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Global Geology 2017, 20(4) 253-258 DOI:
10.3969/j.issn.1673-9736.2017.04.08 ISSN: 1673-9736 CN: 22-1371/P |
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Seismic inversion modeling method for faulted basins:a case study of Liaohe Beach in Bijialing region |
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JING Siliang, LU Qi, WANG Dian |
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College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China |
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There is not much correlation between sand content and P-wave impedance in faulted basins, and the prediction results cannot be guaranteed. Due to sedimentary facies control, there is inconsistency between sand content and low frequency trend of P-wave impedance, causing problems for seismic inversion modeling, which directly affects final seismic inversion results. The acoustic impedance increases with burial depth. When the same layers of sand and shale formation endure different compaction, the acoustic impedance values will be different. Therefore, The seismic inversion modeling of faulted basin is different from that of conventional basins. The authors built an inversion model using uncompact sandstone percentage, directly compensating for the low frequency trend of the inversion model. In addition, the model's intermediate frequency is similar to P-wave impedance, ensuring that the inversion results are converged correctly. The final results of the inversion can be used directly as sandstone percentage. The aforementioned method was applied to Liaohe Beach in the Bijialing region and obtained optimistic lithology inversion effects:the results were correlated well with the depositional facies map and with lithology in the well borehole. The inversion results can be used to define the sand body horizontally and can separate sand bodies vertically, which is very difficult on conventional seismic section. Therefore the inversion results played an important role in reservoir prediction. |
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�ؼ�����
sandstone percentage curves
modelling
inversion
Bijialing region
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Seismic inversion modeling method for faulted basins:a case study of Liaohe Beach in Bijialing region |
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JING Siliang, LU Qi, WANG Dian |
|
|
College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China |
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Abstract:
There is not much correlation between sand content and P-wave impedance in faulted basins, and the prediction results cannot be guaranteed. Due to sedimentary facies control, there is inconsistency between sand content and low frequency trend of P-wave impedance, causing problems for seismic inversion modeling, which directly affects final seismic inversion results. The acoustic impedance increases with burial depth. When the same layers of sand and shale formation endure different compaction, the acoustic impedance values will be different. Therefore, The seismic inversion modeling of faulted basin is different from that of conventional basins. The authors built an inversion model using uncompact sandstone percentage, directly compensating for the low frequency trend of the inversion model. In addition, the model's intermediate frequency is similar to P-wave impedance, ensuring that the inversion results are converged correctly. The final results of the inversion can be used directly as sandstone percentage. The aforementioned method was applied to Liaohe Beach in the Bijialing region and obtained optimistic lithology inversion effects:the results were correlated well with the depositional facies map and with lithology in the well borehole. The inversion results can be used to define the sand body horizontally and can separate sand bodies vertically, which is very difficult on conventional seismic section. Therefore the inversion results played an important role in reservoir prediction. |
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Keywords:
sandstone percentage curves
modelling
inversion
Bijialing region
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�ո����� 2017-03-05 ������ 2017-04-10 ����淢������ |
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DOI: 10.3969/j.issn.1673-9736.2017.04.08 |
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ͨѶ����: LU Qi |
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����Email: luqi@jlu.edu.cn |
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Lai W C, Song Z C, Zhou X H,et al. 2009. Geology-seismic technique of reservoir prediction and its application in Bohai offshore area. Geoscience,23(5):933-939. (in Chinese)
Liu X B, Lin J C, Han C M,et al. 2002. Present conditions and prospects of the researches on seismic reservoir.Acta Geoscientia Sinica,23(1):73-79. (in Chinese)
Liu Y Y, Yu B S, Zhu J F,et al.Diagenesis and its influence on physical properties in Paleogene clastic reservoir in the west sag of the Beach area, Liaohe Depression.Geoscience, 23(4):731-738.(in Chinese)
Mu X. 2005. Effect of parameters control on sparse spike impedance inversion. Chinese Journal of Engineering Geophysics,2(2):104-108. (in Chinese)
Sun H B, Xie W Y. 2008. Oil and gas exploration and development in Liaohe River. Beijing:Geological Publishing House, 89-100. (in Chinese)
Sun H B, Zan L X. 2002. Geological characteristics and exploration potential in Liaohe zone.Special Oil and Gas Reservoirs,9(3):2-4. (in Chinese with English abstract)
Wang J Y. 1998. Geophysical inversion theory. Beijing:China University of Geosciences Press, 11-12. (in Chinese)
Wei D, Wang H Y, Du Y S,et al. 2013. Application of seismic inversion technology in reservoir prediction:a case study of Dongying Formation in the east sag of Liaohe beach area.Reservoir Evaluation and Development,3(1):9-10. (in Chinese)
Zhao H, Jiang J, Zheng J J,et al. 2003. Several important link in seismic inversion technology application in Jason.Petroleum Geophysics.,1(1):41-42. (in Chinese)
Zhao Z Z, Zhao X Z, Wang Y M,et al.2004. Theory and practice of reservoir earthquake prediction. Beijing:Science Press, 6-8. (in Chinese) |
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