Presenting Author: [email protected] roll is the most common coherent noise observed in the land seismic data, mainly characterized by low frequency and low velocities. In this study, we are demonstrating the application of a model-based surface wave attenuation technique for the efficient removal of ground roll from 2D seismic data. The method employs inversion and adaptive subtraction filtering of surface waves. A 1D viscoelastic model is characterized by considering layer thickness, P & Sv wave velocities, density, and P & Sv wave quality factors (Qp & Qs) for each layer, to compute a synthetic seismogram. A linear Radon transform is used to generate dispersion spectra of input shot gather and synthetic shot gather generated from the model. The misfit between the dispersion spectra of input shot gather and synthetic shot gather is given by an objective function ‘J’,\(J\left(m\right)=\ {|\left|s-o\right||}_{2}\), where ‘s’ is the dispersion spectrum of the synthetic data generated by the model, ‘o’ is the dispersion spectrum of the shot gather and \({||.||}_{2}\)is the L2-norm of the difference between ‘s’ and ‘o’. The main focus is to minimize the objective function J. The local minima always seems to be the bottleneck for most of the non-linear inversion problems. To overcome this constraint, we implemented the Genetic Algorithm (GA) method in the surface-wave inversion process using the tool available in a commercial software. GA is a derivative-free search approach towards global minima, for the solution of the inversion problem. Once an optimized model is achieved from GA, synthetic data is generated and is adaptively subtracted from the shot gather. As the 1D model obtained cannot represent any lateral variations of physical parameters in the earth, adaptive subtraction and GA are implemented several times to mitigate this limitation.The proposed technique is applied to process a 2D shot gather data (Fig. 1-a) accessed from the SEG wiki Open data set collection of oz Yilmaz-40 shots. In this data, ground roll is masking the reflection events in the shot gather. After implementation of the proposed technique, it is observed that the ground roll is efficiently attenuated and reflections became more prominent by restoring the actual amplitudes, as shown in Fig. (1-b). The dispersion spectrum of both shot gathers is shown in Fig. 1 (c-d), it is observed that the ground roll present in the low-frequency zone (0-15 Hz) is attenuated. The results of the study suggest that the proposed method is quite efficient for surface wave attenuation.

Old abandoned coal working create major hazards in the form of subsidence of the coalfields. To avoid such hazards, there is need to detect these cavities prior to start of deeper seam mining. There are number of geophysical techniques available for detecting subsurface cavity. High-resolution seismic survey is one such technique which provides accurate results as compared to others. Usually, most of the seismic processing and interpretation of these cavity detection was performed based on stacked data only. To understand these signatures more precisely, in our study, an attempt has been made to image these cavities with the help of Reverse Time Migration (RTM) combined with Full Waveform Inversion (FWI). RTM mostly used for hydrocarbon exploration targets with low central frequency as source. Application of this method to shallow subsurface exploration is still in research stage. Like the same way for velocity model updating, FWI gives mostly appropriate optimization results as compare to other techniques, but it also has the limitation to application of low frequency only. In this paper we first develop a 2D realistic Water Filled Cavity (WFC) model with a work flow of RTM combined with FWI in a high-frequency Ricker source wavelet as 100 Hz. In order to provide a velocity model with high accuracy for RTM, we apply FWI to estimate the subsurface velocity by considering an initial smooth velocity model with addition of 30 % Gaussian noise. The conventional RTM fails to image the cavities and yield a large amount of low frequency back scattered noise at shallow depth during the time of cross correlation due to time/space lag. To avoid these situation, we introduced an automatic shift operator at the time of imaging condition that operates automatically both in time or space. It leads to reduce the lag and improve the results by minimizing the noises at shallow subsurface. By comparing both the results it is observed that most of the noises in the migrated section of conventional method were eliminated by the improved form of RTM with the help of FWI velocity model estimation.