Introduces the concept of the convolutional model and describes the use of deconvolution in removing coherent noise and minimizing the effect of the wavelet on the final stack. Defines deconvolution parameters. Examines single-trace, deterministic and multi-trace deconvolution methods, along with alternative methods such as maximum likelihood, minimum entropy and L1-norm deconvolution. Addresses practical considerations in applying deconvolution methods and provides a suggested processing scheme.

Code: IHRDC_IPIMS_t36653


Duration: 2.3 hours