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Advances in Unconventional Oil and Gas Accumulation, Reservoir Evaluation and Seepage Mechanism

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

Deadline for manuscript submissions: closed (30 August 2023) | Viewed by 7530

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Special Issue Editors

Prof. Dr. Shu Tao

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Guest Editor

Department of Energy and Environment, School of Energy Resources, China University of Geosciences, Beijing 100083, China
Interests: exploration and development of unconventional oil and gas resources such as coalbed methane, shale gas, shale oil, oil shale, and tight sandstone gas
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Dr. Huazhou Huang

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Guest Editor

School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
Interests: coalbed methane reservoir characterization; coproduced water with coalbed methane; coalbed methane drainage; abandoned coal mine gas extraction; gob gas extraction in coal mining area
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Dr. Shuoliang Wang

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Guest Editor

School of Energy Resources, China University of Geosciences (Beijing), Beijing 100083, China
Interests: unconventional natural oil and gas exploration and production; carbon dioxide geologic sequestration; enhanced oil recovery; ultra low velocity ercolation; vertical equilibrium; relative permeability
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Dr. Yanjun Meng

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Guest Editor

College of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China
Interests: coalbed methane reservoir engineering; fracturing fluid; reservoir damage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Fossil fuels are important to both the global and Chinese economies, and “unconventional” oil and gas resources—resources that cannot be produced, transported, or refined using traditional techniques—are expected to play an increasingly large role in helping the U.S. and China meet future energy needs. With rising energy prices, unconventional oil and gas resources have received renewed domestic attention in recent years. The efficient exploration and development of unconventional oil and gas requires the support of a series of geological and engineering studies, including exploration, evaluation, drilling, completion, and production. The aim of this Special Issue is to introduce the latest progresses in unconventional oil and gas geology and engineering, especially for reservoir evaluation, geological enrichment factors, enrichment models, permeability-integrated evaluation and mechanism analysis.

Prof. Dr. Shu Tao
Dr. Huazhou Huang
Dr. Shuoliang Wang
Dr. Yanjun Meng
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

unconventional oil and gas
reservoir evaluation
seepage mechanism
hydrocarbon enrichment models
reservoir petrophysics

Related Special Issue

Exploration and Development of Unconventional Oil and Gas Resources: Latest Advances and Prospects in Energies (7 articles)

Published Papers (6 papers)

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Research

16 pages, 11136 KiB

Open AccessArticle

Multiscale Fine Characterization of a Coal Pore–Fracture System Based on SEM, CT, and NMR in the Jingbian Block, Ordos Basin

by Suping Zhao, Rong Ding, Wenguang Tian and Jincheng Ye

Energies 2023, 16(14), 5315; https://doi.org/10.3390/en16145315 - 11 Jul 2023

Cited by 1 | Viewed by 1164

Abstract

To achieve an accurate and comprehensive characterization of the multiscale pore–fracture characteristics of Permian coal in the Jingbian Block, Ordos Basin, a combination of scanning electron microscopy (SEM), X-ray computed tomography (CT), and nuclear magnetic resonance (NMR) techniques was utilized. With these experiments, the mineral composition, pore size distribution (PSD), porosity, and connectivity of pores in coal samples were characterized through qualitative and quantitative methods. The results show that the SEM experiments enabled qualitative identification of pores and mineral types. The coal samples primarily contained gas pores, cell pores, intercrystalline pores, and moldic pores, and clay minerals were the predominant fracture fillings. The 3D reconstruction of the CT experiments shows that the pores and fractures generally expand horizontally, while the minerals show obvious bedding expansion characteristics. Moreover, the estimation of full-size porosity in coal samples can be achieved by combining CT and NMR experiments. The full-size porosity of samples G11-5-1, G11-5-6, G11-5-9, and G11-5-11 was 8.93%, 9.11%, 10.45%, and 11.63%, respectively. The connectivity differences are primarily determined by the throat development degree and the connected pore–fracture count. Samples with more connected pores and larger throat radii exhibit excellent connectivity. Full article

(This article belongs to the Special Issue Advances in Unconventional Oil and Gas Accumulation, Reservoir Evaluation and Seepage Mechanism)

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16 pages, 5953 KiB

Open AccessArticle

Numerical-Well-Testing Interpretation of Injection/Falloff Testing for Coalbed Methane Well in Hedong Coalfield

by Shiyue Fang, Xujing Zhang, Xinzhan Li, Yue Chen, Baiyi He, Yuan Bao and Dongmin Ma

