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SUMMARY We show that diffraction stack migration can be used to estimate the distribution of near-surface faults. The assumption is that near-surface faults generate detectable back-scattered surface waves from impinging surface waves. The processing steps are to isolate the back-scattered surface waves, and then migrate them by diffraction migration using the surface wave velocity as the migration velocity. Instead of summing events along trial quasi-hyperbolas, surface wave migration sums events along trial quasi-linear trajectories that correspond to the moveout of back-scattered surface waves. A deconvolution filter derived from the data can be used to collapse a dispersive arrival into a non-dispersive event. Results with synthetic data and field records validate the feasibility of this method. Applying this method to USArray data or passively recorded exploration data might open new opportunities in mapping tectonic features over the extent of the array.

Standard migration images can suffer from migration artifacts due to 1) poor source-receiver sampling, 2) weak amplitudes caused by geometric spreading, 3) attenuation, 4) defocusing, 5) poor resolution due to limited source-receiver aperture, and 6) ringiness caused by a ringy source wavelet. To partly remedy these problems, least-squares migration (LSM), also known as linearized seismic inversion or migration deconvolution (MD), proposes to linearly invert seismic data for the reflectivity distribution. If the migration velocity model is sufficiently accurate, then LSM can mitigate many of the above problems and lead to a more resolved migration image, sometimes with twice the spatial resolution. However, there are two problems with LSM: the cost can be an order of magnitude more than standard migration and the quality of the LSM image is no better than the standard image for velocity errors of 5% or more. We now show how to get the most from leastsquares migration by reducing the cost and velocity sensitivity of LSM.

SUMMARY The seismic scanning tunneling macroscope (SSTM) is proposed for detecting the presence of near-surface impedance anomalies and faults. Results with synthetic data are consistent with theory in that scatterers closer to the surface provide brighter SSTM profiles than those that are deeper. The SSTM profiles show superresolution detection if the scatterers are in the near-field region of the recording line. The field data tests near Gulf of Aqaba, Haql, KSA clearly show the presence of the observable fault scarp, and identify the subsurface presence of the hidden faults indicated in the tomograms. Superresolution detection of the fault is achieved, even when the 35 Hz data are lowpass filtered to the 5-10 Hz band.

We show that superresolution imaging in the far-field region of the sources and receivers is theoretically possible if migration of resonant multiples is employed. A resonant multiple is one that bounces back and forth between two scattering points or two neighboring reflectors. For a source with frequency f , N roundtrips in propagating between two scatterers increases the effective frequency to 2N × f and decreases the effective wavelength λ to λ/2N. Thus, interbed multiples can, in principle, be used as high-frequency probes to estimate detailed properties of layers. This is not only applicable to crustal reflections, but also to mantle and core reverberations of interest to earthquake seismologists.

The research is supported by funding from King Abdullah University of Science and Technology (KAUST) and grant agreement number OCRF-2014-CRG3-2300. For computer time, this research used the resources of the IT Research Computing Group and Supercomputing Laboratory at KAUST. We thank them for providing the computational resources required for carrying out this work. We sincerely thank PEMEX for providing the data used in this study (Lu et al., 2014), and CNH, Mexico, for further permission to conclude and publish our work.

Structures will be mispositioned across prestack migration gathers in the presence of inaccuracies in the velocity model. Stacking these misaligned gathers runs the risk of destroying important structures in the stacked migration image. To mitigate this problem, we propose a trim statics inspired by the non-local means algorithm originally developed for image denoising. This method differs from the conventional one in two fundamental respects. First, the trim statics are computed by comparing image patches instead of individual image traces. Second, no global pilot trace is needed because only two migration images at a time participate in trim statics and are stacked into one image. A multitude of migration images are stacked recursively in this two-to-one fashion. Tests with a Gulf of Mexico dataset show a noticeable improvement in the feature coherency of the stacked migration image.

The quality of migration images depends on the accuracy of the velocity model. For large velocity errors, the migration image is strongly distorted, which unflattens events in the common image gathers and consequently leads to a blurring in the stacked migration image. To mitigate this problem, we propose dynamic image warping to flatten the common image gathers before stacking and to enhance the signal-to-noise ratio of the migration image. Numerical tests on the Marmousi model and GOM data show that image warping of the prestack images followed by stacking leads to much better resolved reflectors than the original migration image. The problem, however, is that the reflector locations have increased uncertainty because the wrong velocity model is still used.

SUMMARY A three dimensional least-squares Kirchhoff migration (LSM) is developed in the prestack plane-wave domain to increase the quality of migration images and the computational efficiency. Due to the limitation of current 3D marine acquisition geometries, a cylindrical-wave encoding is adopted for the narrow azimuth streamer data. To account for the mispositioning of reflectors due to errors in the velocity model, a regularized LSM is devised so that each plane-wave or cylindrical-wave gather gives rise to an individual migration image, and a regularization term is included to encourage the similarities between the migration images of similar encoding schemes. Both synthetic and field results show that: 1) plane-wave or cylindrical-wave encoding LSM can achieve both computational and IO saving, compared to shot-domain LSM, however, plane-wave LSM is still about 5 times more expensive than plane-wave migration; 2) the regularized LSM is more robust compared to LSM with one reflectivity model common for all the plane-wave or cylindrical-wave gathers.

Summary A background velocity model containing the correct lowwavenumber information is desired for both the quality of the migration image and the success of waveform inversion. We propose to invert for the low-wavenumber part of the velocity model by minimizing the phase difference between predicted and observed reflections. The velocity update is exclusively along the reflection wavepaths and, unlike conventional FWI, not along the reflection ellipses. This allows for reconstructing the smoothly varying parts of the background velocity model. Tests with synthetic data show both the benefits and limitations of this method.

The main difficulty with the data-domain full waveform inversion (FWI) is that it tends to get stuck in the local minima associated with the waveform misfit function. This is the result of cycle skipping which degrades the low-wavenumber update in the absence of low-frequencies and long-offset data. An image-domain objective function is defined as the normed difference between the predicted and observed common image gathers (CIGs) in the subsurface offset domain. This new objective function is not constrained by cycle skipping at the far subsurface offsets. To test the effectiveness of this method, we apply it to marine data recorded in the Gulf of Mexico. Results show that image-domain FWI is less sensitive to the initial model and the absence of low-frequency data compared with conventional FWI. The liability, however, is that it is almost an order of magnitude more expensive than standard FWI.

Conventional acoustic least-squares migration inverts for a reflectivity image that best matches the amplitudes of the observed data. However, for field data applications, it is not easy to match the recorded amplitudes because of the viscoelastic nature of the earth and inaccuracies in the estimation of source signature and strength at different shot locations. To relax the requirement for strong amplitude matching of least-squares migration, we use a normalized cross-correlation objective function that is only sensitive to the similarity between the predicted and the observed data. Such a normalized cross-correlation objective function is also equivalent to a time-domain phase inversion method where the main emphasis is only on matching the phase of the data rather than the amplitude. Numerical tests on synthetic and field data show that such an objective function can be used as an alternative to visco-acoustic least-squares reverse time migration (Qp-LSRTM) when there is strong attenuation in the subsurface and the estimation of the attenuation parameter Qp is insufficiently accurate.