Recovering Soil Distributions from Seismic Data using Laboratory Velocity Measurements

Abstract

Imaging the shallow subsurface is a problem central to many environmental and engineering applications. Recent advances in laboratory measurement techniques have provided high quality compressional velocity (Vp) and shear velocity (Vs) data for soils at low pressures that can be used to improve interpretation of field data. This paper presents a new approach for constraining interpretation of seismic velocity data in terms of subsurface soil distribution, intended for application to environmental and engineering problems. An inversion code has been developed to obtain the soil distribution in the shallow sub-surface from Vp and Vs data. The code minimizes the misfit between the observed (simulated field) Vp, Vs pairs of data in the region of interest and velocities for known soil composition as determined by second-order curve fits to laboratory velocity-pressure data for soils. The paper shows how laboratory data can be used to infer lithology from simulated field data for two near-surface examples. The laboratory data used for this purpose are ultrasonic velocity measurements from artificial soils made by combining various amounts of sand, clay, and peat moss. The availability of laboratory data for Vp and Vs at low pressures allows quantification of the improvement in resolution that may be possible if Vp and Vs seismic data are used together to image the shallow subsurface. It is shown that using the two datasets together provides better estimates of subsurface structure than either Vp or Vs alone can provide.