华南火成岩区深层地热勘探地震处理关键技术

doi:10.11720/wtyht.2024.1084

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Abstract

Southern China's igneous province,as a significant geothermal resource area in China,possesses abundant geothermal resources owing to its favorable accumulation conditions for medium-to-high temperature geothermal resources.However,gravity-magnetic-magnetotelluric exploration methods fail to sufficiently characterize the formation structures,geothermal reservoir boundaries,and the spatial distribution of geothermal reservoirs within the concealed fault zones,posing challenges in exploring deep geothermal resources.Hence,this study delved into the key seismic processing techniques for deep geothermal exploration based on 3D seismic exploration data,establishing a targeted processing flow.First,the problem of low signal-to-noise ratios in deep layers was solved through fine-scale preprocessing for deep geothermal reservoirs,laying a solid data foundation.Then,a high-precision velocity model was built via fault-guided tomography velocity modeling.Finally,the high-precision imaging of deep geothermal reservoirs was achieved using the amplitude-preserving low-frequency reverse-time migration technology,thus improving the imaging quality and the characterization accuracy of geothermal reservoir spaces and high-steep boundaries.Field data-based testing verified the validity and practicability of the processing flow.

Key words： deep geothermal exploration geothermal reservoir boundary preprocessing velocity modeling high-precision imaging

Received: 03 April 2023 Published: 26 February 2024

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	Articles by authors
	Hao ZHENG
	Yue CUI
	Lu XU
	Peng QI

Cite this article:

Hao ZHENG,Yue CUI,Lu XU, et al. A key seismic processing technique for deep geothermal exploration in igneous province in southern China[J]. Geophysical and Geochemical Exploration, 2024, 48(1): 88-97.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2024.1084 OR https://www.wutanyuhuatan.com/EN/Y2024/V48/I1/88

Kinds of noises exist in seismic data of Southern China

Workflow of seismic data denoising

Comparison of surface wave noise before(a) and after(b) suppression

Comparison of abnormal amplitude noise before(a) and after(b) suppression

Comparison of irregular coherent noise before(a) and after(b) suppression

Comparison of matching pursuit Fourier interpolation before(a) and after(b) application

Workflow of fault-guided velocity tomography

Comparison of velocity iterative update
a—initial velocity model;b—large-scale velocity update without fault constraint;c—small-scale velocity update with fault constraint

Comparison of CIGs corresponding to the iterative process
a—CIGs of initial velocity model;b—CIGs of large-scale velocity without fault constraint;c—CIGs of small-scale velocity with fault constraint

Fig.8a);b—PSDM section by updated velocity model(Fig.8c)
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Comparison of PSDM sections corresponding to the initial velocity and the updated velocity
a—PSDM section of initial velocity model(Fig.8a);b—PSDM section by updated velocity model(Fig.8c)

Comparison of Kirchhoff migration(a) and RTM migration(b)

The key processing flow for deep geothermal imaging(the yellow position in the figure is the key technology)

Boundary imaging comparison of previous imaging results(a) and current imaging results(b)

Basement insider imaging comparison of previous imaging results(a) and current imaging results(b)

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