Exploration Geophysics - Volume 48, Issue 1, 2017

Severe residential damage in the Furukawa district, Miyagi, Japan, occurred during the Great Eastern Japan Earthquake of 2011. We model the shallow subsurface structure based on aftershock records from a dense seismometer network and results of microtremor observations. Site amplifications estimated from the model explain the damage distribution well.

We conducted single-site and array observations of microtremors in order to revise the shallow subsurface structure of the Furukawa district, Miyagi, Japan, where severe residential damage was reported during the Great Eastern Japan Earthquake of 2011, off the Pacific coast of Tohoku. The phase velocities of Rayleigh waves are estimated from array observations at three sites, and S-wave velocity models are established. The spatial distribution of predominant periods is estimated for the surface layer, on the basis of the spectral ratio of horizontal and vertical components (H/V) of microtremors obtained from single-site observations. We then compared ground motion records from a dense seismometer network with results of microtremor observations, and revised a model of the shallow (~100 m) subsurface structure in the Furukawa district. The model implies that slower near-surface S-wave velocity and deeper basement are to be found in the southern and eastern areas. It was found that the damage in residential structures was concentrated in an area where the average value for the transfer functions in the frequency range of 2 to 4 Hz was large.

The Hinode area of Itako City in Ibaraki Prefecture, Japan, suffered severe liquefaction damage in the Great Eastern Japan Earthquake in 2011. The National Institute of Advanced Industrial Science and Technology (AIST) has carried out numerous investigations in the area. We have conducted risk analysis using cone penetration testing and electric resistivity data. The distribution of the risk estimated from both data sets is in agreement with the distribution of actual damage.

The Hinode area of Itako City in Ibaraki Prefecture, Japan, suffered some of the most severe liquefaction damage of any areas in the Great Eastern Japan Earthquake in 2011. This liquefaction damage has been investigated by Itako City, as well as by universities and research institutes in Japan. The National Institute of Advanced Industrial Science and Technology (AIST) has carried out numerous investigations along the Tone River, and in particular, intensive surveys were done in the Hinode area. We have conducted a risk analysis based on the thickness and depth of the liquefaction layer measured using cone penetration testing (CPT) data and electric resistivity data obtained in the Hinode area. The distribution of the risk estimated from CPT at 143 points, and that obtained from analysis of the resistivity survey data, agreed with the distribution of actual damage. We also carried out conventional risk analyses method using the liquefaction resistance factor (FL) and liquefaction potential index (PL) methods with CPT data. The results show high PL values over the entire area, but their distribution did not agree well with actual damage in some parts of the study area. Because the analysis of the thickness and depth of the liquefaction layer, using geophysical prospecting methods, can cover a widespread area, this method will be very useful in investigating liquefaction risk, especially for gas and water pipelines.

A fundamental step in reservoir characterisation and modelling is the preconditioning of the initial reservoir model to honour both the geological knowledge and seismic data. In this paper, we analyse the issues that have significant impact on the (mis)match of the reservoir model with well logs and inverted seismic data.

Integration of 3D and time-lapse 4D seismic data into reservoir modelling and history matching processes poses a significant challenge due to the frequent mismatch between the initial reservoir model, the true reservoir geology, and the pre-production (baseline) seismic data. A fundamental step of a reservoir characterisation and performance study is the preconditioning of the initial reservoir model to equally honour both the geological knowledge and seismic data. In this paper we analyse the issues that have a significant impact on the (mis)match of the initial reservoir model with well logs and inverted 3D seismic data. These issues include the constraining methods for reservoir lithofacies modelling, the sensitivity of the results to the presence of realistic resolution and noise in the seismic data, the geostatistical modelling parameters, and the uncertainties associated with quantitative incorporation of inverted seismic data in reservoir lithofacies modelling. We demonstrate that in a geostatistical lithofacies simulation process, seismic constraining methods based on seismic litho-probability curves and seismic litho-probability cubes yield the best match to the reference model, even when realistic resolution and noise is included in the dataset. In addition, our analyses show that quantitative incorporation of inverted 3D seismic data in static reservoir modelling carries a range of uncertainties and should be cautiously applied in order to minimise the risk of misinterpretation. These uncertainties are due to the limited vertical resolution of the seismic data compared to the scale of the geological heterogeneities, the fundamental instability of the inverse problem, and the non-unique elastic properties of different lithofacies types.

