Shallow Water Body Data Processing Based on the Seismic Oceanography

LIU Huaishan*, HU Yi, YIN Yanxin, WANG Linfei, TONG Siyou, and MA Hai



Shallow Water Body Data Processing Based on the Seismic Oceanography

LIU Huaishan, HU Yi, YIN Yanxin, WANG Linfei, TONG Siyou, and MA Hai

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Physical properties of sea water, such as salinity, temperature, density and acoustic velocity, could be demarcated through degradation of energy caused by water absorption, attenuation and other factors. To overcome the challenging difficulties in the quick monitoring of these physical properties, we have explored the high resolution marine seismic survey to instantly characterize them. Based on the unique wavefield propagating in the sea water, we have developed a new approach to suppress the noise caused by the shallow sea water disturbance and obtain useful information for estimating the sea water structure. This approach improves seismic data with high signal-to-noise ratio and resolution. The seismic reflection imaging can map the sea water structure acoustically. Combined with the knowledge of local water body structure profile over years, the instant model for predicting the sea water properties could be built using the seismic data acquired from the specially designed high precision marine seismic acquisition. This model can also be updated with instant observation and the complete data processing system. The present study has the potential value to many applications, such as 3D sea water monitoring, engineering evaluation, geological disaster assessment and environmental assessment.

seismic oceanography; seismic exploration; seismic reflection profiling; marine water body characteristics; rapid monitoring

1 Introduction

With the rapid economic development of coastal areas in China, physical properties of sea water and their variations with time need to be obtained in shallow sea areas (Liu and Duan, 2004; Wang., 2008). The property of sea water (salinity, temperature, density, acoustic velocity,.) can be used to study the phenomena such as meso- scale eddies, oceanic front, internal wave and suspended material flux and lose move (Broecker, 1997; Fukasawa., 2004; Osborn, 1998). Their spatial and time distribution is significant for analyzing a variety of global environment, the safety of marine military activities, ocean transportation, distribution of marine productivity and fisheries. In addition, high resolution imaging of shallow sea water structure is essential to 3D sea water properties detecting, large sea-crossing bridge, tunnel, nuclear power station, port, oil and gas exploration as well as development platform, seabed pipeline detection, geological hazards assessment, environment appraisal and so on (Barbel and Xiang, 2006; Zhang, 2005a, 2005b; Chen., 2004; Yang., 2001; Liu., 2005; Xia and Mi, 2002;Li., 2004; Guo., 2005).

At present, physical properties of sea water are widely measured in the form of dragging type at fixed position (Rudnick and Ferrari, 1999), whose vertical sampling interval is less than one meter via the settings of different sampling frequency and running velocity. Though it is possible to achieve higher vertical resolution, the lateral resolution of this method is lower. The previous sea water properties structure of the entire area is interpolated, smoothed and simulated according to the measured data from various observation stations. Thus, the variation of physical properties of sea water between different stations is sometimes unknown. In the ocean, the distance between the stations for measuring sea water properties is too large in general and it results in lower horizontal resolution. Water structure in shallow sea tends to be more complex and changeable due to the effects of seabed topography, tide, surface flow and climate. Even though the distance between the oceanographic stations is set to be shorter than that in deep sea, the physical oceanography parameters usually vary at faster speed. So it is difficulty to capture the variance of sea water structure, much less describing the real process.

High precision marine seismic acquisition system improves the quality of marine seismic data. Owing to this advanced system, the physical properties of sea water can be studied using the seismic reflection method. With the aid of seismic reflection method and parameters calibration of the sea water properties at the appointed position, Holbrook(2003, 2005) applied seismological method to physical oceanography research for the first time. And they achieved the fine structure of the sea water properties successfully. This new method is defined as ‘seismic oceanography’. It estimates the distribution of physical properties of sea water, using the corresponding relation between the seismic stacked profile and the fine structure of sea water properties. This relation can be established by seismic reflection coefficient, wave velocity and temperature. Compared with the traditional survey methods, seismic oceanography method can obtain better distribution of physical properties of sea water with higher horizontal resolution at the level of less than 10m. Moreover, it can monitor sea water properties in real time. Therefore, the new method improves the precision of imaging of sea water body and promotes understanding of ocean environment.

