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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: 10 February 2025 | Viewed by 14484

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Special Issue Editors

Dr. Wei Zhou

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Guest Editor

School of Earth Science and Resources, Chang'an University, Xi'an, China
Interests: enhanced oil recovery; reservoir simulation; multiphase flow in porous media; chemical flooding; oilfield chemistry

Dr. Hongbin Yang

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Guest Editor

College of Petroleum Engineering, China University of Petroleum (Huadong), Qingdao 266580, China
Interests: functional gelling control agent; low-cost and high-efficiency chemical flooding system; production fluid treatment; temperature-resistant cleaning fracturing fluid
Special Issues, Collections and Topics in MDPI journals

Dr. Martin Ma

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Guest Editor

Computational Earth Science, Los Alamos National Laboratory, Los Alamos, NM, USA
Interests: reservoir simulation; production optmization; machine learning; CO₂ storage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to collect high-quality original research articles and review papers from the fields of Production Forecasting, Process Design, and Implementation in Petroleum Engineering. We encourage researchers from various fields within the journal’s scope to contribute original papers highlighting the latest developments in their research field or to invite relevant experts and colleagues to do so. Topics of interest for this Special Issue include, but are not limited to:

Production forecasting for various enhanced oil recovery (EOR) methods;
Design and field implementation of various EOR processes;
Machine learning applications in Petroleum Engineering;
Production forecasting for simulated horizontal wells with multi-stage hydraulic fractures;
Modeling and optimizing multi-stage hydraulic fractures;
Advanced optimization algorithms for production forecasting;
Experimental and numerical modeling of single and multiphase flows in oil and gas reservoirs;
Design and field implementation of water shutoff technologies and conformance control treatments;
Design and field implementation of CO₂ utilization and storage;
Reservoir evaluation of unconventional oil and gas reservoirs;
Reservoir characterization of unconventional oil and gas reservoirs.

Dr. Wei Zhou
Dr. Hongbin Yang
Dr. Martin Ma
Guest Editors

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Keywords

production forecasting
field implementation
process design
optimization algorithms
machine learning
multiphase flows
CO₂ utilization and storage
reservoir evaluation
reservoir characterization

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Published Papers (9 papers)

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Research

17 pages, 11126 KiB

Open AccessArticle

A Study on the Remaining Reserves of the Weiyuan Shale Gas Block in Three-Dimensional Development

by Yaoqiang Lin, Sijie He, Nan Wang, Jichang Zhu, Weifeng Ning, Yujin Wan and Mengfei Zhou

Appl. Sci. 2024, 14(21), 9738; https://doi.org/10.3390/app14219738 - 24 Oct 2024

Viewed by 524

Abstract

After 5 different plans of development, the Weiyuan block is struggling to maintain stable production and urgently needs a new method to improve the recovery rate. Practice at home and abroad shows that three-dimensional development can effectively improve the degree of vertical shale gas utilization. Therefore, this paper first analyzes the distribution of reservoirs in the Weiyuan block and calculates the distribution of remaining reserves through the methods of fine description of gas reservoirs and establishment of a three-dimensional geological model. The results show that the recovery degree of the platform in the main production area of Weiyuan is 35~60%, and the average remaining reserves of the wells are (1.2~3) × 10⁸ m³, and there is three-dimensional development potential in the local area. Secondly, through the establishment of a fracture and rock mechanics model, the target layer system for three-dimensional development of the Weiyuan block is preliminary selected from five aspects, namely, remaining reserves, reservoir characteristics, fracture density, mechanical characteristics, and the comparison of the height of the fracture network. Finally, in order to check the correctness of the target layer for three-dimensional development and evaluate the effect of the three-dimensional development, four scenarios for the lower branch of the H8 platform are designed and numerically simulated using Petrel RE software. The results of the numerical simulation show that Option 2 is the most effective, which can increase the production of the platform by 1.76 × 10⁸ m³, and the recovery rate grows from 16.4% to 31.0%, with an overall increase of 14.6%. The relevant understanding can provide a reference for the three-dimensional development strategy of the Weiyuan shale gas block. Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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17 pages, 27624 KiB