Energies 2023, 16(13), 4864; https://doi.org/10.3390/en16134864 - 22 Jun 2023

Cited by 1 | Viewed by 1139

Abstract

Numerical well testing is used mostly in oil/gas, geothermal, and coalbed methane injection/falloff well-testing interpretations while few published studies have been presented on how to adjust the models and numerical experiments parameters. Meanwhile, there is no simple and highly applicable evaluation standard on the approximation degree between the simulated and field-measured pressure response. In this paper, seven groups of numerical experiments were conducted to obtain the simulated pressure response. The Pearson correlation coefficients and the grey correlation between the simulated and field-measured pressure response were calculated to evaluate the approximation degree. In homogeneous, stress-independent, multi-layered, heterogeneous and integrated models, the simulated pressure response curves all fit to the field data well at the early and late time of the falloff period. However, the highest approximation degree was only found in the integrated model. Finally, the permeability, initial pressure, skin factor and investigation radius of the tested CBM reservoir were determined. The results show that, to obtain a reliable interpretation result, it is best to give an approximation degree evaluation standard on the approximation degree between the simulated and field-measured pressure response, build an integrated numerical model, and input the correct parameters, such as the effective thickness and the testing fluid viscosity. Otherwise, it will also drop into a pitfall of multi-results. The method we used is very relevant to CBM exploration and safe mining in Hedong coalfield. Full article

(This article belongs to the Special Issue Advances in Unconventional Oil and Gas Accumulation, Reservoir Evaluation and Seepage Mechanism)

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14 pages, 2132 KiB

Open AccessArticle

Research on Displacement Efficiency by Injecting CO₂ in Shale Reservoirs Based on a Genetic Neural Network Model

by Shunli Qin, Juhua Li, Jingyou Chen, Xueli Bi and Hui Xiang

Energies 2023, 16(12), 4812; https://doi.org/10.3390/en16124812 - 20 Jun 2023

Cited by 1 | Viewed by 977

Abstract

Carbon dioxide injection can help solve two issues in shale reservoir production. Firstly, it can reduce carbon emissions while, secondly, improving unconventional reservoir recovery. There are many controlling factors for CO₂ injection to enhance oil recovery in shale reservoirs, and the effect of field implementation varies greatly. The key to popularizing this extraction technology is determining the main controlling factors of CO₂ displacement efficiency. Using CO₂ shale displacement laboratory results, the grey correlation analysis method was used to determine the main controlling factors affecting core oil displacement efficiency, such as shale reservoir physical parameters (rock compressibility, porosity, median pore size, matrix permeability, TOC, and oil saturation) and engineering parameters (soaking time and injection pressure). The genetic algorithm (GA) was introduced to optimize the backpropagation (BP) neural network to construct the prediction model of the CO₂ indoor displacement experiments in shale cores. The results showed that the injection pressure among the engineering parameters, the CO₂ soaking time among the gas injection parameters, and the porosity among the shale physical parameters were the main controlling factors affecting the oil displacement efficiency. The prediction accuracy of the genetic neural network model improved, and the coefficient of determination (R²) reached 0.983. Compared with the conventional neural network model, the mean absolute error (MAE) was reduced by 30%, the root mean square error (RMSE) was reduced by 46%, and the R² increased by 11%. Optimizing the learning and training of the prediction model significantly reduces the cost of laboratory experiments. The deep-learning model completed by training can intuitively show the degree of influence of input parameters on output parameters, providing a theoretical basis for the study of CO₂ displacement mechanisms in shale reservoirs. Full article

(This article belongs to the Special Issue Advances in Unconventional Oil and Gas Accumulation, Reservoir Evaluation and Seepage Mechanism)

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17 pages, 3881 KiB

Open AccessArticle

A Novel Method for the Calculation of Oil–Water Relative Permeability for Tight Oil Reservoirs by Considering Nonlinear Seepage Characteristics

by Junhong Jia, Yongqiang Zhang, Weiliang Xiong, Congbo Gou, Wenjian Liu and Shuoliang Wang

Energies 2023, 16(11), 4273; https://doi.org/10.3390/en16114273 - 23 May 2023

Viewed by 1230

Abstract

In view of the lack of clear physical significance of the parameters of the traditional nonlinear seepage models and the difficulty of obtaining accurate experimental measurements of the two-phase relative permeability curve, a nonlinear seepage model of a tight reservoir is established on the basis of fractal theory and boundary layer theory. The results show that the proposed model can comprehensively reflect the effects of reservoir matrix physical properties, reservoir fluid physical properties, wettability, and displacement-pressure gradient on the single-phase and two-phase nonlinear seepage characteristics of tight reservoirs. Furthermore, the introduction of the permeability loss factor makes the two-phase relative permeability model more representative of the morphological characteristics of the actual relative permeability curve and avoids the disadvantage that the relative permeability at the end point of the wetting phase has in the traditional model. Finally, by taking the tight core of Changqing Oilfield as an example, a sensitivity analysis of the proposed model is conducted, which proves the practical application of this model. The proposed model provides a convenient theoretical method for the accurate characterization of nonlinear seepage characteristics of tight reservoirs and is of great significance to the numerical simulation, productivity evaluation, and optimization of tight reservoirs. Full article

