Subsurface structure map foR the Lost Soldier field

1944 ◽  
Author(s):  
E.A. Swedenborg
Keyword(s):  
Author(s):  
Clementine Chirol ◽  
Kate L. Spencer ◽  
Simon J. Carr ◽  
Iris Möller ◽  
Ben Evans ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Saurabh Mittal ◽  
S. P. Sharma ◽  
Arkoprovo Biswas ◽  
D. Sengupta

This study is an attempt to correlate VLF-EM data with the radiometric measurements to decipher the subsurface structure and to locate uranium mineralization in the shear zone. The study area is around Beldih mine which is an open cast apatite mine located on the South Purulia Shear Zone. VLF method has been applied to map the structure and the presence of radioactive minerals has been delineated by the detection of highαandγcounts with respect to the background radiations. High radiation counts and high surfaceγactivity are found just above the higher apparent current-density zones in all the profiles studied, at various locations, indicating uranium and/or thorium mineralization as well as good correlation between these techniques.


Geophysics ◽  
1986 ◽  
Vol 51 (1) ◽  
pp. 12-19 ◽  
Author(s):  
James F. Mitchell ◽  
Richard J. Bolander

Subsurface structure can be mapped using refraction information from marine multichannel seismic data. The method uses velocities and thicknesses of shallow sedimentary rock layers computed from refraction first arrivals recorded along the streamer. A two‐step exploration scheme is described which can be set up on a personal computer and used routinely in any office. It is straightforward and requires only a basic understanding of refraction principles. Two case histories from offshore Peru exploration demonstrate the scheme. The basic scheme is: step (1) shallow sedimentary rock velocities are computed and mapped over an area. Step (2) structure is interpreted from the contoured velocity patterns. Structural highs, for instance, exhibit relatively high velocities, “retained” by buried, compacted, sedimentary rocks that are uplifted to the near‐surface. This method requires that subsurface structure be relatively shallow because the refracted waves probe to depths of one hundred to over one thousand meters, depending upon the seismic energy source, streamer length, and the subsurface velocity distribution. With this one requirement met, we used the refraction method over a wide range of sedimentary rock velocities, water depths, and seismic survey types. The method is particularly valuable because it works well in areas with poor seismic reflection data.


Geotectonics ◽  
2021 ◽  
Author(s):  
M. A. F. Miraj ◽  
S. Shahzad ◽  
M. J. Munawar ◽  
N. Ahsan ◽  
R. F. Saleem ◽  
...  

2022 ◽  
Vol 41 (1) ◽  
pp. 47-53
Author(s):  
Zhiwen Deng ◽  
Rui Zhang ◽  
Liang Gou ◽  
Shaohua Zhang ◽  
Yuanyuan Yue ◽  
...  

The formation containing shallow gas clouds poses a major challenge for conventional P-wave seismic surveys in the Sanhu area, Qaidam Basin, west China, as it dramatically attenuates seismic P-waves, resulting in high uncertainty in the subsurface structure and complexity in reservoir characterization. To address this issue, we proposed a workflow of direct shear-wave seismic (S-S) surveys. This is because the shear wave is not significantly affected by the pore fluid. Our workflow includes acquisition, processing, and interpretation in calibration with conventional P-wave seismic data to obtain improved subsurface structure images and reservoir characterization. To procure a good S-wave seismic image, several key techniques were applied: (1) a newly developed S-wave vibrator, one of the most powerful such vibrators in the world, was used to send a strong S-wave into the subsurface; (2) the acquired 9C S-S data sets initially were rotated into SH-SH and SV-SV components and subsequently were rotated into fast and slow S-wave components; and (3) a surface-wave inversion technique was applied to obtain the near-surface shear-wave velocity, used for static correction. As expected, the S-wave data were not affected by the gas clouds. This allowed us to map the subsurface structures with stronger confidence than with the P-wave data. Such S-wave data materialize into similar frequency spectra as P-wave data with a better signal-to-noise ratio. Seismic attributes were also applied to the S-wave data sets. This resulted in clearly visible geologic features that were invisible in the P-wave data.


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