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Processes
Special Issues
Recent Advances in Oil Reservoir Simulation and Multiphase Flow
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Recent Advances in Oil Reservoir Simulation and Multiphase Flow

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: 31 March 2027 | Viewed by 2976

Editors

Dr. Shiqian Xu

E-Mail Website
Guest Editor
Petroleum Engineering School, Southwest Petroleum University, Chendu 610500, China
Interests: unconventional reservoirs; reservoir simulation; optimization
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sen Wang

E-Mail Website
Guest Editor
School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Interests: multiphase flow; multiscale modeling; unconventional reservoirs
Dr. Xiukun Wang

E-Mail Website
Guest Editor
Unconventional Petroleum Research Institute, China University of Petroleum (Beijing), Beijing 102249, China
Interests: unconventional reservoirs; enhanced oil recovery; multiphase flow
Special Issues, Collections and Topics in MDPI journals
Dr. Shiyuan Zhan

E-Mail Website
Guest Editor
College of Energy, Chengdu University of Technology, Chendu 610059, China
Interests: multiphase flow; unconventional reservoirs; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advanced reservoir multiphase flow simulation is a key challenge in petroleum engineering. With the increasing complexity of reservoir characteristics (from conventional to unconventional resources) and the growing emphasis on improving the recovery of unconventional reservoirs such as tight oil and shale oil, advanced multiscale modeling and intelligent optimization have become indispensable tools. Recent research advances have covered all aspects of reservoir simulation, from molecular-scale interactions to field-scale simulation, integrating artificial intelligence and high-performance computing technologies. This Special Issue aims to gather cutting-edge research results that combine theoretical advancements, computational innovations, and practical applications, covering all scales of reservoir research and promoting interdisciplinary collaboration to address the sustainable and efficient development of diverse oil and gas resources.

This Special Issue on “Recent Advances in Oil Reservoir Simulation and Multiphase Flow” seeks high quality works focusing on novel methodologies, high-fidelity modeling, and intelligent optimization for a wide spectrum of oil reservoirs. Topics include, but are not limited to, the following:

  • Molecular Scale: Molecular dynamics simulations for interfacial phenomena, EOR agent mechanisms, and fluid behavior in nanopores.
  • Pore Scale: Lattice Boltzmann Method (LBM), computational fluid dynamics (CFD) in porous media, microfluidic experiments, pore-network modeling, and digital rock technology.
  • Core Scale: Experimental studies (e.g., NMR, micro-CT, displacement tests) for model validation and constitutive relationship development.
  • Reservoir Scale: Advanced numerical simulation techniques, including discrete fracture modeling (DFN), embedded discrete fracture models (EDFM), and coupled multi-physics simulations.
  • AI/ML-assisted reservoir characterization, history matching, and production forecasting.
  • Smart optimization of well placement, hydraulic fracturing design, and injection/production strategies.
  • Real-time data assimilation and closed-loop reservoir management.
  • Uncertainty quantification and risk-based decision-making under geological and dynamic uncertainties.

Dr. Shiqian Xu
Prof. Dr. Sen Wang
Dr. Xiukun Wang
Dr. Shiyuan Zhan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • reservoir simulation
  • multiphase flow
  • multiscale modeling
  • unconventional reservoirs
  • enhanced oil recovery
  • artificial intelligence
  • optimization
  • historymaching

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Published Papers (6 papers)

