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C.s. Kabir - One of the best experts on this subject based on the ideXlab platform.
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Material-balance analysis of gas and gas-condensate Reservoirs with diverse drive mechanisms
Journal of Natural Gas Science and Engineering, 2016Co-Authors: C.s. Kabir, B. Parekh, M. A. MustafaAbstract:Abstract Material-balance (MB) analysis for in-place volume estimation in gas Reservoirs has been in practice for decades. Nonlinear responses from geoPressure Reservoirs with or without aquifer influx present special interpretation challenges. One of the main challenges of in-place volume estimates involves the estimation of Average-Reservoir Pressure with production. To that end, modern Pressure sensors installed at bottomhole and/or surface largely help establish a given well's dynamic performance by way of rate-transient analysis. This paper explores the applicability and limitations of the standard analytical tools in volumetric, geoPressure, and waterdrive systems for a diverse array of fluids, from dry gas to near-critical gas/condensate. The systematic approach presented in this paper attempts to increase accuracy in results by ensuring consistency in solutions from multiple methods used to first assess the Average-Reservoir Pressure from production performance data, followed by in-place volume estimation. In this context, we examined analytical tools, such as the pav/z vs. cumulative gas production (Gp) plot, and cumulative Reservoir voidage vs. cumulative total expansion plot. Both pot aquifer and unsteady-state Carter-Tracy aquifer models were considered to account for water influx. Besides the use of Cole and drive indices plots, two diagnostic log-log plots are introduced involving total expansivity and change in Average-Reservoir Pressure. In addition, we sought solution objectivity by introducing a diagnostic tool in the Walsh and Yildiz-McEwen MB plots. Both MB methods involve plotting of cumulative Reservoir voidage (F) vs. cumulative total expansion (Et), whereas the diagnostic tool consists of plotting F/Et vs. Et on the same graph. Initially, synthetic data helped us understand the overall system behavior and instilled confidence in the solutions obtained for various combinations of drive mechanisms. Statistical design of experiments prompted us to explore independent variables, such as aquifer-to-hydrocarbon PV ratio, production rate, degree of overPressure, and the aquifer source. Those learnings were validated with published and new field data encompassing an array of Reservoirs with various drive mechanisms and fluid type.
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analyzing variable rate flow in volumetric oil Reservoirs
Journal of Petroleum Science and Engineering, 2015Co-Authors: Ar R Elgmati, Ralph E Flori, C.s. KabirAbstract:Abstract Estimating Average-Reservoir Pressure ( p av ) and its evolution with time is critical to analyzing and optimizing Reservoir performance. Normally, selected wells are shut in periodically for buildup tests to determine p av 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 loss of revenue. A direct method for estimating p av 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 generally untrue for real wells. This paper extends that approach so that it can be used to analyze field data with variable rates/variable Pressures during boundary-dominated flow (BDF). 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 estimate Average-Reservoir Pressure that uses flowing Pressures and production rates during BDF, 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.
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Quantifying Reservoir connectivity, in-place volumes, and drainage-area Pressures during primary depletion
Journal of Petroleum Science and Engineering, 2012Co-Authors: Omer Izgec, C.s. KabirAbstract:Abstract This study presents an analytical formulation for multiple wells when production interference sets in amongst the wells, including the outer boundaries. This analytical solution estimates the connected pore-volume associated with each well, leading to Average-Reservoir Pressure, and identifies the absence or existence of Reservoir continuity. Only flowing bottomhole Pressure (BHP) and rate data are needed for the analysis; the knowledge of Reservoir geometry or shape factor and Average-Reservoir Pressure is not required. Streamline simulations have aided generation of synthetic cases involving different heterogeneity settings. The new analytical model corroborates the results of those flow simulations. Synthetic examples validate the proposed approach, whereas a field example verifies the notion presented in this study.
Emad Shariff - One of the best experts on this subject based on the ideXlab platform.
