2. Yunnan Earthquake Agency, Kunming 650224, China;
3. Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China
The airgun was invented by Chelminski in 1963. The high-pressure gas in the gun body is instantaneously released from the water to generate seismic waves. It has a good excitation effect and has obvious advantages in terms of controllability and operability when compared to other ways of exciting the source. Large-capacity modulated airgun arrays formed by using a combination of multiple airguns are widely used in offshore oil exploration and deep crustal structure research. In recent years, it has been proposed that large-capacity non-modulated airgun arrays be used to excite terrestrial reservoirs in order to detect regional-scale deep structures in terrestrial areas, and to develop methods for artificially inducing seismic waves on land (Chen Yong et al., 2007; Luo Guichun et al., 2006). Through a series of large-capacity non-modulated airgun array tests, it is found that when the source frequency is low and the energy is large, the farthest propagation distance of a single excitation can reach nearly two hundred kilometers. After multiple stacking, it can be increased to 500km. It can be used in the detection of underground structures in depths of up to hundreds of kilometers (Wang Baoshan et al., 2011). Secondly, the large-capacity non-modulated airgun array source is excited in water without irreparable damage to the environment and the medium, and has excellent repeatability and environmental protection. Therefore, the large-capacity non-modulated airgun array source of the reservoir is an ideal source for deep-seismic detection and monitoring at a regional scale (Chen Yong et al., 2008; Lin Jianmin et al., 2008; Wang Baoshan et al., 2011). At the same time, during the process of seismogenic earthquakes, the change in the stress state of the underground medium will cause the change in the seismic wave velocity. It is of great significance for earthquake prediction research to dynamically monitor the wave velocity change by using the active source height repeat and high energy characteristics. Since 2010, airgun source launching platforms have been built in Binchuan in Yunnan, Hutubi in Xinjiang, and Zhangye in Gansu, and the airgun source flowing excitation tests were carried out in the Anhui section of the Yangtze River to conduct continuous high-precision monitoring of underground media and has provided seismological observation with a powerful tool for regional scale. (Wang Bin et al., 2016; Wei Bin et al., 2016; Zhang Yuansheng et al., 2016; Xu Yihe et al., 2016).
When the large-capacity non-modulated airgun array source test is carried out in the reservoir, the characteristics of the seismic wave generated by the excitation depends not only on the configuration of the airgun source itself (the capacity of the airgun, the excitation pressure, etc.), but also on the excitation environment which shows great influence. For example, the changing of the reservoir's water level where the airgun is located, and the depth of the airgun source, especially in shallow water environments and the limited water area. The airgun source excitation process is the interaction process between the airgun source and the shallow water zone, which together constitute the airgun source excitation system in the shallow water zone. Tang Jie et al. (2009) and Lin Jianmin et al. (2010) simulated and analyzed near-field waveform data recorded by the hydrophone in the airgun excitation test in the Shangguanhu Reservoir in September 2007, and found that different excitation conditions of the airgun source depth and working pressure have an effect on the pressure pulse and bubble pulse. Chen Meng (2014) analyzed the effects of different excitation pressures, depths of sinking and reservoir water levels on seismic signals excited by large-capacity non-modulated airgun arrays at the Binchuan airgun seismic signal launching station based on Binchuan's multiple airgun tests. The impact of changes in the water level of the reservoir is far greater than the impact of the depth of the source. Hu Jiupeng et al. (2017) used numerical methods to simulate the effects of different water shapes on the excitation waveform of airguns. It is proposed that the shape of water has a strong influence on high-frequency signal components and weak influence on low-frequency signal components. Sun Nan et al. (2017) numerically simulated the influence of reservoir water depth on the waveform amplitude. It was found that the waveform amplitude increased with the water depth when the water level was less than 30m. Therefore, when we study the reservoir excitation airgun source, we must comprehensively consider the interaction and coupling of the airgun source and water. In this paper, the finite difference numerical method is used to simulate the influence of the water level, and the excitation energy and depth of sinking in the finite water body on the source signal of the reservoir excitation airgun, which has certain significance for deepening the application of the airgun source.1 AIRGUN TEST DATA IN BINCHUAN
The first land-excited airgun source launching platform in the world was built in Binchuan, Yunnan Province in 2012. The large-capacity non-modulated airgun array of the reservoir was used as the source to excite the seismic wave. The Dayindian Reservoir in Binchuan was selected as the excitation water body. The reservoir is a medium-sized reservoir. The dam height is 58m, the length is 144m, the storage capacity is 4, 085×104m3, and the maximum water depth is about 20m (Wang Bin et al., 2015). The reservoir is mainly based on agricultural irrigation, and functions as flood control and water supply in the county. Due to changes in living and production water, the water level has significant seasonal changes. For example, in 2013 (Fig. 1), the deepest water level was 22m and the shallowest was lower than 10m, which did not satisfy the excitation conditions.