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Research

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17 pages, 4249 KB  
Article
Phase Behavior and Critical Properties of Hydrocarbons in Shale Illite Nanopores
by Sirong Zhu, Ning Li, Zhiwen Huang, Kai Ye, Fangpeng He, Shiqian Xu, Kuankuan Wu and Wenxi Ren
Processes 2026, 14(16), 2534; https://doi.org/10.3390/pr14162534 - 7 Aug 2026
Viewed by 397
Abstract
Clay minerals are significant constituents of shale reservoirs, yet the confinement-induced phase behavior of hydrocarbons within clay nanopores has received comparatively less attention than in carbonaceous materials. In this study, Grand Canonical Monte Carlo (GCMC) simulations were performed to investigate the confinement-induced shifts [...] Read more.
Clay minerals are significant constituents of shale reservoirs, yet the confinement-induced phase behavior of hydrocarbons within clay nanopores has received comparatively less attention than in carbonaceous materials. In this study, Grand Canonical Monte Carlo (GCMC) simulations were performed to investigate the confinement-induced shifts in the critical properties of hydrocarbons within illite slit pores ranging from 2 to 20 nm. The simulation results indicate apparent reductions in both critical temperature (Tc) and critical pressure (Pc) under confined conditions. The relative shift in critical properties is more pronounced for n-pentane than for methane, which is attributed to the larger molecular size and complex chain-like structure of n-pentane compared to methane. The simulation results also show that the extent of these shifts varies among different pore geometries and materials due to the differences in fluid–solid interactions and specific surface areas. Illite exerts a weaker confinement effect than graphite, while cylindrical pores intensify the shift compared to slit pores. As the pore size increases from 2 to 20 nm, the nanoconfinement-induced shifts in the critical properties of alkanes in illite slit pores progressively diminish, and the critical properties approach their corresponding bulk values at a pore size of 20 nm. Finally, new correlations are proposed to quantify the critical property shifts in illite slit nanopores. Overall, this study provides a quantitative characterization of confinement-induced critical-property shifts for the investigated hydrocarbons in illite slit nanopores. Full article
(This article belongs to the Special Issue Recent Advances in Oil Reservoir Simulation and Multiphase Flow)
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20 pages, 6443 KB  
Article
Impacts of Waterflooding Erosion and Fluid–Solid Coupling on Porosity and Permeability Evolution in Offshore Unconsolidated Sandstone Reservoirs
by Yuyang Liu, Wensheng Zhou, Jingwei Huang and Zhijie Wei
Processes 2026, 14(14), 2308; https://doi.org/10.3390/pr14142308 - 15 Jul 2026
Viewed by 264
Abstract
Aiming at the significant pore structure reconfiguration and mechanical response evolution of offshore unconsolidated sandstone reservoirs during long-term high-intensity waterflooding development, this study proposes a novel fluid–solid coupling mathematical model incorporating waterflooding erosion effects. This method enables coupled simulations of reservoir deformation, fluid [...] Read more.
Aiming at the significant pore structure reconfiguration and mechanical response evolution of offshore unconsolidated sandstone reservoirs during long-term high-intensity waterflooding development, this study proposes a novel fluid–solid coupling mathematical model incorporating waterflooding erosion effects. This method enables coupled simulations of reservoir deformation, fluid flow, and waterflooding-induced pore structure evolution. Compared with conventional methods, the proposed method not only accounts for the influence of mechanical responses on reservoir seepage parameters, but also incorporates pore structure evolution induced by waterflooding erosion under high-intensity waterflooding conditions. The model is validated against MRST, demonstrating its reliability. Multiple case studies are further conducted to systematically investigate the impacts of waterflooding erosion and fluid–solid coupling on the evolution of reservoir properties. The results indicate that under long-term high-intensity waterflooding conditions, waterflooding erosion dominates the evolution of reservoir petrophysical properties in the vicinity of injection wells. Although the fluid–solid coupling effect is weakened under high-porosity conditions, waterflooding erosion remains across different porosity reservoirs. It is a key factor controlling reservoir petrophysical property evolution during long-term high-intensity waterflooding. Full article
(This article belongs to the Special Issue Recent Advances in Oil Reservoir Simulation and Multiphase Flow)