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integrated investigation of dynamic drainage volume and inflow performance relationship transient ipr to optimize multistage fractured horizontal wells in tight shale formations
Journal of Energy Resources Technology-transactions of The Asme, 2016Co-Authors: Bin Yuan, Rouzbeh Ghanbarnezhad Moghanloo, Emad ShariffAbstract:This study presents an integrated approach to evaluate the efficiency of fracturing stimulation and predict well production performance. As the Pressure disturbance propagates throughout the Reservoir during long-time transient flow regimes, it will shape an expanding drainage volume. A macroscopic “compressible tank model (CTM)” using weak (integral) form of mass balance equation is derived to relate dynamic drainage volume (DDV) and Average Reservoir Pressure to production history in extremely shale Reservoirs. Fluids and rock compressibility, desorption parameters (for shale or coal gas), and production rates control the speed at which the boundaries advance. After the changes of Average Reservoir Pressure within the expanding drainage volume are obtained, a new empirical inflow performance relationship (transient IPR) correlation is proposed to describe well performance during long transient flow periods in shale Reservoirs. This new empirical correlation shows better match performance with field data than that of conventional Vogel-type IPR curves. The integrated approach of both CTM model and transient IPR correlation is used to determine and predict the optimal fracturing spacing and the size of horizontal section for few wells from one of shale oil plays in U.S. The results suggest the existence of optimal fracture spacing and horizontal well length for multistage fractured horizontal wells in shale oil Reservoirs. In practice, this paper not only provides an insight in understanding the long transient flow production characteristics of shale Reservoirs using concept of expanding drainage volume. Neither methods require comprehensive inputs for the strong form (differential) nor any prior knowledge about the sophisticated shale Reservoir features (shape, size, etc.), the ultimate drainage volume, the ultimate recovery, optimal fracture spacing, and the length of horizontal section for each well can also be easily obtained by this new integrated analytical method.
Jared Schuetter - One of the best experts on this subject based on the ideXlab platform.
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SIMPLIFIED PREDICTIVE MODELS FOR CO₂ SEQUESTRATION PERFORMANCE ASSESSMENT RESEARCH TOPICAL REPORT ON TASK #3 STATISTICAL LEARNING BASED MODELS
2014Co-Authors: Srikanta Mishra, Jared SchuetterAbstract:We compare two approaches for building a statistical proxy model (metamodel) for CO₂ geologic sequestration from the results of full-physics compositional simulations. The first approach involves a classical Box-Behnken or Augmented Pairs experimental design with a quadratic polynomial response surface. The second approach used a space-filling maxmin Latin Hypercube sampling or maximum entropy design with the choice of five different meta-modeling techniques: quadratic polynomial, kriging with constant and quadratic trend terms, multivariate adaptive regression spline (MARS) and additivity and variance stabilization (AVAS). Simulations results for CO₂ injection into a Reservoir-caprock system with 9 design variables (and 97 samples) were used to generate the data for developing the proxy models. The fitted models were validated with using an independent data set and a cross-validation approach for three different performance metrics: total storage efficiency, CO₂ plume radius and Average Reservoir Pressure. The Box-Behnken–quadratic polynomial metamodel performed the best, followed closely by the maximin LHS–kriging metamodel.
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Building Statistical Proxy Models for CO2 Geologic Sequestration
Energy Procedia, 2014Co-Authors: Jared Schuetter, K Srikanta Mishra, Priya Ravi Ganesh, Douglas D. MooneyAbstract:Abstract We compare two approaches for building a statistical proxy model (metamodel) for CO 2 geologic sequestration from the results of full-physics compositional simulations. The first approach involves a classical Box-Behnken experimental design with a quadratic polynomial response surface. The second approach used a space-filling maxmin Latin Hypercube sampling design with the choice of four different meta-modeling techniques: quadratic polynomial, kriging, multivariate adaptive regression spline (MARS) and additivity and variance stabilization (AVAS). Simulations results for CO 2 injection into a Reservoir-caprock system with 9 design variables (and 97 samples) were used to generate the data for developing the proxy models. The fitted models were validated with an independent data set for three different performance metrics: total storage efficiency, CO 2 plume radius and Average Reservoir Pressure. The Box-Behnken–quadratic polynomial metamodel performed the best, followed closely by the maximin LHS–kriging metamodel.