The waveform records obtained by the excitation test conducted at different water level periods show different waveform characteristics (Fig. 2). For example, the CKT station (a) and 53273 station (b) waveforms are different at three different water levels, where CKT station is located on the reservoir bank, 53273 station is 4km far from the reservoir. In the actual waveform data application, the waveform data (approximate source) of the CKT station is commonly used for deconvolution, so as to eliminate the influence caused by the change in water levels, and (c) is the waveform of the 53273 station after deconvolution processing. As a result of the opposite of deconvolution, this phenomenon may be caused by the difference in the performance of the water levels due to the different epicentral distances. Therefore, the deconvolution of the approximate source may not completely eliminate the influence of the water level change. Moreover, in addition to the reservoir water level, the factors causing the waveform characteristics in the air gun test do not exclude other factors such as temperature, air pressure, and internal water content of the medium. Therefore, the numerical simulation method can be used to analyze the influence of reservoir water body, which can be used as an auxiliary means to provide theoretical basis for the analysis and application of subsequent actual waveforms.
As one of the most commonly used numerical simulation methods, the finite difference method has solved the processing of internal arbitrary non-uniform mediums in seismic wave simulation and strong ground motion simulation, and can accurately and efficiently simulate seismic waves of complex terrains in accordance with real geological conditions. (Zhang Wei et al., 2006; Sun Yaochong et al., 2017). This paper will use the finite difference method to simulate the influence of different factors on the airgun source in the layered half-space model containing finite water, including the water depth, excitation energy, and depth of the source, so as to study the excitation of the airgun source and provide a theoretical basis and support for the study of reservoir excitation airgun sources.2.1 Model
In the numerical simulation, the layered half-space medium model with a finite water body is selected to simulate the reservoir excitation airgun source environment, the Gaussian shape finite water body is set, the explosion source is selected as the excitation source, and the source time function is the first-order differential form of the Ricker wavelet with the main frequency of 10Hz. The media model configuration is shown in Fig. 3. The specific media parameters are listed in Table 1. Among them, the source of the model is placed at a depth of 10m below the surface of the water, simulating the way an airgun source sinks in a reservoir. In order to reflect the influence of the water level changing on the amplitude of the waveform on the distance as much as possible, the water body is placed on one side of the study area, and a survey line with 90 receivers is placed on the surface of the area medium (Fig. 3).
In the numerical simulation, the boundary of the study area adopts the absorption layer method, that is, the wave field is absorbed in the mesh layer with a certain width at the boundary of the region, so that after the waveform propagates to the boundary of the region, the attenuation is gradually weakened in the absorption layer without reflection, thereby avoiding the influence on the phase characteristics of the area studied (Berenger J.P., 1994; Sun Yaochong et al., 2016). The wave field snapshot obtained by numerical simulation can also be found (Fig. 4). After the wave field propagates to the regional boundary, there is no phenomenon of reflection back to the study area, indicating that the phase characteristics to be studied are not affected by the regional boundary.
By simulating the influence of the water depth, excitation energy and depth of the source in the finite water body on the waveform characteristics, the effects of the excitation environment and airgun source configuration in a shallow water environment are explored. An important parameter of the airgun signal is the maximum amplitude. When studying the damage of the airgun source to the environment and the impact on aquatic organisms, especially when the airgun is excited in a shallow water environment, the maximum amplitude of the airgun excitation signal has important guiding significance. (Lin Jianmin et al., 2010). In the numerical simulation, the parameter "normalized amplitude change" is the relative change of the maximum amplitude of the waveform to characterize the change of the maximum amplitude of the waveform when the different influencing factors change.2.2.1 Water Level
When the water depth in the finite water body is less than 30m, the wave field energy and waveform amplitude are enhanced with the water level deepening. In the simulation, the water depth changes are set to 15-20m, 20-25m, 15-25m, 20-30m, respectively, so we can get the effect of water level change on the waveform amplitude with the distribution of the epicentral distance. The results show (Fig. 5) that as the epicentral distance increases, the waveform amplitude caused by the change in water level gradually decreases. Stations that are close to the water body have a large fluctuation in the amplitude of the received signal, and the amplitude of the x-direction changes in a sinusoidal distribution, and that of the z-direction is cosine-distributed. Therefore, waveform amplitude variations may be present in negative values in some stations. The negative change in the x-direction of some station signals with an epicenter distance of 100-200m is very obvious, that is, the increase in the water level causes the maximum decrease of the waveform amplitude. For the same water level change range (dh=5m), the influence of high water level change (25-20m) is larger than the low water level (20-15m), and the larger the change range (dh=10m relative to dh=5m), the greater the impact.
