Rare earth elements (REEs) geochemistry of Sinian–Cambrian reservoir solid bitumens in Sichuan Basin, SW China: potential application to petroleum exploration

Gao, Ping; Liu, Guangdi; Wang, Zecheng; Jia, Chengzao; Wang, Tongshan; Zhang, Pengwei

doi:10.1002/gj.2757

Cited by 19 publications

(13 citation statements)

References 48 publications

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“…The δCe ratio can be an indicator for paleoredox conditions in sediments. 62 − 64 Some researchers believe that the δCe ratio in organic extracts and solid bitumen is inherited from the precursor kerogens. 62 , 64 However, the δCe ratio will be easily obliterated by diagenetic alterations.…”

Section: Discussionmentioning

confidence: 99%

“… 62 − 64 Some researchers believe that the δCe ratio in organic extracts and solid bitumen is inherited from the precursor kerogens. 62 , 64 However, the δCe ratio will be easily obliterated by diagenetic alterations. 65 Eu is the only other REE with many factors and a complex process affecting its content.…”

Section: Discussionmentioning

confidence: 99%

“… 65 Eu is the only other REE with many factors and a complex process affecting its content. 66 In general, negative Eu anomalies in sediments are indicator of the oxidation environment; 62 yet, in a word, there are few studies on the source and impact factors of Ce and Eu anomalies in crude oil. Therefore, the cause of Ce and Eu anomalies in crude oil is not clear.…”

Section: Discussionmentioning

confidence: 99%

“…The δCe and δEu ratios are negative related to both PC1 and PC2 except for a weak positive of δEu ratios to PC1, which reflects that these two parameters are not comparable and inheritable in oil group classification. The δCe ratio can be an indicator for paleoredox conditions in sediments. − Some researchers believe that the δCe ratio in organic extracts and solid bitumen is inherited from the precursor kerogens. , However, the δCe ratio will be easily obliterated by diagenetic alterations . Eu is the only other REE with many factors and a complex process affecting its content .…”

Section: Discussionmentioning

confidence: 99%

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Application of Rare-Earth Elements and Comparison to Molecular Markers in Oil–Source Correlation of Tight Oil: A Case Study of Chang 7 of the Upper Triassic Yanchang Formation in Longdong Area, Ordos Basin, China

et al. 2020

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The biomarker features of 10 Chang 7 crude oil samples were investigated by gas chromatography–mass spectrometry (GC–MS), and the rare-earth element (REE) compositions of 16 Chang 7 and Chang 8 crude oil samples were determined by inductively coupled plasma–mass spectrometry (ICP–MS) for the first time in Longdong area. Oil–source correlation analysis was improved by biomarkers and REEs. The distribution and relative ratios of a series of biomarker parameters in saturated hydrocarbons and aromatic hydrocarbons of crude oil samples indicate that Chang 7 tight oil has already reached the mature stage. The organic matter mainly comes from lower aquatic organisms of algae, with some contribution of micro-organisms and bacteria, while the forming environment of tight oil is mainly the transitional environment of sub-oxidizing to sub-reducing. The V/(V + Ni) and Ni/Co ratios of crude oil samples suggest that the specific redox conditions of Chang 7 1 and Chang 7 2 samples were slightly oxic, while Chang 7 3 and Chang 8 samples were formed under an anoxic environment. The results of both biomarker-based and REE-based oil–source correlation analysis indicate that Chang 7 1 and Chang 7 2 tight oils come from Chang 7 mudstone, while most of the Chang 7 3 tight oils are from Chang 7 oil shale, with part of mixed from Chang 7 mudstone. This recognition may indicate that Chang 7 mudstone and oil shale are two relatively independent hydrocarbon self-generation and near-storage systems. The analysis results demonstrate that the REE composition in crude oil is an efficient and accurate tool for oil–source correlation in the petroleum system.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Application of Rare-Earth Elements and Comparison to Molecular Markers in Oil–Source Correlation of Tight Oil: A Case Study of Chang 7 of the Upper Triassic Yanchang Formation in Longdong Area, Ordos Basin, China

et al. 2020

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“…Trace and rare earth elements are not only widely used to discriminate the paleoenvironmental reconstruction, provenance, and tectonic setting of sediments [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] but also employed in crude oil classifications and oil-source correlations [18][19][20][21][22][23][24][25][26]. In the past times, many authors had focused on the study of trace and rare earth elements in mudstone whole rocks [3-5, 12, 25].…”