L. Mattar - One of the best experts on this subject based on the ideXlab platform.
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An Improved Pseudo-Time for Gas Reservoirs With Significant Transient Flow
Journal of Canadian Petroleum Technology, 2007Co-Authors: D.m. Anderson, L. MattarAbstract:Abstract The use of semi-analytic methods for correcting flow equations to accommodate changing gas properties with Pressure has become increasingly common. It is a mainstay of modern production decline analysis, as well as gas deliverability forecasting. The use of pseudo-time is one method which enables a time-based correction of gas properties, honouring the gas material balance within the time-based flow equation. By using pseudo-time, the analytical well/Reservoir models, derived for the liquid case (slightly compressible fluid), can be modified for gas by re-evaluating the gas properties as the Reservoir Pressure depletes. These gas correction procedures are well documented in the literature. Also well documented is the iterative nature of the gas properties correction methods, as original gas-in-place is a required input into the equations. The pseudo-time correction is based on the Average Reservoir Pressure and works very well for boundary dominated flow. However, when transient flow prevails, the pseudo-time concept is not valid and its use can create anomalous responses. This will occur in low permeability systems or in Reservoirs with irregular shapes, especially where some of the boundaries are very distant from the well. The semi-analytic gas correction has a ‘representative Pressure’ at its root, which, in the existing models, is always the Average Reservoir Pressure. We propose a straightforward modification to the determination of this Pressure as follows. The representative Pressure ought to be based on a ‘radius of investigation’ or ‘region of influence’ (in the case of non-radial systems), rather than the Average Reservoir Pressure. In the case of a depleting system, the representative Pressure would be the same as the Average Reservoir Pressure. The following paper outlines the proposed procedure and illustrates its advantages over the existing method by using synthetic and field data examples. Introduction Background Literature on the derivation and usage of pseudo-time is prevalent(21,32). The definition that will be used in this paper is shown below: Equation (1) (Available In Full Paper) The above is used in the pseudo-steady-state equation for gas, which is at the core of most modern production decline analysis methods. It is also used in analytical well/Reservoir models, whose conventional formulations are only valid for slightly compressible fluids with constant properties over a given Pressure range. These models enjoy widespread usage for both history matching and forecasting, and their inclusion of pseudo-time for gas Reservoirs is vital. To illustrate the value of pseudo-time, let us take the simple case of a vertical well in the centre of a circular gas Reservoir. We will assume constant rate production and pseudo-steady-state conditions. Thus, the model that describes the Pressure response at the well can be reduced to the pseudo-steady-state equation for gas(5 3). Equation (2) (Available In Full Paper) The ƒ(t) in Equation (2) is the chosen time function. Figure 1 shows the Pressure response plotted against time for two cases: ƒ(t) = time (t) and ƒ(t) = pseudo-time (ta). Also compared is the numerical solution using the same input parameters. Upon comparison of the solutions, it is clear that pseudo-time has a significant impact on the flow equation for gas.
