We present the results of applying autocorrelogram migration to inverse vertical seismic‐while‐drilling (IVSPWD) profile data collected in the Austin Chalk formation. The seismic reflections were excited by a drill bit moving along a horizontal well at a depth of 2800 m. The data were recorded by a receiver array on the surface. There were 609 twenty‐second traces recorded at each of 10 three‐component stations. After preprocessing, the traces were autocorrelated and migrated. Two imaging conditions were examined. The ghost‐reflection imaging condition produced a reflectivity section that agreed with a nearby common‐depth‐point section. The migration section obtained with a primary‐reflection imaging condition produced a reflectivity section inferior in quality to that of the ghost image. A possible explanation is that the drill‐bit location was not precisely known, which can be shown to induce weak errors in the ghost‐imaging condition but stronger errors in the primary‐reflection imaging condition. Ghost migration images reflections not only below the drill bit, but also above the drill bit. This investigation is one of the first examples of successfully imaging the earth's reflectivity section from horizontal drill‐bit data, and it offers a potentially useful method for seismic imaging from drill‐bit data.

We present the equations for migrating IVSPWD (inverse vertical seismic profile while drilling) and common-midpoint-point (CMP) autocorrelograms. These equations generalize the 1-D autocorrelation imaging methods of Katz and Claerbout to 2-D and 3-D media, and also provide a formal mathematical justification for inverting the reflectivity distribution from autocorrelograms. The autocorrelogram imaging conditions are designed to migrate either the primary reflection energy or the free-surface ghost reflections. The main advantage in migrating autocorrelograms is that the source wavelet does not need to be known, which is the case for seismic data generated by a rotating drill-bit or for vibroseis data with a corrupted pilot signal. Another advantage is that the source and receiver static problems are mitigated by autocorrelation migration. The key limitation is that autocorrelation of traces produces undesirable coherent noises, which are denoted as "virtual multiples". Similar to "physical 1 multiples", such noise can, in principle, be partially suppressed by filtering and stacking of migration images obtained from many different shot gathers. Results with both synthetic and field data validate this conjecture, and show that autocorrelogram migration can be a better alternative to standard migration when the source signal is not adequately known.

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Current microzonation mapping procedures often call for the generation of complicated mathematical ground-motion models. These models require that expensive geophysical and geological surveys be performed to gather input information. A more desirable method of estimating ground motions would be to measure these effects directly. Microtremor analysis procedures provide such a direct method. Microtremor data were collected at several sites at Beatty, Nevada, and compared to nuclear event and mathematical model ground-motion spectra. The frequency at which peak amplitudes occurred on all spectra agreed. These frequencies appear at the resonance frequency of the surface layer when stimulated by compressional waves. Results of this experiment add validity to the use of microtremors in microzonation studies.

The application of microtremor spectra in predicting frequency-dependent amplification effects of local site geology was investigated. Long time-interval (> 45 min) microtremor data were used to estimate Power Spectral Density (PSD) plots. Peaks occurring in these PSD plots were correlated with peaks of transfer functions (Haskell, 1960 and 1962) calculated from known geological models. The resulting apparent positive correlations indicate that a procedure of estimating PSD plots from long time intervals of microtremor data would be useful in predicting response spectra for earthquake risk evaluation.

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