Numerical simulation in exploration geophysics provides important insights into subsurface wave propagation phenomena. Although elastic wave simulations take longer to compute than acoustic simulations, an elastic simulator can construct more realistic wavefields including shear components. Therefore, it is suitable for exploration of the responses of elastic bodies. To overcome the long duration of the calculations, we use a Graphic Processing Unit (GPU) to accelerate the elastic wave simulation. Because a GPU has many processors and a wide memory bandwidth, we can use it in a parallelised computing architecture. The GPU board used in this study is an NVIDIA Tesla C1060, which has 240 processors and a 102 GB/s memory bandwidth. Despite the availability of a parallel computing architecture (CUDA), developed by NVIDIA, we must optimise the usage of the different types of memory on the GPU device, and the sequence of calculations, to obtain a significant speedup of the computation. In this study, we simulate two- (2D) and threedimensional (3D) elastic wave propagation using the Finite-Difference Time-Domain (FDTD) method on GPUs. In the wave propagation simulation, we adopt the staggered-grid method, which is one of the conventional FD schemes, since this method can achieve sufficient accuracy for use in numerical modelling in geophysics. Our simulator optimises the usage of memory on the GPU device to reduce data access times, and uses faster memory as much as possible. This is a key factor in GPU computing. By using one GPU device and optimising its memory usage, we improved the computation time by more than 14 times in the 2D simulation, and over six times in the 3D simulation, compared with one CPU. Furthermore, by using three GPUs, we succeeded in accelerating the 3D simulation 10 times.
In recent years, microtremor array observations have been used for estimation of shear-wave velocity structures. One of the methods is the conventional spatial autocorrelation (SPAC) method, which requires simultaneous recording at least with three or four sensors. Modified SPAC methods such as 2sSPAC, and linear array methods, allow estimating shear-wave structures by using only two sensors, but suffer from instability of the spatial autocorrelation coefficient for frequency ranges higher than 1.0 Hz. Based on microtremor measurements from four different size triangular arrays and four same-size triangular and linear arrays, we have demonstrated the stability of SPAC coefficient for the frequency range from 2 to 4 or 5 Hz. The phase velocities, obtained by fitting the SPAC coefficients to the Bessel function, are also consistent up to the frequency 5 Hz. All data were processed by the SPAC method, with the exception of the spatial averaging for the linear array cases. The arrays were deployed sequentially at different times, near a site having existing Parallel Seismic (PS) borehole logging data. We also used the imaginary part of the SPAC coefficients as a data-quality indicator. Based on perturbations of the autocorrelation spectrum (and in some cases on visual examination of the record waveforms) we divided data into so-called 'reliable' and 'unreliable' categories. We then calculated the imaginary part of the SPAC spectrum for 'reliable', 'unreliable', and complete (i.e. 'reliable' and 'unreliable' datasets combined) datasets for each array, and compared the results. In the case of insufficient azimuthal distribution of the stations (the linear array) the imaginary curve shows some instability and can therefore be regarded as an indicator of insufficient spatial averaging. However, in the case of low coherency of the wavefield the imaginary curve does not show any significant instability.
Recently, stratigraphic reservoirs are getting more attention than structural reservoirs which have mostly developed. However, recognizing stratigraphic thin gas reservoirs in a stacked section is usually difficult because of tuning effects. Moreover, if the reflections from the brine-saturated region of a thin layer have the same polarity with those from the gas-saturated region, we could not easily identify the gas reservoir with conventional data processing technique. In this study, we introduced a way to delineate the gas-saturated region in a thin layer reservoir using a spectral decomposition method. First of all, amplitude spectrum with the variation of the frequency and the incident angle was investigated for the medium which represents property of Class 3, Class 1 or Class 4 AVO response. The results show that the maximum difference in the amplitude spectra between brine and gas-saturated thin layers occurs around the peak frequency independent of the incident angle and the type of AVO responses. In addition, the amplitude spectra of the gas-saturated zone are greater than those of brine-saturated one in Class 3 and Class 4 at the peak frequency while those of phenomenon occur oppositely in Class 1. Based on the results, we applied spectral decomposition method to the stacked section in order to distinguish the gas-saturated zone from the brine-saturated zone in a thin layer reservoir. To verify our new method, we constructed a thin-layer velocity model which contains both gas and brine-saturated zones which have the same reflection polarities. As a result, in the spectral decomposed sections near the peak frequency obtained by Wigner-Ville Distribution (WVD), we could identify the difference between reflections from gas- and brinesaturated region in the thin layer reservoir, which was hardly distinguishable in the stacked section.