Open AccessArticle

Large-Scale Physical Simulation Experiment of Water Invasion Law for Multi-Well Development in Sandstone Gas Reservoirs with Strong Water Drive

by Feifei Fang, Sijie He, Jian Zhuang, Jie Zhang and Yanan Bian

Appl. Sci. 2024, 14(17), 8067; https://doi.org/10.3390/app14178067 - 9 Sep 2024

Cited by 1 | Viewed by 543

Abstract

In order to clarify the water invasion law and residual gas distribution characteristics in edge and bottom water gas reservoirs with multi-well development, a large-scale three-dimensional physical simulation model was developed and a physical simulation experiment method for the water invasion law of multi-well development in sandstone gas reservoirs with strong water drives was established. Water invasion physical simulation experiments of multi-well development under the conditions of different water body multiples and production systems were conducted. The results show the following: (1) Gas wells near fractures and high-permeability zones experience the earliest water breakthrough. The larger the water body multiple, the faster the rate of water invasion, the earlier the water breakthrough time of gas wells, the more severe the degree of water invasion in gas reservoirs, and the lower the ultimate recovery rate. (2) Shutting in low-position gas wells immediately after water breakthrough reduces the overall water production of the gas reservoir and extends the overall water-free gas production period. However, the ultimate recovery rate is lower than when the wells are not shut in. (3) The residual gas in the fracture model is mainly distributed around the fracture and the edge of the gas reservoir, with the ultimate recovery rate ranging from 38.5% to 58.2%. The residual gas in the fracture–high-permeability zone model is mainly distributed around the fracture–high-permeability zone and the edge of the gas reservoir, with the ultimate recovery rate ranging from 28.32% to 41.8%. The experimental results have important guiding significance for the economical and efficient development of similar gas reservoirs. Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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18 pages, 14858 KiB

Open AccessArticle

Research on Mechanism of Non-Uniform In-Situ Stress Induced Casing Damage Based on Finite Element Analysis

by Tianjiang Wu, Mei Li, Nana Liu, Tao Zhang and Junwei Su

Appl. Sci. 2024, 14(14), 5987; https://doi.org/10.3390/app14145987 - 9 Jul 2024

Viewed by 988

Abstract

Casing damage is a common problem encountered during oil and gas field development due to the complex stress state of the casing. Despite the large number of studies focusing on this problem, the mechanism of non-uniform in-situ stress-induced casing damage in a low-permeability reservoir is still unclear. In this study, casing damage due to non-uniform in-situ stress variations was investigated, and then the tectonic stress coefficients in the study area were determined by an in-situ stress inversion technique, which led to the derivation of formulas for calculating the maximum and minimum horizontal in-situ stresses. Subsequently, finite element numerical simulations were performed to assess the stress distribution during the formation of the casing cement sheath in a G155 block, a typical low-permeability reservoir. The results indicate that casing damage is caused not only by non-uniform in-situ stresses but also by various additional creep-induced loads. Subsequent finite element investigations into casing behavior under mudstone creep conditions indicated that immersion of mudstone in water instigated further shearing and deformation of the casing, culminating in premature well failure prior to water inundation. Notably, Von Mises stress levels exhibited a positive correlation with injection production ratios, with values exceeding critical thresholds leading to distinct modes of mechanical failure including shear-induced deformations, longitudinal tensile stress, and localized yielding near water wells. Maintenance of an optimal injection production ratio is identified as a key strategy for prolonging casing longevity in the region. To this end, recommendations include augmenting the casing wall thickness or enhancing the steel pressure specifications to mitigate casing damage progression, thereby extending the operational lifespan. This research serves as a pivotal theoretical framework for informing future development strategies aimed at mitigating and preempting casing failures in a low-permeability reservoir. Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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16 pages, 6831 KiB

Open AccessArticle

Optimization of CO₂ Injection Huff and Puff Process in Shale Reservoirs Based on NMR Technology

by Yang Gao, Dehua Liu, Sichen Li, Liang Cheng and Jing Sun

Appl. Sci. 2024, 14(6), 2411; https://doi.org/10.3390/app14062411 - 13 Mar 2024

Viewed by 1004

Abstract

The pore mobilization characteristics of CO₂ when in shale reservoirs is an important indicator for evaluating the effectiveness of its application for enhanced recovery in shale reservoirs, and it is important to develop a comprehensive set of physical simulation methods that are consistent with actual field operations. This has underscored the need for efficient development techniques in the energy industry. The huff-n-puff seepage oil recovery method is crucial for developing tight oil reservoirs, including shale oil. However, the small pore size and low permeability of shale render conventional indoor experiments unsuitable for shale oil cores. Consequently, there is a need to establish a fully enclosed experimental method with a high detection accuracy to optimize the huff and puff process parameters. The NMR technique identifies oil and gas transport features in nanogaps, and in this study, we use low-field nuclear magnetic resonance (NMR) online displacement technology to conduct CO₂ huff and puff experiments on shale oil, covering the gas injection, well stewing, and production stages. After conducting four rounds of huff-n-puff experiments, key process parameters were optimized, including the simmering time, huff-n-puff timing, number of huff-n-puff rounds, and the amount of percolant injected. The findings reveal that as the number of huff-n-puff rounds increases, the time required for well stabilization decreases correspondingly. However, the enhancement in recovery from additional huff-n-puff rounds becomes negligible after three rounds, showing only a 1.16% improvement. CO₂ re-injection is required when the pressure falls to 70% of the initiaformation pressure to ensure efficient shale oil well development. This study also indicates that the most economically beneficial results are achieved when the injection volume of the huff-n-puff process is 0.44 pore volumes (PVs). Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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16 pages, 3446 KiB