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18 pages, 6020 KB  
Article
Experimental Study on Sand-Washing in Horizontal Wells
by Yong Li, Han Xiao, Ruitao Sun, Xingmin Huang and Benchun Yao
Processes 2026, 14(14), 2275; https://doi.org/10.3390/pr14142275 - 13 Jul 2026
Viewed by 367
Abstract
In horizontal wells, sand readily settles at the bottom of the annulus under gravity, forming sand beds that may lead to string sticking in sand-washing operations. To clarify the dynamic evolution of annular sand beds, a horizontal wellbore sand-washing experimental system was developed. [...] Read more.
In horizontal wells, sand readily settles at the bottom of the annulus under gravity, forming sand beds that may lead to string sticking in sand-washing operations. To clarify the dynamic evolution of annular sand beds, a horizontal wellbore sand-washing experimental system was developed. Clean water and a 0.3 wt% guar gum solution were used as washing fluids to investigate sand-bed front morphology, self-excited oscillation, stratified transport, and deposition height under different inlet Reynolds numbers. The results show that, during clean water sand-washing, the sand-bed front exhibited inflection-point instability, stagnation-point formation, and secondary bed branching with increasing inlet Reynolds number, accompanied by periodic self-excited oscillations. In contrast, no oscillation occurred in the guar gum solution, and the sand-bed front became more streamlined. For both fluids, stratified transport consisting of a convective layer and a shear-slip layer was observed above the sand bed, while the slip-layer thickness in the guar gum solution was approximately 45.0% lower than that in water. Based on dimensional analysis and experimental data, correlations for the dimensionless migration velocity of the sand front and the local Reynolds number were established. An implicit method for predicting the maximum sand-bed height was proposed, with an error below 1.15%. The results indicate that the sand-bed deposition height decreases nearly linearly with increasing inlet Reynolds number, whereas the absolute migration velocity of the sand front remains low, resulting in poor sand-washing efficiency. The findings provide guidance for optimizing sand-washing flow rates and assessing sand-sticking risks in horizontal wells. Full article
(This article belongs to the Special Issue Recent Advances in Oil Reservoir Simulation and Multiphase Flow)
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16 pages, 12167 KB  
Article
A Numerical Well Testing Method for Horizontal Wells in Hydraulically Fractured Shale Reservoirs Based on 3D Simulation and the Embedded Discrete Fracture Model
by Zhipeng Ou, Shengjun Liu, Wenhan Yue, Jia Ni, Youshi Jiang, Mengchong Peng and Zhen Li
Processes 2026, 14(12), 1941; https://doi.org/10.3390/pr14121941 - 14 Jun 2026
Viewed by 361
Abstract
Shale oil is a vital unconventional resource. Large-scale hydraulic fracturing serves as the core technology for the efficient development of shale oil reservoirs. Well testing can be applied to characterize the reservoir parameters of fractured shale formations. Nevertheless, conventional well testing approaches fail [...] Read more.
Shale oil is a vital unconventional resource. Large-scale hydraulic fracturing serves as the core technology for the efficient development of shale oil reservoirs. Well testing can be applied to characterize the reservoir parameters of fractured shale formations. Nevertheless, conventional well testing approaches fail to account for numerous discrete fractures and complex formation geometries. Based on the embedded discrete fracture model (EDFM)—an effective tool for simulating flow in discrete fractures—this work proposes a numerical well testing approach for horizontal wells in hydraulically fractured shale reservoirs. The effects of fracture permeability, number of fracture clusters, matrix permeability, and water saturation on well testing curves are also investigated. The results showed that the parameters such as the main fracture permeability, the number of fracture clusters, and the matrix permeability all have significant effects on the well test curves. When the permeability of main fractures exceeds 20D, radial flow characteristics appear in Stage V. For the distance between fracturing intervals and pressure monitoring points within 0 m to 200 m, it imposes the most significant impact on Stage I and Stage II. The half-length of main fractures, the SRV extent in the Y-direction, and boundary conditions mainly affect Stage VI and Stage VII. Full article
(This article belongs to the Special Issue Recent Advances in Oil Reservoir Simulation and Multiphase Flow)
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Review

