Soil type data analytics prediction using electrical resistivity and S-wave velocities for shallow (<20 m) unconsolidated sediments

Document Type

Conference Proceeding

Publication Date

1-1-2020

Abstract

Soil type estimation on a landside of a flood-protection levee using electrical resistivity values and S-wave velocities are predicted using a conventional least-squares polynomial approximation and machine learning techniques such as random forest (RF) and support vector machine (SVM) models. The horizontal-component S-wave velocities and electrical resistivity measurements are estimated from seismic reflection CDP gathers and Electrical Resistivity Tomography methods, respectively. Data come from a flood-plain point bar setting in the Lower Mississippi River Valley, Louisiana, where swale-filling clays separating sandy ridges deposits are the main surface features comprising the upper 10 meters of highly heterogeneous soils.

Publication Source (Journal or Book title)

Seg Technical Program Expanded Abstracts

First Page

2024

Last Page

2028

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