Oil and Gas Drilling Processes: Control and Optimization, 2nd Edition

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

Deadline for manuscript submissions: 31 December 2025 | Viewed by 472

Special Issue Editors


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Guest Editor
College of Geophysics and Petroleum Resources, Yangtze University, Jingzhou 434023, China
Interests: formation evaluation; rock mechanics; multiphase flow; experimental study
Special Issues, Collections and Topics in MDPI journals
College of Petroleum Engineering, China University of Petroleum, Beijing 102249, China
Interests: petroleum engineering; rock mechanics; coupled THMC behaviors in gas hydrate reservoirs
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Geoscience and Technology, Southwest Petroleum University China, Chengdu 610500, China
Interests: MWD and LWD; experimental study; numerical study; rock strength
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This is the second edition of the Special Issue, following the success of the first edition, where more than ten papers were collected. Furter details can be found here:
https://www.mdpi.com/journal/processes/special_issues/8BK21Z0PK8.

Successful drilling and completion are key to efficient oil and gas production in hydrocarbon-bearing reservoirs. The reliable and accurate characterization of fluid flow within wellbores and the mechanical behaviors of rocks associated with drilling and completion are crucial in this process. The use of numerical modeling, simulation, experimental methods, and field data analysis is also of great significance.

This Special Issue, entitled “Oil and Gas Drilling Processes: Control and Optimization, 2nd Edition”, will curate novel or practical advances in research on the use of numerical, experimental, analytical, and field studies related to drilling processes. The studies of rock mechanics, fluid mechanics, and parameter optimization are all linked.

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

  • The development of numerical or analytical methods for fluid mechanics and rock mechanics-related behaviors during drilling and production;
  • The development of experimental methods related to fluid mechanics and rock mechanics in drilling;
  • Numerical and/or experimental methods in the characterization of multiphase flow in wellbores during drilling, completion, or production;
  • Formation evaluation techniques related to control and optimization during drilling and production.

Prof. Dr. Rui Deng
Dr. Xuyang Guo
Dr. Meng Chen
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 100 words) can be sent to the Editorial Office for announcement on this website.

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-blind 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 monthly 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

  • drilling
  • completion
  • rock mechanics
  • multiphase flow
  • well log
  • formation evaluation
  • MWD and LWD
  • experimental study
  • numerical study

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Published Papers (1 paper)

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Research

14 pages, 6249 KiB  
Article
Application of the NOA-Optimized Random Forest Algorithm to Fluid Identification—Low-Porosity and Low-Permeability Reservoirs
by Qunying Tang, Yangdi Lu, Xiaojing Yang, Yuping Li, Wei Zhang, Qiangqiang Yang, Zhen Tian and Rui Deng
Processes 2025, 13(7), 2132; https://doi.org/10.3390/pr13072132 - 4 Jul 2025
Viewed by 332
Abstract
As an important unconventional oil and gas resource, tight oil exploration and development is of great significance to ensure energy supply under the background of continuous growth of global energy demand. Low-porosity and low-permeability reservoirs are characterized by tight rock properties, poor physical [...] Read more.
As an important unconventional oil and gas resource, tight oil exploration and development is of great significance to ensure energy supply under the background of continuous growth of global energy demand. Low-porosity and low-permeability reservoirs are characterized by tight rock properties, poor physical properties, and complex pore structure, and as a result the fine calculation of logging reservoir parameters faces great challenges. In addition, the crude oil in this area has high viscosity, the formation water salinity is low, and the oil reservoir resistivity shows significant spatial variability in the horizontal direction, which further increases the difficulty of oil and water reservoir identification and affects the accuracy of oil saturation calculation. Targeting the above problems, the Nutcracker Optimization Algorithm (NOA) was used to optimize the hyperparameters of the random forest classification model, and then the optimal hyperparameters were input into the random forest model, and the conventional logging curve and oil test data were combined to identify and classify the reservoir fluids, with the final accuracy reaching 94.92%. Compared with the traditional Hingle map intersection method, the accuracy of this method is improved by 14.92%, which verifies the reliability of the model for fluid identification of low-porosity and low-permeability reservoirs in the research block and provides reference significance for the next oil test and production test layer in this block. Full article
(This article belongs to the Special Issue Oil and Gas Drilling Processes: Control and Optimization, 2nd Edition)
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