Open AccessArticle

Calculation Model of Drainage Radius of Single-Layer/Multi-Layer Commingled Gas Production Wells in a Closed Constant-Volume Gas Reservoir and Its Application

by Cuiping Xin, Wei Zhou, Lei Zhang, Xiangyang Qiao, Yongke Wang and Yue Xiao

Appl. Sci. 2024, 14(5), 1873; https://doi.org/10.3390/app14051873 - 24 Feb 2024

Viewed by 1259

Abstract

Gas drainage radius is the most important parameter for determining reasonable well spacing. However, the drainage radius of both single-layer and multi-layer commingled gas production wells cannot be directly obtained through reservoir well tests. In order to address the above challenge, for single-layer gas production wells in a closed constant-volume gas reservoir, a calculation model for drainage radius is derived using the modified flowing material balance method. The results indicate that the calculated error of this model is only 0.73% and much smaller than that of the flowing material balance method (5.78%), implying its high accuracy. For multi-layer commingled gas production wells, another calculation model of drainage radius is established by coupling the pseudo-steady-state production capacity equation with the material balance principle. The research results demonstrate that the novel calculation model has a maximum relative error of only 2.33% and requires only two production profile tests to rapidly calculate the drainage radius of each layer within the gas reservoir, suggesting its satisfactory simplicity, significant efficiency and high precision. The proposed calculation models of drainage radius achieve a convenient and rapid calculation for both single-layer and multi-layer commingled gas production wells, and fill the theoretical gap in efficient calculation of drainage radius for a closed constant-volume gas reservoir. Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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13 pages, 1975 KiB

Open AccessArticle

A New Model for Cleaning Small Cuttings in Extended-Reach Drilling Based on Dimensional Analysis

by Liping Jin, Gan Wang, Jingen Deng, Ze Li, Mingchi Zhu and Rong Wang

Appl. Sci. 2023, 13(22), 12118; https://doi.org/10.3390/app132212118 - 7 Nov 2023

Cited by 1 | Viewed by 1046

Abstract

A wellbore’s cleanliness affects drilling efficiency, economy and drilling safety directly in extended-reach drilling operations. Wellbore cleaning in extended-reach drilling has always been a tough problem. Field experience has shown that inefficient transport of small cuttings is a main factor for excessive drag and torque during extended-reach drilling. However, very little is known about the transport of small cuttings. In this paper, we use the data fitting method of dimensional analysis and regression analysis to establish a wellbore cleaning model for high-inclination sections, then use water and Polyanionic Cellulose (PAC) as a drilling fluid to analyze the settlement cleaning of small cuttings in the wellbore. The data from the example wells were used for field simulations to finally derive many factors like drilling fluid density, drilling fluid displacement, drill pipe rotation speed, diameter of cuttings and annulus hydraulic diameter, which affect the thickness of the dimensionless cutting bed. The results show that the dimensionless cutting thickness decreases with increasing drilling fluid density, drilling fluid displacement and drill pipe rotation speed; and increases with increasing cutting size and annular hydraulics diameter. Meanwhile, the effect of drilling fluid discharge, drill pipe rotation speed and cutting size on the thickness of the dimensionless cutting bed decreases as their values increase. This model can be utilized to design parameters in drilling and to predict the transport of cuttings in high-inclination sections. The successful establishment of the wellbore cleaning model for small cuttings in high-inclination sections of extended-reach drilling wells is highly innovative, which is a successful combination of theory and practice and has important guiding significance for promoting the development of wellbore cleaning technology. Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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14 pages, 6965 KiB

Open AccessArticle

Enhancing Oil Recovery and Altering Wettability in Carbonate Reservoir Rocks through (3-Glycidoxypropyl)trimethoxysilane–SiO₂ Nanofluid Injection

by Hochang Jang and Jeonghwan Lee

Appl. Sci. 2023, 13(19), 11105; https://doi.org/10.3390/app131911105 - 9 Oct 2023