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Dynamic Material Balance-Oil-or Gas-in-Place Without Shut-Ins
Journal of Canadian Petroleum Technology, 2006Co-Authors: L. Mattar, David Mark Anderson, G. StottsAbstract:Reservoir engineers use the material balance calculation method to estimate hydrocarbons-in place. The method consists of producing a certain amount of fluids and measuring the Average Reservoir Pressure before and after production. Mass balance can be calculated if the PVT properties of the system are known. In this study, equations were derived for a volumetric Reservoir with no water drive or external fluid influx. Mass balance calculations are based on obtaining static Reservoir Pressures as a function of cumulative production. Therefore, the wells must be shut-in, in order to determine the Average Reservoir Pressure. The Dynamic Material Balance equation is an extension of the Flowing Material Balance. It is applicable to either constant flow rate or variable flow rate, and can be used for both gas and oil Reservoirs. The Dynamic Material Balance equation converts the flowing Pressure at any point in time to the Average Reservoir Pressure that exists in the Reservoir at a given time. Then, the classical material balance calculations become applicable, and a conventional material balance plot can be generated. The procedure depends on knowing the flow rate and flowing sand face Pressure at any given point in time. The flowing Pressure is used to calculate the Average Reservoir Pressure and the corresponding cumulative production, to calculate the original oil- or gas-in-place by traditional methods. The study showed that it is possible to obtain the Average Reservoir Pressure without shutting-in a well. 7 refs., 5 figs.
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dynamic material balance oil or gas in place without shut ins
Journal of Canadian Petroleum Technology, 2005Co-Authors: L. Mattar, David Mark Anderson, G. StottsAbstract:Material balance calculations for determining oil- or gas-inplace require static Reservoir Pressures, which can only be obtained when the well is shut in. In a previous publication (1) titled "The 'Flowing' Gas Material Balance," it was shown that the Reservoir Pressure could be obtained from the flowing Pressure for wells producing at a constant rate. The "Dynamic Material Balance" is an extension of the "Flowing Material Balance" and can be applied to either constant or variable flow rates. Both methods are applicable for gas and oil. The "Dynamic Material Balance" is a procedure that converts the flowing Pressure at any point in time to the Average Reservoir Pressure that exists in the Reservoir at that time. Once that is done, the classical material balance calculations become applicable, and a conventional material balance plot can be generated. The procedure is graphical and very straightforward: a) knowing the flow rate and flowing sandface Pressure at any given point in time, convert the measured flowing Pressure to the Average Pressure that exists in the Reservoir at that time; and, b) use this calculated Average Reservoir Pressure and the corresponding cumulative production, to calculate the original oil- or gas-inplace by traditional methods. The method is illustrated using data sets.
Bin Yuan - One of the best experts on this subject based on the ideXlab platform.
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integrated investigation of dynamic drainage volume and inflow performance relationship transient ipr to optimize multistage fractured horizontal wells in tight shale formations
Journal of Energy Resources Technology-transactions of The Asme, 2016Co-Authors: Bin Yuan, Rouzbeh Ghanbarnezhad Moghanloo, Emad ShariffAbstract:This study presents an integrated approach to evaluate the efficiency of fracturing stimulation and predict well production performance. As the Pressure disturbance propagates throughout the Reservoir during long-time transient flow regimes, it will shape an expanding drainage volume. A macroscopic “compressible tank model (CTM)” using weak (integral) form of mass balance equation is derived to relate dynamic drainage volume (DDV) and Average Reservoir Pressure to production history in extremely shale Reservoirs. Fluids and rock compressibility, desorption parameters (for shale or coal gas), and production rates control the speed at which the boundaries advance. After the changes of Average Reservoir Pressure within the expanding drainage volume are obtained, a new empirical inflow performance relationship (transient IPR) correlation is proposed to describe well performance during long transient flow periods in shale Reservoirs. This new empirical correlation shows better match performance with field data than that of conventional Vogel-type IPR curves. The integrated approach of both CTM model and transient IPR correlation is used to determine and predict the optimal fracturing spacing and the size of horizontal section for few wells from one of shale oil plays in U.S. The results suggest the existence of optimal fracture spacing and horizontal well length for multistage fractured horizontal wells in shale oil Reservoirs. In practice, this paper not only provides an insight in understanding the long transient flow production characteristics of shale Reservoirs using concept of expanding drainage volume. Neither methods require comprehensive inputs for the strong form (differential) nor any prior knowledge about the sophisticated shale Reservoir features (shape, size, etc.), the ultimate drainage volume, the ultimate recovery, optimal fracture spacing, and the length of horizontal section for each well can also be easily obtained by this new integrated analytical method.