The determination of seismic velocities in refractors for near-surface seismic refraction investigations is an ill-posed problem. Small variations in the computed time parameters can result in quite large lateral variations in the derived velocities, which are often artefacts of the inversion algorithms. Such artefacts are usually not recognized or corrected with forward modelling. Therefore, if detailed refractor models are sought with model based inversion, then detailed starting models are required. The usual source of artefacts in seismic velocities is irregular refractors. Under most circumstances, the variable migration of the generalized reciprocal method (GRM) is able to accommodate irregular interfaces and generate detailed starting models of the refractor. However, where the very-near-surface environment of the Earth is also irregular, the efficacy of the GRM is reduced, and weathering corrections can be necessary. Standard methods for correcting for surface irregularities are usually not practical where the very-near-surface irregularities are of limited lateral extent. In such circumstances, the GRM smoothing statics method (SSM) is a simple and robust approach, which can facilitate more-accurate estimates of refractor velocities. The GRM SSM generates a smoothing 'statics' correction by subtracting an average of the time-depths computed with a range of XY values from the time-depths computed with a zero XY value (where the XY value is the separation between the receivers used to compute the time-depth). The time-depths to the deeper target refractors do not vary greatly with varying XY values, and therefore an average is much the same as the optimum value. However, the time-depths for the very-near-surface irregularities migrate laterally with increasing XY values and they are substantially reduced with the averaging process. As a result, the time-depth profile averaged over a range of XY values is effectively corrected for the near-surface irregularities. In addition, the time-depths computed with a Bero XY value are the sum of both the near-surface effects and the time-depths to the target refractor. Therefore, their subtraction generates an approximate 'statics' correction, which in turn, is subtracted from the traveltimes The GRM SSM is essentially a smoothing procedure, rather than a deterministic weathering correction approach, and it is most effective with near-surface irregularities of quite limited lateral extent. Model and case studies demonstrate that the GRM SSM substantially improves the reliability in determining detailed seismic velocities in irregular refractors.
It is necessary to consider various geological parameters such as lithology, geological structure, earthquake, hydraulic geology, geochemistry, geological engineering, and geothermal in order to select potential sites for HLW(high-level radioactive waste) geological disposal. In particular, the geological lineament reflects the characteristics of various geological parameters and can be used as an important criterion for site selecting such as nuclear power plants and HLW repositories. In this paper, the Finnish lineament classification method for HLW disposal site selection through the lineament analysis was applied to the lineament data in the Korean peninsula. For this purpose, we used previous lineament data from the KIGAM(Korea Institute of Geoscience and Mineral Resources) and obtained new lineament data from the field geologists such as structural geologist, paleoseismologist, and geomorphologist. To ensure the reliability of the new lineament analysis data, we used high-resolution satellite images and hill-shade relief maps which were constructed by a digital elevation model. In the prevailing direction analysis from the acquired lineament data, the NNE-SSW direction was the most dominant, but the ENE-WSW and NNW-SSE directions also showed highly frequency depending on the experts. Applying the Finnish classification method, the geometrical development characteristics of the lineament corresponding to the Class 1 and 2 used for the wide-wide candidate site were compared. As a result of direction analysis for Class 1, the NNE-SSW direction was the most dominant and the WNW-ESE direction also showed a high frequency. In the case of Class 2, the NNE-SSW is the most prevalent and WNW-ESE or ENE-WSW direction also had highly frequency depending on the experts. Different lineament analysis results based on the same data are interpreted as a result of subjective experience and analytical criteria from the every experts. Therefore, it is necessary to establish integrated criteria and consider geophysical data for the publication of reliable nation-wide lineament map.
