scholarly journals Gas-condensate banking and well deliverability - a comparative study using analytical- and numerical models

2016 ◽  
Vol 33 (2) ◽  
pp. 259
Author(s):  
Jann Ursin
Keyword(s):  
Comparative Study ◽  
Numerical Models ◽  
Gas Condensate

An Equation of State Compositional Model

1980 ◽  
Vol 20 (05) ◽  
pp. 363-376 ◽  
Author(s):  
Keith H. Coats
Keyword(s):  
Equation Of State ◽  
Critical Point ◽  
Oil And Gas ◽  
Numerical Models ◽  
Volatile Oil ◽  
Gas Condensate ◽  
Numerical Dispersion ◽  
Stable Convergence ◽  
Compositional Model ◽  
Miscible Flooding

Abstract This paper describes an implicit, three-dimensional formulation for simulating compositional-type reservoir problems. The model treats three-phase flow in Cartesian (x-y-z) or cylindrical (r-theta-z) geometries. Applicability ranges from depletion or cycling of volatile oil and gas condensate to miscible flooding operations involving either outright or multicontact-miscibility.The formulation uses an equation of state for phase equilibrium and property calculations. The equation of state provides consistency and smoothness as gas- and oil-phase compositions and properties converge near a critical point. This avoids computational problems near a critical point associated with use of different correlations for K values as opposed to phase densities. Computational testing with example multicontact-miscibility (MCM) problems indicates stable convergence of this formulation as phase properties converge at a critical point. Results for these MCM problems show significant numerical dispersion, primarily affecting the calculated velocity of the miscible-front advance. Our continuing effort is directed toward reduction of this numerical disperson and comparison of model results with laboratory experiments for both MCM and outright-miscibility cases.We feel that the implicit nature of the model enhances efficiency as well as reliability for most compositional-type problems. However, while we report detailed problem results and associated computing times, we lack similar reported times to compare the overall efficiency of an implicit compositional formulation with that of a semi-implicit formulation. Introduction Many papers have treated increasingly sophisticated or efficient methods for numerical modeling of black-oil reservoir performance. That type of reservoir allows an assumption that reservoir gas and oil have different but fixed compositions, with the solubility of gas in oil being dependent on pressure alone.A smaller number of papers have presented numerical models for simulating isothermal "compositional" reservoirs, where oil and gas equilibrium compositions vary considerably with spatial position and time. With some simplification, the reservoir problems requiring compositional treatment can be divided into two types. The first type is depletion and/or cycling of volatile oil and gas condensate reservoirs. The second type is miscible flooding with MCM generated in situ.A distinction between these types is that the first usually involves phase compositions removed from the critical point, while the second type generally requires calculation of phase compositions and properties converging at the critical point. A compositional model should be capable of treating the additional problem of outright miscibility where the original oil and injected fluid are miscible on first contact.A difficulty in modeling the MCM process is achievement of consistent, stable convergence of gas-and oil-phase compositions, densities, and viscosities as the critical point is approached. A number of studies have reported models that use different correlations for equilibrium K-values as opposed to phase densities. Use of an equation of state offers the advantage of a single, consistent source of calculated K-values, phase densities, and their densities near a critical point. SPEJ P. 363＾

A Compositional Rescaled Exponential Model for Multiphase-Production-Performance Analysis of Boundary-Dominated Gas/Condensate Reservoirs

SPE Journal ◽  
2018 ◽  
Vol 24 (02) ◽  
pp. 618-646
Author(s):  
Ryan Will ◽  
Qian Sun ◽  
Luis F. Ayala
Keyword(s):  
Performance Analysis ◽  
Numerical Models ◽  
Compositional Analysis ◽  
Gas Condensate ◽  
Production Performance ◽  
Analytical Models ◽  
Reservoir Modeling ◽  
Well Performance ◽  
Reservoir Performance ◽  
Hydrocarbon Reservoir

Summary Hydrocarbon-reservoir-performance forecasting is an integral component of the resource-development chain and is typically accomplished using reservoir modeling, by means of either numerical or analytical methods. Although complex numerical models provide rigorous means of capturing and predicting reservoir behavior, reservoir engineers also rely on simpler analytical models to analyze well performance and estimate reserves when uncertainties exist. Arps (1945) empirically demonstrated that certain reservoirs might decline according to simple, exponential, hyperbolic, or harmonic relationships; such behavior, however, does not extend to more-complex scenarios, such as multiphase-reservoir depletion. Because of this limitation, an important research area for many years has been to transform the equations governing flow through porous media in such a way as to express complex reservoir performance in terms of closed analytical forms. In this work, we demonstrate that rigorous compositional analysis can be coupled with analytical well-performance estimations for reservoirs with complex fluid systems, and that the molar decline of individual hydrocarbon-fluid fractions can be expressed in terms of rescaled exponential equations for well-performance analysis. This work demonstrates that, by the introduction of a new partial-pseudopressure variable, it is possible to predict the decline behavior of individual fluid constituents of a variety of gas/condensate-reservoir systems characterized by widely varying richness and complex multiphase-flow scenarios. A new four-region-flow model is proposed and validated to implement gas/condensate-deliverability calculations at late times during variable-bottomhole-pressure (BHP) production. Five case studies are presented to support each of the model capabilities stated previously and to validate the use of liquid-analog rescaled exponentials for the prediction of production-decline behavior for each of the hydrocarbon species.