Since the maximum depth of the water level of the Binchuan Reservoir is around 20m, the influence of the water level on the waveform amplitude from 15m to 20m is analyzed (Fig. 6). The results show that the effect on the x-direction is slightly more pronounced in magnitude and distance than that on the z-direction. According to the difference in the influence of the water level change on different epicentral distances, the amplitude variation is divided into two parts: the relatively large and the relatively small. The root mean square value RMS is used to indicate the change range. In the x-direction, when the water level changes from 15m to 20m, the range of the amplitude variation can reach 200m. In the range of ≤200m, the influence of the water level change can cause the amplitude variation to be 0.15 (±0.38) times. In the range of ≥200m, the influence of the water level change can cause the amplitude variation to be 0.18 (±0.05) times. In the z-direction, the influence of the water level change is relatively small, especially in the range of ≤100m, the amplitude variation is only 0.01 (±0.04) times. In the range of ≥100m, the amplitude variation is 0.10 (±0.05) times.
Studies on airguns in offshore oil exploration have shown that the excitation pressure has the most significant effect on the seismic signals generated by the airgun (Johnston R.C., 1980). In large-capacity airgun array tests, when the total capacity of the airgun is constant, the excitation energy is proportional to the excitation pressure. The effect of the excitation pressure can be reflected by simulating the effect of the excitation energy change on the waveform amplitude. When the excitation environment is consistent, the excitation energy is 1.0×106J, 1.3×106J, and 1.7×106J respectively. According to the energy magnitude conversion form the excitation energy of 1.3×106J is equivalent to the energy of an M0.8 earthquake. The simulation results show that the amplitude of the waveform signal received by the different stations is increasing over the airgun excitation energy (Fig. 7).
In the marine airgun test, the amplitude (A) of the airgun signal is exponentially related to the excitation pressure (p) (Giles B.F. et al., 1973; Dragoset B., 2000), so the simulation results are fitted by an exponential function (Fig. 8(a)). The exponential coefficient of the function is 0.94, which is very close to 1, indicating that the amplitude of the simulated waveform is approximately linear with the excitation energy. At the same time, the waveforms recorded by the simulated excitation energy changes at different epicentral distances show that when the excitation energy is increased by 5 times (Fig. 8(b)), the maximum amplitude of the waveform received at different distances is increased by about 5 times, and the disturbance range is less than 0.003%, therefore, the difference in waveform amplitude caused by the change in excitation energy does not change with the epicentral distance.
The depth of the airgun array determines the distance between the airgun array and the bottom of the reservoir, which also affects the airgun seismic signals generated by the airgun array. In order to study the effect of the depth on the airborne source signal in a finite water body, we simulated the different depths of the sinking. When the excitation conditions are the same, the water level is fixed to 20m, and the source is placed at 7m, 10m and 13m depth respectively. The result shows the waveform amplitude with the depth of 13m is larger than that of 10m, and the latter has amplitude larger than that of 7m (Fig. 9). That is, the amplitude of the waveform increases with the focal depth.
In order to analyze the variation characteristics of the amplitude difference in different epicenter distances due to the different focal depths, the water level is fixed to 30m, and the focal depth varies from 15-20m and 20-25m respectively, and thus the simulated amplitude variation based on distance is obtained. The results show that when the focal depth is from 15m to 20m, the amplitude of the waveform recorded by the stations with different epicentral distances is about 1.48 times. When the depth of the sinking depth is from 20m to 25m, the amplitude of the recorded waveform changes is about 1.25 times (Fig. 10). In the range of the epicenter distance of 100-200m, the x-direction amplitude changes obviously disturbed. Generally speaking, the disturbance of the x-direction amplitude change is more obvious than that of the z-direction.
