Intelligent Well Technologies: Modeling, Design, Monitoring, and Control Optimization

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 949

Special Issue Editors


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Guest Editor
Institute of GeoEnergy Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK
Interests: oil and gas production technology; intelligent well technology; pressure and temperature transient analysis

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Guest Editor
Institute of GeoEnergy Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK
Interests: well decommissioning; advanced well completion technology; intelligent well and field design and optimization; integrated asset modelling; optimization under uncertainty; surrogate modelling

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Guest Editor
Faculty of Technology, Natural Sciences and Maritime Sciences, Department of Process, Energy and Environmental Technology, University of South-Eastern Norway, 3918 Porsgrunn, Norway
Interests: multiphase flow; oil production using inflow control devices; near well simulation

Special Issue Information

Dear Colleagues,

Intelligent (smart or advanced or ‘flow control completion’) well (i-well) technology is being successfully used in thousands of wells worldwide. Dozens of companies are involved in manufacturing, modelling, installing, and optimizing i-well equipment. I-wells have their completion intervals divided into zones with packers, followed by the regulation of production or injection in each zone using flow control devices. This improves the well’s in/outflow profile and reduces production of unwanted fluids, resulting in increased oil or gas recovery.

The concept of i-well technology is around 25 years old and is still developing. While it is able to solve a wide range of problems, from local well-scale conformance issues to field-scale flood management, for the same reason, it requires addressing a wide range research tasks. This includes well completion design optimization studies, overall well and field production and injection optimization under uncertainty, complex wellbore flow modelling studies, well monitoring at the sandface level, etc.

Moreover, the design of downhole flow control devices is evolving too: the original family of passive, inflow control devices (ICDs) and active interval control valves (ICVs) was later joined by more fluid-viscosity-sensitive autonomous ICDs (AICDs) and inflow control devices (AICVs), while the new types (e.g., fluid-density-sensitive AICDs) are being developed and introduced. This results in continuing expansion of the application of intelligent well technology to ever more complex tasks and fields, making it amazingly resilient and adaptive both to the traditional oil and gas challenges, and to the new ones like thermal recovery, CO2 EOR and  storage, etc.

This Special Issue will focus on intelligent well technologies, including their completion modeling, design, wellbore flow monitoring, and well and field control optimization aspects.

Topics of interest include:

Optimization of the sandface flow control completion design. This includes selection and placement of the right flow control devices and packers, single-bore and multilateral wells, conformance management, etc.

Wellbore flow modeling in advanced wells: both steady-state and transient; well-only and well- and reservoir-scale challenges.

Real-time monitoring, flow profiling, production logging, well integrity surveillance, and problem detection in intelligent wells. This includes both traditional and new types of sensors (e.g., fiber-optic), and both traditional and novel data interpretation techniques.

Well production and/or injection optimization with intelligent wells, both deterministic (i.e., using a single reservoir model realization) and under uncertainty (i.e., dealing with an ensemble of reservoir model realization, finding robust optimum strategies).

Active vs. passive and/or autonomous advanced well completions: comparative studies.

Dr. Khafiz Muradov
Dr. Morteza Haghighat Sefat
Prof. Dr. Britt Margrethe Emilie Moldestad
Guest Editors

Manuscript Submission Information

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Keywords

  • intelligent or smart or advanced well completion
  • flow control device
  • wellbore flow modelling
  • robust production optimization and field management
  • uncertainty management
  • well completion design
  • in-well monitoring
  • active and passive control

Published Papers (1 paper)

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29 pages, 7943 KiB  
Article
Completion Performance Evaluation in Multilateral Wells Incorporating Single and Multiple Types of Flow Control Devices Using Grey Wolf Optimizer
by Jamal Ahdeema, Morteza Haghighat Sefat, Khafiz Muradov, Ali Moradi and Britt M. E. Moldestad
Processes 2024, 12(4), 785; https://doi.org/10.3390/pr12040785 - 13 Apr 2024
Viewed by 588
Abstract
There has been a tendency in oil and gas industry towards the adoption of multilateral wells (MLWs) with completions that incorporate multiple types of flow control devices (FCDs). In this completion technique, passive inflow control devices (ICDs) or autonomous inflow control devices (AICDs) [...] Read more.
There has been a tendency in oil and gas industry towards the adoption of multilateral wells (MLWs) with completions that incorporate multiple types of flow control devices (FCDs). In this completion technique, passive inflow control devices (ICDs) or autonomous inflow control devices (AICDs) are positioned within the laterals, while interval control valves (ICVs) are installed at lateral junctions to regulate the overall flow from each lateral. While the outcomes observed in real field applications appear promising, the efficacy of this specific downhole completion combination has yet to undergo comparative testing against alternative completion methods that employ a singular flow control device type. Additionally, the design and current evaluations of such completions are predominantly based on analytical tools that overlook dynamic reservoir behavior, long-term production impacts, and the correlation effects among different devices. In this study, we explore the potential of integrating various types of flow control devices within multilateral wells, employing dynamic optimization process using numerical reservoir simulator while the Grey Wolf Optimizer (GWO) is used as optimization algorithm. The Egg benchmark reservoir model is utilized and developed with two dual-lateral wells. These wells serve as the foundation for implementing and testing 22 distinct completion cases considering single-type and multiple types of flow control devices under reactive and proactive management strategies. This comprehensive investigation aims to shed light on the advantages and limitations of these innovative completion methods in optimizing well and reservoir performance. Our findings revealed that the incorporation of multiple types of FCDs in multilateral well completions significantly enhance well performance and can surpass single-type completions including ICDs or AICDs. However, this enhancement depends on the type of the device implemented inside the lateral and the control strategy that is used to control the ICVs at the lateral junctions. The best performance of multiple-type FCD-based completion was achieved through combining AICDs with reactive ICVs which achieved around 75 million USD profit. This represents 42% and 22% increase in the objective function compared to single-type ICDs and AICDs installations, respectively. The optimal settings for ICD and AICD in individual applications may significantly differ from the optimal settings when combined with ICVs. This highlights a strong correlation between the different devices (control variables), proving that using either a common, simplified analytical, or a standard sequential optimization approach that do not explore this inter-dependence between devices would result in sub-optimal solutions in such completion cases. Notably, the ICV-based completion, where only ICVs are installed with lateral completion, demonstrated superior performance, particularly when ICVs are reactively controlled, resulting in an impressive 80 million USD NPV which represents 53% and 30% increase in the objective function compared to single-type ICDs and AICDs installations, respectively. Full article
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