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An interpretative high-resolution seismic data processing method based on multi-level fractional calculus
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Lijun GAO1, 2, Haiying LI2, Wei YANG2, Wei GONG2, Qingqing LI1
World Nuclear Geoscience | 2025, 42(3) : 552 - 564
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World Nuclear Geoscience | 2025, 42(3): 552-564
• RESEARCH ARTICALS •
An interpretative high-resolution seismic data processing method based on multi-level fractional calculus
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Lijun GAO1, 2, Haiying LI2, Wei YANG2, Wei GONG2, Qingqing LI1
Affiliations
  • 1 Key Laboratory of Deep Oil& Gas，China University of Petroleum (East China)，Qingdao 266580，China
  • 2 Sinopec Northwest China Petroleum Bureau，Urumqi 830011， China
Published: 2025-06-08 doi: 10.3969/j.issn.1672-0636.2025.03.007
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In seismic exploration，high-resolution seismic reflection imaging data volumes are critical tools for achieving fine identification of thin sandstone bodies and fault structures in sedimentary basins. However，actual seismic imaging profiles often face the loss of low- and high-frequency signals，leading to low seismic imaging resolution and ineffective identification of oil，gas，uranium，coal，and other mineral resources. In signal processing，integral and differential algorithms of effective signals respectively reflect their low- and high-frequency components. Based on this principle，this paper proposes an interpretative high-resolution processing method using multi-level fractional calculus. By separately calculating different fractional-order components of effective signals，the missing low- and high-frequency components in seismic imaging profiles are obtained. Through the introduction of multivariate Gaussian theory，Bayesian theory，and statistical inversion to improve the solving process of weighting coefficients，a broadband high-resolution seismic imaging profile is established. Compared with traditional calculus-based high-resolution processing methods，this method effectively enhances the accuracy of weighting coefficient determination and avoids the impact of calculation errors on precision. Processing results from both onshore and offshore actual data demonstrate that the proposed method significantly improves the resolution and frequency bandwidth of seismic data，thereby enhancing high-resolution identification of sand bodies and related structures.

multivariate Gaussian  /  multi-level fractional-order calculus  /  resolution  /  seismic data
Lijun GAO, Haiying LI, Wei YANG, Wei GONG, Qingqing LI. An interpretative high-resolution seismic data processing method based on multi-level fractional calculus[J]. World Nuclear Geoscience, 2025 , 42 (3) : 552 -564 . DOI: 10.3969/j.issn.1672-0636.2025.03.007
Funding
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  • Study on identification，description and evaluation technology of ultra-deep and super-deep carbonate rock traps(P24136)
  • Integrated research and application of ultra-deep and super-deep drilling geological engineering(P24009)
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Year 2025 volume 42 Issue 3
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Article Info
doi: 10.3969/j.issn.1672-0636.2025.03.007
  • Receive Date：2025-05-26
  • Online Date：2025-11-10
  • Published：2025-06-08
Article Data
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History
  • Received：2025-05-26
  • Revised：2025-05-31
Funding
Study on identification，description and evaluation technology of ultra-deep and super-deep carbonate rock traps(P24136)
Integrated research and application of ultra-deep and super-deep drilling geological engineering(P24009)
Affiliations
    1 Key Laboratory of Deep Oil& Gas，China University of Petroleum (East China)，Qingdao 266580，China
    2 Sinopec Northwest China Petroleum Bureau，Urumqi 830011， China
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https://castjournals.cast.org.cn/joweb/hdzkx/EN/10.3969/j.issn.1672-0636.2025.03.007
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表12种不同金属材料的力学参数
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Family		 属数
Number of
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Number of
species		 占总种数比例
Percentage of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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