The numerical simulation results show that the amplitude variation of the stations near the reservoir is greatly affected by the change in water level, and the amplitude variation of the station at different epicentral distances is very different. After exceeding a certain epicentral distance range, the effect of the water level change on the waveform amplitude is basically unchanged. This may be related to the propagation path of the waveform received by the station with different epicentral distances and its phase. The waveform signal near the water body is more affected by the presence of the water body, and the seismic phase is more complicated, thus causing the greater amplitude difference by the water level change. The simulation results that the influence of the vertical component on the amplitude and distance are weaker than other components which also confirmed in the excitation airgun source test of the Binchuan Reservoir. The waveform signals recorded by 53262 station (4.8km away from the reservoir) shown in Fig. 11 that when the water level is increased from 14.5-20.5m, the amplitude variation of the vertical component is smaller than that of other components. This may be due to the fact that the energy of other components is mostly converted by the P-wave, while the energy of the vertical component is more likely to be converted by S-wave, so that the vertical component is affected less by the change of water level than the other components.
In the large-capacity airgun test of the reservoir, when the airgun capacity is constant, the excitation pressure is proportional to the excitation energy. The influence of the simulated excitation energy change on the waveform amplitude in this study is consistent with the conclusion ofChen Meng (2014) on the characteristics of the Binchuan airgun signal. The excitation energy is in a linear relationship with the waveform amplitude. When the working pressure of the airgun increase, the pressure in the excitation bubble increase, the corresponding bubble radius and the bubble wall movement speed are relatively large, and the amplitude of the corresponding bubble pulse becomes larger.
The influence of the variation of the focal depth on the propagation characteristics of the wave field shows that the maximum amplitude of the airgun signal is nearly linearly increasing with the focal depth. In this paper, the main frequency of the analog signal (~10Hz) is similar to the bubble pulse frequency of the Shangguan Lake airgun excitation signal by Lin Jianmin et al. (2010). He also believes that there is a relatively regular change in the influence of the airgun depth on the amplitude of the bubble pulse. The maximum amplitude value increases nearly linearly with the airgun sink depth. This may be due to the fact that the deeper the airgun sinking depth, that is, the greater the hydrostatic pressure, the better the coupling with the water body during bubble excitation and oscillation. Therefore, the more effective the airgun excitation sound wave energy, the larger the amplitude of the received waveform.4 CONCLUSION
The large-capacity airgun source excitation signal of the reservoir has a certain dependence on the airgun configuration and excitation environment such as water level, excitation energy and focal depth. From the simulation results and the above analysis and discussion, we draw the following conclusions:
During the waveform propagation process, for the stations near the limited water body, the amplitude of the received airgun signal is greatly affected by the change in the water level, and the influence of the high water level and the large water level change is even greater. But for the stations beyond a certain epicentral distance, the influence of the water level change on its signal amplitude will be weakened and basically stable. For the airgun signal excited by the Binchuan Reservoir, the amplitude disturbance caused by the water level change is very small (±0.05 times) after a certain distance of propagation. Therefore, the influence on the water level change can be removed by referring to the numerical simulation results. The amplitude of the waveform is nearly linearly increasing with the excitation energy and the focal depth. That is, the larger the excitation energy, and the deeper the focal depth, the better the bubble pulse excitation effect, and the more suitable it is for the detection of deep penetration of the underground structures.
According to the research of this paper, although the numerical simulation results are in good agreement with the actual experimental conclusions, due to the limitation of calculation conditions and cost, only the relatively simple two-dimensional medium model and the source time function are used for simulation, and the complexity and fineness of the actual airgun excitation test cannot be achieved, and there are some quantitative differences between the numerical simulation results and the actual airgun signal characteristics. Therefore, it is hoped that in the next step we can use a more elaborate model medium and a more accurate source time function to simulate and determine as far as possible the impact of the airgun configuration and excitation environment on the reservoir excitation airgun source, so as to provide a basis for the subsequent study of the velocity structure of the underground medium using airgun data.ACKNOWLEDGEMENTS
Thanks to Prof. Zhang Wei from the Southern University of Science and Technology, Mr. Wang Weitao from the Institute of Geophysics, China Earthquake Administration, Dr. Zhang Wenqiang and Dr. Cao Wenzhong from the University of Science and Technology of China for answering and guiding the questions in the process of simulation analysis. Thanks to the anonymous reviewers for the revision of this article.
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