Exploration Geophysics - Volume 50, Issue 2, 2019

Full waveform inversion (FWI) using passive seismic data can use amplitude, phase and travel time information from the data simultaneously. However, at least three challenges are involved in passive seismic full waveform inversion (PSFWI): a low signal-to-noise ratio (SNR), source location uncertainty and an unknown source wavelet. In this study, we propose a method that combines seismic interferometry and a source-independent inversion algorithm to solve these problems. Using seismic interferometry, the original passive seismic data recorded on the surface can be reconstructed into new virtual source records that have a relatively high SNR and certain source location. The source-independent algorithm eliminates the influence of source wavelet error on the final inversion results. Through numerical tests, we discuss the effects of passive source number and recording time on the inversion results and find that increasing the source number or recording time can improve inversion quality. We extract the background velocity model from the results of PSFWI and use it as the initial model of active source FWI. Least square reverse time migration (LSRTM) is then conducted to verify the accuracy of the inverted velocity models. The final results demonstrate that our PSFWI method can construct accurate long-wavelength velocity structures for subsequent active source FWI. The velocity model constructed using our successive inversion strategy can improve the LSRTM results.

The response spectra of the 20 Gyeongju earthquake series, including the main earthquake (12 September 2016; ML = 5.8), were compared with the design response spectra (Regulatory Guide 1.60, 1973; United States Nuclear Regulatory Commission) for Korean nuclear power plants and the Korean Building Code (KBC) of 2016 for general structures and buildings. A total of 720 horizontal and vertical accelerations were used to derive the response spectra after normalisation by reference to peak ground acceleration. The horizontal and vertical response spectra were strongly dependent on the epicentral distance and the resonance frequency. When developing design response spectra, it is necessary to consider distances >200 km from the epicenter, given the strong dependence of the response on distance. The vertical responses were consistently lower than the horizontal responses, in good agreement with the various existing seismic design standards and empirical rules. It is essential to develop site-specific seismic design standards, reflecting local seismotectonic environments. Such efforts require large amounts of data covering earthquakes of various magnitudes in the Korean Peninsula and surrounding areas, and such standards should replace Regulatory Guide 1.60. In terms of the KBC 2016, it is necessary to make the criteria more conservative in the short periods, and then to create comprehensive design response spectra by referencing large amounts of qualitative data from the region around the Korean Peninsula on earthquakes of various magnitudes and their effects at different distances from the epicenter.

This paper presents a first-arrival tomography incorporating a fast sweeping method (FSM) solving the factored eikonal equation (factored FSM). The traveltime calculation method plays a significant role in velocity inversion. However, for a point source condition, all finite-difference based eikonal solvers suffer from the source singularity problem. Numerical error caused by source singularity will propagate from the source to all computational domains, and makes traveltimes inaccurate. A FSM solving the factored eikonal equation can deal with the source singularity problem very well. Therefore, a first-arrival tomography is developed by incorporating 2D and 3D factored FSMs to provide more accurate traveltimes in velocity inversion. For comparison, an open source package PStomo_eq is used to invert the same data set. It incorporates the traveltime calculation algorithms fdtime2d.c and fdtime3d.c. Traveltime accuracy tests show that factored FSM can generate more accurate traveltimes than FSM, fdtime2d.c and fdtime3d.c. Numerical and field data tests show that inversion with factored FSM can acquire much better tomograms than inversion with fdtime2d.c and fdtime3d.c. Therefore, it is worthwhile using a more accurate traveltime computation method in velocity inversion.

Epicentral distance can be estimated from growth of the initial P-waves in real time, and this estimation is used in the earthquake early-warning system in Japan, especially for railways. This estimation is based on the relationship between the growing initial P-waves and epicentral distance. The initial P-waves grow gradually with increasing distance from the epicentre because geometrical spreading, scattering and intrinsic attenuation blunt their shape. Therefore, the growing form of the initial P-waves can be used to estimate the epicentral distance. However, in practice, the relationship is not uniform and the growth curves (i.e. gradient) are not a perfect function of epicentral distance. Therefore, the epicentral distance estimated from the initial P-waves involves significant uncertainty, which decreases the accuracy of the early-warning system for strong motions. In this study, we examined the causes of error in this relationship using theoretical calculations based on the Born approximation, which indicate that the growth curves of the P-waves fluctuate due to regionally different heterogeneous conditions in the subsurface medium. Therefore, we propose a robust relationship between the initial P-waves and epicentral distance considering regional heterogeneous conditions by analysing real earthquakes (magnitude 4–5) in Japan.

