SPE Members Abstract Recently three dimensional streamline modeling of multiphase flow has gained increasing popularity. It has also become an important tool as a fast and reliable flow simulator for solving inverse problems in reservoir characterization. However, field scale application of three dimensional streamline modeling has been rather limited. The difficulties with regard to field applications have been changing well configurations as a result of infill drilling, zone isolations, recompletions, etc. A critical issue here is the remapping of streamlines and hence, fluid saturations as the dynamics of field conditions dictate. Past efforts to handle infill drilling during streamline simulation have been to average streamlines over an underlying grid and then to proceed with numerical computations along streamlines. Such an approach undermines one of the major strengths of streamline modeling, which in addition to the fast solution, is to preserve the self-sharpening nature of the saturation fronts during waterflooding Averaging of streamlines in conjunction with the lower order numerical solution of multiphase flow equations along streamlines lead to a significant loss in accuracy. We present two major improvements to the existing streamline modeling. First, instead of averaging streamlines during changing well conditions, we used a 3-D mapping algorithm for streamlines. Thus, we perform a mapping of streamlines to streamlines rather than streamlines to grid blocks whenever field conditions change. Second, along streamlines we use a third-order Total Variation Diminishing (TVD) scheme to solve the multiphase flow equations to minimize numerical dispersion, and prevent any nonphysical oscillations. We demonstrate these improvements by comparison with high resolution numerical simulations using both synthetic as well as field examples. The results clearly indicate the power and versatility of the approach for large-scale field application. Introduction Streamline approach to modeling multidimensional, multiphase flow essentially comprises of two steps: generating streamlines in 3D space and then solving the 1D governing equations analytically or numerically along the streamlines. Streamlines can be generated from an underlying velocity (and thus, pressure) field using the transit time algorithm as outlined by Datta-Gupta and King. Multiphase flow equations can then be solved in travel time coordinates which greatly facilitate analytical as well as numerical solution. These aspects of streamline modeling are further explored in this paper. The streamline approach applied to waterflooding essentially decouples the pressure and saturation solutions. Since for typical waterfloods the total mobility is a rather weak function of saturation, the streamlines do not shift significantly with time and thus needs to be updated only infrequently. This can result in very significant savings in computation time as reported by several authors. Streamline simulation preserves sharp fronts by minimizing numerical dispersion and allows for dynamic data integration during reservoir characterization, as well as uncertainty evaluation using multiple geostatistical realizations. Another advantage is the simplicity with which streamlines may be used to visualize three-dimensional flow from arbitrary well patterns in heterogeneous reservoirs. Till now, application of 3D streamline modeling of multiphase flow has been limited to simple pattern configurations, e.g. 5-spots or line drives. We report in this paper what we believe is the first 3D field application involving multiple patterns with irregular pattern geometry and changing well configurations. In addition, we present two major modifications made to an existing multiphase, three dimensional streamline simulator making it suitable for field scale waterflood applications. First, to prevent smearing of saturation and concentration fronts, we map these quantities from streamlines onto streamlines using a 3D interpolation algorithm that uses a Modified Quadratic Shepard method. The 3-D mapping algorithm is robust, computationally efficient and does not lead to any significant smearing of saturation fronts. Second, we implemented along each streamline a higher order numerical solution that is Total Variation Diminishing (TVD) and thus does not lead to non-physical oscillations while preserving the sharp fronts. This is achieved by discretizing each streamline along travel time coordinates and defining a third order flux term that includes anti-dispersion corrective term. P. 265^
Certain reservoirs have ll. recurring wellbore damage problem caused by deposition of solid paraffin particles in the pore space. This paper describes the simulation of the reservoir processes of paraffin precipitation, convection, and deposition. The effect of reservoir heating treatments is included. IntroductionMost paraffin solids are mixtures of hydrocarbons ranging from C I8 H 38 to C 70 H 172 . Deposition of these thick, waxy substances in wellbores and production facilities can reduce operating efficiency. However, certain reservoirs also have paraffin deposition in the pore space, causing productivity damage. These reservoirs are the subject of this paper.
SPE Members Abstract Geostatistical techniques generate fine-scale reservoir description that can integrate a variety of data such as cores, logs, and seismic traces. However, predicting dynamic behavior of fluid flow through multiple fine-scale realizations has still remained an illusive goal. Typically an upscaling algorithm is applied to obtain a coarse scale heterogeneity model. Most of the upscaling algorithms are based on single phase pressure solution and are thus questionable at best for multiphase flow applications. Pseudo-relative permeabilities have often been used as a tool for multiphase flow upscaling But such approaches are highly process dependent and thus, have limited applicability. We describe a powerful, versatile, multiphase three dimensional streamline simulator for integrating fine-scale reservoir descriptions with dynamic performance predictions. Unlike conventional streamtube models, the proposed approach relies on the observation that in a velocity field derived by finite difference, streamlines can be approximated by piece-wise hyperbolas within grid blocks. Thus, the method can be easily applied in 3-D and incorporated into conventional finite-difference simulators. Once streamlines are generated in three dimensions, a variety of one dimensional problems can be solved analytically along the streamlines. The power and utility of the streamline simulator is demonstrated through application to a detailed characterization and waterflood performance of the La Cira field, Colombia, South America. We illustrate the advantage of the streamline simulator through comparisons with a commercial simulator for a waterflood pattern. The streamline simulator is shown to be orders of magnitude faster than traditional numerical simulators and does not suffer from numerical dispersion or instability. We illustrate the use of this simulator for evaluation of multiple, fine-scale realizations of heterogeneity models and quantification of uncertainty in predicting dynamic behavior of fluid flow. Introduction A geostatistical approach is commonly used to reproduce reservoir heterogeneities1. The objective is to generate a few "typical descriptions incorporating heterogeneity elements that are difficult to include by conventional methods. Conditional simulation is used for creating property (permeability, porosity, etc.) distribution with a prescribed spatial correlation structure that honors measured data at well locations. Stochastic reservoir modeling provides multiple equiprobable, reservoir models, all data intensive, rather than a single, smooth usually data poor deterministic model. Experience has shown that these data intensive, stochastic reservoir models yield a better history match of production data, yet provide a measure of uncertainty in prediction of future performance. Fine-scale realizations are the most detailed representation of the heterogeneities that exist in the petroleum reservoir. The ideal flow simulation process would be to input this fine-scale data in its entirety. However conventional numerical simulators do not allow this readily. Reservoir models built for conventional simulators using the fine-scale data are huge and unmanageable. The flow simulation process thus becomes very tedious, slow and expensive. This is in addition to any hardware limitations that may exist. Typically an upscaling algorithm is applied to obtain a coarse-scale heterogeneity model. This coarse-scale model is then input into the conventional simulators. However, most of the upscaling algorithms are based on single phase pressure solution and are thus questionable at best for multiphase flow applications. Pseudo-relative permeabilities have often been used as a tool for multiphase flow upscaling But such approaches are highly process dependent and have limited applicability. There is a definite need for a fast and powerful simulator that allows the easy use of fine-scale realizations as such without the need for any upscaling. In this paper we describe a new, fully three-dimensional, multiphase, streamline simulator for modeling waterflood performance. P. 195
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.