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Petroleum and Natural Gas Engineering

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 1729

Special Issue Editors

Dr. Jiaxue Li

E-Mail Website
Guest Editor
Engineering Institute, China University of Petroleum (Beijing), Beijing 102249, China
Interests: oil and gas engineering; oilfield surface engineering chemistry; natural gas transportation; harmless treatment technology for oil and gas field waste; drilling fluid and completion fluid
Dr. Pengfei Zhao

E-Mail Website
Guest Editor
School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
Interests: petroleum engineering; reservoir physics; rock mechanics

Special Issue Information

Dear Colleagues,

This Special Issue aims to highlight recent advancements and innovations in the field of petroleum and natural gas engineering, with a particular focus on hydraulic fracturing and enhanced oil recovery (EOR) techniques. These methods are crucial for optimizing extraction processes and improving overall production efficiency. We also seek to address the latest developments in drilling technologies, which play a supporting role in the exploration and extraction of petroleum and natural gas resources.

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

  • Innovations in hydraulic fracturing fluids and proppants;
  • Modeling and simulation of fracture propagation;
  • Environmental impacts and mitigation strategies of hydraulic fracturing;
  • Real-time monitoring and adaptive fracturing techniques;
  • Chemical, thermal, and gas injection EOR methods;
  • Case studies of successful EOR implementations;
  • Integration of EOR with reservoir management;
  • Advances in drilling technologies and equipment;
  • Drilling optimization and cost reduction strategies;
  • Wellbore stability and control;
  • New materials and techniques for drilling in challenging environments.

We welcome submissions of original research papers, review articles, and case studies that contribute to the understanding and advancement of these critical areas within petroleum and natural gas engineering. This Special Issue aims to compile a comprehensive collection of cutting-edge research that will serve as a valuable resource for researchers, engineers, and practitioners in the field.

Dr. Jiaxue Li
Dr. Pengfei Zhao
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. Energies 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 2600 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

  • hydraulic fracturing
  • enhanced oil recovery (EOR)
  • drilling technologies
  • reservoir management
  • environmental impact

