Enhancing fieldwork productivity in subsurface characterization: advancements in data acquisition with MASW-DS

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

The Multichannel Analysis of Surface Waves (MASW) method utilizes low-frequency surface waves to characterize the shallow subsurface layers. It is a very useful tool in geotechnical engineering for evaluating soil quality and mapping the characteristics of the upper sedimentary layers. Despite its efficiency, the limited productivity of conventional MASW due to its relatively slow data acquisition process, poses a challenge for improvement, especially for large-scale projects. To address this issue, we introduce the Multichannel Analysis of Surface Waves using Dual Streamer (MASW-DS) technique to enhance the fieldwork productivity. This approach involves towing two parallel land geophone streamers behind a truck and simultaneously enabling the acquisition of MASW data with a single source, activated between the two land streamers. Our study evaluates the precision and effectiveness of the proposed MASW-DS technique through a set of synthetic and real data tests and demonstrates its potential for expedited surveys resulting to reduced project costs. Furthermore, this work indicates that MASW-DS provide comparable performance to conventional MASW, even in challenging geological settings. The proposed technique demonstrates negligible differences in the acquired dispersion curves and manages to reproduce the S-wave profiles resulting from the conventional MASW deployment, within the framework of an acceptable accuracy for engineers. The provided results prove the reliability of the MASW-DS technique for subsurface characterization while achieving significant acquisition time savings. Thus, the proposed MASW-DS technique can be used as a valuable and effective tool for geotechnical investigations and civil engineering projects worldwide.

Article activity feed