Recent Advances in Diagenesis and Reservoir 3D Modeling

Topic Information

Dear Colleagues,

Reservoir research plays a crucial role in sustainable development by enhancing our understanding of subsurface resources, improving resource management, and minimizing environmental impacts. By optimizing extraction techniques, reservoir research helps to maximize the efficiency of resource use, reduce waste, and lower carbon emissions. Additionally, reservoirs are a focal point of research in petroleum exploration and development, serving as the primary targets for hydrocarbon exploration and production. Understanding reservoir characteristics, including diagenesis evolution, three-dimensional (3D) modeling, and the influence of overpressure on reservoir evolution, is crucial for efficient resource assessment and development.

For in-depth exploration of reservoir diagenesis evolution processes, it is crucial to understand the mechanisms through which geological conditions influence reservoir pore structure, permeability, and fluid migration. This journal Topic focuses on the latest research developments in petroleum reservoir diagenesis evolution, 3D modeling, and overpressure. Various numerical simulation methods can be discussed to simulate reservoir diagenesis processes across micro to macro scales, thereby analyzing the effects of different diagenetic fluids on reservoir properties. Reservoir 3D modeling is a critical aspect of petroleum exploration and development. This special topic focuses on various advanced 3D modeling techniques, including sedimentary facies modeling, lithofacies modeling, and reservoir property modeling. Challenges and difficulties in reservoir 3D modeling can also be addressed. Additionally, this Topic focuses on reservoir overpressure issues, such as the effects of overpressure on reservoir properties, as well as the formation mechanisms and identification methods of overpressure.

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

1. Mechanisms and influencing factors of reservoir diagenesis evolution.
2. Numerical simulation methods and techniques for reservoir diagenesis processes.
3. Advanced techniques, applications, and challenges of reservoir 3D modeling.
4. Formation mechanisms and identification methods of overpressure and the impacts of overpressure on reservoir evolution.

Prof. Dr. Liqiang Zhang
Dr. Yiming Yan
Dr. Chao Li
Dr. Tingbin Sun
Dr. Binfeng Cao
Dr. Xingru Wu
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Geosciences geosciences	2.4	5.3	2011	23.5 Days	CHF 1800	Submit
Minerals minerals	2.2	4.1	2011	18 Days	CHF 2400	Submit
Resources resources	3.6	7.2	2012	26.1 Days	CHF 1600	Submit
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400	Submit

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Published Papers (2 papers)

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All Geosciences Minerals Resources Sustainability

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29 pages, 13392 KiB  

Open AccessArticle

Enhanced Data-Driven Machine Learning Models for Predicting Total Organic Carbon in Marine–Continental Transitional Shale Reservoirs

by Sizhong Peng, Congjun Feng, Zhen Qiu, Qin Zhang, Wen Liu and Wanli Gao

Sustainability 2025, 17(5), 2048; https://doi.org/10.3390/su17052048 - 27 Feb 2025

Viewed by 215

Abstract

Natural gas, as a sustainable and cleaner energy source, still holds a crucial position in the energy transition stage. In shale gas exploration, total organic carbon (TOC) content plays a crucial role, with log data proving beneficial in predicting total organic carbon content [...] Read more.

Natural gas, as a sustainable and cleaner energy source, still holds a crucial position in the energy transition stage. In shale gas exploration, total organic carbon (TOC) content plays a crucial role, with log data proving beneficial in predicting total organic carbon content in shale reservoirs. However, in complex coal-bearing layers like the marine–continental transitional Shanxi Formation, traditional prediction methods exhibit significant errors. Therefore, this study proposes an advanced, cost- and time-saving deep learning approach to predict TOC in marine–continental transitional shale. Five well log records from the study area were used to evaluate five machine learning models: K-Nearest Neighbors (KNNs), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGB), and Deep Neural Network (DNN). The predictive results were compared with conventional methods for accurate TOC predictions. Through K-fold cross-validation, the ML models showed superior accuracy over traditional models, with the DNN model displaying the lowest root mean square error (RMSE) and mean absolute error (MAE). To enhance prediction accuracy, δR was integrated as a new parameter into the ML models. Comparative analysis revealed that the improved DNN-R model reduced MAE and RMSE by 57.1% and 70.6%, respectively, on the training set, and by 59.5% and 72.5%, respectively, on the test set, compared to the original DNN model. The Williams plot and permutation importance confirmed the reliability and effectiveness of the enhanced DNN-R model. The results indicate the potential of machine learning technology as a valuable tool for predicting crucial parameters, especially in marine–continental transitional shale reservoirs lacking sufficient core samples and relying solely on basic well-logging data, signifying its importance for effective shale gas assessment and development. Full article

(This article belongs to the Topic Recent Advances in Diagenesis and Reservoir 3D Modeling)

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21 pages, 8843 KiB  

Open AccessArticle

Organic Geochemical Characteristics and Hydrocarbon Significance of the Permian System Around the Bogda Mountain, Junggar Basin, Northwest China

by Jiaquan Zhou, Chao Li, Ziyi Song and Xinlei Zhang

Sustainability 2025, 17(1), 347; https://doi.org/10.3390/su17010347 - 5 Jan 2025

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Abstract

Shale oil and gas resources have become an alternative energy source and are crucial in the field of sustainable oil and gas exploration. In the Junggar Basin, the Permian is not only the most significant source rock, but also an important field in [...] Read more.

Shale oil and gas resources have become an alternative energy source and are crucial in the field of sustainable oil and gas exploration. In the Junggar Basin, the Permian is not only the most significant source rock, but also an important field in shale oil and gas exploration. However, there are significant differences in the effectiveness of source rocks in different layers. During the Permian, the Bogda region effectively recorded the transition from marine environments in the Early Permian to terrestrial environments in the Late Permian, providing a viable opportunity for studying the Permian source rock of the Junggar Basin. We conducted an analysis of the total organic carbon (TOC), Rock-Eval pyrolysis, vitrinite reflectance (Ro), and biomarker compounds of Permian source rocks around the Bogda Mountain. The results indicate that the Lower Permian strata were primarily deposited in a moderately reducing marine environment, with the main organic matter sourced from planktonic organisms. These strata are currently in a high to over-mature stage, evaluated as medium-quality source rocks, and may have already generated and expelled substantial quantities of oil and gas, making the Lower Permian hydrocarbon resources within the basin a noteworthy target for deep condensate oil and gas exploration in adjacent depressions. The Middle Permian Wulabo and Jingjingzigou formations were deposited in a moderately oxidizing marine–continental transitional environment with significant terrestrial organic input. The kerogen type is predominantly Type III, and these formations are presently in the mature to over-mature stage with low organic abundance and poor hydrocarbon generation potential. The Middle Permian Lucaogou Formation was deposited in a moderately reducing saline lacustrine environment, with algae and planktonic organisms as the primary sources of organic matter. The kerogen types are mainly Type I and II₁, and it is currently within the oil-generation window. It is characterized by high organic abundance and evaluated as good to excellent source rocks, possessing substantial potential for shale oil exploration. The Upper Permian Wutonggou Formation was primarily deposited in a highly oxidizing continental environment with significant terrestrial input. The primary organic source comprises higher plants, resulting in Type III kerogen. These strata exhibit low organic abundance, are currently in the immature to mature stage, and are evaluated as poor source rocks with limited exploration potential. The information presented in this paper has important theoretical significance and practical value for oil and gas exploration and development in the Junggar Basin. Full article

(This article belongs to the Topic Recent Advances in Diagenesis and Reservoir 3D Modeling)
(This article belongs to the Section Sustainability in Geographic Science)

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