ALBERT

Description: 〈span〉〈div〉Summary〈/div〉Marchenko methods are a suite of geophysical techniques that convert seismograms of energy created by surface sources and measured by surface receivers into seismograms that would have been recorded by a virtual receiver at an arbitrary point inside the subsurface – an operation called redatuming. In principle these redatumed seismograms contain all contributions from direct, primary (singly-reflected) and multiply-reflected waves that would have been recorded by a real subsurface receiver, without requiring prior information about interfaces that generated the reflections. The potential of these methods for seismic imaging and redatuming has been demonstrated extensively in previous literature, but only using one- and two-dimensional Marchenko methods. There remain aspects of the methods that are poorly understood when applied in a three-dimensional world, so we investigate the application of Marchenko methods to three-dimensional data, subsurface structures and wavefields. We first show that for waves propagating in three dimensions, Marchenko methods can be applied to seismic data collected using both linear (so-called 2D-seismic) and areal (3D-seismic) acquisition arrays. However, for 2D acquisition arrays the Marchenko workflow requires additional dimensionality correction factors to obtain accurate solutions, even in a subsurface that only varies with depth. Without these correction factors phase errors occur in redatumed Marchenko estimates; these errors propagate through the Marchenko algorithm and create depth errors in the Marchenko images. Furthermore, applying Marchenko methods to fully three-dimensional seismic wavefields recorded by linear (2D-seismic) arrays that contain out-of-plane reflections deteriorates surface-to-subsurface Green’s function estimates with spurious energy and resulting images are less accurate than those created using ‘conventional’ imaging methods. The application of fully three-dimensional Marchenko methods using data recorded on areal arrays solves both of the above problems, creating accurately redatumed wavefields and images with reduced artifact contamination. However, it appears that source/receiver spacing at most of $\lambda _A\Big /4$ is required for accurate results using existing Marchenko methods, where λ〈sub〉〈span〉A〈/span〉〈/sub〉 is the dominant wavelength and in many real 3D seismic acquisition scenarios this is impractical.〈/span〉

Description: 〈span〉〈div〉ABSTRACT〈/div〉Geoscientists often have little information about earth’s subsurface heterogeneities prior to mapping them using seismic or other geophysical data. Marchenko methods are a set of novel, data-driven techniques that help us to project surface seismic data to points in the subsurface, to form seismograms as though they had been created at each point. In so doing, Marchenko methods account for many of the complex, multiply reflected seismic wave interactions that take place in the real earth’s subsurface. The resulting seismograms are the information required to create subsurface images that are more accurate than standard methods. Our aim is to introduce these concepts with the minimum amount of mathematics required to understand how the Marchenko method can iterate to a solution and to provide a well-commented, easily editable MATLAB code package for demonstration and training purposes. Green’s function estimation using the Marchenko method is first illustrated for a constant velocity, variable density, 1D medium, with results that indicate a near-perfect match when compared with true, synthetically modeled solutions. Similar quality results are shown for variable velocity, 2D Green’s function estimation. Finally, we determine how these estimates could be used to create images of the subsurface, which, when compared with standard methods, contain reduced contamination due to multiple-related artifacts. Our code package includes the 2D data set required to reconstruct the relevant figures that we present, and it allows for experimentation with the implementation of the Marchenko method and the application of Marchenko imaging.〈/span〉

Description: 〈span〉〈div〉SUMMARY〈/div〉Marchenko methods are a suite of geophysical techniques that convert seismograms of energy created by surface sources and measured by surface receivers into seismograms that would have been recorded by a virtual receiver at an arbitrary point inside the subsurface—an operation called redatuming. In principle these redatumed seismograms contain all contributions from direct, primary (singly-reflected) and multiply-reflected waves that would have been recorded by a real subsurface receiver, without requiring prior information about interfaces that generated the reflections. The potential of these methods for seismic imaging and redatuming has been demonstrated extensively in previous literature, but only using 1-D and 2-D Marchenko methods. There remain aspects of the methods that are poorly understood when applied in a 3-D world, so we investigate the application of Marchenko methods to 3-D data, subsurface structures and wavefields. We first show that for waves propagating in three dimensions, Marchenko methods can be applied to seismic data collected using both linear (so-called 2-D seismic) and areal (3-D seismic) acquisition arrays. However, for 2-D acquisition arrays the Marchenko workflow requires additional dimensionality correction factors to obtain accurate solutions, even in a subsurface that only varies with depth. Without these correction factors phase errors occur in redatumed Marchenko estimates; these errors propagate through the Marchenko algorithm and create depth errors in the Marchenko images. Furthermore, applying Marchenko methods to fully 3-D seismic wavefields recorded by linear (2-D seismic) arrays that contain out-of-plane reflections deteriorates surface-to-subsurface Green’s function estimates with spurious energy and resulting images are less accurate than those created using ‘conventional’ imaging methods. The application of fully 3-D Marchenko methods using data recorded on areal arrays solves both of the above problems, creating accurately redatumed wavefields and images with reduced artefact contamination. However, it appears that source–receiver spacing at most of $\lambda _A /4$ is required for accurate results using existing Marchenko methods, where λ〈sub〉〈span〉A〈/span〉〈/sub〉 is the dominant wavelength and in many real 3-D seismic acquisition scenarios this is impractical.〈/span〉