Conventional seismic exploration technology aims mainly to explore the seabed and the underground geological structure. There has been little study on physical properties of sea water (salinity, temperature, density, acoustic velocity and other parameters) with seismic exploration technique before the 21st century. Holbrook’s team has made a breakthrough in this field (Holbrook., 2003). Applying the conventional seismic processing method to three seismic reflection profiles acquired from the North Atlantic, they studied the relationships between reflection coefficient and acoustic velocity and between acoustic velocity and temperature; they also pointed out the relationship between seismic stacking profiles and the corresponding thermohaline fine structure. They found the seismic line across different water masses of the North Atlantic Current (NAC) and the Labrador Current (LC) in the seismic profiles, showed the different reflection features, and discovered four reflection types at least. With synchronizing XBT correction, 0.1℃ temperature change can be observed in seismic profile and its horizontal resolution can reach 6 m, which is far smaller than the one (several kilometers to tens of kilometers) as obtained by the traditional positioning survey. So the new technique is a powerful complement to the traditional oceanographic survey, appearing as a highly promising new tool for studying marine fine processes. Although Holbrooksuccessfully studied the thermohaline fine structure via reflection seismic profile method, there was not enough temperature data to describe temperature changes at small scales. Nandi. (2004) found that the temperature variation of about 0.03℃ can be distinguished in low-frequency seismic reflection profile via the seismic survey and the synchronization of the large amounts of XBT and XCTD survey data in Norwegian Sea. They further verified that the seismic reflection method can be used for describing the frontal process of water masses. They also found that the seismic reflection amplitude and water temperature changes have good corresponding relation. It indicates that seismic reflection amplitude changes can be used for estimating the water temperature, which provides another ocean temperature telemetry method. Higher horizontal resolution (10m) and vertical resolution (0.03℃) makes the seismic reflection method a new approach to study ocean fronts, internal waves and deep water masses boundary shape. There are similar results with the Kuroshio and the Oyashio frontal (Nakamura., 2006), and with Ireland, Karl Strait (Hardy., 2007) and other marine areas.

Ocean internal wave is one of the most important processes in physical oceanography. It affects many other ocean processes, including nutrient distribution (Lennert-Cody and Franks, 1999), sediment resuspension (Cacchione., 2002) and occurrence of turbulence (Garrett., 2003). But the traditional observation methods mainly rely on fixed point observation and longtime anchor towed. Seismic oceanography research proves that such a method is able to capture the small changes in internal waves and provide the quantitative information of the internal wave energy changes (Holbrook., 2005). Because the seismic reflection data obtained via seismic oceanography method has high resolution in lateral direction and reveals water body properties throughout entire sea water layer, this new method shows great advantages in the quantitative study on internal wave. Along with the gradual development of seismic oceanography research, all sorts of reflection seismic processing methods have been used, such as AVO method on water temperature (Páramo and Holbrook, 2005), and full waveform inversion temperature profiles (Wood., 2008).

Considering the promising method of seismic oceanography, the European Union put forward the large ‘geophysical research program’ (GO) project in 2006. The project has organized marine geophysicists and physical oceanographers from six EU countries to use the geophysical method to study the ocean. The start of the project also shows that seismic oceanography is about to become one of the important methods for global ocean changes study and physical oceanography research (Lucas, 2008). Songhave also conducted the study on the seismic oceanography in China (Song., 2008; Song and Dong, 2007; Dong and Song, 2007).

