Topic Editors

School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, China
Prof. Dr. Wei Liu
College of Energy, Chengdu University of Technology, Chengdu 610059, China
Prof. Dr. Shibao Yuan
College of Petroleum Engineering, Xi’an Shiyou University, Xi’an, China

Multi-Phase Flow and Unconventional Oil/Gas Development

Abstract submission deadline
31 January 2024
Manuscript submission deadline
31 March 2024
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2365

Topic Information

Dear Colleagues,

Unconventional oil and gas resources have huge reserves, but the geological structures of reservoirs are generally complex. Therefore, the flowing capability of reservoir fluids often needs to be improved during the oil and gas production process in order to be developed effectively. In recent years, the problems of multi-phase flow during oil and gas production in unconventional reservoirs (heavy oil reservoirs, fractured carbonate reservoirs, low-permeability reservoirs, etc.) have obtained the attention of many scholars. In addition, the effects of oil‒gas and oil‒water interfaces during multi-phase flow in reservoirs and the effects of the addition of surfactants, polymers and nanoparticles on multi-phase flow are also the major focus of this theme. Mathematical modeling and numerical simulation of multi-phase flow in formation‒wellbore‒surface facility processes are also included. In order to strengthen the deep integration of multi-phase flow mechanics theory and engineering and promote the development of emerging interdisciplinary subjects, we have launched this Special Issue call for papers with the support of relevant academic journals. We invite you to submit manuscripts on topics including (but not limited to) the following:

  1. Multi-phase flow from wellbore to ground facilities;
  2. Multi-phase flows and EOR mechanisms of oil and gas in reservoirs;
  3. Application of nanoparticles and chemicals in unconventional reservoirs and the effects on multi-phase flow;
  4. Mathematical modeling and numerical simulation of multiphase flow in the formation‒wellbore‒surface facility process;
  5. Application of artificial intelligence in multi-phase flow.
Prof. Dr. Binfei Li
Prof. Dr. Wei Liu
Prof. Dr. Shibao Yuan
Topic Editors

Keywords

  • multi-phase flow
  • oil and gas development
  • unconventional reservoirs
  • nanoparticles and chemicals
  • phase behavior
  • numerical simulation
  • artificial intelligence

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.838 4.5 2011 14.9 Days 2300 CHF Submit
Energies
energies
3.252 5.5 2008 15.5 Days 2200 CHF Submit
Gases
gases
- - 2021 15.0 days * 1000 CHF Submit
Gels
gels
4.432 2.9 2015 10.9 Days 1800 CHF Submit
Nanomaterials
nanomaterials
5.719 7.4 2011 12.7 Days 2600 CHF Submit
Processes
processes
3.352 4.7 2013 12.7 Days 2000 CHF Submit

* Median value for all MDPI journals in the second half of 2022.


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Published Papers (3 papers)

