Applying Streamline Method for Viscoplastic Oil Flow Simulation

2019 ◽  
Author(s):  
Yan Nevmerzhitskiy
Keyword(s):  
Flow Simulation ◽  
Oil Flow ◽  
Streamline Method

Implementation of a Streamline Method For Flow Simulation of Large Fields

10.2118/96-55 ◽  
1996 ◽  
Author(s):  
R.A. Behrens ◽  
R.C. Jones ◽  
A.S. Emanuel
Keyword(s):  
Flow Simulation ◽  
Streamline Method

scholarly journals Using data analytics to quantify the impact of production test uncertainty on oil flow rate forecast

2020 ◽  
Vol 75 ◽  
pp. 7 ◽  
Author(s):  
Danielle D. Monteiro ◽  
Maria Machado Duque ◽  
Gabriela S. Chaves ◽  
Virgílio M. Ferreira Filho ◽  
Juliana S. Baioco
Keyword(s):  
Multiphase Flow ◽  
Flow Rate ◽  
Data Analytics ◽  
Flow Analysis ◽  
Flow Simulation ◽  
Production Test ◽  
Total Production ◽  
Oil Flow ◽  
Using Data ◽  
The Impact

In general, flow measurement systems in production units only report the daily total production rates. As there is no precise control of individual production of each well, the current well flow rates and their parameters are determined when production tests are conducted. Because production tests are performed periodically (e.g., once a month), information about the wells is limited and operational decisions are made using data that are not updated. Meanwhile, well properties and parameters from the production test are typically used in multiphase flow models to forecast the expected production. However, this is done deterministically without considering the different sources of uncertainties in the production tests. This study aims to introduce uncertainties in oil flow rate forecast. To do this, it is necessary to identify and quantify uncertainties from the data obtained in the production tests, consider them in production modeling, and propagate them by using multiphase flow simulation. This study comprises two main areas: data analytics and multiphase flow simulation. In data analytics, an algorithm is developed using R to analyze and treat the data from production tests. The most significant stochastic variables are identified and data deviation is adjusted to probability distributions with their respective parameters. Random values of the selected variables are then generated using Monte Carlo and Latin Hypercube Sampling (LHS) methods. In multiphase flow simulation, these possible values are used as input. By nodal analysis, the simulator output is a set of oil flow rate values, with their interval of occurrence probabilities. The methodology is applied, using a representative Brazilian offshore field as a case study. The results show the significance of the inclusion of uncertainties to achieve greater accuracy in the multiphase flow analysis of oil production.

Adaptive Multiscale Streamline Simulation and Inversion for High-Resolution Geomodels

SPE Journal ◽  
2008 ◽  
Vol 13 (01) ◽  
pp. 99-111 ◽  
Author(s):  
Vegard R. Stenerud ◽  
Vegard Kippe ◽  
Knut-Andreas Lie ◽  
Akhil Datta-Gupta
Keyword(s):  
High Resolution ◽  
History Matching ◽  
Flow Simulation ◽  
Basis Functions ◽  
Time Inversion ◽  
Fine Scale ◽  
Dynamic Data ◽  
Travel Time Inversion ◽  
Production Response ◽  
Streamline Method