Acoustic reflection logging while drilling (LWD) measurement has overwhelming advantages in detecting reflectors outside the borehole, making it a prominent technology in geosteering during LWD operations. This paper carries out a comprehensive numerical investigation into the acoustic reflection logging responses in LWD environments by combining the analytical real axis integration (RAI) solution and an exquisitely improved finite difference method (FDM). Mutual validation of these two methods using typical and well-known cases ensures the reliability of the modelling methodology. Numerical studies on LWD and wireline acoustic reflection logging reveal that a ring source rather than four azimuthally orthogonal point sources can excite acoustic LWD monopole waves without interference from higher order wave modes. Lower order spatial differential operators are more efficient for FDM simulations of LWD cases when variance in the medium is obvious. Compared with the wireline monopole case, LWD monopole reflection acoustic logging can obtain higher quality reflected waves and has a superior ability to identify the azimuth of a geological reflector away from the borehole.

Geoscientists have always sought various approaches to improve reservoir characterisation by compartmentalising the depth interval into subsections with the highest consistency in pore throat size and distribution. Hydraulic flow units have demonstrated success in segmenting the depth interval of interest into subsections with distinguishable rock and fluid properties. At the primary stage, flow zone indicator values are calculated from core data within the reservoir of interest. A flow zone indicator is an acceptably unique measurement of the flow character of a reservoir interval, giving the relationship between petrophysical properties at the pore scale, like tortuosity and surface area, and the formation scale, say porosity and permeability. The next step segments the reservoir into more accurately delineated depth intervals, or hydraulic flow units. Several statistical approaches have been used successfully to group data into subsections of high similarity and consistency, herein referred to as hydraulic flow units. In this paper, a robust method was proposed for the prediction of flow zone indicators in uncored wells, which may lead to advances in reservoir management, saving a considerable amount of revenue merely by accurately predicting depth interval flow properties without the need for expensive coring operations. The results of this study show that adaptive neuro-fuzzy inference systems can be used with higher levels of confidence to model the unknown, but invaluable, data in uncored but logged wells. The results of this study proved the success of machine-learning approaches in identifying underlying trends and relationships within the data, as well as predicting unknown properties based on training data validated by blind test data. This study shows that soft computing and machine-learning approaches can be used to prognosticate the underlying hydraulic flow units based on well log responses in carbonate reservoirs.

This paper describes an algorithm for estimating the direction of source magnetisation with acceptable accuracy through comparison of pseudogravity and total gradient data. In this algorithm, the location of the horizontal centroid of a magnetic source should first be identified (from the extrema of the total gradient or by any other method), the direction of source magnetisation is then modified until the pseudogravity data (produced from windowed magnetic data over the magnetic source) peak directly over the estimated location of the horizontal centroid of the magnetic source. That direction is the estimated direction of magnetisation of the magnetic source.

In this paper, the applicability of ground-based synthetic aperture radar (GB-SAR) as an early warning system for landslide monitoring is discussed. The effectiveness of the differential interferometric SAR (DInSAR) technique used in GB-SAR depends strongly on the geography of the monitored location. Therefore, an assessment of the system compatibility to select the most appropriate remote monitoring method is essential prior to any hardware implementation. In the preliminary part of this study, a 3D model was created using a LiDAR survey, and proposed locations for GB-SAR installation were examined. A 3D simulation was carried out to estimate the illumination from each of the proposed GB-SAR locations. The proposed model increased the efficiency of the GB-SAR positioning by minimising installation cost and time. Hardware configuration parameters, such as platform height, maximum range, and the direction and view angle of the radar line of sight were estimated by considering the optimum reflected power and ground illumination. Unlike on flat terrain, deployment of GB-SAR in a mountainous area is challenging because of surface anomalies and continuous changes in meteorological parameters, such as atmospheric temperature, pressure and relative humidity. In this study, the experimental site was located 3 km from the Aso volcano, and the weather conditions in the Aso caldera became a critical factor in accurately estimating the interferometric phase. The presence of atmospheric artefacts also compromises the applicability of the classical DInSAR technique. Here, we minimised the atmospheric phase screen by estimating the optimum data acquisition interval from GB-SAR monitoring under extreme weather conditions. The developed methodologies were then used to design a new landslide early warning system that measures real-time displacement over an area of 1 km² within 10 s of scanning. This fully automatic monitoring system updates every 15 min and presents displacement information in a 3D interface. The system we have developed has been deployed for continuous monitoring of the mountainous environment of a road reconstruction site in Minami-Aso, Kumamoto, Japan where a large-scale landslide was triggered following the Kumamoto earthquake in 2016.