(This article belongs to the Special Issue Advances in Unconventional Oil and Gas Accumulation, Reservoir Evaluation and Seepage Mechanism)

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23 pages, 7449 KiB

Open AccessArticle

Research on Production Profiling Interpretation Technology Based on Microbial DNA Sequencing Diagnostics of Unconventional Reservoirs

by Haitong Yang, Lei Wang, Xiaolong Qiang, Zhengcheng Ren, Hongbo Wang, Yongbo Wang and Shuoliang Wang

Energies 2023, 16(1), 358; https://doi.org/10.3390/en16010358 - 28 Dec 2022

Viewed by 1026

Abstract

Production profiling technology is an important method for monitoring the dynamics of oil and gas reservoirs which can effectively improve the efficiency of oil recovery. Production profiling is a technique in which a test instrument is lowered from the tubing to the bottom of the well to measure flow, temperature, pressure, and density in a multi-layer section of a producing well. Normal production profiling process needs to stop production, operate complex, consume long time and high cost. Furthermore, the profile cannot be continuously monitored for a long time. To address these limitations, this paper proposes a production profiling interpretation method based on reservoir primitive microbial DNA sequencing. The microbial stratigraphic baseline with high-resolution features is obtained by sampling and DNA sequencing of produced fluid and cuttings from different wells. Specifically, the random forest algorithm is preferred and improved by comparing the accuracy, precision, recall, F1-score, and running time of three clustering methods: Naïve-Bayes classifier, random forest classifier, and back-propagation classifier. Constructing PSO-random forest model is based on stratigraphic records and produced fluid bacteria features. The computational accuracy and efficiency of this method allows it to describe the production profile for each formation. Moreover, this test process does not need to stop production with simple operation and does not pollute the formation. Meanwhile, by sampling fluid production at different stages, it can achieve the purpose of long-term effective dynamic monitoring of the reservoir. Full article

(This article belongs to the Special Issue Advances in Unconventional Oil and Gas Accumulation, Reservoir Evaluation and Seepage Mechanism)

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21 pages, 3475 KiB

Open AccessArticle

Geochemistry of the Tanshan Oil Shale in Jurassic Coal Measures, Western Ordos Basin: Implications for Sedimentary Environment and Organic Matter Accumulation

by Wei He, Shu Tao, Lianfu Hai, Rui Tao, Xiangcheng Wei and Lei Wang

Energies 2022, 15(22), 8535; https://doi.org/10.3390/en15228535 - 15 Nov 2022

Cited by 2 | Viewed by 1223

Abstract

The Tanshan area is located in the southern section of the west margin of the Ordos basin. The Middle Jurassic Yan’an Formation is relatively thick and rich in coal and oil shale layers, having positive potential for energy development. In order to explore the sedimentary environment of oil shale and the controlling factors of organic matter accumulation, 18 oil shale samples collected from two boreholes (Guyou-3 and Guyou-4) in the Tanshan area were selected as the research objects, and organic geochemical and elemental geochemical tests were carried out systematically. The results show that oil shales have the characteristics of medium oil content, medium ash, high calorific value, low sulfur and low maturity stage, which constitutes good hydrocarbon generation potential. The organic matter is mainly humic type, resulting from terrigenous debris and higher plant debris. The indictors of C-value (mean 81.90), Th/U ratio (mean 3.44), CaO/(MgO·Al₂ O₃) ratio (mean 0.07), δEu (mean 0.71), δCe (mean 1.15), V/(V + Ni) ratio (mean 0.79), Ce_anom index (mean −0.04), Ba_bio index (mean 488.97 μg/g), P/Ti ratio (mean 0.08), TOC/S ratio (mean 59.80), Sr/Ba ratio (mean 0.57) and (La/Yb)_N ratio (mean 14.71) indicate that Tanshan oil shales were formed in a warm–humid climate and anoxic-reducing environment, with a low-salinity water body and a low deposition rate but also a relatively low initial paleoproductivity. Paleoclimate conditions, organic matter sources and redox properties of paleowater are the main controlling factors affecting the accumulation of organic matter in oil shales. Although low paleoproductivity and deposition rates are not conducive to the preservation of organic matter, under the conditions of warm and humid climate and a reducing water environment, the continuous and stable input of terrigenous debris and higher plant debris can also cause the enrichment of organic matter. Full article

(This article belongs to the Special Issue Advances in Unconventional Oil and Gas Accumulation, Reservoir Evaluation and Seepage Mechanism)

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