Previous researches in seismic oceanography have mainly focused on the water structures and features in deep water. There is little research of this kind for shallow water all over the world. But many physical oceanography phenomena such as vortex, upwelling, circulation,, on China continental shelf are changeful and need to be studied. We shall study the complexity of water structure on China’s continental shelf and the corresponding seismic wavefield characteristics in shallow sea by combining the seismic section and synchronized temperature-salinity data in the process of the frontal intersection (Marsset., 1998; Müller., 2002; Luc, 1999; Bernhard and Roger, 1999; Riedel and Theilen, 2001; Bull., 2005; Gutowski., 2002).

Compared with open ocean, shallow sea water environment is complex and variable. Seismic reflection data has many disturbances (such as a variable period ghost reflection and multiple wave or singing, guided waves, currents, tides, swells and waves). How to identify the relationship between the seismic reflection wavefield characteristics and parameters of shallow sea water is a key problem to be solved. How to suppress the disturbing waves and get the best signal-to-noise ratio and resolution of seismic imaging profile for properties of sea water is also an important problem.

This paper sets up a reasonable sea water structure model, using the sea water structure data obtained by seismic reflection method in shallow sea. The objects are: 1) to study seismic wavefield features, especially the special noises in the seismic reflection data of shallow sea; 2) to illuminate the characteristics of the special noises in shallow sea such as ghost reflection multiples, ringings, guided waves, current, tide, swells, and so on; 3) to put forward high-definition imaging theories of how to suppress or attenuate various disturbing waves in the seismic reflection data of shallow sea and to improve signal-to-noise ratio and resolution of seismic data. And then a new approach to suppress and analyze special disturbing waves in the seismic data of shallow sea is proposed. By means of this new method, thermohaline fine structure, water mass boundaries and ocean internal waves can be distinguished with high precision seismic reflection data in shallow sea. As a promising method, it could be widely used for 3D sea water body monitoring, engineering evaluation, geological disaster assessment, environmental assessment and so on.

2 Seismic Detection of Shallow Marine Water Body

How to eliminate all kinds of disturbing waves and separate effective waves from seismic record has been an important problem in seismic data processing. Along with the development of seismic exploration technology, the denoising techniques have been increasing in geophysical field. The common denoising techniques include frequency domain filtering, frequency-space domain filtering, beam filtering, Radon transform, Wavelet transform and so on (Winsborrow., 2005; Shipp and Singh, 2002; Liu., 2005; Wan, 2005; Bao., 2005; Wang., 2005; Yuan., 2005; Hong., 2004; Li., 2003; Liu., 2003a, 2003b; Han., 2003; Zhou., 2009a, 2009b).

The differences of frequency spectrum between a majority of noises and the effective signal are small. 2D filtering technology mainly uses the velocity difference to eliminate the disturbing waves. And the filtering can be performed in f-k domain and x-t domain. Traditional 2D filtering techniques often result in obvious signal distortion in filtering out some useful signals while eliminating the disturbing ones. The smoothing effect of 2D filtering makes the whole section dull. The inconsistency of the disturbing wave amplitude changes results in earthworm- ed-type events which are false. The above-mentioned shortcomings result from the big difference of the disturbing waves distributions in time-space domain. Conventional 2D filtering factor often has a wide stop band, which makes some effective signal distorted after filtering.

Based on the theoretical modeling and real seismic record research, we improve on the high signal-to-noise ratio, high resolution and high-definition imaging theory for the noise suppression. And then we propose a new approach to analyze and eliminate the special disturbing waves in shallow sea seismic data (see Fig.1).

Fig.1 The processing flow chart of special disturbing wave suppression in the marine seismic data.

2.1 Wavefield Transform

From the shallow water structure and the seismic reflection data in the shallow sea, we study first the features of those special disturbing waves that cause the various noises mentioned earlier. Then the formation mechanism of the special disturbing waves in shallow sea water can be identified. In order to eliminate these special disturbing waves with high fidelity, the special disturbing wavefield should first be transformed into a simple one according to the characteristics of these waves. First assume target wavefield is related to a parametric variable, and then map the target wavefield onto the new domain, using the transition of special wavelet transform and Radon transform. In the new domain, the original complex wavefield (such as the period-variable ghost reflection and multiple waves) is transformed into parallel linear wavefield. Thus the noises can be suppressed and attenuated using their coherence for improving the objective wavefield. After the noises are eliminated from the objective wavefield, the inverse transform of this denoised wavefield can be made. Then the effective waves can be completely stayed in the record without distortion. Therefore, this method is of high fidelity.

