Coupling of Geochemical and Multiphase Flow Processes for Validation of the MUFITS Reservoir Simulator Against TOUGH

Abstract This study investigated the ability to produce accurate multiphase flow profiles simulating the response of producing reservoirs, using Generative Deep Learning (GDL) methods. Historical production data from numerical simulators were used to train a GDL model that was then used to predict the output of new wells in unseen locations. This work describes a procedure in which data analysis techniques are used to gain insight into reservoir flow behavior at a field level based on existing historical data. The procedure includes clustering, dimensionality reduction, correlation, in addition to novel interpretation methodologies that synthesize the results from reservoir simulation output, characterizing flow conditions. The insight was then used to build and train a GDL algorithm that reproduces the multiphase reservoir behavior for unseen operational conditions with high accuracy. The trained algorithm can be used to further generate new predictions of the reservoir response under operational conditions for which we do not have previous examples in the training data set. We found that the GDL algorithm can be used as a robust multiphase flow simulator. In addition, we showed that the physics of flow can be captured and manipulated in the GDL latent space after training to reproduce different physical effects that did not exist in the original training data set. Applying the methodology to the problem of determining multiphase production rate from new producing wells in undrilled locations showed positive results. The methodology was tested successfully in predicting multiphase production under different scenarios including multiwell channelized and heterogeneous reservoirs. Comparison with other shallow supervised algorithms demonstrated improvements realized by the proposed methodology, compared to existing methods. The study developed a novel methodology to interpret both data and GDL algorithms, geared towards improving reservoir management. The method was able to predict the performance of new wells in previously undrilled locations without using a reservoir simulator.

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Study of the formation mechanisms of CO2 hydrates from matching the experimental data with a porous media setting by multiphase flow-geochemical-thermal reservoir simulator

Journal of the Taiwan Institute of Chemical Engineers ◽

10.1016/j.jtice.2020.09.015 ◽

2020 ◽

Vol 114 ◽

pp. 115-124

Author(s):

Tzu-Keng Lin ◽

Muhammad Dahyar ◽

Ming-Jer Lee ◽

Bieng-Zih Hsieh

Keyword(s):

Experimental Data ◽

Porous Media ◽

Multiphase Flow ◽

Formation Mechanisms ◽

Thermal Reservoir ◽

Reservoir Simulator

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A compositional wellbore/reservoir simulator to model multiphase flow and temperature distribution

Journal of Petroleum Science and Engineering ◽

10.1016/j.petrol.2009.02.012 ◽

2009 ◽

Vol 69 (1-2) ◽

pp. 40-52 ◽

Cited By ~ 32

Author(s):

P. Pourafshary ◽

A. Varavei ◽

K. Sepehrnoori ◽

A. Podio

Keyword(s):

Temperature Distribution ◽

Multiphase Flow ◽

Reservoir Simulator

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Modern Trends in CFD Simulations: Application to GTL Technology

Chemical Product and Process Modeling ◽

10.2202/1934-2659.1000 ◽

2006 ◽

Vol 1 (1) ◽

Cited By ~ 4

Author(s):

Abid Akhtar ◽

Vishnu K Pareek ◽

Moses O Tade

Keyword(s):

Multiphase Flow ◽

Bubble Column ◽

Fluid Dynamic ◽

Scale Up ◽

Operating Conditions ◽

Special Focus ◽

Cfd Simulations ◽

Multiphase Reactors ◽

Flow Processes ◽

Gas To Liquid

Multiphase flow processes are frequently observed in several important reactor technologies. These technologies are found in diverse applications such as in manufacture of petroleum-based fuels and products, conversion of synthesis gas into liquid hydrocarbons (Gas-to-liquid technology), production of commodity chemicals, pharmaceuticals, herbicides, pesticides, polymers etc. Due to the inherent complexity of these processes, the knowledge of fluid dynamic and transport parameters is necessary for development of appropriate reactor models and scale-up rules. It is, therefore, of paramount importance to develop understanding and predictive tools to simulate multiphase flow processes for better and economically viable reactor technologies. In the past, knowledge of hydrodynamics and transport characteristics of multiphase reactors has been interpreted in the form of empirical correlations, which have numerous restrictions in terms of their validity for different operating conditions. Computational fluid dynamics (CFD) simulation, on the other hand, deals with the solution of fluid dynamic equations on digital computers, requiring relatively few restrictive assumptions and thus giving a complete description of the hydrodynamics of these reactors. This detailed predicted flow field gives an accurate insight to the fluid behaviour and can sometimes give information, which cannot be obtained from experiments. These days, due to cheaper computational resources, CFD simulations are becoming economically reliable for modeling of multiphase processes including GTL (Gas-to-liquid) processes. In this paper, a comprehensive review of different multiphase flow simulation approaches has been presented. The recent progress made in hydrodynamic modeling of multiphase reactors, their capabilities and limitations (with special focus on GTL processes) are discussed in detail. Finally, case studies with different simulation approaches (Eulerian-Eulerian and VOF (Volume of fluid) simulations of bubble column reactors operating in different flow regimes) are discussed to demonstrate the power of this emerging research tool.

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