Prestack Diffraction Separation Using the Schrödinger Equation-Based Adaptive Transformation

Abstract

Small-scale subsurface geological discontinuities, such as caves and fractures, can provide storage space for oil and gas. High-resolution imaging of these small-scale geological discontinuities is important for the development of oil and gas reservoirs. These small-scale subsurface discontinuous geological features are manifested as diffracted waves. Diffraction imaging can clearly delineate the spatial distribution of small-scale structures. However, high-energy reflections always mask diffractions. An essential prerequisite for diffraction imaging is the removal of strong reflection interference from seismic data. We propose a prestack diffraction separation method based on a Schrödinger equation–based adaptive transform. To extract diffractions from shot gathers, we first apply a normal moveout (NMO) operator to enhance the kinematic differences between diffracted and reflected waves. Subsequently, we apply an adaptive transformation method constructed within a quantum mechanical framework based on the Schrödinger equation. Unlike fixed-basis transforms, this method employs data-adaptive wave functions to characterize seismic data, enabling a more effective capture of the amplitude and frequency characteristics of both diffracted and reflected waves in NMO-corrected shot gathers. Different wave functions, such as those representing the diffracted and reflected components, correspond to distinct components in the data. We reconstructed the reflections using the wave functions corresponding to the reflected components. Through the subtraction of reconstructed reflections from the shot gathers, the diffraction patterns were isolated. The proposed diffraction separation workflow based on the Schrödinger equation–based adaptive transform can effectively extract weak diffractions from seismic data, laying the foundation for subsequent high-resolution diffraction imaging. Synthetic data tests validated that the method can effectively detect 5-m karst caves and faults with the same throw. Nankai dataset applications show the capability of the separation workflow to successfully extract fracture-related diffractions under complex geological conditions, thereby facilitating the detailed characterization of geological features such as fractures.