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Dr. Jianjun Zhu
School of Storage and Transportation Engineering, China University of Petroleum (Beijing), Beijing 102249, China
Prof. Dr. Jianli Wang
1. Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Department of Mechanical Engineering, Southeast University, Nanjing 210096, China
2. Engineering Research Center of New Light Sources Technology and Equipment, Ministry of Education, Southeast University, Nanjing 210096, China
Dr. Haiwen Zhu
Department of Petroleum Engineering, University of Tulsa, Tulsa, OK 74104, USA
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Advances in Monitoring, Modeling and Control of Multiphase Flow in Artificially Lifted Wells

Abstract submission deadline
30 April 2027
Manuscript submission deadline
30 June 2027
Viewed by
727

Topic Information

Dear Colleagues,

This Topic showcases end-to-end advances that enable reliable, efficient, and low-emission production from artificially lifted wells by integrating monitoring, modeling, and control. We welcome contributions that bridge field data, laboratory/rig experiments, mechanistic theory, computational modeling (CFD and reduced-order), and data-driven/AI methods to support real-time decision-making across ESP, rod-pump/beam-pump, PCP, jet-pump, gas-lift, plunger-lift, and hybrid systems. While centered on oil and gas, we also encourage relevant work in geothermal and subsurface fluid management (e.g., produced water/CCUS), where multiphase lift and flow assurance are critical.

Topics may include, but are not limited to, the following：

  1. Monitoring and Diagnostics: Downhole/fiber-optic sensing (DTS/DAS/pressure/temperature), acoustics and magnetics, surface metering and virtual metering, sensor fusion and edge/IIoT, flow-pattern and GVF identification, sand-/water-cut monitoring, calibration and uncertainty quantification, and open datasets and benchmarks.
  2. Modeling and Digital Twins: Mechanistic and transient multiphase wellbore models (slugging, flow-regime transitions), coupled reservoir–well–network simulation, CFD and surrogate/ROMs, physics-informed ML, system identification, parameter estimation, and validation under HPHT/deep/deviated conditions.
  3. Control and Optimization: VSD control of ESPs, gas-lift rate allocation and network optimization, plunger-lift cycle optimization, model-predictive control and reinforcement learning, startup/deliquification strategies, anomaly detection/predictive maintenance, energy efficiency and methane/emissions reduction, and constraints from sand/wax/scale and HSE.
  4. Applications and Case Studies: Field trials and pilot implementations, comparative assessments of lift technologies, software/tools and reproducible workflows, techno-economic and lifecycle assessments, and best practices and standards.

Accepted article types: Original research, reviews, perspectives, data descriptors/benchmarks, and software notes.

Dr. Jianjun Zhu
Prof. Dr. Jianli Wang
Dr. Haiwen Zhu
Topic Editors

Keywords

  • artificial lift
  • multiphase flow
  • monitoring and sensing
  • virtual metering
  • digital twin
  • CFD and ROM
  • physics-informed ML
  • MPC/RL
  • ESP
  • gas-lift
  • plunger-lift
  • PCP
  • flow assurance
  • emissions and energy efficiency

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Energies
energies 		3.2 7.3 2008 16.8 Days CHF 2600 Submit
Geosciences
geosciences 		2.1 5.1 2011 23.6 Days CHF 1800 Submit
Minerals
minerals 		2.2 4.4 2011 17.7 Days CHF 2400 Submit
Sustainability
sustainability 		3.3 7.7 2009 17.9 Days CHF 2400 Submit
Modelling
modelling 		1.5 2.2 2020 24.9 Days CHF 1200 Submit

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Published Papers (1 paper)

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22 pages, 11008 KB  
Article
Numerical Modeling and Simulation of Thermal Effect-Driven Bottom Hole Pressure Variation and Control Technology During Tripping-Out in HTHP Ultra-Deep Wells
by Hu Yin, Hongzhuo Yan and Chunzhu Chen
Modelling 2026, 7(1), 21; https://doi.org/10.3390/modelling7010021 - 15 Jan 2026
Viewed by 201
Abstract
Controlling bottom hole pressure (BHP) during tripping-out is a key challenge in ultra-deep well drilling. Under high-temperature and high-pressure (HTHP) conditions, ultra-deep wells feature long tripping-out cycles, where thermal effects are prone to causing BHP reduction and increasing kick risk. However, existing pressure [...] Read more.
Controlling bottom hole pressure (BHP) during tripping-out is a key challenge in ultra-deep well drilling. Under high-temperature and high-pressure (HTHP) conditions, ultra-deep wells feature long tripping-out cycles, where thermal effects are prone to causing BHP reduction and increasing kick risk. However, existing pressure control technologies struggle to adapt to the requirements of narrow safe density windows in deep formations. This study establishes a transient tripping-out temperature field model, taking the PS6 ultra-deep vertical well as a case study to calculate the variations in temperature, equivalent static density (ESD), and BHP during tripping-out at 2910 m and 9026 m. A weighted drilling fluid supplementation method is presented, with supplementary parameters designed and its feasibility verified. The results indicate that during the entire tripping-out process, the bottom hole temperature at 2910 m increases by 17.5 °C and BHP rises by 0.016 MPa; at 9026 m, the temperature increases by 72.6 °C and BHP decreases by 2.410 MPa. Compared with the traditional “heavy mud cap” technology, the presented method can control BHP within a smaller fluctuation range (within 0.339 MPa) during tripping-out, better adapting to the safe tripping requirements of narrow safe density windows in deep formations and effectively mitigating kick risk. Full article
(This article belongs to the Topic Advances in Monitoring, Modeling and Control of Multiphase Flow in Artificially Lifted Wells)
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