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Research on Offshore Oil and Gas Numerical Simulation
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Research on Offshore Oil and Gas Numerical Simulation

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312).

Deadline for manuscript submissions: 15 June 2025 | Viewed by 3860

Special Issue Editor

Dr. Jianchun Xu

E-Mail Website
Guest Editor
School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Interests: unconventional oil and gas development; CCUS; numerical simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Numerical Simulation is wildly used in petroleum engineering for oil and gas development. The Special Issue “Research on Offshore Oil and Gas Numerical Simulation” will address the most recent advances in modeling methods and simulation techniques for offshore oil and gas reservoirs. Submissions should discuss the use of numerical simulations in the petroleum industry. The fields include reservoir evaluation and engineering, deep water oil and gas development, enhanced oil recovery, proxy models, data analytics, multiphase flow in porous media, CO2 Sequestration, and the development of unconventional resources such as tight oil, tight gas, gas hydrate, and smart wells.

Dr. Jianchun Xu
Guest Editor

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. Journal of Marine Science and Engineering 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 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

  • multiphase, multicomponent flow in porous media
  • modeling and simulation methods
  • proxy model
  • production optimization
  • numerical simulation of unconventional oil and gas reservoirs
  • smart wells

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Published Papers (4 papers)

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Research

24 pages, 7475 KiB  
Article
Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images: A Case Study in the South China Sea
by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue and Zeyu Zhang
J. Mar. Sci. Eng. 2025, 13(5), 997; https://doi.org/10.3390/jmse13050997 - 21 May 2025
Abstract
Electrical imaging logging technology precisely characterizes the features of the formation on the borehole wall through high-resolution resistivity images. However, the problem of blank strips caused by the mismatch between the instrument pads and the borehole diameter seriously affects the accuracy of fracture [...] Read more.
Electrical imaging logging technology precisely characterizes the features of the formation on the borehole wall through high-resolution resistivity images. However, the problem of blank strips caused by the mismatch between the instrument pads and the borehole diameter seriously affects the accuracy of fracture identification and formation continuity interpretation in marine oil and gas reservoirs. Existing inpainting methods struggle to reconstruct complex geological textures while maintaining structural continuity, particularly in balancing low-frequency formation morphology with high-frequency fracture details. To address this issue, this paper proposes an inpainting method using a dual-stream network based on the collaborative optimization of wavelet and spatial-channel convolution. By designing a texture-aware data prior algorithm, a high-quality training dataset with geological rationality is generated. A dual-stream encoder–decoder network architecture is adopted, and the wavelet transform convolution (WTConv) module is utilized to enhance the multi-scale perception ability of the generator, achieving a collaborative analysis of the low-frequency formation structure and high-frequency fracture details. Combined with the spatial channel convolution (SCConv) to enhance the feature fusion module, the cross-modal interaction between texture and structural features is optimized through a dynamic gating mechanism. Furthermore, a multi-objective loss function is introduced to constrain the semantic coherence and visual authenticity of image reconstruction. Experiments show that, in the inpainting indexes for Block X in the South China Sea, the mean absolute error (MAE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) of this method are 6.893, 0.779, and 19.087, respectively, which are significantly better than the improved filtersim, U-Net, and AOT-GAN methods. The correlation degree of the pixel distribution between the inpainted area and the original image reaches 0.921~0.997, verifying the precise matching of the low-frequency morphology and high-frequency details. In the inpainting of electrical imaging logging images across blocks, the applicability of the method is confirmed, effectively solving the interference of blank strips on the interpretation accuracy of marine oil and gas reservoirs. It provides an intelligent inpainting tool with geological interpretability for the electrical imaging logging interpretation of complex reservoirs, and has important engineering value for improving the efficiency of oil and gas exploration and development. Full article
(This article belongs to the Special Issue Research on Offshore Oil and Gas Numerical Simulation)
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18 pages, 7693 KiB  
Article
Numerical Simulation of Natural Gas Hydrate Depressurization Extraction Considering Phase Transition Characteristics
by Qiang Fu, Mingqiang Chen, Weixin Pang and Lirong Dong
J. Mar. Sci. Eng. 2025, 13(3), 511; https://doi.org/10.3390/jmse13030511 - 5 Mar 2025
Viewed by 579
Abstract
Natural gas hydrate (NGH) is a clean resource characterized by abundant potential reserves, clean combustion, and high energy density. Although significant progress has been made in the development of NGH resources all around the world, challenges still exist that hinder commercial exploitation, such [...] Read more.