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56 pages, 2645 KB  
Review
Machine Learning Across the Heavy Oil Value Chain: A Review of Methodological Maturity and Industrial Deployability
by George Simonelli, Diogo Souza Neiva Cardoso, Adriana Vieira dos Santos and Luiz Carlos Lobato dos Santos
Processes 2026, 14(17), 2681; https://doi.org/10.3390/pr14172681 (registering DOI) - 22 Aug 2026
Abstract
Heavy and extra-heavy oils represent a large and growing share of recoverable hydrocarbon resources, yet their extreme viscosity, high heteroatom content, and non-Newtonian behavior routinely defeat empirical correlations developed for conventional crude. Machine learning has emerged as a candidate response to this modeling [...] Read more.
Heavy and extra-heavy oils represent a large and growing share of recoverable hydrocarbon resources, yet their extreme viscosity, high heteroatom content, and non-Newtonian behavior routinely defeat empirical correlations developed for conventional crude. Machine learning has emerged as a candidate response to this modeling gap, but existing reviews largely catalog applications without asking whether the technology is actually ready for industrial deployment. This critical review synthesizes machine learning applications across five thematic domains of the heavy-oil value chain: physicochemical property prediction, enhanced oil recovery, flow assurance, reactive recovery, and downstream upgrading. Studies are read through a three-phase historical lens, tracing the field’s progression from empirical-correlation replacement to methodological diversification to physics-informed and closed-loop integration, and evaluated against a Technology Readiness Level (TRL) scale adapted specifically for heavy-oil machine learning. The multilayer perceptron anchors more of the primary corpus than any other architecture, a pattern that, in our interpretation, reflects small-sample, low-dimensional regression needs rather than any demonstrated advantage over other architectures. Enhanced oil recovery is the only cluster to reach organizational-scale deployment, anchored by a single multi-decade operator program, Chevron’s San Joaquin Valley i-field; the remaining clusters are constrained less by modeling sophistication than by single-basin datasets and undisclosed uncertainty. Measured against three falsifiable deployability criteria, fidelity preservation below 10° API, operator-grade interpretability, and demonstrated laboratory-to-field transferability, no study in the reviewed corpus is documented to satisfy all three simultaneously; because industrial implementations are frequently proprietary, this is a statement about the published record identified by this search, not a claim that the capability does not exist. Federated learning, physics-informed architectures, and sequence-aware models emerge as the directions most likely to close this gap. Full article
(This article belongs to the Special Issue Recent Advances in Oil Reservoir Simulation and Multiphase Flow)
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51 pages, 31166 KB  
Review
Cuttings-Bed Dynamics and Wellbore Cleaning: A Critical Review of Multiscale Modeling, Multiphase Flow, and Cross-Scale Validation
by Zijian Li, Bo Zhang, Liping Jiang, Tao Yang, Tai Luo, Xianping Cao, Xu Yang, Gao Li, Hongtao Li, Xiaofeng Sun and Stephen Butt
Processes 2026, 14(14), 2245; https://doi.org/10.3390/pr14142245 - 9 Jul 2026
Viewed by 647
Abstract
Reliable wellbore cleaning remains difficult in deviated, horizontal, extended-reach, deep, and ultra-deep wells because the downhole distribution and mechanical state of cuttings beds cannot usually be observed directly. This review examines cuttings-bed dynamics, multiscale modeling, compressible multiphase constraints, and field-validation pathways for drill [...] Read more.
Reliable wellbore cleaning remains difficult in deviated, horizontal, extended-reach, deep, and ultra-deep wells because the downhole distribution and mechanical state of cuttings beds cannot usually be observed directly. This review examines cuttings-bed dynamics, multiscale modeling, compressible multiphase constraints, and field-validation pathways for drill cuttings transport and wellbore cleaning. Bibliometric mapping of 625 Web of Science records was combined with critical assessment of 204 technically screened studies and 56 engineering-oriented OnePetro records. Bed height, cuttings concentration, pressure response, equivalent circulating density/bottomhole-pressure (ECD/BHP) margin, solids residence time, and packoff tendency are identified as bridge variables linking particle-scale behavior with operational risk. Recent studies strengthen wet-bed erosion and friction characterization, non-spherical and geometry-resolved CFD–DEM, hybrid prediction, compressible pressure–solids coupling, and field observability. Study-level comparison shows that ML approaches differ markedly in data provenance, validation design, physical integration, uncertainty reporting, and transfer evidence. An uncertainty-aware, field-calibratable workflow is proposed that links synchronized measurements, complementary models, latent-state estimates with prediction intervals, section-specific probabilistic thresholds, operational response, and post-action verification. Quantitative benchmark criteria are defined for particle realism, wet-bed mechanics, tool-induced flow, compressible transport, transient field models, and advisory outputs. Full article
(This article belongs to the Special Issue Recent Advances in Oil Reservoir Simulation and Multiphase Flow)
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