Seismic diffractions play a vital role in identifying discontinuous geological structures, such as tiny faults and cavities which are important because of their close relationship with the reservoir properties of oil and gas. In this paper, we focus on an extraction method for separation of seismic diffractions. The energy of reflection is usually much stronger than that of the diffraction, thus, removing reflection becomes a key problem for diffraction applications. In order to extract seismic diffractions accurately and stably, we propose an optimised regularisation method based on the local plane-wave equation. By considering two constraints arising from the Sobolev penalty function and the difference operator, we build a stable minimisation model for determining seismic slopes. In computation, an iterative method based on projection onto a convex set for solving the nonlinear minimisation is developed, which can provide fast and accurate solutions. Subtracting the predicted reflections from the seismic image, we can extract the seismic diffractions. Numerical experiments illustrate the effectiveness of the diffraction extraction method in separating tiny faults, scatterers and cavities. Finally, a carbonate reservoir field example is provided to demonstrate the high-resolution capability of the method in revealing small-scale discontinuous geological features.

By considering two constraints from the Sobolev penalty function and the difference operator, we have developed an optimised regularisation model for extracting seismic diffractions. An efficient iterative method based on projection onto a convex set has been developed to solve the minimisation problem. The proposed method has high-resolution capability for detecting small-scale discontinuities.

Frequency-dependent seismic responses from a fractured sandstone layer show complex azimuthal variations due to anisotropic propagation and attenuation of transmission waves associated with fluid flow. It would be practical to investigate wavetrains reflected from the fractured layers that are regarded as integrated units.

Azimuthal P-wave amplitude variation with offset (AVO) offers a method for the characterisation of a naturally fractured system in a reservoir. This information is important for the analysis of fluid flow during production of, for example, oil, petroleum and natural gas. This paper provides a modelling scheme by incorporating the squirt-flow model for the prediction of velocity dispersion and attenuation with azimuthal reflectivity method for the calculation of frequency-dependent seismic responses. Azimuthal AVO responses from a fractured poroelastic sandstone layer encased within shale are investigated based on the proposed method. Azimuthal reflections are a combination of the dynamic information including the contrast in anisotropic properties, anisotropic propagation and attenuation within the layer, as well as tuning and interferences. Modelling results indicate that seismic responses from the top of the sandstone layer are dominated by reflection coefficients, and show azimuthal variations at far offset which is consistent with conventional azimuthal AVO theory. Reflections from the base, however, demonstrate complex azimuthal variations due to anisotropic propagation and attenuation of transmission waves within the layer. Tuning and interferences further complicate the azimuthal AVO responses for thinner layer thickness. The AVO responses of top reflections show no azimuthal variations for lower fluid mobility, while those of base reflections show visible and stable azimuthal variations even at near and moderate offsets for different fluid mobility. Results also reveal that it would be practical to investigate wavetrains reflected from the fractured layers that are regarded as integrated units, especially for thinner layers where reflections from the top and base are indistinguishable. In addition, near-offset stacked amplitudes of the reflected wavetrains show detectable azimuthal variations, which may offer an initial look at fracture orientations before AVO analysis.

A method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering is proposed. Magnetic anomaly inversion methods are used to estimate the initial locations of targets. The self-adaptive fuzzy c-means clustering algorithm is then used to cluster these initial locations, giving the number and locations of magnetic targets.

We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.

Absorbing boundary conditions are necessary in numerical simulation for reducing the artificial reflections from model boundaries. In this paper, we overview the most important and typical absorbing boundary conditions developed throughout history. We first derive the wave equations of similar methods in unified forms; then, we compare their absorbing performance via theoretical analyses and numerical experiments. The Higdon boundary condition is shown to be the best one among the three main absorbing boundary conditions that are based on a one-way wave equation. The Clayton and Engquist boundary is a special case of the Higdon boundary but has difficulty in dealing with the corner points in implementaion. The Reynolds boundary does not have this problem but its absorbing performance is the poorest among these three methods. The sponge boundary has difficulties in determining the optimal parameters in advance and too many layers are required to achieve a good enough absorbing performance. The hybrid absorbing boundary condition (hybrid ABC) has a better absorbing performance than the Higdon boundary does; however, it is still less efficient for absorbing nearly grazing waves since it is based on the one-way wave equation. In contrast, the perfectly matched layer (PML) can perform much better using a few layers. For example, the 10-layer PML would perform well for absorbing most reflected waves except the nearly grazing incident waves. The 20-layer PML is suggested for most practical applications. For nearly grazing incident waves, convolutional PML shows superiority over the PML when the source is close to the boundary for large-scale models. The Higdon boundary and hybrid ABC are preferred when the computational cost is high and high-level absorbing performance is not required, such as migration and migration velocity analyses, since they are not as sensitive to the amplitude errors as the full waveform inversion.

We provide a thorough review of all typical absorbing boundary conditions and derive their equations in a uniform mathematical form. We examine their performance via numerical experiments and qualitatively show their advantages and disadvantages. Finally, we provide some suggestions on choosing different boundary conditions for practical applications.