I present the theory of interferometric imaging (II). Interferometric imaging is any algorithm that images crosscorrelated data for the reflectivity or source distribution. As examples, I show that II can image arbitrary reflectivity distributions by migrating ghost reflections in passive seismic data, generalize the receiver-function imaging method used by seismologists, and migrate free-surfa...

A B S T R A C T A new type of seismic imaging, based on Feynman path integrals for waveform modelling , is capable of producing accurate subsurface images without any need for a reference velocity model. Instead of the usual optimization for traveltime curves with maximal signal semblance, a weighted summation over all representative curves avoids the need for velocity analysis, with its common...

Seismic reflection data can be redatumed to a specified boundary in the subsurface by solving an inverse (or multidimensional deconvolution) problem. The redatumed data can be interpreted as an extended image of the subsurface at the redatuming boundary, depending on the subsurface offset and time. We retrieve targetenclosed extended images by using two redatuming boundaries, which are selected...

Marchenko redatuming allows one to use surface seismic reflection data to generate the seismic response at any point in the subsurface due to sources at the surface. Without requiring much information about the earth’s properties, the seismic response generated by Marchenko redatuming contains accurate estimates of not only the primaries, but also internal multiples. A target-oriented imaging m...

(a) Estimated (16x faster, SNR=9.6 dB).

Attenuation in seismic wave propagation is a common cause for poor illumination of subsurface structures. Attempts to compensate for amplitude loss in seismic images by amplifying the wavefield may boost high-frequency components and create undesirable imaging artifacts. In this paper, rather than amplifying the wavefield directly, we develop a stable compensation operator using smooth division...

An analysis of a passh'e seismic method for subsur­face imaging is presenled. in which ambienl seismic noise is em­ployed as the source of iIIu,;"ination of undergro~nd scal~erers.The imaging algorithm can ,"corporate new data mto the '!'lagein a recursive fashion, which causes image background nOise todiminish over time. Under the assumption of spatially-incoherentambie...

The ultimate goal for seismic depth imaging is to find new hydrocarbon prospects or improve existing ones. High quality seismic data and an accurate velocity model are the main drivers for good imaging. Prospects may be identified on seismic data in areas which can range from high to low signal. Roughly speaking, prospects generated for shallow targets will be on good signal data and prospects ...

Wave-equation, finite-frequency imaging and inversion still faces considerable challenges in addressing the inversion of highly complex velocity models as well as in dealing with nonlinear imaging (e.g., migration of multiples, amplitudepreserving migration). Extended images (EI’s), as we present here, are particularly important for designing image-domain objective functions aimed at addressing...

The core problem in seismic exploration is to invert the subsurface reflectivity from the surface recorded seismic data. However, most of the seismic inverse problems are ill-posed by nature. To overcome the ill-posedness, different regularized least squares methods are introduced in the literature. In this paper, we developed a preconditioning non-monotone gradient method, proved it converges ...