2.2 Eliminating the Influence of Amplitude and Time Difference

In order to achieve the best estimate of the disturbing waves, it is necessary to eliminate the influence of amplitude and time difference within the time window in which the noise is suppressed. The fluctuation of amplitudes and time values between the adjoining traces impact on the multi-channel filtering badly, and it is more obvious in high frequency. Therefore, the ability of special disturbing waves to pass through the broadband filter is greatly restricted.

2.3 Optimal Wavefield Separation

The amplitude variance and time difference being removed on the seismic record, the special disturbing waves can be predicted by optimal wavefield suppression and attenuation theory, such as wavelet matching pursuit, time-frequency transform, time-space domain filtering, median filtering,. After wavefield transform, the apparent velocity of the special disturbing waves becomes infinite in space domain. Thus the special disturbing wave with obvious kinematic features can be achieved by targeted processing using the above theories.

For example, applying the matching pursuit of Wigner energy distribution proposed by Mallat and Zhang (1993) to time-frequency analysis of seismic records, we can accurately obtain the time-frequency distribution of each and all traces in seismic data. From the features of the time-frequency energy distribution, it is easy to distinguish the features of the effective wave and extract the time range including the signals.

To define signal and noise in frequency wave-number domain (or wavelet domain) is flexible. So the special disturbing waves obtained in frequency-wavenumber domain can be transformed into the time domain by means of multi-iteration method. And then the special disturbing waves can be predicted and eliminated by means of optimum extremum method. Thus the signal-to-noise ratio resolution of the denoised seismic data is improved at the same time, especially the part of high frequency.

2.4 Wavefield Inverse Transform and Restoring Signal

The signal can be estimatedsubtracting the special disturbing waves predicted from the record with amplitude correction and time difference correction, which is performed after wavefield transform. Using the above- mentioned amplitude scaling factors to adjust the amplitude of the estimated signal, we can recover the true amplitudes of the signal. And then we can obtain the seismic reflection data only including the effective signal, after reverse correction of the time difference.

Finally, we transform the signal data back into the original seismic record using wavefield inverse transform. In order to remove the mutation phenomenon of transform, the slope smooth processing is necessary.

If there are many special disturbing waves, the above record without noises can be input again and repeat the above process as new seismic record. The effective signal record will eventually be obtained after repeating the similar processing.

This new approach has the following advantages: 1) it can be used for noise suppression without doing damage on the signals and it is still effective for the noises in any time difference mode; 2) it is a robust method which is not sensitive to the noise amplitude and phase changes; 3) neither mixing wave data, nor the phenomenon of earthworm encountered by F-K filter would not be produced; 4) it is not limited to uniform spatial sampling and can be applied to denoising the local noise of high false frequency. Also it can keep the bandwidth of signal while the noise is suppressed.

3 Shallow Water Structure Model Processing

On the basis of the previous temperature and salinity data, we set up a shallow sea water model and performed forward modeling of seismic wavefield with this model. Using this model, we mainly study the characteristics and the propagation law of seismic wavefield in shallow water. China’s coastal waters have various layers, such as the thermocline, halocline and pycnocline. There are also other marine environmental parameter layers. The thermocline is the most representative, which includes both seasonal thermocline and perennial stabilized thermocline. Water structure forward modeling is mainly based on thermocline and halocline parameters setting. In the coastal waters, besides the thermocline, there also exist water masses with different property parameters in horizontal direction. Assuming there exist Nearshore Diluted Water Mass (F) and Shore Mixed Water Mass (M), being in shallow water and existing only in the surface layer. Characteristics of F: temperature 19.40℃, salinity<31; characteristics of M: temperature 22.31-22.45℃, salinity 31.81-32.30. They are listed in Table 1 and the water model constructed is shown in Fig.2.

