Conditional stochastic inversion of common-offset GPR reflection data

We present a stochastic inversion procedure for common-offset ground-penetrating radar (GPR) reflection measurements. Stochastic realizations of subsurface properties that offer an acceptable fit to GPR data are generated via simulated annealing optimization. The realizations are conditioned to borehole porosity measurements available along the GPR profile, or equivalent measurements of another petrophysical property that can be related to the dielectric permittivity, as well as to geostatistical parameters derived from the borehole logs and the processed GPR image. Validation of our inversion procedure is performed on a pertinent synthetic data set and indicates that the proposed method is capable of reliably recovering strongly heterogeneous porosity structures associated with surficial alluvial aquifers. This finding is largely corroborated through application of the methodology to field measurements from the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

Characterization of the engineering geological units with the shear wave velocity parameter: statistical analysis of data from the Italian seismic microzonation studies

<p>The availability of a unique database, where all data of the seismic microzonation studies carried out in about 1900 municipalities of Italy (https://www.webms.it/) are achieved with a standardized format, allowed statistical elaborations in terms of subsoil parameters. In particular, we analysed borehole logs and geophysical data in order to characterize them with the shear wave velocity (Vs) vertical profile, and the code of standardized engineering geological units, according to the Italian Guidelines for Seismic Microzonation (Seismic Microzonation Working Group, 2015; 2018). The Vs parameter, extracted from about 3700 geophysical surveys, was correlated to the engineering geological units from the borehole logs, with 1meter step. The correlation was performed for about 1700 available Down-Hole (DH) surveys and for about 2000 Multichannel Analyses of Surface Waves (MASW). For these latter, we selected only MASW surveys located near boreholes, no more than 100 m away. The statistical analysis on the distribution and dispersion of Vs parameter allowed to calculate the Vs values related to the mode, mean, median, standard deviation, first quartile, third quartile, minimum and maximum, and the trend with depth of Vs for each engineering geological unit. Validation with external datasets (e.g. Italian Vs30 map, Mori et al., 2020) demonstrates that the characterization of engineering geological units in term of Vs, based on velocity profiles extracted by the Italian seismic microzonation dataset, allow to reliably characterize the engineering geological model, where no geophysical data are available. Statistics of subsoil parameters will represent a fundamental tool for computing local seismic ground motion parameters (e.g. PGA, H<sub>SM</sub>) in the areas not covered by seismic microzonation studies.</p><p><strong>References</strong></p><p>- Mori, F., Mendicelli, A., Moscatelli, M., Romagnoli, 796 G., Peronace, E., Naso, G., 2020. A new Vs30 map for Italy based on the seismic microzonation dataset. Engineering Geology 275, 105745. https://doi.org/10.1016/j.enggeo.2020.105745.</p><p>- Seismic Microzonation Working Group, 2015. Guidelines for Seismic Microzonation http://www.protezionecivile.gov.it/httpdocs/cms/attach_extra/GuidelinesForSeismicMicrozonation.pdf</p><p>- Seismic Microzonation Working Group, 2018. Standard di rappresentazione e archiviazione informatica Versione 4.1. http://www.protezionecivile.gov.it/attivita-rischi/rischio-sismico/attivita/commissione-supporto-monitoraggio-studi-microzonazione/standard-rappresentazione-archiviazione-informatica</p>

Formation of undulating topography and gravel beds at the bases of incised valleys: Last Glacial Maximum examples beneath the lowlands facing Tokyo Bay

Recent studies using well density distributed borehole logs have revealed undulating topography at the bases of incised valleys formed during the Last Glacial Maximum (LGM). In this study, from analysis of 4702 borehole logs, undulating topography forming a series of pits 1–2 km long, < 1 km wide, 5–10 m deep, and spaced at 1–2-km intervals was discovered at the bases of LGM incised valleys beneath the Tama River Lowland on the west coast of Tokyo Bay. This undulating topography can be attributed to scouring at braided river channel confluences. In the study area, single borehole logs are available within each 187 m × 187 m grid cell, and the logs sample both the bottom and marginal portions of the scouring, which suggests that this undulating topography is not an artifact of erroneous values arising from mathematical interpolation. The morphologies and incision depths of two incised valleys in the study area show a cover effect of the gravel bed at the base of the post-LGM incised-valley fills. The basal age of this basal gravel bed (BG) is confirmed at < 30 ka because the LGM incised valleys dissect the MIS 3 Tachikawa buried terrace overlain by the AT tephra dated 30.0 ka. This means that the BG, which represents braided-river sediments, is interpreted as resulting from the LGM sea-level lowstand after 30 ka.

