. Moreover, a practical work flow of implementing the superposition rate in production-data and well-test analysis is presented. Finally, real-field examples are used to demonstrate the practicality of superposition rate. A comparison between the superposition-rate and superposition-time methods is presented. The superposition rate shows advantages over the superposition time. A key improvement of the superposition rate in quality diagnostics and data analysis is that it does not modify time scale. Consequently, the superposition rate keeps all production data in the sequence of their occurrence.
Summary In this study, we provide a detailed review and comparison of the various graphical methods, available in the literature, to interpret/analyze rate‐ and pressure‐transient data acquired from multistage hydraulically fractured horizontal wells (MHFHWs) completed in unconventional gas reservoirs. The methods reviewed in this study do not address complex transport mechanisms and complex fracture networks, but do address transient matrix linear flow (Ibrahim and Wattenbarger 2006; Nobakht and Clarkson 2012a, 2012b; Chen and Raghavan 2013) and boundary‐dominated flow (BDF). The methods for BDF are the contacted‐volume methods based on the ending times of linear flow (Wattenbarger et al. 1998; Behmanesh et al. 2015) and the flowing material‐balance (FMB) methods. The Agarwal‐Gardner FMB method (Agarwal et al. 1999) and the conventional FMB method involve plotting rate‐normalized pseudopressure vs. material‐balance pseudotime. We delineate the advantages and limitations associated with each method and identify the best methods of interpretation and analysis. Three different production modes—constant rate (CR), constant bottomhole pressure (BHP) (CBHP), and variable‐rate BHP—are considered. For comparison, various synthetic test data sets generated from a high‐resolution spectral gas simulator, which treats nonlinear gas flow rigorously and accurately to simulate rate‐transient data, is used. Both synthetic noise‐free and noisy‐rate pressure‐data sets considering wide ranges of initial reservoir pressure and BHP, as well as real‐field data sets, are used to compare the methods. For linear flow, the Nobakht‐Clarkson method (Nobakht and Clarkson 2012a, 2012b) yields the best results, although its use is tedious because it requires an iterative procedure. The Chen and Raghavan (2013) method for linear flow seems to provide results that are comparable with the Nobakht‐Clarkson method (Nobakht and Clarkson 2012b) but does not require an iterative procedure. The Ibrahim‐Wattenbarger method (Ibrahim and Wattenbarger 2006) for linear‐flow analysis always overestimates flow capacity compared with the other methods. Among the methods that discuss the ending time of linear flow, it was found that the unit‐impulse method from Behmanesh et al. (2015) provides the best results for predicting gas in place. For BDF, the results show that the Agarwal‐Gardner FMB method (Agarwal et al. 1999) is quite vulnerable to the error in rate/pressure data, whereas the conventional FMB method is more robust to noise and provides more accurate estimates of gas in place.
Summary It is well-known that many unconventional reservoirs experience porosity and permeability changes with pressure change during production. In recent work, authors have incorporated geomechanical modeling into production-analysis procedures to account for stress sensitivity of permeability of unconventional gas reservoirs, such as shale gas. Such corrections are necessary both for deriving accurate estimates of reservoir and hydraulic-fracture properties from rate-transient analysis (RTA) and for developing accurate long-term forecasts. It is possible with some shale-gas reservoirs that dynamic changes may occur in both the induced hydraulic fracture and matrix permeability, which could have a substantial impact on shale-gas productivity. The stress dependence of shale-gas permeability has been quantified in the laboratory by several researchers, but measurements of this kind for propped or unpropped fractures under in-situ conditions are less routinely acquired. For the latter, a variety of mechanisms, caused in part or wholly by stress changes in the induced hydraulic fracture, could lead to conductivity changes. In the current work, we investigate the impact of both stress-dependent matrix permeability and fracture-conductivity changes on rate-transient signatures and derived reservoir and hydraulic-fracture properties. Stress-dependent matrix permeability is incorporated into RTA by use of modified pseudopressure and pseudotime formulations, and fracture-conductivity changes are approximated by applying a time-dependent (dynamic) skin effect. We demonstrate that when RTA incorporates both matrix permeability changes and dynamic skin, the resulting rate-transient signature looks very similar to those of other shale plays (longterm transient linear flow). Uncorrected data appear to have a very short transient-linear-flow period, followed by apparent boundary-dominated flow. The impact of the applied corrections on the estimates of system permeability and fracture half-length is demonstrated, as is the impact on production forecasts.