To reveal and classify site characteristics in densely populated areas in Chuncheon, Korea, Rayleigh-waves were recorded at 50 sites including four sites in the forest area using four 1-Hz velocity sensors and 24 4.5-Hz vertical geophones during the period of January 2011 to May 2013. Dispersion curves of the Rayleigh waves obtained by the extended spatial autocorrelation method were inverted to derive shear-wave velocity ($v_s$) models comprising 40 horizontal layers of 1-m thickness. Depths to weathered rocks ($D_b$), shear wave velocities of these basement rocks ($v_s^b$), average velocities of the overburden layer ($\bar{v}_s^s$), and the average velocity to a depth of 30 m ($v_s30$), were then derived from those models. The estimated values of $D_b$, $v_s^b$, $\bar{v}_s^s$, and $v_s30$ for 46 sites at lower altitudes were in the ranges of 5 to 29 m, 404 to 561 m/s, 208 to 375 ms/s, and 226 to 583 m/s, respectively. According to the Korean building code for seismic design, the estimated $v_s30$ indicates that the lower altitude areas in Chuncheon are classified as $S_C$ (very dense soil and soft rock) or $S_D$ (stiff soil). To determine adequate proxies for $v_s30$, we compared the computed values with land cover, lithology, topographic slope, and surface elevation at each of the measurement sites. Due to a weak correlation (r = 0.41) between $v_s30$ and elevation, the best proxy of them, applications of this proxy to Chuncheon of a relatively small area seem to be limited.
Recently, the studies about rock physics model (RPM) in shale reservoir are widely performed. In shale reservoir, the degree of the maturity can be estimated by kerogen and GOR (Gas-Oil Ratio). The researches on the rock physics model of shale reservoir with the amount of kerogen have been actively carried out but not with GOR. Thus, in this study, we analyzed the changes in seismic velocity and density, and AVO (Amplitude Variation with Offset) response depending on changes in GOR and the amount of kerogen. Since the shale consists of plate-like particles, it has vertical transverse isotropy (VTI). Therefore we estimated the seismic velocity and density by using Backus averaging method and analyzed AVO responses based on these estimated properties. The results of analysis showed that the changes in the velocity with the GOR variation are small but the velocity changes with the variation in kerogen amount are relatively larger. In case, GOR 180 (Litre/Litre) which is boundary between heavy oil and light oil, when volume fraction of kerogen increased from 5% to 35%, the P-wave velocity normal to the layering increased 51%. That is, it helps estimating maturity of kerogen through the velocity. Meanwhile, when rates of oil-gas mixture are large, the effect of GOR variation on the velocity change became larger. In case volume fraction of kerogen is 5%, the P-wave velocity normal to the layering was estimated $1.46km/s^2$ in heavy oil (GOR 40) but $1.36km/s^2$ in light oil (GOR 300). The AVO responses analysis showed class 4 regardless of the GOR and amount of kerogen because variation of poisson's ratio is small. Therefore, shale reservoir has possibility to have class 4.