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Article
Study on Flow Characteristics of Flue Gas and Steam Co-Injection for Heavy Oil Recovery
Processes 2023, 11(5), 1406; https://doi.org/10.3390/pr11051406 - 06 May 2023
Viewed by 538
Abstract
Flue gas is composed of N2 and CO2, and is often used as an auxiliary agent for oil displacement, with good results and very promising development prospects for co-injection with steam to develop heavy oil. Although research on the oil [...] Read more.
Flue gas is composed of N2 and CO2, and is often used as an auxiliary agent for oil displacement, with good results and very promising development prospects for co-injection with steam to develop heavy oil. Although research on the oil displacement mechanism of flue gas has been carried out for many years, the flow characteristics of steam under the action of flue gas have rarely been discussed. In this paper, the flow resistance and heat transfer effect of flue gas/flue gas + steam were evaluated by using a one-dimensional sandpack, a flue gas-assisted steam flooding experiment was carried out using a specially customized microscopic visualization model, and the microscopic flow characteristics in the process of the co-injection of flue gas and steam were observed and analyzed. The results showed that flue gas could improve the heat transfer effect of steam whilst accelerating the flow of steam in porous media and reducing the flow resistance of steam. Compared with pure steam, when the volume ratio of flue gas and steam was 1:2, the mobility decreased by 2.8 and the outlet temperature of the sandpack increased by 35 °C. This trend intensified with an increase in the proportion of flue gas. In the microscopic oil displacement experiments, the oil recovery and sweep efficiency of the flue gas and steam co-injection stage increased by 4.7% and 32.9%, respectively, compared with the pure steam injection stage due to the effective utilization of blocky remaining oil and corner remaining oil caused by the expansion of fluid channels, the flow of flue gas foam, and the dissolution and release of flue gas in heavy oil. Full article
(This article belongs to the Topic Multi-Phase Flow and Unconventional Oil/Gas Development)
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Article
Fast and Robust Prediction of Multiphase Flow in Complex Fractured Reservoir Using a Fourier Neural Operator
Energies 2023, 16(9), 3765; https://doi.org/10.3390/en16093765 - 27 Apr 2023
Viewed by 616
Abstract
Predicting multiphase flow in complex fractured reservoirs is essential for developing unconventional resources, such as shale gas and oil. Traditional numerical methods are computationally expensive, and deep learning methods, as an alternative approach, have become an increasingly popular topic. Fourier neural operator (FNO) [...] Read more.
Predicting multiphase flow in complex fractured reservoirs is essential for developing unconventional resources, such as shale gas and oil. Traditional numerical methods are computationally expensive, and deep learning methods, as an alternative approach, have become an increasingly popular topic. Fourier neural operator (FNO) networks have been shown to be a hundred times faster than convolutional neural networks (CNNs) in predicting multiphase flow in conventional reservoirs. However, there are few relevant studies on applying FNO to predict multiphase flow in reservoirs with complex fractures. In the present study, FNO-net and U-net (CNN-based) were successfully applied to predict pressure and gas saturation fields for the 2D heterogeneous fractured reservoirs. The tested results show that FNO can accurately depict the influence of fine fractures, while the CNN-based method has relatively poor performance in the treatment of fracture systems, both in terms of accuracy and computational speed. In addition, by adding initial conditions and boundary conditions to the loss function of FNO, we prove the necessity of adding physical constraints to the data-driven model. This work contributes to improving the understanding of the applicability of FNO-net, and provides new insights into deep learning methods for predicting multiphase flow in complex fractured reservoirs. Full article
(This article belongs to the Topic Multi-Phase Flow and Unconventional Oil/Gas Development)
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Article
Mechanical Behavior of Gas-Transmission Pipeline in a Goaf
Processes 2023, 11(4), 1022; https://doi.org/10.3390/pr11041022 - 28 Mar 2023
Viewed by 541
Abstract
To solve the safety hazard of a buried gas pipeline caused by subsidence of a mined-out area, a three-dimensional model of a buried pipeline in a mined-out area was established using geological parameters and the finite-element software ABAQUS. The effects of the friction [...] Read more.
To solve the safety hazard of a buried gas pipeline caused by subsidence of a mined-out area, a three-dimensional model of a buried pipeline in a mined-out area was established using geological parameters and the finite-element software ABAQUS. The effects of the friction coefficient of the pipe and soil, the coal-seam dip angle, and the horizontal angle on the mechanical behavior of the pipe under varying widths of goaf area were investigated. The results indicate that the maximum equivalent stress of the pipeline is negatively correlated with the horizontal angle. Concerning longitudinal mining, the pipeline exhibits a high-stress zone when the mining length is >200 m, the surface displacement appears in a small range when the mining length is 40 m, and the stratum displacement range increases gradually with the increase in the mining length. When the width of the goaf is constant, the maximum equivalent stress of the pipeline is positively correlated with the tube-soil friction coefficient and negatively correlated with the coal seam dip angle. The position of maximum stress gradually tends to appear near the uphill side of the coal seam, with an increase in the coal seam dip angle. Full article
(This article belongs to the Topic Multi-Phase Flow and Unconventional Oil/Gas Development)
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