S U M M A R YClaerbout's daylight imaging concept is generalized to a theory of interferometric seismic imaging (II). Interferometric seismic imaging is defined to be any algorithm that inverts correlated seismic data for the reflectivity or source distribution. As examples, we show that II can image reflectivity distributions by migrating ghost reflections in passive seismic data and generalizes the receiver-function imaging method used by seismologists. Interferometric seismic imaging can also migrate free-surface multiples in common depth point (CDP) data and image source distributions from passive seismic data. Both synthetic and field data examples are used to illustrate the different possibilities of II. The key advantage of II is that it can image source locations or reflectivity distributions from passive seismic data where the source position or wavelet is unknown. In some cases it can mitigate defocusing errors as a result of statics or an incorrect migration velocity. The main drawback with II is that severe migration artefacts can be created by partial focusing of virtual multiples.
SUMMARYThe acoustic time history of the sun's surface is a stochastic t¡ x¡ y¢ -cube of information. Helioseismologists cross-correlate these noise traces to produce impulse response seismograms, providing the proof of concept for a long-standing geophysical conjecture. We pack the x¡ y¢ -mesh of time series into a single super-long one-dimensional time series. We apply Kolmogoroff spectral factorization to the supertrace, unpack, and find the multidimensional acoustic impulse response of the sun. State-of-the-art seismic exploration recording equipment offers tens of thousands of channels, and permanent recording installations are becoming economically realistic. Helioseismology, therefore, provides a conceptual prototype for using natural noises for continuous reservoir monitoring.
Illumination problems caused by finite-recording aperture and lateral velocity lensing can lead to biased amplitudes in migrated seismic images. I calculate weighting functions that compensate for illumination problems in wave-equation depth migration. The methodology takes into account reflector dip as well as both shot and receiver geometries, and because it is based on wave-equation migration, it naturally models the finite-frequency effects of wave propagation. The first step in the process is to model synthetic data with the true recording geometry over a reference model. Migrating the synthetic data then produces an image whose amplitude can be compared to the reference image to produce an illumination-based weighting function. These weighting functions can be applied directly to the migrated images to mitigate the effects of poor subsurface illumination. The reference model should be as close to the true model as possible; good choices include the migrated image, or a synthetic image with a single known dip that corresponds to the expected dip of a reflector of
Nonrepeatable noise, caused by differences in vintages of seismic acquisition and processing, can often make comparison and interpretation of time-lapse 3-D seismic data sets for reservoir monitoring misleading or futile. In this Gulf of Mexico case study, the major causes of nonrepeatable noise in the data sets are the result of differences in survey acquisition geometry and binning, temporal and spatial amplitude gain, wavelet bandwidth and phase, differential static time shifts, and relative mispositioning of imaged reflection events. We attenuate these acquisition and processing differences by developing and applying a cross-equalization data processing flow for time-lapse seismic data. The cross-equalization flow consists of regridding the two data sets to a common grid; applying a space and time-variant amplitude envelope balance; applying a first pass of matched filter corrections for global amplitude, bandwidth, phase and static shift corrections, followed by a dynamic warp to align mispositioned events; and, finally, running a second pass of constrained space-variant matched filter operators. Difference sections obtained by subtracting the two data sets after each step of the cross-equalization processing flow show a progressive reduction of nonrepeatable noise and a simultaneous improvement in timelapse reservoir signal.
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