scholarly journals Near-surface diffractor detection at archaeological sites based on an interferometric workflow

Geophysics ◽  
2021 ◽  
pp. 1-75
Author(s):  
Jianhuan Liu ◽  
Deyan Draganov ◽  
Ranajit Ghose ◽  
Quentin Bourgeois
Keyword(s):  
Field Data ◽  
Waveform Inversion ◽  
Synthetic Data ◽  
Spatial Summation ◽  
Archaeological Site ◽  
Archaeological Sites ◽  
Magnetic Survey ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Reflection Data

Detecting small-size objects is a primary challenge at archaeological sites due to the high degree of heterogeneity present in the near surface. Although high-resolution reflection seismic imaging often delivers the target resolution of the subsurface in different near-surface settings, the standard processing for obtaining an image of the subsurface is not suitable to map local diffractors. This happens because shallow seismic-reflection data are often dominated by strong surface waves which might cover weaker diffractions, and because traditional common-midpoint moveout corrections are only optimal for reflection events. Here, we propose an approach for imaging subsurface objects using masked diffractions. These masked diffractions are firstly revealed by a combination of seismic interferometry and nonstationary adaptive subtraction, and then further enhanced through crosscoherence-based super-virtual interferometry. A diffraction image is then computed by a spatial summation of the revealed diffractions. We use phase-weighted stack to enhance the coherent summation of weak diffraction signals. Using synthetic data, we show that our scheme is robust in locating diffractors from data dominated by strong Love waves. We test our method on field data acquired at an archaeological site. The resulting distribution of shallow diffractors agrees with the location of anomalous objects identified in the Vs model obtained by elastic SH/Love full-waveform inversion using the same field data. The anomalous objects correspond to the position of a suspected burial, also detected in an independent magnetic survey and corings.

An example of extreme near-surface variability in shallow seismic reflection data

2016 ◽  
Vol 4 (3) ◽  
pp. SH1-SH9
Author(s):  
Steven D. Sloan ◽  
J. Tyler Schwenk ◽  
Robert H. Stevens
Keyword(s):  
Seismic Reflection ◽  
Field Data ◽  
Low Velocity ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Shallow Subsurface ◽  
Reflection Data ◽  
Shallow Seismic ◽  
Low Velocity Layer ◽  
Velocity Layer

Variability of material properties in the shallow subsurface presents challenges for near-surface geophysical methods and exploration-scale applications. As the depth of investigation decreases, denser sampling is required, especially of the near offsets, to accurately characterize the shallow subsurface. We have developed a field data example using high-resolution shallow seismic reflection data to demonstrate how quickly near-surface properties can change over short distances and the effects on field data and processed sections. The addition of a relatively thin, 20 cm thick, low-velocity layer can lead to masked reflections and an inability to map shallow reflectors. Short receiver intervals, on the order of 10 cm, were necessary to identify the cause of the diminished data quality and would have gone unknown using larger, more conventional station spacing. Combined analysis of first arrivals, surface waves, and reflections aided in determining the effects and extent of a low-velocity layer that inhibited the identification and constructive stacking of the reflection from a shallow water table using normal-moveout-based processing methods. Our results also highlight the benefits of using unprocessed gathers to pragmatically guide processing and interpretation of seismic data.

Structural interpretation using refraction velocities from marine seismic surveys

Geophysics ◽  
1986 ◽  
Vol 51 (1) ◽  
pp. 12-19 ◽  
Author(s):  
James F. Mitchell ◽  
Richard J. Bolander
Keyword(s):  
Sedimentary Rock ◽  
Seismic Energy ◽  
Seismic Survey ◽  
Subsurface Structure ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Reflection Data ◽  
Wide Range ◽  
Streamer Length ◽  
Set Up

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.

Migration‐based traveltime waveform inversion of 2-D simple structures: A synthetic example

Geophysics ◽  
2001 ◽  
Vol 66 (3) ◽  
pp. 845-860 ◽  
Author(s):  
François Clément ◽  
Guy Chavent ◽  
Susana Gómez
Keyword(s):  
Least Squares ◽  
Waveform Inversion ◽  
Domain Of Attraction ◽  
Optimization Methods ◽  
Data Sets ◽  
Seismic Reflection Data ◽  
Prestack Migration ◽  
Reflection Data ◽  
Full Wave ◽  
The Time Domain

Migration‐based traveltime (MBTT) formulation provides algorithms for automatically determining background velocities from full‐waveform surface seismic reflection data using local optimization methods. In particular, it addresses the difficulty of the nonconvexity of the least‐squares data misfit function. The method consists of parameterizing the reflectivity in the time domain through a migration step and providing a multiscale representation for the smooth background velocity. We present an implementation of the MBTT approach for a 2-D finite‐difference (FD) full‐wave acoustic model. Numerical analysis on a 2-D synthetic example shows the ability of the method to find much more reliable estimates of both long and short wavelengths of the velocity than the classical least‐squares approach, even when starting from very poor initial guesses. This enlargement of the domain of attraction for the global minima of the least‐squares misfit has a price: each evaluation of the new objective function requires, besides the usual FD full‐wave forward modeling, an additional full‐wave prestack migration. Hence, the FD implementation of the MBTT approach presented in this paper is expected to provide a useful tool for the inversion of data sets of moderate size.