Kim, Taehyung;Kim, Young-Seog;Lee, Youngmin;Choi, Jin-Hyuck
The Journal of Engineering Geology
/
v.26
no.2
/
pp.277-290
/
2016
Deep geological cross-sectional data is generally not common nor easy to construct, because it is expensive and requires a great deal of time. As a result, geological interpretations at depth are limited. Many scientists attempt to construct geological cross-sections at depth using geological surface data and geophysical data. In this paper, we suggest a method for constructing cross-sections from limited geological surface data in a target area. The reason for this study is to construct and interpret geological cros-sections at depth to evaluate heat flow anomaly along the Yangsan fault. The Yangsan Fault passes through the south-eastern part of the Korean Peninsula. The cross-section is constructed from Sangbukmyeon to Unchonmyeon passing perpendicularly through the Yangsan Fault System trending NW-SE direction. The geological cross-section is constructed using the following data: (1) Lithologic distributions and main structural elements. (2) Extensity of sedimentary rock and igneous rock, from field mapping. (3) Fault dimension calculated based on geometry of exposed surface rupture, and (4) Seismic and core logging data. The Yangsan Fault System is composed of the Jain fault, Milyang fault, Moryang fault, Yangsan fault, Dongnae fault, and Ingwang fault which strike NNE-SSW. According to field observation, the western section of the Yangsan fault bounded by igneous rocks and in the eastern section sedimentary rocks are dominant. Using surface fault length we infer that the Yangsan Fault System has developed to a depth of kilometers beneath the surface. According to seismic data, sedimentary rocks that are adjacent to the Yangsan fault are thin and getting thicker towards the east of the section. In this study we also suggest a new method to recognize faults using core loggings. This analysis could be used to estimate fault locations at different scales.
Using airborne magnetic data, magnetic characteristics were studied at the Samryangjin caldera area developed in the volcanics of the Yuchon sub-basin, the south eastern part of the Gyeongsang basin. Residual magnetics, reduction to the pole, horizontal derivative, and vertical derivative maps are prepared. Using these maps, the magnetic lithofaces are zoned and the geological structures such as caldera and faults were qualitatively interpreted. In addition, the two quantitative interpretations were performed. Firstly, the forward modelling were done to the 14.5 line km crossing the caldera area to the northeast-southwest direction. Applying the 3-D Euler deconvolution method to the whole study area, the depth extent and the characteristics of the magnetic anomalous bodies were studied. According to the results, the magnetic lithofaces of the area are zoned by 4 units. In general, these are well matched with the geological distributions. But the biotite granites intruded in the northern boundary of the Samryangjin caldera show the high magnetic intensity, while the biotite granites of the other areas show the low magnetic intensity and the different magnetic lithofaces. Thus, we interpreted that the biotite granites are closely related with the volcanic activity of the Samryngjin caldera, and are intruded in the fracture zones developed along the caldera rim. The Samryangjin caldera and fault structures of the area can be easily recognized by the distinct magnetic structures from the various magnetic anomaly maps. Also the topographic characteristics well reflect these structures. The results of the forward modelling show that the magnetic basement depth of the Gyeongsang sedimentary basin is on the average about 6 km and in maximum 10 km. And the depth becomes shallower toward the caldera boundary due to the shallow intrusion of the volcanics. The results of the 3-D Euler method also show the caldera and fault structures. And the relatively shallow magnetic anomalous bodies which are related with the volcanics are generally developed to the east-west and northeast directions, while the deep magnetic anomalous bodies to the northwest direction.
In field surveys using the dipole-dipole electrical resistivity method, we often encounter negative apparent resistivity. The term 'negative apparent resistivity' refers to apparent resistivity values with the opposite sign to surrounding data in a pseudosection. Because these negative apparent resistivity values have been regarded as measurement errors, we have discarded the negative apparent resistivity data. Some people have even used negative apparent resistivity data in an inversion process, by taking absolute values of the data. Our field experiments lead us to believe that the main cause for negative apparent resistivity is neither measurement errors nor the influence of self potentials. Furthermore, we also believe that it is not caused by the effects of induced polarization. One possible cause for negative apparent resistivity is the subsurface geological structure. In this study, we provide some numerical examples showing that negative apparent resistivity can arise from geological structures. In numerical examples, we simulate field data using a 3D numerical modelling algorithm, and then extract 2D sections. Our numerical experiments demonstrate that the negative apparent resistivity can be caused by geological structures modelled by U-shaped and crescent-shaped conductive models. Negative apparent resistivity usually occurs when potentials increase with distance from the current electrodes. By plotting the voltage-electrode position curves, we could confirm that when the voltage curves intersect each other, negative apparent resistivity appears. These numerical examples suggest that when we observe negative apparent resistivity in field surveys, we should consider the possibility that the negative apparent resistivity has been caused by geological structure.
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