A study of ScS-S and PcP-P differential travel times and absolute S wave travel times from two deep focus South American earthquakes indicates that the scatter observed in ScS-S times by Hales and Roberts (1970) and Jordan (1972) results from lateral heterogeneities in the lower mantle along the path of the S phase. Both ScS-S and PcP-P times delineate a region of anomalously high velocity in the lower mantle beneath the Caribbean, which may be responsible for some observations of body wave multipathing at Lasa. The total velocity variation associated with this anomaly is estimated to be 1% or greater, and the ratio of P velocity variation to S velocity variation is about 1:1. The observed velocity contrasts may be due to a thermal anomaly, in which case lateral temperature differences of at least 200ø-300øC are required. We suggest that the high-velocity anomaly beneath the Caribbean marks a site of descending-material in the convecting mantle. The presence of lateral variations of seismic velocities in the crust and upper mantle is an established fact but only recentlyhas evidence accumulated that supports the existence of lateral heterogeneity in the lower mantle [Chinnery. 1969; Davies and Sheppard, 1972; Julian and Sengupta, 1973]. The awareness that velocities in the lower mantle are laterally variable has not come sooner partially because any deep heterogeneities are obscured by the geographical variations in the velocities near the surface. Data that are particularly suitable for the study of lower mantle structure are the differences in the travel times of PcP and P and the times of ScS and S. At distances greater than 30 ø or so these differential travel times are not much affected by even gross velocity variations in the crust and uppermost mantle, and they are relatively insensitive to event mislocations as well. Hales and Roberts [1970] presented 30 observations of ScS-S differential travel times from intermediate depth-of-focus events and used these times to estimate the radius of the core-SHA, Springhill, Ala.; ATL, Atlanta, Ga.; OXF, Oxford, Miss.; BLA, Blacksburg, Va.; JCT, Junction City, Tex.; GEO, Georgetown, Washington, D.C.; DAL, Dallas, Tex.; OGD, Ogdensburg, N.J.; SCP, State College, Pa.; FLO, Florissant, Mo.; WES, Weston, Mass.; LUB, Lubbock, Tex.; AAM, Ann Arbor, Mich.; ALQ, Albuquerque, N.M.; TUC, Tucson, Ariz.; GOL, Golden, Colo.; RCD, Rapid City, N. D.; GSC, Goldstone, Calif.; DUG, Dugway, Utah; BOZ, Bozeman, Mont.; and BKS, Berkeley, Calif. *Residuals are computed as observed values minus values of Jeffreys and Bullen [1940].

Plasma wakefields can enable very high accelerating gradients for frontier high energy particle accelerators, in excess of 10 GeV/m. To overcome limits on total acceleration achievable, specially shaped drive beams can be used in both linear and nonlinear plasma wakefield accelerators (PWFA), to increase the transformer ratio, implying that the drive beam deceleration is minimized relative to acceleration obtained in the wake. In this Letter, we report the results of a nonlinear PWFA, high transformer ratio experiment using high-charge, longitudinally asymmetric drive beams in a plasma cell. An emittance exchange process is used to generate variable drive current profiles, in conjunction with a long (multiple plasma wavelength) witness beam. The witness beam is energy-modulated by the wakefield, yielding a response that contains detailed spectral information in a single-shot measurement. Using these methods, we generate a variety of beam profiles and characterize the wakefields, directly observing beam-loaded transformer ratios up to R = 7.8. Furthermore, a spectrally-based reconstruction technique, validated by 3D particle-in-cell simulations, is introduced to obtain the drive beam current profile from the decelerating wake data.

Despite significant advances in marine streamer design, seismic data are often plagued by coherent noise having approximately linear moveout across stacked sections. With an understanding of the characteristics that distinguish such noise from signal, we can decide which noise‐suppression techniques to use and at what stages to apply them in acquisition and processing. Three general mechanisms that might produce such noise patterns on stacked sections are examined: direct and trapped waves that propagate outward from the seismic source, cable motion caused by the tugging action of the boat and tail buoy, and scattered energy from irregularities in the water bottom and sub‐bottom. Depending upon the mechanism, entirely different noise patterns can be observed on shot profiles and common‐midpoint (CMP) gathers; these patterns can be diagnostic of the dominant mechanism in a given set of data. Field data from Canada and Alaska suggest that the dominant noise is from waves scattered within the shallow sub‐buttom. This type of noise, while not obvious on the shot records, is actually enhanced by CMP stacking. Moreover, this noise is not confined to marine data; it can be as strong as surface wave noise on stacked land seismic data as well. Of the many processing tools available, moveout filtering is best for suppressing the noise while preserving signal. Since the scattered noise does not exhibit a linear moveout pattern on CMP‐sorted gathers, moveout filtering must be applied either to traces within shot records and common‐receiver gathers or to stacked traces. Our data example demonstrates that although it is more costly, moveout filtering of the unstacked data is particularly effective because it conditions the data for the critical data‐dependent processing steps of predictive deconvolution and velocity analysis.

In a study of the contamination of reflection seismic data by interfering noise from other seismic crews, controlled experiments were performed in the Gulf of Mexico and the North Sea. In each experiment, a survey ship traversed a line several times collecting both data free of and data contaminated by interfering crew noise. In the Gulf of Mexico experiment, the “noise” ship followed a prescribed course about 11 km from the survey ship. In the North Sea experiment, the noise ship was positioned at stationary locations 10 and 40 km broadside to the survey line. Recorded interference noise in both experiments had peak amplitudes well above the 0.5 to 1.5 Pa (5 to 15 μbar) limit beyond which crews typically must agree on time‐sharing. Despite recorded crew noise that was three to eight times higher than levels typically considered acceptable, the conventionally processed common‐midpoint stack of the contaminated Gulf of Mexico data shows only slight evidence of the interference noise; in contrast, the North Sea stack is severely contaminated by crew noise as early as 1 s. However, when each unstacked trace is scaled by time‐varying weights that vary inversely with the local power in the trace, the crew noise is no longer visible in the contaminated stack of either data set. Trace‐weight normalization in this process is designed to ensure that stacked signal amplitudes are generally preserved. A simulated line wherein the actual Gulf of Mexico data are contaminated by crew noise five times stronger than that recorded in the field [yielding effective peak noise values of 7.5 to 20 Pa (75 to 200 μbar)] also shows no evidence of crew noise after inverse‐power weighted stacking. When data processing includes conventional stacking, we recommend that the specified tolerable amount of crew noise be based upon the root‐mean‐square amplitude of the crew noise computed over an entire record. With burst suppression techniques, such as inverse power‐weighted stacking, we recommend that the specified level be based upon the duration of the strong‐amplitude burst as well. With both criteria, field specifications can be chosen that remain conservative while tolerating considerably more crew‐interference noise than in the past. Issues of the influence of crew noise on the analysis of prestack data remain for future study.

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