Summary Estimating reservoir-flow capacity is crucial for production estimation, hydraulic-fracturing design, and field development. Laboratory experiments can be used to measure the permeability of rock samples, but the results might not be representative at a field scale because of reservoir heterogeneity and pre-existing natural-fracture systems. Diagnostic fracture-injection tests (DFITs) have now become standard practice to estimate formation pore pressure and formation permeability. However, in low-permeability reservoirs, after-closure radial flow is often absent and this can result in significant uncertainties in interpreting DFIT data. In addition, the established methods for analyzing DFIT data make two oversimplified assumptions: Carter leakoff and constant fracture compliance (or stiffness) during fracture closure. However, both assumptions are violated during fracture closure; therefore, G-function-based models and subsequent related work can lead to an incorrect interpretation and are not capable of consistently fitting both before- and after-closure data coherently. Moreover, current after-closure analysis relies on classic well-test solutions with a constant injection rate. In reality, a “constant injection rate” does not equal “constant leakoff rate into the formation,” because more than 90% of the injected fluid stays inside the fracture at the end of pumping instead of leaking into the formation. The variable leakoff rate clearly violates the constant-rate boundary condition used in existing well-test solutions. In this study, we extend our previous work and derive time-convolution solutions to pressure-transient behavior of a closing fracture with infinite and finite fracture conductivity. We show that the G-function and the square-root-of-time models are only special cases of our general solutions. In addition, we found that after-closure linear-flow and bilinear-flow analysis can be used to infer pore pressure reliably but fail to estimate other parameters correctly. Most importantly, we present a new approach to history match the entire duration of DFIT data to estimate formation-flow capacity, even without knowing closure stress and the roughness properties of the fracture surface. Our approach adds significant value to DFIT interpretation and uncertainty analysis, especially in unconventional reservoirs where the absence of after-closure radial flow is the norm. Two representative field cases are also presented and discussed.
Atadeger, Aykut (The University of Tulsa) | Batur, Ela (The University of Tulsa and Turkish Petroleum Corporation) | Onur, Mustafa (The University of Tulsa) | Thompson, Leslie G. (Cimarex Energy Company)
Abstract In this study, we provide a detailed review and comparison of the various graphical methods, available in the literature, to interpret/analyze rate and pressure transient data acquired from multistage hydraulically fractured horizontal wells (MHFHWs) completed in unconventional gas reservoirs. The methods reviewed are based on transient matrix linear flow (Ibrahim and Wattenbarger 2006; Nobakht and Clarkson 2012a, 2012b; Chen and Raghavan 2013) and boundary-dominated flow due to the stimulated reservoir volume (SRV). The methods for boundary-dominated flow are the contacted volume methods based on the ending times of linear flow (Wattenbarger et al. 1998; Behmanesh et al. 2015) and the material balance methods (FBMs); Agarwal-Gardner method (Agarwal et al. 1999) and conventional method involving plotting rate-normalized pseudo pressure versus pseudo time material-balance time. We delineate the advantages and limitations associated with each method and identify the best methods of interpretation and analysis. Three different production modes; constant rate (CR), constant bottomhole-pressure (CBHP), and variable-rate/bottomhole pressure, are considered. For comparison, various synthetic test data sets generated from a high-resolution spectral gas simulator, which treats nonlinear gas flow rigorously and accurately to simulate rate transient data, is used. Both synthetic noise-free and noisy rate/pressure data sets considering wide ranges of initial reservoir pressure and bottomhole pressure as well as real field data sets are used to compare the methods. For linear flow, the Nobakht-Clarkson method yields the best results, although its use is tedious as it requires an iterative procedure. The Chen-Raghavan method for linear flow seems to provide comparable results to the Nobakht-Clarkson method, but does not require iterative procedure. The Ibrahim-Wattenbarger method for linear flow analysis always overestimates flow capacity as compared to the other methods. For boundary dominated flow, the results show that the Agarwal-Gardner FBM method is quite vulnerable to the error in rate/pressure data, while the conventional FBM method is more robust to noise and provides more accurate estimates of gas in place. Among the methods based on the ending time of linear flow, it was found that unit-impulse method based on Behmanesh et al. (2015) provides best results for predicting gas in place.