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Sparkers are the sound source widely used in marine seismic exploration to provide high-resolution vertical sections. Sparkers are relatively simple, inexpensive, high-frequency sources. In this study, the types of noise occurring in sparker source data were analyzed and attenuated by a processing technique. Frequency–wave number (f–k) filtering is used for attenuating the linear noise. Predictive deconvolution is used for attenuating the ghost waves and bubble effects. A complete processing workflow was designed for processing the data, and the migration section was obtained. The results show that the sparker source data are capable of achieving vertical sections with very high resolution. It is suggested as a necessary technique for high-accuracy gas hydrate exploration in the South China Sea.

The signal-to-noise ratio (SNR), vertical resolution and fidelity of marine seismic data are closely related to the characteristics of hydrophones, namely the sensitivity and the frequency band range. In this article, we analyzed and processed seismic data collected in 2017 from a towed marine streamer equipped with optical fiber cable and hydrophones. Results from a pre-stack time migration section revealed that the optical fiber seismic data yielded high SNR, vertical resolution and fidelity. For validation purpose, a comparison of these data with those acquired by classic piezoelectric hydrophones along a migration section located in a very close location was carried out. This comparison showed that the SNR, fidelity and vertical resolution from the two means of measurements were comparable.

For shallow water environments, reverberation disturbance mainly derives from the bottom scattering. Although acoustic scattering strength is a feature of the bottom, scattering characteristics are different for various sediment types and areas. Backscattering strength at a grazing angel range of 20°–70° over a broad band of 6–24 kHz from a sand bottom in the area of the South Yellow Sea was measured, utilizing a pair of omnidirectional transmitter and hydrophone. The backscattering strength depends on the grazing angle with a positive gradient and performs a faster rate at grazing angle range of 60°–70°. For frequency dependence, the backscattering strength overall enhances with the frequency. Fitting curves of Lambert’s law to the measured data indicate that Lambert’s law departs from the data at grazing angle range of 60°–70°. Fitting curves of a scattering model on the basis of that of Jackson et al. against the data indicate that the seafloor roughness scattering is primary relative to the sediment volume scattering for frequency lower than 10 kHz and at grazing angle range of 60°–90° for high frequency.

Acoustic bottom scattering is the main source of reverberation background in target detection and recognition near the seafloor. Accurate estimation of bottom scattering strength is necessary for prediction of sonar performance in the presence of reverberation in shallow-water environments. A measurement of bottom backscattering strength at midfrequency in a shallow-water environment of the South Yellow Sea of China was carried out in April 2016, where the water depth was 39 m. The surface of the seafloor was relatively flat and covered by some shell fragments observed through a digital camera system. Core data showed that the main component of sediment at this experiment site was fine sand. The backscattering strength as a function of grazing angle (20°–70°) in the frequency range of 6–12 kHz was extracted from monostatic backscattering data, employing an omni-directional source and an omni-directional hydrophone. The measured backscattering strength increases with the increase of the grazing angle, and changes more rapidly at large grazing angles (60°–70°). Comparing the data at different frequencies, it is found that the measured backscattering strength slightly increases with the increase of the acoustic frequency. A fit of Lambert's law to the measured data shows that the backscattering strength deviates from the Lambert's law at large grazing angles. Finally, the fitted result of a scattering model to the measured data suggests that seafloor roughness scattering is larger than that from sediment volume heterogeneity in the measurement frequency band.

An inversion method using backscattering strength is used to obtain bottom parameters. A backscattering model based on the effective density fluid approximation was established as the forward model. The objective function used to scale the mismatch between the model predictions and the measured data (obtained by employing two monostatic transducers with narrow directivity) was established on the assumption that the data errors follow a Gaussian distribution. The maximum a posteriori estimations of inversion parameters were obtained by using a two-step hybrid optimization algorithm combining the differential evolution algorithm and the particle swarm optimization algorithm. The uncertainty and the correlation of inversion parameters were presented using marginal probability distributions and a covariance matrix through Bayesian inversion. Using this method, we can acquire not only geoacoustic parameters (including sound speed and attenuation) but also partial physical parameters of marine sediments and statistical character parameters of seafloor roughness and sediment heterogeneity. Finally, the efficiency of this inversion method was verified through comparison between inversion results and sampling data from sand sediment at the bottom of a water tank.

