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Abstract Superposition-time functions offer an effective way for handling variable-rate data. However, these functions can also be biased and misleading. The superposition approach may generally be more useful for well-test analysis (constant rate solutions) than rate-transient analysis. Calculated data points do not tend to be sequential with superposition time but do tend to fall on a straight line corresponding to the superposition function chosen. Examples of superposition are logarithm of time (infinite acting vertical wells) and material balance time (boundary dominated flow). Production data from shale gas wells are usually subjected to operating issues that yield noises and outliers. When the rate data are noisy or contain outliers, distinguishing their effects from common regime will be difficult if the superposition time functions are used as a plotting time function on log-log plots. The superposition function may then lead to a log-log plot that has erroneous straight-line segments. A simple technique is presented to rapidly check whether or not there is data bias on the superposition-time specialized plots. The technique is based on evaluating the superposition time function of each flow regime for the maximum production time. Whatever data are beyond the maximum production time (MPT) are considered as biased data and depend on the superposition function chosen. A workflow involving different diagnostic and filtering techniques is proposed. Different synthetic examples and field examples are used in this study. Once all the problematic issues were detected and filtered out, it was clear that superposition time data beyond the MPT is biased and should be ignored. Thus, the proposed MPT technique can be relied on to detect and filter out biased data points on superposition-time log-log plots. Both raw and filtered data were analyzed using type-curve matching of linear-flow typecurves developed by Wattenbarger et al. (1998) for calculating the original gas in place (OGIP). It has been found that biased data yield a noticeable reduction in OGIP. Such reduction is attributed to the early fictitious onset of boundary dominated flow.
Abstract Estimating average-reservoir pressure (pav) and its evolution with time is critical to analyzing and optimizing reservoir performance. Conventionally, selected wells are shut in periodically for buildup tests to determine pav over time. Unfortunately, shutting-in wells leads to loss of production. Today, however, real-time surveillance—the continuous measurement of flowing pressures and rate data from the oil and gas wells—offers an attractive alternative technique to obtain average-reservoir pressure while avoiding revenue loss. A direct method for estimating pav from flowing pressures and rate data is available. However, the method is for an idealized case that assumes constant production rate during pseudosteady-state (PSS) flow, which is not generally true for real wells. This paper extends that approach so that it can be used to analyze field data with variable rates/variable pressure during PSS flow. This approach is based on a combination of rate-normalized pressure and superposition-time function. The mathematical basis is presented in support of this approach, and the method is validated with synthetic examples and verified with field data. This modified approach is used to make direct estimation of average-reservoir pressure that uses flowing pressures and production rates during PSS flow, allowing the classical material balance calculations to be performed. These calculations, in turn help determine the reserves, recovery factor, and reservoir drive mechanisms, allowing the reservoir performance and management to be properly evaluated. Furthermore, this method can be used to calculate both connected oil volume and reservoir drainage area as a function of time. Finally, this approach provides a reasonable estimation of the reservoir's shape factor.
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.
Abstract Unconventional wells often show linear flow. Rate Transient Analysis (RTA) so far has only concentrated on the primary (early-time) linear flow. However, real production data has often shown more than one transient flow regimes. There are only few studies that focus on analyzing the flow regimes following the primary linear flow. It is not clear how to deal with the transition period as well as the compound (late-time) linear flow. When does the transition start? How long does the transition last? Does compound linear flow always exist? What are the diagnostic values of analyzing the period of transition to compound linear flow? This work answers these questions. We developed a dimensionless typecurve for a single multi-fractured horizontal well (large inter-well spacing). We investigated the end of the primary linear flow, the duration of the transition and the start of the compound linear flow, for different fracture spacing to fracture half-length ratios. We investigated the effect of skin and superposition time functions. In the end, we proposed a workflow to analyze the production data from multiple-fractured horizontal wells by using the newly developed typecurve, and we presented a field example to show the application of the proposed methodology.
The concept of a continuous succession of steady states is applied to obtain a solution to the nonlinear partial differential equation describing the transient flow of a pressure-dependent fluid through a stress-sensitive formation. This equation also was solved numerically to check the validity of the succession of steady states solution.
Porous media are not always rigid or nondeformable. Porous media are not always rigid or nondeformable. Usually, average values are used for both pressure-dependent rock and fluid properties. This method pressure-dependent rock and fluid properties. This method reduces the errors involved, but generally does not eliminate them.
In the diffusivity equation, the diffusivity is a constant independent of pressure. When both pressure changes and property changes are small, the constant property assumption is justified. If, however, rock and fluid property changes are important over the pressure range property changes are important over the pressure range of interest, then these changes cannot be neglected, and a variable property solution should be obtained.
Raghavan et al. derived a flow equation stating that rock and fluid properties vary with pressure. This equation, when expressed as a function of a pseudopressure, m(p), resembles the diffusivity equation. Samaniego et al. studied this problem for a greater variety of flow conditions. The diffusivity-like equation that describes this pressure-dependent flow is similar to the differential equation describing the flow of either an ideal or real gas through porous media. The concept of "a continuous succession of steady states" was applied successfully by several authors to obtain a solution for the nonlinear partial differential equation describing the transient flow of gas through porous media. This same method is used here to find an approximate solution for the transient-pressure dependent flow problem.
To date no general correlations have been available to predict reservoir performance when reservoir rock and predict reservoir performance when reservoir rock and fluid properties are general functions of pressure. This paper presents a performance-prediction procedure based paper presents a performance-prediction procedure based on the drainage radius concept and a material-balance equation. Radial- and linear-bounded systems are considered. Using this method, the sandface pressure and the average reservoir pressure are calculated easily. Results were obtained for five different sets of rock and fluid property data. Solutions of general utility can be obtained for engineering problems without using a digital computer.
The method described here is based on the assumptions usually used in well testing theory. We assume horizontal fluid flow with no gravity effects, a fully penetrating well, an isothermal single-phase fluid obeying Darcy's law, an isotropic and homogeneous formation, and purely elastic rock properties (physical property changes purely elastic rock properties (physical property changes with stress changes are reversible).
The assumption of horizontal flow is not quite valid because of change in porosity and reservoir rock thickness with fluid pressure. However, Samaniego showed that the vertical component of flow is negligible for most rock and fluid properties of interest and can be neglected. Gavalas and Seinfel also assumed this.
The rock properties needed in the flow equation as functions of pressure are porosity, permeability, and pore compressibility. pore compressibility. JPT