https://petroleumjournals.online/journals/index.php/reservoir/issue/feed e-journal of reservoir engineering 2008-06-10T11:04:07+00:00 Dr. Abraham Faga afaga@petroleumjournals.online Open Journal Systems e-journal of reservoir engineering is a peer reviewed, open access journal published by Petroleum Journals Online https://petroleumjournals.online/journals/index.php/reservoir/article/view/25 Using Horizontal Wells to Sequester CO2 and Enhance Coalbed Methane Recovery: A Simulation Study of Operating Procedures 2008-06-10T11:04:01+00:00 W. Neal Sams wsams@netl.doe.gov Grant Bromhal grant.bromhal@netl.doe.gov Sinisha A. Jikich sjikic@netl.doe.gov Turgay Ertekin eur@psu.edu Duane H. Smith dsmith@netl.doe.gov Because of increased concern about anthropogenic carbon dioxide emissions, a pilot project is being implemented in northwest West Virginia to study the technical feasibility of carbon dioxide sequestration in unmineable coal seams. The project consists of four 3000 ft horizontal wellbores forming the exterior of a square with four horizontal wellbores at its center. Methane production occurs from all wellbores until the reservoir is sufficiently depleted, then the central wellbores are converted to carbon dioxide injectors while production continues from the exterior wellbores. In our simulations for this project, injection and production continue until the mole fraction of carbon dioxide in the produced gas reaches 0.1. The design factors studied were the lengths and orientations of the central wells, while the operational factors studied were the pressures in the injection wells. We examined both cases where the injectors are oriented perpendicular to the exterior wellbores and cases where the injectors are oriented toward the corners of the squre formed by the outer horizontal wells. The performance of a pilot project is also compared with that of a pattern in a fully-developed field. This comparison clarifies the role of methane produced from outside the isolated pattern, and how this methane must be accounted for in reaching an optimum design for a fully developed field on the basis of the results for the single, isolated-pattern pilot. For a pilot project, operating parameters that give the longest project life also yield the greatest methane production. On the other hand, for a developed field the main factor controlling methane production is sweep. Although the longest injectors have poor sweep efficiency, short injectors represent little improvement over the performance of intermediate length injectors, but they significantly lower production rates. Injection pressure has only a weak effect on total methane production in a developed field. Higher injection pressures result in slightly more methane left in place in unswept areas of the reservoir, but also result in a higher production rate. The sequestration performance for either case is controlled by a combination of sweep efficiency and average pressure in the swept area. The interaction of sweep and reservoir pressure on performance results in a maximum in performance for intermediate length injectors. For low permeability anisotropy the diagonal injectors yield better sequestration performance, but for high anisotropy the perpendicular injectors with unequal lengths perform better. In all cases a long diffusion time constant places an upper limit on injection rates that also yield good performance. 2008-02-27T00:00:00+00:00 Copyright (c) https://petroleumjournals.online/journals/index.php/reservoir/article/view/26 A Numerical Approach to Simulate and Design VAPEX Experiments 2008-06-10T11:04:02+00:00 Luciane Bonet Cunha luciane.cunha@ualberta.ca XinJie Wu xjw2005@yahoo.ca Marcel Polikar marcel.polikar@ualberta.ca The Vapor Extraction (VAPEX) process is a promising technique directed towards heavy oil reservoirs that are typically thin and underlain with water, and cannot be exploited economically or technically by conventional thermal recovery methods. The VAPEX technique was developed by Butler and Mokrys in the 1990s as an alternative to Steam-Assisted Gravity Drainage. This process is mechanistically complex and some questions regarding its expected performance are still pending. A numerical model can play a critical role in addressing important questions about the process. Specifically, a numerical model can predict the performance of the process, especially the occurrence and effect of asphaltenes precipitation during the �upgrading� process. This work proposes an alternative approach to simulate numerically the asphaltene precipitation effect of the VAPEX process. The model was constructed using a commercial thermal reservoir simulator. It was then validated using published experimental data. The effect of relative permeability curves, reaction frequency factor, selection of reactant, apparent dispersion coefficient, and operating parameters on performance were investigated. In addition, the model was used to design a physical experiment. The operating conditions of the experiment were optimized to represent the main mechanisms of the VAPEX process. The results of the study indicate that the numerical model can reproduce the process with acceptable accuracy. Moreover, despite the significant viscosity reduction, it was found that there was no significant evidence to demonstrate blockage of fluid flow through the porous medium due to asphaltene precipitation. Further experiments would be required to confirm these findings. 