The Effect of Diagenetic Evolution on Shale Gas Exploration and Development of the Longmaxi Formation Shale, Sichuan Basin, China

Wang, Jia; Tan, Xianfeng; Tian, Jingchun; Luo, Long; Gao, Xingjian; Luo, Chao; Zeng, Chunlin; Zhang, Lei; Xue, Weiwei

doi:10.3389/feart.2021.661581

Cited by 6 publications

(5 citation statements)

References 34 publications

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“…The classic neural networking (NN) approximation is adopted for handling various geophysical concerns, including wavelet calculations, velocity investigation, autopick of horizons, lithofacies classification on seismic, − and for the relationship of seismic extracted attributes toward their reservoir characteristics . However, notwithstanding its numerous effective procedures in exploration geophysics, the classic NN method has severe restrictions and shortcomings.…”

Section: Discussionmentioning

confidence: 99%

“…CWT offers precise characterization of stratigraphic reservoirs within the time−frequency domain, ultimately delivering the finest vertical seismic resolutions. 54,55 The basic methodology comprises that CWT decomposes the signal by convolving it with the wavelet. 56 These wavelets are scaled and translated to cover all possible scales and positions and are then correlated with the signal.…”

Section: Methodsmentioning

confidence: 99%

“…CWT conveys remarkably improved vertical seismic resolution when observed as a repeated panel of a nonstationary seismic signal. CWT offers precise characterization of stratigraphic reservoirs within the time–frequency domain, ultimately delivering the finest vertical seismic resolutions. , …”

Section: Methodsmentioning

confidence: 99%

“…CWT offers precise characterization of stratigraphic reservoirs within the time–frequency domain, ultimately delivering the finest vertical seismic resolutions. 54 , 55 …”

Section: Methodsmentioning

confidence: 99%

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ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation

Akram,

Akhter,

et al. 2024

ACS Omega

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The endeavor to explore and characterize oil and gas reservoirs presents significant challenges due to the inherent heterogeneities that are further compounded by the existence of thin sand layers encapsulated in shale strata. This complexity is intensified by limited and low-resolution seismic data, missing critical well-log information, and inaccessible angle stack data. Conventional reservoir classification approaches have struggled to address these issues, primarily due to their limitations in handling missing data effectively and, hence, precise estimations. This study focuses on the characterization of thin, heterogeneous potential sands of the B-interval within the Lower Goru Formation, a proven gas reservoir in the Badin area. The reservoir sands with varying thicknesses are assessed in detail for their optimized description and field productions by handling challenges, including low seismic resolutions, heterogeneities, and missing data sets. An innovative solution is developed based on the integration of continuous wavelet transform (CWT) and machine learning (ML) techniques for the approximation of missing data sets, i.e., S-wave (DTS), along with enhanced elastic and petrophysical properties. The improved properties are augmented by the high resolution attained by CWT and captured variability more profoundly through the implication of residual neural networks (ResNet). The limitations of conventional approaches are harnessed by ML solutions that operate with limited input data and deliver significantly improved results in characterizing enigmatic thin sand reservoirs. The high-frequency petroelastic properties reliably determined the thin heterogeneous potential sand bodies and illuminated a channelized play fairway that can be tested for additional wells with low-risk involvement.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…CWT offers precise characterization of stratigraphic reservoirs within the time–frequency domain, ultimately delivering the finest vertical seismic resolutions. 54 , 55 …”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation

Akram,

Akhter,

et al. 2024

ACS Omega

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“…Shale was characterized by typical "self-generation and storage" [3,18], and good organic geochemical indexes and reservoir parameters are the key factors for shale gas rich integrated reservoirs [2,22]. The hydrocarbon generation of organic matter during shale diagenesis will promote the formation of organic matter pores in shale, and the transformation and recrystallization of clay minerals will lead to the changes of shale matrix pores [20,23,24]. Therefore, studying shale geochemistry and its reservoir characteristics is necessary to understand the relationship between the two, and determining this is key to conducting informative shale gas geological research.…”

Section: Introductionmentioning

confidence: 99%

Relationship between Organic Geochemistry and Reservoir Characteristics of the Wufeng-Longmaxi Formation Shale in Southeastern Chongqing, SW China

