VOID DETECTION USING DISTRIBUTED ACOUSTIC SENSING AMBIENT NOISE INTERFEROMETRY

Sinkhole formation due to the collapse of sediments into subsurface voids has been an ongoing issue in many industries. Every year, millions of dollars worth of damage are caused due to the failure to identify near-surface voids in various projects. In many cases, particularly in active karst-forming environments, sinkholes might form after the project operations have started and can lead to catastrophic failures causing irreparable damage to the property and surrounding environment. Invasive testing techniques require that a probe physically intersect the underlying potential voids for successful detection. Nondestructive techniques provide a complementary option for subsurface void detection over a large volume of the underlying material. Seismic methods, particularly, are well suited for shallow and deep void detection in various environments. Active seismic source testing using an array of nodes or geophones on the ground surface has been the method of choice for void detection applications. Nonetheless, there are instances where the prolonged deployment of nodal and geophone arrays is not feasible, such as in specific mining applications or harsh environments. Furthermore, active testing methods have limitations since not all surface conditions can accommodate the deployment of a large source for seismic acquisition surveys. Distributed acoustic sensing (DAS) as an emerging technology does not have many limitations of traditional arrays and can easily be deployed to measure ambient noise fluctuations. This study analyzes the feasibility of using such a method for void detection and subsurface material characterization. Numerical experiments are performed by placing a DAS array on the surface for various array geometries and channel spacings. Ambient noise emissions are synthetically modeled and are recorded by the DAS array. Different seismic imaging techniques are then employed for subsurface characterization and void detection. A relationship between the array size and geometry, channel spacing, void size, and depth is established and reported using various seismic imaging techniques. The findings of this study provide valuable insights into the application of DAS using ambient noise interferometry for void detection in future field-testing applications.