Summary A particularly efficient reservoir simulator can be obtained by combining a recent multiscale mixed finite-element flow solver with a streamline method for computing fluid transport. This multiscale-streamline method has shown to be a promising approach for fast flow simulations on high-resolution geologic models with multimillion grid cells. The multiscale method solves the pressure equation on a coarse grid while preserving important fine-scale details in the velocity field. Fine-scale heterogeneity is accounted for through a set of generalized, heterogeneous basis functions that are computed numerically by solving local flow problems. When included in the coarse-grid equations, the basis functions ensure that the global equations are consistent with the local properties of the underlying differential operators. The multiscale method offers a substantial gain in computation speed, without significant loss of accuracy, when basis functions are updated infrequently throughout a dynamic simulation. In this paper, we propose to combine the multiscale-streamline method with a recent "generalized travel-time inversion" method to derive a fast and robust method for history matching high-resolution geocellular models. A key point in the new method is the use of sensitivities that are calculated analytically along streamlines with little computational overhead. The sensitivities are used in the travel-time inversion formulation to give a robust quasilinear method that typically converges in a few iterations and generally avoids much of the time-consuming trial-and-error seen in manual history matching. Moreover, the sensitivities are used to enforce basis functions to be adaptively updated only in areas with relatively large sensitivity to the production response. The sensitivity-based adaptive approach allows us to selectively update only a fraction of the total number of basis functions, which gives substantial savings in computation time for the forward flow simulations. We demonstrate the power and utility of our approach using a simple 2D model and a highly detailed 3D geomodel. The 3D simulation model consists of more than 1,000,000 cells with 69 producing wells. Using our proposed approach, history matching over a period of 7 years is accomplished in less than 20 minutes on an ordinary workstation PC. Introduction It is well known that geomodels derived from static data only—such as geological, seismic, well-log, and core data—often fail to reproduce the production history. Reconciling geomodels to the dynamic response of the reservoir is critical for building reliable reservoir models. In the past few years, there have been significant developments in the area of dynamic data integration through the use of inverse modeling. Streamline methods have shown great promise in this regard (Vasco et al. 1999; Wang and Kovscek 2000; Milliken et al. 2001; He et al. 2002; Al-Harbi et al. 2005; Cheng et al. 2006). Streamline-based methods have the advantages that they are highly efficient "forward" simulators and allow production-response sensitivities to be computed analytically using a single flow simulation (Vasco et al. 1999; He et al. 2002; Al-Harbi et al. 2005; Cheng et al. 2006). Sensitivities describe the change in production responses caused by small perturbations in reservoir properties such as porosity and permeability and are a vital part of many methods for integrating dynamic data. Even though streamline simulators provide fast forward simulation compared with a full finite-difference simulation in 3D, the forward simulation is still the most time-consuming part of the history-matching process. A streamline simulation consists of two steps that are repeated:solution of a 3D pressure equation to compute flow velocities; andsolution of 1D transport equations for evolving fluid compositions along representative sets of streamlines, followed by a mapping back to the underlying pressure grid. The first step is referred to as the "pressure step" and is often the most time-consuming. Consequently, history matching and flow simulation are usually performed on upscaled simulation models, which imposes the need for a subsequent downscaling if the dynamic data are to be integrated in the geomodel. Upscaling and downscaling may result in loss of important fine-scale information.

THE EFFECT OF HELICAL GROOVE PRESENCE ON THE TRIBOLOGICAL PERFORMANCE OF JOURNAL BEARINGS

Tribologia ◽  
2018 ◽  
Vol 279 (3) ◽  
pp. 131-138
Author(s):  
Jarosław SĘP ◽  
Leszek TOMCZEWSKI ◽  
Lidia GAŁDA
Keyword(s):  
Load Capacity ◽  
Three Dimensional ◽  
Flow Simulation ◽  
Equation System ◽  
Journal Bearings ◽  
Operating Conditions ◽  
Static Characteristics ◽  
Hydrodynamic Bearings ◽  
Oil Flow ◽  
Helical Groove

The hydrodynamic bearings could suffer critical damages operating in contaminated environments that cause machine breakdown. In such hard operating conditions, hydrodynamic bearings with grooved journals are less sensitive to damage compared to plain bearings. The wear resistance of the grooved journal bearings is several times greater than that of smooth journal bearings. Contaminants existing in the oil film are moved out from the bearing clearance by the groove created on the journal surface. The presence, shape, and geometry of the groove strongly influence the bearings performance. The aim of this article is to study the selected static characteristics of bearings consisting of a journal with the helical groove on its surface. The static characteristics were determined based on the flow simulation in the oil clearance. A three-dimensional, adiabatic model of the oil flow was assumed. The oil flow was described with the Navier-Stokes continuity and energy equations. The equation system was solved by the finite volume method. The numerical model of the flow was verified experimentally on a test stand. It has been established that the grooved journal application leads to a decrease of load capacity in whole range of eccentricity and for all examined clearances. The oil flow rate increase was mainly observed due to spiral groove presence on the shaft.

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