FREQUENCY-DEPENDENT TRAVELTIME TOMOGRAPHY FOR 2D AND 3D NEAR-SURFACE SEISMIC REFRACTION DATA

We demonstrate improved resolution in P-wave velocity tomograms obtained by inversion of the synthetic SAGEEP 2011 refraction traveltime data (Zelt 2010) using Wavepath-Eikonal Traveltime Inversion (WET; Schuster 1993) and Wavelength-Dependent Velocity Smoothing (WDVS; Zelt and Chen 2016). We use a multiscale inversion approach and a Conjugate-Gradient based search method. Our default starting model is a 1D-gradient model obtained directly from the traveltime first arrivals assuming diving waves (Sheehan, 2005). As a second approach, we map the first breaks to assumed refractors and obtain a layered starting model using the Plus-Minus refraction method (Hagedoorn, 1959). We compare tomograms obtained using WDVS to smooth the current velocity model grid before forward modeling traveltimes vs. tomograms obtained without WDVS. Results show that WET images velocity layer boundaries more sharply when engaging WDVS. We determine the optimum WDVS frequency iteratively by trial-and-error. We observe that the lower the used WDVS frequency, the stronger the imaged velocity contrast at the top-of-basement. Using a WDVS frequency that is too low makes WDVS based WET inversion unstable exhibiting increasing RMS error, too high modeled velocity contrast and too shallow imaged top-of-basement. To speed up WDVS, we regard each nth node only when scanning the velocity along straight scan lines radiating from the current velocity grid node. Scanned velocities are weighted with a Cosine-Squared function as described by (Zelt and Chen, 2016). We observe that activating WDVS allows decreasing WET regularization (smoothing and damping) to a higher degree than without WDVS.References:Hagedoorn, J.G., 1959, The Plus-Minus method of interpreting seismic refraction sections, Geophysical Prospecting, Volume 7, 158-182.Rohdewald, S.R.C., 2021, SAGEEP11 data interpretation, https://rayfract.com/tutorials/sageep11_16.pdf.Schuster, G.T., Quintus-Bosz, A., 1993, Wavepath eikonal traveltime inversion: Theory. Geophysics, Volume 58, 1314-1323.Sheehan, J.R., Doll, W.E., Mandell, W., 2005, An evaluation of methods and available software for seismic refraction tomography analysis, JEEG, Volume 10(1), 21-34.Shewchuk, J.R., 1994, An Introduction to the Conjugate Gradient Method Without the Agonizing Pain, http://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf. Zelt, C.A., 2010, Seismic refraction shootout: blind test of methods for obtaining velocity models from first-arrival travel times, http://terra.rice.edu/department/faculty/zelt/sageep2011.Zelt, C.A., Haines, S., Powers, M.H. et al. 2013, Blind Test of Methods for Obtaining 2-D Near-Surface Seismic Velocity Models from First-Arrival Traveltimes, JEEG, Volume 18(3), 183-194. Zelt, C.A., Chen, J., 2016, Frequency-dependent traveltime tomography for near-surface seismic refraction data, Geophys. J. Int., Volume 207, 72-88.

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Inverting the head wave coefficient with multi-fold near-surface seismic refraction data

ASEG Extended Abstracts ◽

10.1080/22020586.2019.12072941 ◽

2019 ◽

Vol 2019 (1) ◽

pp. 1-4

Author(s):

Derecke Palmer

Keyword(s):

Seismic Refraction ◽

Head Wave ◽

Near Surface ◽

Seismic Refraction Data ◽

Refraction Data

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THE LITHOSTRATIGRAPHY OF THE NEAR-SURFACE IN PART OF SEDIMENTARY KOLMANI FIELD IN NORTHERN BENUE TROUGH, NIGERIA, USING SOIL CORE AND SEISMIC REFRACTION DATA

Earth Sciences Pakistan ◽

10.26480/esp.02.2020.53.59 ◽

2020 ◽

Vol 4 (2) ◽

pp. 53-59

Author(s):

Glory G. Akpan ◽

Etim D. Uko ◽

Owajiokiche D. Ngerebara

Keyword(s):

Wave Velocity ◽

Seismic Refraction ◽

Compressional Wave ◽

Soil Samples ◽

Soil Core ◽

Compressional Wave Velocity ◽

Near Surface ◽

Weathered Layer ◽

Seismic Refraction Data ◽

Refraction Data

Soil samples from 31 shallow boreholes were acquired at depths 0m, 1m, 2m, 3m, 4m, 5m, 7m, 10m, 15m, 20m, 25m, 30m, 35m, 40m, 45m, 50m, 55m, and 60m in Pingida (Kolmani Field) in Ako LGA, Gombe State, Nigeria. Using the same boreholes, seismic refraction data was also acquired. The aim of the survey was to delineate the near-surface lithology and velocity layering. The boreholes were drilled using rotary drilling rig and the core samples acquired and described using Wentworth Scale. Seismic refraction data acquired using a single trace Stratavisor NZXP portable digital recorder. The recording spread consisted of a single SM4- 10Hz geophone positioned at depths where the soil samples were taken. A hammer was used as the energy source and placed 3m away from the hole to obtain the first breaks. The refraction data was interpreted using UDISYS Version 1.0.0.0 software. The soil layers in the Kolmani Field have three distinct layers specified as follows, namely, top weathered and sub-consolidated layers made up of intercalation of sandstone, gravel ash clay and muddy coal shale. The lithologic strata do not correlate throughout the field resulting from the highly variable elevation which ranged from 317m and 524m with average of 389.16m. The top weathered layer of laterite intercalated with cobblestones with compressional wave velocity ranging from 342 ms-1 to 517 ms-1 with an average of 405.03 ms-1. Beneath the weathered layer is the sub-consolidated Clay layer intercalated with silt and laterite of compressional wave velocity ranging from 440 ms-1 to 1854 ms-1 of average of 826 ms-1. The underlying consolidated layer is the shale and coal layer having compressional wave velocity ranging from 1518 ms-1 to 4201 ms-1 with an average of 2162.65 ms-1. The dominant lithologic sequences encountered are laterite, clay, silt, sand, gravel, coal and shale. The results of this work can be used for static corrections in seismic reflection processing, planning and assessing risk for engineering structures, and for groundwater exploration. The laterite, clay, silt, sand, gravel, coal and shale can be utilized in agriculture, construction, process industries, and environmental remediation.

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