Wang

Wang²,

Zhang

et al. 2021

Energies

Self Cite

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Shale gas accumulates in reservoirs that have favorable characteristics and associated organic geochemistry. The Wufeng-Longmaxi formation of Well Yucan-6 in Southeast Chongqing, SW China was used as a representative example to analyze the organic geochemical and reservoir characteristics of various shale intervals. Total organic carbon (TOC), vitrinite reflectance (Ro), rock pyrolysis, scanning electron microscopy (SEM), and nitrogen adsorption analyses were conducted, and a vertical coupling variation law was established. Results showed the following: the Wufeng-Longmaxi formation shale contains kerogen types I and II2; the average TOC value at the bottom of the formation is 3.04% (and the average value overall is 0.78%); the average Ro value is 1.94%; the organic matter is in a post mature thermal evolutionary stage; the shale minerals are mainly quartz and clay; and the pores are mainly intergranular, intragranular dissolved pores, organic matter pores and micro fractures. In addition, the average specific surface area (BET) of the shale is 5.171 m2/g; micropores account for 4.46% of the total volume; the specific surface area reaches 14.6%; and mesopores and macropores are the main pore spaces. There is a positive correlation between TOC and the quartz content of Wufeng-Longmaxi shale, and porosity is positively correlated with the clay mineral content. It is known that organic pores and the specific area develop more favorably when the clay mineral content is higher because the adsorption capacity is enhanced. In addition, as shale with a high clay mineral content and high TOC content promotes the formation of a large number of nanopores, it has a strong adsorption capacity. Therefore, the most favorable interval for shale gas exploration and development in this well is the shale that has a high TOC content, high clay mineral content, and a suitable quartz content. The findings of this study can help to better identify shale reservoirs and predict the sweet point in shale gas exploration and development.

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Influence of Mineralogy, Organic Matter and Thermal Maturity on the Diagenetic Evolution of Pore Systems in the Shales of Cambay and Raniganj Basin, India

Boruah,

Prusty

2023

Journal of the Geological Society of India

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The mineral composition, organic matter, thermal maturity, and diagenesis control the shale reservoir properties, including the pore distribution, variable fluid distribution, microstructure, heterogeneity, etc. The shale layers of the Cambay Formation and the Raniganj Formation are considered prospective shale gas resources in India. This paper focuses on the detailed analysis of shale from the Cambay Formation (Eocene age) of the Cambay Basin and the Raniganj Formation (Permian age) of the Raniganj Basin, India. The whole rock X-ray diffraction data indicates that quartz is the dominant mineral in both the shales (Raniganj and Cambay shale) of the Raniganj and the Cambay Basin. The main clay minerals are clinochlore, smectite-kaolinite, illite, and kaolinite in the Raniganj shale, while kaolinite, montmorillonite, and illitesmectite are the dominant clay minerals in the Cambay shale. The total organic content (TOC) ranges from 4.97 to 17.88 wt.% and 1.16-7.6% in the Raniganj and Cambay shales respectively. For the studied shale section, the TOC shows a gradual decrease with respect to depth in both shale types. The Raniganj shale has 3.8 to 8.3 percent total porosity, and the Cambay shale contains 1.16 to 6.5% total porosity. The increasing thermal maturity with the higher TOC corresponds to the more developed organic pores in the Raniganj shale. In contrast, the secondary pores are developing in the Cambay shale due to dissolution activities and enhancing the storage capacity. The study infers that the mineral composition and diagenesis are playing a crucial role in the pore system evolution of the shale in both the basins.

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The Effect of Diagenetic Evolution on Shale Gas Exploration and Development of the Longmaxi Formation Shale, Sichuan Basin, China

Cited by 6 publications

References 34 publications

ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation

ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation

Relationship between Organic Geochemistry and Reservoir Characteristics of the Wufeng-Longmaxi Formation Shale in Southeastern Chongqing, SW China

Influence of Mineralogy, Organic Matter and Thermal Maturity on the Diagenetic Evolution of Pore Systems in the Shales of Cambay and Raniganj Basin, India

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