Section: Introductionmentioning

confidence: 99%

Trace and Rare Earth Element Partitioning in Organic Fractions of Mudstones during the Oil Formation

Gao

Li²,

Xiao

2022

Geofluids

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In order to investigate trace and rare earth element partitioning in organic fractions of mudstones, this study isolated organic fractions of mudstones, including insoluble organic fraction (kerogen), soluble organic fraction (extract), or expelled hydrocarbon (reservoir solid bitumen), and the isolated organic fractions and their corresponding whole rocks for trace and rare earth element compositions were measured. Analysis of trace and rare earth element compositions in organic fractions of lacustrine and marine mudstones revealed that mudstone kerogens were more enriched in rare earth elements (REE) and redox-sensitive trace elements (e.g., U, Mo, and Ni) relative to corresponding whole rocks. During the oil generation, middle rare earth elements (Sm-Ho), especially Eu, migrated from kerogen to extract more easily than the rest REE. The Eu was easily transferred to soluble hydrocarbon under the acidic and reducing environments formed by oil generation, resulting in the higher concentrations of Eu relative to its neighboring REE (Sm and Gd) and the pronounced positive Eu anomalies. Transition metal elements (e.g., Mo, V, Cr, Co, Ni, Cu, and Zn) also more easily released from kerogen than the rest elements, especially V and Ni. The enrichment and mobilization of trace elements in organic fractions of mudstones, such as Mo, U, V, Ni, and Ba, are closely related with their geochemical behaviors during the depositional and early digenetic processes, providing the potential information for predicting the distribution characteristics of trace elements in the expelled hydrocarbons of mudstones (e.g., crude oil and solid bitumen) and fingerprinting of oil to source.

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Enhanced semi‐supervised ensemble machine learning approach for earthwork construction simulation activity sequence automatically updating driven by weather data

Zhang

Peng

et al. 2022

Geological Journal

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Construction activity sequence changes are among the most crucial considerations in establishing construction simulation models. However, conventional simulation models are designed with a fixed sequence of simulation activities, which is unable to update automatically. Existing machine learning methods require abundant time for manual labelling and are unsuitable for construction data with high‐dimensional and heterogeneous characteristics. The motivation for this work is to develop a labour‐saving activity sequence classification model for earthwork construction simulation which realizes flexibly modifying simulation activities according to different weather conditions. Three heterogeneous semi‐supervised classifiers with complementary characteristics were ensembled to reduce the workload of manual labelling and enhance the generalization ability of activity sequence classification based on weather data. Furthermore, Dempster–Shafer‐based evidence reasoning improved by a security filtering mechanism was adopted to enhance the accuracy of semi‐supervised classification. The proposed enhanced ensemble semi‐supervised activity sequence classification model was embedded in an earthwork construction simulation model, which was evaluated in a case study of rockfill dam construction. The proposed classifier outperformed four common semi‐supervised methods and two common supervised methods in terms of accuracy and generalization ability. Additionally, the proposed simulation method outperformed conventional simulation methods in terms of the construction schedule, construction intensity and consistency of the simulated activity sequence with the true values by 65.55%, 28.47% and 88.15%, respectively.

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Rare earth elements (REEs) geochemistry of Sinian–Cambrian reservoir solid bitumens in Sichuan Basin, SW China: potential application to petroleum exploration

Cited by 19 publications

References 48 publications

Application of Rare-Earth Elements and Comparison to Molecular Markers in Oil–Source Correlation of Tight Oil: A Case Study of Chang 7 of the Upper Triassic Yanchang Formation in Longdong Area, Ordos Basin, China

Application of Rare-Earth Elements and Comparison to Molecular Markers in Oil–Source Correlation of Tight Oil: A Case Study of Chang 7 of the Upper Triassic Yanchang Formation in Longdong Area, Ordos Basin, China

Trace and Rare Earth Element Partitioning in Organic Fractions of Mudstones during the Oil Formation

Enhanced semi‐supervised ensemble machine learning approach for earthwork construction simulation activity sequence automatically updating driven by weather data

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