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

16 pages, 5909 KiB  
Article
Application of Two-Dimensional NMR for Quantitative Analysis of Viscosity in Medium–High-Porosity-and-Permeability Sandstones in North China Oilfields
by Wei Zhang, Si Li, Shaoqing Wang, Jianmeng Sun, Wenyuan Cai, Weigao Yu, Hongxia Dai and Wenkai Yang
Energies 2024, 17(21), 5257; https://doi.org/10.3390/en17215257 - 22 Oct 2024
Viewed by 427
Abstract
The viscosity of crude oil plays a pivotal role in the exploration and development of oil fields. The predominant reliance on laboratory measurements, which are constrained by manual expertise, represents a significant limitation in terms of efficiency. Two-dimensional nuclear magnetic resonance (NMR) logging [...] Read more.
The viscosity of crude oil plays a pivotal role in the exploration and development of oil fields. The predominant reliance on laboratory measurements, which are constrained by manual expertise, represents a significant limitation in terms of efficiency. Two-dimensional nuclear magnetic resonance (NMR) logging offers a number of advantages over traditional methods. It is capable of providing faster measurement rates, as well as insights into fluid properties, which can facilitate timely adjustments in oil and gas development strategies. This study focuses on the loose sandstone reservoirs with high porosity and permeability containing heavy oil in the Huabei oilfield. Two-dimensional nuclear magnetic resonance (NMR) measurements and analyses were conducted on saturated rocks with different-viscosity crude oils and varying oil saturation levels, in both natural and artificial rock samples. This study elucidates the distribution patterns of different-viscosity crude oils within the two-dimensional NMR spectra. Furthermore, the T1 and T2 peak values of the extracted oil signals were employed to establish a model correlating oil viscosity with NMR parameters. Consequently, a criterion for determining oil viscosity based on two-dimensional NMR was formulated, providing a novel approach for estimating oil viscosity. The application of this technique in the BQ well group of the Huabei oilfield region yielded an average relative error of 15% between the actual oil viscosity and the computed results. Furthermore, the consistency between the oil types and the oil discrimination chart confirms the reliability of the method. The final outcomes meet the precision requirements for practical log interpretation and demonstrate the excellent performance of two-dimensional nuclear magnetic resonance (NMR) logging in calculating oil viscosity. The findings of this study have significant implications for subsequent exploration and development endeavors in the research area’s oilfields. Full article
(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)
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14 pages, 4648 KiB  
Article
Asynchronous Injection–Production Method in the High Water Cut Stage of Tight Oil Reservoirs
by Jianwen Chen, Dingning Cai, Tao Zhang, Linjun Yu, Dalin Zhou and Shiqing Cheng
Energies 2024, 17(19), 4838; https://doi.org/10.3390/en17194838 - 26 Sep 2024
Viewed by 573
Abstract
Asynchronous injection–production cycle (AIPC) in a horizontal–vertical well pattern is an efficient strategy for enhancing water injection in tight reservoirs. However, current studies lack consideration of waterflood-induced fractures (WIFs) caused by long-term water injection. This paper takes block Z in the Ordos Basin, [...] Read more.
Asynchronous injection–production cycle (AIPC) in a horizontal–vertical well pattern is an efficient strategy for enhancing water injection in tight reservoirs. However, current studies lack consideration of waterflood-induced fractures (WIFs) caused by long-term water injection. This paper takes block Z in the Ordos Basin, China, as the research object and first clarifies the formation conditions of WIFs considering the horizontal principal stress and flow line. Then, the pressure-sensitive permeability equations for the induce-fracture region between wells are derived. Finally, the WIFs characteristics in a horizontal–vertical well network with different injection modes are discussed by numerical simulation. The results show that WIFs preferentially form where flow aligns with the maximum principal stress, influencing permeability distribution. Controlling the injection rate of vertical wells on the maximum principal stress and flow line and cyclically adjusting the production rate of horizontal wells can regulate the appropriate propagation of WIFs and expand the swept areas. The parallel injection mode (PIM) and the half-production injection mode are superior to the full-production injection mode. This study can provide theoretical support for the effective development of tight oil reservoirs. Full article
(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)
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22 pages, 6614 KiB  
Article
Prediction of Key Development Indicators for Offshore Oilfields Based on Artificial Intelligence
by Ke Li, Kai Wang, Chenyang Tang, Yue Pan, Yufei He, Shaobin Cai, Suidong Chen and Yuhui Zhou
Energies 2024, 17(18), 4594; https://doi.org/10.3390/en17184594 - 13 Sep 2024
Viewed by 496
Abstract
As terrestrial oilfields continue to be explored, the difficulty of exploring new oilfields is constantly increasing. The ocean, which contains abundant oil and gas resources, has become a new field for oil and gas resource development. It is estimated that the total amount [...] Read more.
As terrestrial oilfields continue to be explored, the difficulty of exploring new oilfields is constantly increasing. The ocean, which contains abundant oil and gas resources, has become a new field for oil and gas resource development. It is estimated that the total amount of oil resources contained in ocean areas accounts for 33% of the global total, while the corresponding natural gas resources account for 32% of the world’s resources. Current prediction methods, tailored to land oilfields, struggle with offshore differences, hindering accurate forecasts. With oilfield advancements, a vast amount of rapidly generated, complex, and valuable data has piled up. This paper uses AI and GRN-VSN NN to predict offshore oilfield indicators, focusing on model-based formula fitting. It selects highly correlated input indicators for AI-driven prediction of key development metrics. Afterwards, the Shapley additive explanations (SHAP) method was introduced to explain the artificial intelligence model and achieve a reasonable explanation of the measurement’s results. In terms of crude-oil extraction degree, the performance levels of the Long Short-Term Memory (LSTM) neural network, BP neural network, and ResNet-50 neural network are compared. LSTM excels in crude-oil extraction prediction due to its monotonicity, enabling continuous time-series forecasting. Artificial intelligence algorithms have good prediction effects on key development indicators of offshore oilfields, and the prediction accuracy exceeds 92%. The SHAP algorithm offers a rationale for AI model parameters, quantifying input indicators’ contributions to outputs. Full article
(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)
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