Natural gas hydrate (NGH) is a clean resource characterized by abundant potential reserves, clean combustion, and high energy density. Although significant progress has been made in the development of NGH resources all around the world, challenges still exist that hinder commercial exploitation, such as a low daily gas production rate and short steady production periods. One significant reason lies in the complex gas–liquid–solid phase transitions occurring within the formation during production, which lead to changes in flow capacity. Understanding the phase change mechanism of NGH reservoirs will help to further reveal the production increase mechanism. To address the phase transitions’ effect on production, this paper establishes a numerical simulation model for the depressurization exploitation of natural gas hydrates in order to investigate phase transition characteristics at the field scale. First, the phase equilibrium calculation method is presented and the phase equilibrium curve is modified by considering the capillary effect, soluble salt, and surface adsorption. Then, the phase transition model is successfully characterized in a simulation and the numerical simulation model is established based on the first test project parameters in the Shenhu area. The production characteristics of different sediment types (montmorillonite, South China Sea sediments, kaolin, and silt) are analyzed under the effects of water content and salinity. It is shown that lower initial water content and higher salinity result in higher gas production. The results provide a better understanding of the effects of phase transition parameters on NGH production at the field scale. Full article
(This article belongs to the Special Issue Research on Offshore Oil and Gas Numerical Simulation)
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26 pages, 17105 KiB  
Article
CNN-GRU-ATT Method for Resistivity Logging Curve Reconstruction and Fluid Property Identification in Marine Carbonate Reservoirs
by Jianhong Guo, Hengyang Lv, Qing Zhao, Yuxin Yang, Zuomin Zhu and Zhansong Zhang
J. Mar. Sci. Eng. 2025, 13(2), 331; https://doi.org/10.3390/jmse13020331 - 12 Feb 2025
Viewed by 736
Abstract
Geophysical logging curves are crucial for oil and gas field exploration and development, and curve reconstruction techniques are a key focus of research in this field. This study proposes an inversion model for deep resistivity curves in marine carbonate reservoirs, specifically the Mishrif [...] Read more.
Geophysical logging curves are crucial for oil and gas field exploration and development, and curve reconstruction techniques are a key focus of research in this field. This study proposes an inversion model for deep resistivity curves in marine carbonate reservoirs, specifically the Mishrif Formation of the Halfaya Field, by integrating a deep learning model called CNN-GRU-ATT, which combines Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), and the Attention Mechanism (ATT). Using logging data from the marine carbonate oil layers, the reconstructed deep resistivity curve is compared with actual measurements to determine reservoir fluid properties. The results demonstrate the effectiveness of the CNN-GRU-ATT model in accurately reconstructing deep resistivity curves for carbonate reservoirs within the Mishrif Formation. Notably, the model outperforms alternative methods such as CNN-GRU, GRU, Long Short-Term Memory (LSTM), Multiple Regression, and Random Forest in new wells, exhibiting high accuracy and robust generalization capabilities. In practical applications, the response of the inverted deep resistivity curve can be utilized to identify the reservoir water cut. Specifically, when the model-inverted curve exhibits a higher response compared to the measured curve, it indicates the presence of reservoir water. Additionally, a stable relative position between the two curves suggests the presence of a water layer. Utilizing this method, the oil–water transition zone can be accurately delineated, achieving a fluid property identification accuracy of 93.14%. This study not only introduces a novel curve reconstruction method but also presents a precise approach to identifying reservoir fluid properties. These findings establish a solid technical foundation for decision-making support in oilfield development. Full article
(This article belongs to the Special Issue Research on Offshore Oil and Gas Numerical Simulation)
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19 pages, 10799 KiB  
Article
Study on CO2-Enhanced Oil Recovery and Storage in Near-Depleted Edge–Bottom Water Reservoirs
by Jianchun Xu, Hai Wan, Yizhi Wu, Shuyang Liu and Bicheng Yan
J. Mar. Sci. Eng. 2024, 12(11), 2065; https://doi.org/10.3390/jmse12112065 - 14 Nov 2024
Viewed by 1938
Abstract
The geological storage of carbon dioxide (CO2) is a crucial technology for mitigating global temperature rise. Near-depleted edge–bottom water reservoirs are attractive targets for CO2 storage, as they can not only enhance oil recovery (EOR) but also provide important potential [...] Read more.
The geological storage of carbon dioxide (CO2) is a crucial technology for mitigating global temperature rise. Near-depleted edge–bottom water reservoirs are attractive targets for CO2 storage, as they can not only enhance oil recovery (EOR) but also provide important potential candidates for geological storage. This study investigated CO2-enhanced oil recovery and storage for a typical near-depleted edge–bottom water reservoir that had been developed for a long time with a recovery factor of 51.93%. To improve the oil recovery and CO2 storage, new production scenarios were explored. At the near-depleted stage, by comparing the four different scenarios of water injection, gas injection, water-alternating-gas injection, and bi-directional injection, the highest additional recovery of 3.62% was achieved via the bi-directional injection scenario. Increasing the injection pressure led to a higher gas–oil ratio and liquid production rate. After shifting from the near-depleted to the depleted stage, the most effective approach to improving CO2 storage capacity was to increase reservoir pressure. At 1.4 times the initial reservoir pressure, the maximum storage capacity was 6.52 × 108 m3. However, excessive pressure boosting posed potential storage and leakage risks. Therefore, lower injection rates and longer intermittent injections were expected to achieve a larger amount of long-term CO2 storage. Through the numerical simulation study, a gas injection rate of 80,000 m3/day and a schedule of 4–6 years injection with 1 year shut-in were shown to be effective for the case considered. During 31 years of CO2 injection, the percentage of dissolved CO2 increased from 5.46% to 6.23% during the near-depleted period, and to 7.76% during the depleted period. This study acts as a guide for the CO2 geological storage of typical near-depleted edge–bottom water reservoirs. Full article
(This article belongs to the Special Issue Research on Offshore Oil and Gas Numerical Simulation)
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