Cited by 1 | Viewed by 1126

Abstract

This study analyzes the impact of injection condition design factors of (3-glycidoxypropyl)trimethoxysilane (GPTMS)–SiO₂ nanofluid on improving wettability and oil recovery through flotation and core flooding tests, respectively. Flotation tests were conducted to assess improvements in wettability that resulted from varying nanoparticle concentration, reaction time, and treatment temperature. The test results demonstrated that the hydrophilic sample ratio increased by up to 97.75% based on the nanoparticle reaction, confirming significant wettability improvement in all samples. Additionally, time-dependent fluid-flow experiments were conducted to validate oil recovery and rock–fluid interactions. In these experiments, for a 24-h reaction time, nanofluid injection caused a decrease in the maximum contact angle (43.4° from 166.5°) and a remarkable enhancement in the oil recovery rate by over 25%. Moreover, variations in contact angle and sample permeability were observed as the reaction time increased. Subsequently, the core flooding test revealed a critical reaction time of 24 h, maximizing oil recovery while minimizing permeability. Below this point in time, wettability improvement did not significantly enhance oil recovery. Conversely, beyond this threshold, additional adsorption due to particle aggregation decreased permeability, causing reduced oil recovery. Therefore, GPTMS–SiO₂ nanofluid can be utilized as an injection fluid to enhance oil recovery in high-temperature and high-salinity carbonate reservoirs. Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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17 pages, 5788 KiB

Open AccessArticle

Enhancing Production Prediction in Shale Gas Reservoirs Using a Hybrid Gated Recurrent Unit and Multilayer Perceptron (GRU-MLP) Model

by Xianlin Ma, Mengyao Hou, Jie Zhan and Rong Zhong

Appl. Sci. 2023, 13(17), 9827; https://doi.org/10.3390/app13179827 - 30 Aug 2023

Cited by 4 | Viewed by 1629

Abstract

Shale gas has revolutionized the global energy supply, underscoring the importance of robust production forecasting for the effective management of well operations and gas field development. Nonetheless, the intricate and nonlinear relationship between gas production dynamics and physical constraints like shale formation properties and engineering parameters poses significant challenges. This investigation introduces a hybrid neural network model, GRU-MLP, to proficiently predict shale gas production. The GRU-MLP architecture can capture sequential dependencies within production data as well as the intricate nonlinear correlations between production and the governing constraints. The proposed model was evaluated employing production data extracted from two adjacent horizontal wells situated within the Marcellus Shale. The comparative analysis highlights the superior performance of the GRU-MLP model over the LSTM and GRU models in both short-term and long-term forecasting. Specifically, the GRU model’s mean absolute percentage error of 4.7% and root mean squared error of 120.03 are notably 66% and 80% larger than the GRU-MLP model’s performance in short-term forecasting. The accuracy and reliability of the GRU-MLP model make it a promising tool for shale gas production forecasting. By providing dependable production forecasts, the GRU-MLP model serves to enhance decision-making and optimize well operations. Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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20 pages, 4738 KiB

Open AccessArticle

Hybrid Model of Machine Learning Method and Empirical Method for Rate of Penetration Prediction Based on Data Similarity

by Fei Zhou, Honghai Fan, Yuhan Liu, Hongbao Zhang and Rongyi Ji

Appl. Sci. 2023, 13(10), 5870; https://doi.org/10.3390/app13105870 - 10 May 2023

Cited by 5 | Viewed by 4554

Abstract

The rate of penetration (ROP) is an important indicator affecting the drilling cost and drilling performance. Accurate prediction of the ROP has important guiding significance for increasing the drilling speed and reducing costs. Recently, numerous studies have shown that machine learning techniques are an effective means to accurately predict the ROP. However, in petroleum engineering applications, its robustness and generalization cannot be guaranteed. The traditional empirical model has good robustness and generalization ability. Based on the quantification of data similarity, this paper establishes a hybrid model combining a machine learning method and an empirical method, which combines the high prediction accuracy of the machine learning method with the good robustness and generalization of the empirical method, overcoming the shortcomings of any single model. The AE-ED (the Euclidean Distance between the input data and reconstructed data from the autoencoder model) is defined to measure the data similarity, and according to the data similarity of each new piece of input data, the hybrid model chooses the corresponding single model to calculate. The results show that the hybrid model is better than any single model, and all the evaluation indicators perform better, making it more suitable for the ROP prediction in this field. Full article

(This article belongs to the Special Issue Petroleum Engineering: Production Forecasting, Process Design, and Implementation)

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