Using Electric Resistivity Tomography and Borehole Logs to Detect Sedimentation Changes in a Gravel-Bed Ephemeral Channel

&lt;p&gt;Differences in deposit geometry and texture with depth along ephemeral gravel-bed streams strongly reflect fluctuations in bedload, which occur due to environmental changes at the basin scale and morphological channel adjustments. In this study, non-destructive methods, 2D and 3D electrical resistivity tomography(ERT), have been combined with datasets from borehole logs to identify, quantify and analyze the internal geometry of cross-sections of the gravel-bed ephemeral channel, known as Azoh&amp;#237;a Rambla (southeastern Spain). The electrical survey was performed through longitudinal and transverse profiles in two channel reaches, upper and middle stretches. Both profiles utilized 28 stainless steel electrodes reaching 14-30 m in length and an investigation depth of 3-5 m, approximately. Electrical resistivity values were correlated with data obtained from the samples collected from borehole logs (e.g. sediment strength, grain size distribution, compaction, porosity (&amp;#981;), and hydraulic conductivity (k)). To determine &amp;#981; and K granulometric and morphometric variables, such as shape-sphericity indices, particle sorting, effective grain-sizes and void ratios, were used.&lt;/p&gt;&lt;p&gt;The alluvial channel-fills showed the superposition of four layers with uneven thickness and arrangement: 1) a lower sandy-gravel body, scarcely thick, characterized by moderate resistivity (150-500 &amp;#937; &amp;#183; m); 2) a thicker intermediate layer, with moderate to high resistivity values (500 to 1600 &amp;#937; &amp;#183; m); and 3) an upper set composed of coarse gravel and supported matrix, ranging from 1600 to 3000 &amp;#937; &amp;#183; m, and a narrow subsurface layer, the most resistive (&gt; 3000 &amp;#937; &amp;#183; m), corresponding to the most recent armored deposits (gravel and pebbles). Consequently, the ERT results coupled with borehole data suggest that since the channel entrenchment in the Miocene marl substrate, different pulses of vertical sedimentary accretion were produced, denoting a general trend to increase in grain-size (coarsening-upwards) and hydraulic conductivity towards the top of the sedimentary sequence. This research was funded by ERDF/Spanish Ministry of Science, Innovation and Universities&amp;#8212;State Research Agency/Project CGL2017-84625-C2-1-R; State Program for Research, Development and Innovation Focused on the Challenges of Society.&lt;/p&gt;

Evaluation of Lithology Variations in Layered Red Beds with Depth: An Example of the Yellow River Guxian Dam, NW China

Lithology variations, which are recognized as rock type differences, significantly affect the physical properties of rock masses in red beds. In this paper, we introduce a statistical method for quantitatively evaluating the degree of lithology variations in layered red beds with depth. The core of this method is to use borehole logs as random variables for statistical analysis to calculate the percentage of a specified lithology at a given elevation, which involves seven steps of attitude calculation, reference point selection, distance calculation, elevation modification, data discretization, data statistics, and curve plotting. The Yellow River Guxian Dam is chosen as a field case study. We classify rock types of feldspar sandstone, fine sandstone, and conglomerate into hard rocks and that rock types of calcareous siltstone, argillaceous siltstone, and mudstone into soft rocks. Borehole logs recorded during the geological investigation are used to plot the percentage curve of hard rocks. We find that the degree of lithology variations for each lithology group differs greatly, the general behaviors of lithology variations on two sides of the Guxian Dam riverbed are quite similar but still with some differences, and that some thick lithology groups can be finely divided into several subgroups. On the basis of the hard rock percentage curve, we introduce a lithology variation index to quantitatively characterize the degree of lithology variations, which can be used as an important index to supplement the traditional methods when performing rock mass classifications in red beds. We also plot the trilithology percentage curve of sandstone, calcareous siltstone, and argillaceous siltstone, which serves for the determination of physical parameters of the dam foundation rock mass, the identification of the potential shear sliding surface, and the search for an impervious grouting bottom. Moreover, we find that the crest and trough, which are local high and low points in the hard rock percentage curve, can be used to show some characteristics of shear zones. The locations of shear zones are well represented in the form of troughs and that the development of shear zones has a good linear relationship with the hard rock percentage of the corresponding crest. The method proposed in this paper can be promoted and applied in similar projects or studies.