Comparative study of numerical models of the laser forming process

2015 ◽  
Vol 27 (S2) ◽  
pp. S29105 ◽  
Author(s):  
Alberto Torres Cruz ◽  
Dirk F. de Lange ◽  
Hugo I. Medellín Castillo
Keyword(s):  
Comparative Study ◽  
Numerical Models ◽  
Laser Forming ◽  
Forming Process

A comparative study of different numerical models for predicting train noise in high-rise cities

2006 ◽  
Vol 67 (5) ◽  
pp. 432-449 ◽  
Author(s):  
W.K. Lui ◽  
K.M. Li ◽  
P.L. Ng ◽  
G.H. Frommer
Keyword(s):  
Comparative Study ◽  
Numerical Models ◽  
High Rise

Comparative study of different formulations and solution methods for two phase flow in saturated porous media

2010 ◽  
Vol 62 (11) ◽  
pp. 2678-2693
Author(s):  
Mini Mathew ◽  
M. S. Mohan Kumar
Keyword(s):  
Porous Media ◽  
Comparative Study ◽  
Numerical Models ◽  
Heterogeneous Porous Media ◽  
Test Problems ◽  
Sequential Method ◽  
Two Phase ◽  
Sequential Methods ◽  
Solution Methods ◽  
Adaptive Solution

Six models (Simulators) are formulated and developed with all possible combinations of pressure and saturation of the phases as primary variables. A comparative study between six simulators with two numerical methods, conventional simultaneous and modified sequential methods are carried out. The results of the numerical models are compared with the laboratory experimental results to study the accuracy of the model especially in heterogeneous porous media. From the study it is observed that the simulator using pressure and saturation of the wetting fluid (PW, SW formulation) is the best among the models tested. Many simulators with nonwetting phase as one of the primary variables did not converge when used along with simultaneous method. Based on simulator 1 (PW, SW formulation), a comparison of different solution methods such as simultaneous method, modified sequential and adaptive solution modified sequential method are carried out on 4 test problems including heterogeneous and randomly heterogeneous problems. It is found that the modified sequential and adaptive solution modified sequential methods could save the memory by half and as also the CPU time required by these methods is very less when compared with that using simultaneous method. It is also found that the simulator with PNW and PW as the primary variable which had problem of convergence using the simultaneous method, converged using both the modified sequential method and also using adaptive solution modified sequential method. The present study indicates that pressure and saturation formulation along with adaptive solution modified sequential method is the best among the different simulators and methods tested.

scholarly journals A Comparative Study on Different Parallel Solvers for Nonlinear Analysis of Complex Structures

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Lei Zhang ◽  
Guoxin Zhang ◽  
Lixiang Wang ◽  
Zhaosong Ma ◽  
Shihai Li
Keyword(s):  
Comparative Study ◽  
Nonlinear Analysis ◽  
Krylov Subspace ◽  
Numerical Models ◽  
Creep Model ◽  
Preconditioned Conjugate Gradient ◽  
Complex Structures ◽  
Parallel Solvers ◽  
Whole Process ◽  
Deformation Models

The parallelization of 2D/3D software SAPTIS is discussed for nonlinear analysis of complex structures. A comparative study is made on different parallel solvers. The numerical models are presented, including hydration models, water cooling models, modulus models, creep model, and autogenous deformation models. A finite element simulation is made for the whole process of excavation and pouring of dams using these models. The numerical results show a good agreement with the measured ones. To achieve a better computing efficiency, four parallel solvers utilizing parallelization techniques are employed: (1) a parallel preconditioned conjugate gradient (PCG) solver based on OpenMP, (2) a parallel preconditioned Krylov subspace solver based on MPI, (3) a parallel sparse equation solver based on OpenMP, and (4) a parallel GPU equation solver. The parallel solvers run either in a shared memory environment OpenMP or in a distributed memory environment MPI. A comparative study on these parallel solvers is made, and the results show that the parallelization makes SAPTIS more efficient, powerful, and adaptable.

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