Browsing by Subject "unconventional reservoirs"
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Item Applying Decline Curve Analysis in the Liquid-rich Shales: Eagle Ford Shale Study(2014-01-09) Indras, PurviWith the emergence of liquid rich shale (LRS) plays like Eagle Ford and Northern Barnett, the petroleum industry needs a simple, easily applied technique that provides reliable estimates of future production rates in this kind of reservoir. There is no guarantee that methodology that has proved to work in gas reservoirs will necessarily be appropriate in LRS reservoirs. In this work, we found that without corrections of early data, the Stretched Exponential Production Decline (SEPD) model, designed for transient flow, usually produces pessimistic forecasts of future production. The Duong method, another transient model, may be reasonable during long term transient linear flow, but notably optimistic after boundary-dominated flow (BDF) appears. For wells in BDF, the Arps model provides reasonable forecasts, but the Arps model may not be accurate when applied to transient data. A hybrid of early transient and later BDF models proves to be a reasonable solution to the forecasting problem in LRS. In addition, use of diagnostic plots (like log-log rate-time and log-log rate-material balance time plots) improves confidence in flow regime identification and production forecasting. In some LRS?s, BDF is observed within 12 months. In any case, it is essential to identify or to estimate the time to reach BDF and to discontinue use of transient flow models after BDF appears or is expected. We validated our methodology using ?hindcast analysis?; that is, matching the first half of production history to determine model parameters, then forecasting the second half of history and comparing to observed production data. We also found that application of pressure-corrected rates in decline curve analysis (DCA) may substantially improve the interpretation of data from unconventional oil wells flowing under unstable operating conditions. Fetkovich (hydraulically fractured well) type curve analysis can be added to improve confidence in flow regime identification from diagnostic plots and to estimate the Arps hyperbolic exponent b from the matching b stem on the type curve, which can then be extrapolated to determine estimated ultimate recovery.Item Fast Marching Methods: Application via Integration with Commercial E&P Software(2014-10-16) Al-Rukabi, MuhammedDevelopment and production of unconventional reservoirs, especially shale, are on the rise and so is the need to better understand drainage volumes, reliably estimate reservoir properties, and forecast well performance. Numerical simulation and analytical techniques, like decline curve analysis and pressure transient analysis, have been applied to unconventional resources. However, analytical methods rely on several simplifications and while numerical simulation can account for complex geological models it is computationally expensive. Fast Marching Methods (FMM), being a semi-analytical calculation, is between the two approaches and retains the simplicity of the analytical approach while achieving the desired generality. The generalization of the concept of depth of investigation to heterogeneous reservoirs utilizes the idea of diffusive time-of-flight and better accounts for the non-uniform pressure fronts that may be distorted due to heterogeneity effects. The pressure front propagation is obtained by solving the Eikonal equation, which is derived from an asymptotic solution of the diffusivity equation. The FMM solves the Eikonal equation very efficiently using a single non-iterative solution, making it very fast. The FMM estimates the drainage volume and the diffusive time of flight can be used as a spatial coordinate to reduce the 3D diffusivity equation into a 1D equation allowing for rapid forecasting of well pressure and rate performance. In this work, the FMM is implemented into an application plug-in and is integrated with a common commercial E&P software platform. The integration of the FMM Plug-in capitalizes on the simplicity, intuitive appeal, power and utility of the approach, like providing the time-evolution of the drainage volume for visualization, and utilizes the software platform features, like state-of-the-art visualization tools. This work also includes a number of applications that demonstrate the capability of FMM Plug-in to calculate the drainage volume and forecast well pressure or rate performance and validate its results against an industry-reference finite difference simulator. Finally, a study on the scalability of calculations runtime demonstrate the speed advantage that FMM has over finite difference simulators.Item Pressure Normalization of Production Rates Improves Forecasting Results(2013-08-07) Lacayo Ortiz, Juan ManuelNew decline curve models have been developed to overcome the boundary-dominated flow assumption of the basic Arps? models, which restricts their application in ultra-low permeability reservoirs exhibiting long-duration transient flow regimes. However, these new decline curve analysis (DCA) methods are still based only on production rate data, relying on the assumption of stable flowing pressure. Since this stabilized state is not reached rapidly in most cases, the applicability of these methods and the reliability of their solutions may be compromised. In addition, production performance predictions cannot be disassociated from the existing operation constraints under which production history was developed. On the other hand, DCA is often carried out without a proper identification of flow regimes. The arbitrary application of DCA models regardless of existing flow regimes may produce unrealistic production forecasts, because these models have been designed assuming specific flow regimes. The main purpose of this study was to evaluate the possible benefits provided by including flowing pressures in production decline analysis. As a result, it have been demonstrated that decline curve analysis based on pressure-normalized rates can be used as a reliable production forecasting technique suited to interpret unconventional wells in specific situations such as unstable operating conditions, limited availability of production data (short production history) and high-pressure, rate-restricted wells. In addition, pressure-normalized DCA techniques proved to have the special ability of dissociating the estimation of future production performance from the existing operation constraints under which production history was developed. On the other hand, it was also observed than more consistent and representative flow regime interpretations may be obtained as diagnostic plots are improved by including MBT, pseudovariables (for gas wells) and pressure-normalized rates. This means that misinterpretations may occur if diagnostic plots are not applied correctly. In general, an improved forecasting ability implies greater accuracy in the production performance forecasts and more reliable reserve estimations. The petroleum industry may become more confident in reserves estimates, which are the basis for the design of development plans, investment decisions, and valuation of companies? assets.