Repeated Wildfires in the Middle Jurassic Xishanyao Formation (Aalenian and Bajocian Ages) in Northwestern China

Hou, Haihai; Shao, Longyi; Liang, Guodong; Tang, Yue; ZHANG, Huajie; Zhang, Jiaqiang

doi:10.1111/1755-6724.14912

Cited by 12 publications

(5 citation statements)

References 52 publications

(80 reference statements)

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“…Except for the Taoyuan coal mine, the exinite contents of other coal mines are not more than 10%. This indicates that repeated wildfires in the Carbonate–Permian strata in the Huaibei Coalfield did not occur. , …”

Section: Resultsmentioning

confidence: 99%

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Physical Characteristics of Coal Reservoirs and CBM Favorable Area Prediction in the Huaibei Coalfield, Northern China

Zhou,

Hu,

et al. 2024

ACS Omega

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To quantitatively characterize middle-high-ranked coal reservoirs, the physical characteristics of seven coal samples from the Huaibei Coalfield in northern China were investigated in detail based on experiments including proximate analysis, coal petrology, low-temperature nitrogen adsorption (LTNA), mercury intrusion porosimetry (MIP), nuclear magnetic resonance (NMR), and methane isothermal adsorption. The results show that coal maceral in the Huaibei Coalfield is dominated by vitrinite, with a large change in the maximum vitrinite reflectance ranging from 0.7 to 2.5%. The various coal metamorphisms can be attributed to the combined influence of magmatic activities of the Tanlu and Taihang Mountains during the Yanshanian. The coal quality can be characterized by medium-high ash yield, low to very low sulfur content, low phosphorus, and medium-high calorific value. From low-ranked coals to medium-ranked coals, the volume of adsorption and seepage pores decreases but the fracture volume increases due to the stronger dehydration and coal matrix shrinkages. From medium-ranked coals to high-ranked coals, adsorption pores have a significant advantage, suggesting a stronger CH 4 adsorption capacity. There is a positive correlation among the fixed carbon content, coal rank, and Langmuir volume, which can be attributed to the transformation of coal chemical composition and structure by coal metamorphism. The deep Xiaoxi in the Suixiao coal mining area, deep Nanping, deep Taoyuan−Qinan, deep Pengqiao, northern Zhuxianzhuang in the Suxian coal mining area, deep Renlou−Zhaoji, and Xutuan deep in the Linhuan mining area are predicted to be favorable areas for CBM exploration in the Huaibei Coalfield.

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Section: Resultsmentioning

confidence: 99%

“…This indicates that repeated wildfires in the Carbonate−Permian strata in the Huaibei Coalfield did not occur. 29,30 4.4. Coal Reservoir Physical Characteristics.…”

Section: Proximate Analysismentioning

confidence: 99%

Physical Characteristics of Coal Reservoirs and CBM Favorable Area Prediction in the Huaibei Coalfield, Northern China

Zhou,

Hu,

et al. 2024

ACS Omega

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“…The gelification index (GI) is expressed as GI = (Vitrinite + Macrinite)/(Semifusinite + Fusinite + Inertodetrinite). The tissue preservation index (TPI) is determined by TPI = (Telinite + Telocollinite + Semifusinite + Fusinite)/(Desmocollinite + Macrinite + Inertodetrinite). − …”

Section: Resultsmentioning

confidence: 99%

“…The tissue preservation index (TPI) is determined by TPI = (Telinite + Telocollinite + Semifusinite + Fusinite)/(Desmocollinite + Macrinite + Inertodetrinite). 50 − 52 …”