In order to predict the bottom backscattering strength more accurately, the stratified structure of the seafloor is considered. The seafloor is viewed as an elastic half-space basement covered by a fluid sediment layer with finite thickness. On the basis of calculating acoustic field in the water, the sediment layer, and the basement, four kinds of scattering mechanisms are taken into account, including roughness scattering from the water-sediment interface, volume scattering from the sediment layer, roughness scattering from the sediment-basement interface, and volume scattering from the basement. Then a backscattering model for a stratified seafloor applying to low frequency (0.1–10 kHz) is established. The simulation results show that the roughness scattering from the sediment-basement interface and the volume scattering from the basement are more prominent at relative low frequency (below 1.0 kHz). While with the increase of the frequency, the contribution of them to total bottom scattering gradually becomes weak. And the results ultimately approach to the predictions of the high-frequency (10–100 kHz) bottom scattering model. When the sound speed and attenuation of the shear wave in the basement gradually decrease, the prediction of the model tends to that of the full fluid model, which validates the backscattering model for the stratified seafloor in another aspect.

The bottom is a significant boundary of the ocean, whose properties have always been concerned by oceanographers and geologists, and achieved considerable attention in civil and military applications. To realize estimation of bottom parameters efficiently and accurately, a remote sensing method of bottom parameters based on acoustic backscattering characteristics is proposed in this paper. The bottom backscattering strength was measured in a wide band (6–24 kHz) and grazing angle range (20°-70°), employing an omnidirectional projector and an omnidirectional hydrophone. The bottom parameters is efficiently obtained according to a wealth of information of backscattering strength at different frequencies and grazing angles, through fitting of a scattering model to the measured data, including geophysical parameters (geoacoustic parameters and physical parameters) of the marine sediment, and statistic character parameters of the seafloor roughness and the sediment heterogeneity. Finally, the estimate accuracy of some parameters is analyzed by comparing with direct measurement results. The method is hopeful to be a new approach of remote sensing of the bottom properties, which will improve the efficiency in conventional marine environment surveys.

In order to study the properties of sound-speed dispersion in a sandy sediment, the sound speed was measured both at high frequency (90–170 kHz) and low frequency (0.5–3 kHz) in laboratory environments. At high frequency, a sampling measurement was conducted with boiled and uncooked sand samples collected from the bottom of a large water tank. The sound speed was directly obtained through transmission measurement using single source and single hydrophone. At low frequency, an in situ measurement was conducted in the water tank, where the sandy sediment had been homogeneously paved at the bottom for a long time. The sound speed was indirectly inverted according to the traveling time of signals received by three buried hydrophones in the sandy sediment and the geometry in experiment. The results show that the mean sound speed is approximate 1710–1713 m/s with a weak positive gradient in the sand sample after being boiled (as a method to eliminate bubbles as much as possible) at high frequency, which agrees well with the predictions of Biot theory, the effective density fluid model (EDFM) and Buckingham’s theory. However, the sound speed in the uncooked sandy sediment obviously decreases (about 80%) both at high frequency and low frequency due to plenty of bubbles in existence. And the sound-speed dispersion performs a weak negative gradient at high frequency. Finally, a water-unsaturated Biot model is presented for trying to explain the decrease of sound speed in the sandy sediment with plenty of bubbles.

Before analyzing the distribution of submarine minerals, the positions of hydrophones installed in seismic array cables must be known. Generally, the hydrophone positions are computed through inversion calculation based on assumptions that conflict with the facts, and some assumed parameters are adjusted repeatedly to reduce the spatial aliasing in seismic reflection profiling. Furthermore, the inversion calculation cannot study the relations between the cable shape and working conditions. Dynamic analysis is proposed to predict the hydrophone positions and investigate these relations herein. The array cable is modeled by the lumped mass method with respect to the relative-velocity-element-frame. The results of the dynamic analysis and inversion calculation are verified using the recorded depth data. Although the cable shape by inversion calculation is the same as that by dynamic analysis, the cable depth by inversion calculation demonstrates an obvious shift in comparison with the depth data; meanwhile, the results obtained via dynamic analysis match well with the depth data. Additionally, three virtual maneuvers—diving and rising, depth change, and lateral current—are designed to study the relation between the cable shape and working conditions. The obtained results may help guide exploration and promote the development of exploration equipment.

Acoustic bottom scattering is the main source of reverberation background in the shallow water environment. Backscattering characteristics of a sand and a mud bottom in the South Yellow Sea of China were compared. The backscattering strength in the grazing angel range of 20°–70° over a wide band (6–24 kHz) was measured employing an omnidirectional projector and an omnidirectional hydrophone. For the sand site, the backscattering strength enhances with the increase of grazing angle and has a high variation rate at large grazing angles (60°–70°). For the mud site, it decreases with the grazing angle in the range of 50°–70°. A comparison of the data at different frequencies reveals that the backscattering strength in general slightly rises at the sand site, while it somewhat declines at the mud site, with the increase of frequency. A fitting curve of Lambert's law against the backscattering strength indicates that the measured data depart from Lambert's law at large grazing angles. Fitted results of a scattering model based on that of Jackson et al. to the backscattering strength suggest that seafloor roughness scattering is the main scattering mechanism at low frequency (