Seismic shot records of the above-mentioned two water masses were synthesized. By means of processing the multi-channels seismic records by filter, velocity analysis, normal moveout correction, stack and so on, we got the stack section as shown in Fig.3. There are obvious features of water masses in this stack section.

Table 1 Water mass characteristic parameters

Fig.2 1-D water mass model.

Fig.3 Water mass stack profile.

4 Application Test

As shown in Fig.4, when the smooth and continuous seismic reflected wave reaches the slope edge in the East China Sea, it shows an undulating shape with high frequency oscillation. This phenomenon can be explained by the presence of internal wave. It suggests that the internal wave energy will be enhanced when it approaches the slope edge of the continental shelf. The spectral slope will change from −2 to −5/3 after the waves get into the turbulent inertial subrange, which is consistent with seismic profile. This shows that this method can be used to capture the small changes of internal waves in ocean. Also, we can obtain quantitative information for the energy changes of internal wave with this method. Because the marine seismic reflection has higher lateral resolution and the characteristics of penetrating throughout the whole sea water layer, the method is a promising approach to study the internal wave in nemberical quantities.

Fig.5 shows a seismic reflection profile of shallow water in China’s Bohai Sea after eliminating the special disturbing waves. This profile shows that there is an obvious front in this shallow sea.

In the South China Sea, we recorded marine multi- channel seismic data using the self-developed high precision marine seismic data acquisition system. By means of high precision processing techniques, we obtained a better seismic stacking profile which has high signal-to-noise ration and high resolution. The right graph of Fig.6 shows water features in the form of seismic reflection events. The left graph is the relationship between temperature and water depth, which was obtained from the corresponding CTD data. There is about 2℃ temperature change in the depth range of 118-125m. It is in accord with the seismic reflection events which can be obviously seen near 170ms in the seismic profile. The energy of seismic reflection events and the temperature changes are in agreement with each other. Therefore the velocity changes caused by the changes of water temperature can be imaged in the high precision marine seismic profile.

Fig.4 Marine water seismic profile after special disturbing wave suppression in the East China Sea.

Fig.6 The relationship between temperature and high precision seismic reflection profile. Left is the curve of temperature along depth; Right is the seismic stack.

5 Summary

The water structure in the sea is complex and changing, and there are many disturbing waves in the course of marine seismic data acquisition, which is difficult to avoid. Considering these difficulties, we have developed a new approach to suppress the disturbing waves in the shallow sea. The approach is established by the forward modeling and the corresponding seismic wavefield analysis. It obviously improves the signal-to-noise ratio and the resolution of marine seismic reflection data. We can make use of this approach to obtain a better distribution of shallow sea water properties. This method is effective to suppress and attenuate various noises in shallow sea. In addition, a set of new processing and analysis method is established for the suppression and attenuation of the special seismic disturbing waves in shallow sea water.

Acknowledgements

The authors would like to thank the Natural Science Foundation of China (41176077), Subject of 973 (2009 CB219505), Natural Science Foundation of Shandong (ZR2010DM012), Basic Research Special Foundation of the Third Institute of Oceanography affiliated to the State Oceanic Administration (TIOSOA, 2009004) and the Science Research Project for the South China Sea of Ocean University of China for their financial support to this work.

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(Edited by Xie Jun)

10.1007/s11802-013-2100-5

ISSN 1672-5182, 2013 12 (3): 319-326

. Tel: 0086-532-66781556 E-mail: lhs@ouc.edu.cn

(July 13, 2012; revised September 17, 2012; accepted January 14, 2013)

© Ocean University of China, Science Press and Springer-Verlag Berlin Heidelberg 2013