Section: Resultsmentioning

confidence: 99%

Correlating Coal Petrology and Methane Adsorption Parameters of High-Volatile Bituminous Coals with P-Wave Velocity

et al. 2022

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The parameters of coal petrology and methane adsorption are significant to exploit coal and coalbed methane (CBM). Based on borehole core sampling, a new method using the P-wave velocity to predict coal maceral, coal face index, and Langmuir parameter of high-volatile bituminous coals was proposed. The results showed that the P-wave velocity correlated positively with coal skeletal density, apparent density, and ash yield with fitting coefficients (R 2 ) of 0.55, 0.57, and 0.57, respectively, but it negatively correlated with coal porosity and moisture content with R 2 of 0.56 and 0.60, respectively. Vitrinite, ranging from 14.8 to 82.7% with an average of 53.8%, positively correlated with coal porosity due to more micropores in vitrinite and thus negatively correlated with the density and P-wave velocity. Inertinite content was in the range of 5.4 to 27.4% with an average of 11.0%, which correlated negatively with the coal porosity and thus positively with the density and P-wave velocity for most of the samples. Furthermore, the P-wave velocity was weakly positively correlated with mineral content, and a negative correlation was found between the P-wave velocity and vitrinite/ inertinite ratio (V/I), gelification index (GI), and Langmuir volume (V L ). The porosity (Y 1 ), vitrinite content (Y 2 ), inertinite content (Y 3 ), and V L (Y 4 ) of coals could be predicted based on the equations as follows: Y 1 = 7842.4 e −0.003X , Y 2 = −0.0003X 2 + 1.0731X − 924.09, Y 3 = 0.0003X 2 − 1.2797X + 1405, and Y 4 = −0.04X + 101.24, where X is the P-wave velocity. Generally, P-wave velocity could be largely used to predict the variations of the coal maceral and methane adsorption capacity of high-volatile bituminous coals, providing a new and valuable approach for CBM exploration and gas prevention in coal mines.

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“…In recent years, information about wildfires preserved in coal seams has been exposed (Robson et al, 2015;Hou et al, 2022;Zhang et al, 2022). The macerals in the pyrogenic inertinite (fossil charcoal in coal), such as fusinite, semifusinite, and inertodetrinite, have been widely used as direct changes in orbital cycle forcing climate change, which in turn influences wildfire activity (Verardo and Ruddiman, 1996;Thevenon et al, 2004;Hao et al, 2020;Shi et al, 2020;Cheng et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Orbital-scale climate dynamics impacts on Gzhelian peatland wildfire activity in the Ordos Basin

Du,

Lv,

Zhang

et al. 2024

Preprint

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Abstract. The Carboniferous, an important coal-forming period in geological history, was characterized by extensive vegetation and high oxygen levels. Numerous wildfire evidence suggests that high frequency of wildfire occurred at that time, specifically in peatlands. However, the control mechanisms for changes in wildfire activity in peatlands during this period are still not clearly understood. In this study, evidence from the Gzhelian in the Ordos Basin, such as the inertinite/vitrinite (I/V) ratio, indicated the existence of different frequencies of wildfire activity at that time. The CaO/MgO and CaO/MgO • Al2O3 climate indicators revealed that high-frequency wildfires mainly occur in warm and humid climates. Based on former age constraints, we deduced that orbital cycles (long eccentricity) controlled the climate influence on peatland wildfires during the Gzhelian. When eccentricity was high, abundant sunshine and frequent rainfall led to warmer and more humid peatlands. The latter environments were more favourable for vegetation development, leading to increased fuel loads, which in turn led to more frequent wildfires. Moreover, the Gzhelian global wildfire records, showed that evidence of wildfire during this period was mainly located in areas with abundant tropical vegetation, supporting the view that wildfire activity during this period was mainly controlled by the fuel loads. Although Hg could be produced by peatland wildfires, but our results show that Hg was mainly from frequent volcanic activity during this period.

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Repeated Wildfires in the Middle Jurassic Xishanyao Formation (Aalenian and Bajocian Ages) in Northwestern China

Cited by 12 publications

References 52 publications

Physical Characteristics of Coal Reservoirs and CBM Favorable Area Prediction in the Huaibei Coalfield, Northern China

Physical Characteristics of Coal Reservoirs and CBM Favorable Area Prediction in the Huaibei Coalfield, Northern China

Correlating Coal Petrology and Methane Adsorption Parameters of High-Volatile Bituminous Coals with P-Wave Velocity

Orbital-scale climate dynamics impacts on Gzhelian peatland wildfire activity in the Ordos Basin

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