2008-02-27T00:00:00+00:00 Copyright (c) https://petroleumjournals.online/journals/index.php/reservoir/article/view/27 Predicting Reservoir Performance Using Stochastic Monte Carlo Simulation 2008-06-10T11:04:03+00:00 KINGSLEY EROMOSES ABHULIMEN kabhulimen@Syntechsys.com ABSTRACT Predicting reservoir performance using conventional deterministic models can be tasking, especially for very complicated reservoir systems. Our paper presents the use of Monte Carlo model for simulations; logic and analysis to achieve useful probabilistic stochastic simulations results in a very efficient and visual manner with Microsoft excel spreadsheet. A Monte Carlo simulation run was carried out for a typical representative reservoir data. The simple Darcy equation was used as the deterministic model while the normal distribution model was employed as the probabilistic density function model. These models were used to construct a stochastic simulation algorithm to predict performance of reservoir systems. Our work analysed 5000 runs using random inputs. By using random inputs, we are essentially turning the deterministic model into a stochastic model which is then solved iteratively over the chosen number of runs. The darcy equation was used as the deterministic model and it was evaluated using a single well data from the reservior data table. A comparison of the deterministic result [5,219.83], for the single run gave a stochastic value of [3,565.34] for the Monte Carlo Simulation [5430.49], and second run gave a more accurate stochastic value [5,234.07], shows that multiple run can achive closeness to actual result through the Monte Carlo Method. The result being quite close to the deterministic value on second run demonstrated that the Monte Carlo iteration can achive a high enough to reliable estimates multiple runs. Various statistical simulators were also employed to display the standard deviation of the range of generated data from the mean and the standard error was also calculated. 2008-02-26T00:00:00+00:00 Copyright (c) https://petroleumjournals.online/journals/index.php/reservoir/article/view/28 New Deconvolution Methods for Well Test and Production Data Analysis 2008-06-10T11:04:06+00:00 Mircea Andrecut mandrecu@ucalgary.ca The deconvolution method has received much attention recently, and is becoming one of the major tools for well test and production data analysis. Here, we present several new deconvolution algorithms, which we believe that are relevant and can be an important addition to the existing efforts made in this field. We show that the solution of the deconvolution problem can be successfully represented as a linear combination of exponential basis functions. We present three deconvolution algorithms. The first two algorithms are based on regularization concepts borrowed from the well-known Tikhonov and Krylov methods, while the third algorithm is based on the stochastic Monte Carlo method. 2008-02-25T00:00:00+00:00 Copyright (c) https://petroleumjournals.online/journals/index.php/reservoir/article/view/29 Determination of Water Breakthrough Time in Noncommunicating 2008-06-10T11:04:06+00:00 khaled Abdalla Elraies alrayes2006@yahoo.co.uk Mat Hussin Yunan mhussin@fkkksa.utm.my The original Buckley-Leverett fractional flow formula has been extended and more detailed formulation of waterflooding behavior in a multilayered system is presented. In this paper, the layers are assumed to communicate only in the wellbores, and the reservoir may be represented as linear system. Most previous investigations of this nature were limited by assumptions. This study improves on previous work by applying Buckley-Leverett displacement theory to a noncommunicating layered reservoir where permeability, porosity and thickness vary from layer to layer except the oil-water relative permeability and oil viscosity are assumed the same for all layers. Gravity and capillary pressure effects are neglected. These particular considerations have been given to the evaluation of breakthrough time for each layer as a function of cumulative water injection into that layer at the breakthrough. To verify the modified method, calculations were performed a three layered reservoir at three different cases of mobility ratios and compared with Prats et al�s method. It is shown that the breakthrough times in the layer with the lowest permeability-thickness product (kh) are in very good agreement with Prats et al�s method. However, breakthrough times for the layer with the highest kh are slightly different from Prats et al�s method. 2008-02-25T00:00:00+00:00 Copyright (c) https://petroleumjournals.online/journals/index.php/reservoir/article/view/30 Accounting for Interpreted Well Test Pore Volumes in Reservoir Modeling 2008-06-10T11:04:07+00:00 Luciane Bonet Cunha luciane.cunha@ualberta.ca Linan Zhang lzhang@inco.com Clayton Deutsch cdeutsch@ualberta.ca Optimal reservoir management requires reliable reservoir performance forecasts with as little uncertainty as possible. There is a need for improved techniques for dynamic data integration to construct realistic reservoir models by using geostatistical techniques. This paper gives a method to create porosity models that honor interpreted pore volumes from well test data. Well porosity data, seismic data and well test results are integrated in sequential simulation. Seismic data is modified iteratively until the co-simulated porosity matches the interpreted well test pore volume. A number of examples are shown. 2008-02-25T00:00:00+00:00 Copyright (c)