STACKING OF REFLECTIONS FROM COMPLEX STRUCTURES

Geophysics ◽  
1974 ◽  
Vol 39 (4) ◽  
pp. 427-440 ◽  
Author(s):  
Max K. Miller
Keyword(s):  
Deep Structure ◽  
Control Model ◽  
Layer Model ◽  
Low Velocity ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Static Correction ◽  
Reflection Data ◽  
Actual Field ◽  
Interval Velocities

Common‐depth‐point seismic reflection data were generated on a computer using simple ray tracing and analyzed with processing techniques currently used on actual field recordings. Constant velocity layers with curved interfaces were used to simulate complex geologic shapes. Two models were chosen to illustrate problems caused by curved geologic interfaces, i.e., interfaces at depths which vary laterally in a nonlinear fashion and produce large spatial variations in the apparent stacking velocity. A three‐layer model with a deep structure and no weathering was used as a control model. For comparison, a low velocity weathering layer also of variable thickness was inserted near the surface of the control model. The low velocity layer was thicker than the ordinary thin weathering layers where state‐of‐the‐art static correction methods work well. Traveltime, moveout, apparent rms velocities, and interval velocities were calculated for both models. The weathering introduces errors into the rms velocities and traveltimes. A method is described to compensate for these errors. A static correction applied to the traveltimes reduced the fluctuation of apparent rms velocities. Values for the thick weathering layer model were “over corrected” so that synclines (anticlines) replaced false anticlines (synclines) for both near‐surface and deep zones. It is concluded that computer modeling is a useful tool for analyzing specific problems of processing CDP seismic data such as errors in velocity estimates produced by large lateral variations in overburden.

Automating the acquisition of 3D near‐surface seismic reflection data

2009 ◽  
Author(s):  
Steven D. Sloan ◽  
Don W. Steeples ◽  
Georgios P. Tsoflias ◽  
Mihan H. McKenna
Keyword(s):  
Seismic Reflection ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Reflection Data

3-D imaging of subsurface magnetic permeability/susceptibility with portable frequency domain electromagnetic sensors for near surface exploration

2019 ◽  
Vol 219 (3) ◽  
pp. 1773-1785 ◽  
Author(s):  
Julien Guillemoteau ◽  
François-Xavier Simon ◽  
Guillaume Hulin ◽  
Bertrand Dousteyssier ◽  
Marion Dacko ◽  
...  
Keyword(s):  
Magnetic Permeability ◽  
Field Data ◽  
Large Data ◽  
Archaeological Site ◽  
Phase Response ◽  
Magnetic Method ◽  
Data Sets ◽  
Near Surface ◽  
Inversion Procedure ◽  
Multichannel Deconvolution

SUMMARY The in-phase response collected by portable loop–loop electromagnetic induction (EMI) sensors operating at low and moderate induction numbers (≤1) is typically used for sensing the magnetic permeability (or susceptibility) of the subsurface. This is due to the fact that the in-phase response contains a small induction fraction and a preponderant induced magnetization fraction. The magnetization fraction follows the magneto-static equations similarly to the magnetic method but with an active magnetic source. The use of an active source offers the possibility to collect data with several loop–loop configurations, which illuminate the subsurface with different sensitivity patterns. Such multiconfiguration soundings thereby allows the imaging of subsurface magnetic permeability/susceptibility variations through an inversion procedure. This method is not affected by the remnant magnetization and theoretically overcomes the classical depth ambiguity generally encountered with passive geomagnetic data. To invert multiconfiguration in-phase data sets, we propose a novel methodology based on a full-grid 3-D multichannel deconvolution (MCD) procedure. This method allows us to invert large data sets (e.g. consisting of more than a hundred thousand of data points) for a dense voxel-based 3-D model of magnetic susceptibility subject to smoothness constraints. In this study, we first present and discuss synthetic examples of our imaging procedure, which aim at simulating realistic conditions. Finally, we demonstrate the applicability of our method to field data collected across an archaeological site in Auvergne (France) to image the foundations of a Gallo-Roman villa built with basalt rock material. Our synthetic and field data examples demonstrate the potential of the proposed inversion procedure offering new and complementary ways to interpret data sets collected with modern EMI instruments.

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