A practical approach to compensate for diodic effects of PS converted waves

In inhomogeneous media, PS converted waves often suffer from severe diodic effects. The traveltime and amplitude of PS converted waves may be different in the forward and reverse shooting directions, giving rise to different stacking velocities of PS converted waves and velocity ratios. These effects, compounded with the asymmetric raypath of PS converted waves, will further increase the difficulties and costs in processing PS converted-wave data. One common method to solve this problem is to separate a data set into two volumes with different shooting directions (e.g., negative or positive offset directions). Different values of the PS converted-wave velocities are used to process the two data sets separately and the two results are combined in the final stage. The problem with this method is that sometimes it is difficult to correlate the data sets and the final combined result may be degraded. In this paper, we propose a method to overcome this problem and apply this method to a 2D data set for improving the PS converted-wave imaging

Implementation of elastic prestack reverse-time migration using an efficient finite-difference scheme

Elastic reverse-time migration (RTM) can reflect the underground elastic information more comprehensively than single-component P-wave migration. One of the most important requirements of elastic RTM is to solve wave equations. The imaging accuracy and efficiency of RTM depends heavily on the algorithms used for solving wave equations. In this paper, we propose an efficient staggered-grid finite-difference (SFD) scheme based on a sampling approximation method with adaptive variable difference operator lengths to implement elastic prestack RTM. Numerical dispersion analysis and wavefield extrapolation results show that the sampling approximation SFD scheme has greater accuracy than the conventional Taylor-series expansion SFD scheme. We also test the elastic RTM algorithm on theoretical models and a field data set, respectively. Experiments presented demonstrate that elastic RTM using the proposed SFD scheme can generate better images than that using the Taylor-series expansion SFD scheme, particularly for PS images. Furthermore, the application of adaptive variable difference operator lengths can effectively improve the computational efficiency of elastic RTM

The feasibility of compensation for the azimuthal anisotropy of PS-converted waves in HTI media

This paper studies the influence of shear-wave splitting on the azimuthal behaviour of PS converted waves in HTI media. Theoretical analysis and synthetic study show that it is more accurate to separate the fast P-SV1 component from the slow P-SV2 component before compensating for azimuthal anisotropy, especially in water-saturated fractures. NMO corrections to the P-SV1 component in dry and water-saturated models can be improved by the application of the velocity ellipse

Cyclic axial compressive performance of hybrid double-skin tubular square columns

This paper presents an experimental study on the cyclic axial compressive behavior of FRP-concrete-steel hybrid double-skin tubular columns. The square column specimens were cast with an external Fiber Reinforced Polymer jackets, inner steel tube and concrete in between. The height of the columns was 500 mm and the side dimension was 150 mm. The effects of loading scheme, void ratio and diameter-thickness ratio on axial compression behavior were investigated. A total of eight columns were tested under monotonic and cyclic axial compression. The experimental results show that the effect of loading scheme on axial stress-strain envelope curve and the peak load were not significant, and the ultimate state of the square columns subjected to cyclic axial compression was very similar to that of specimens subjected to monotonic axial compression. Besides, compared with void ratio, the diameter-thickness ratio of the inner steel tube has significant influence on the peak load of the columns when subjected to cyclic axial compression

Phase behaviour of P-SV converted waves recorded at the sea-bed

Shear waves recorded at or near the sea-bed, i.e. a water–sediment interface, may suffer from unwanted phase change, which is detrimental to velocity analysis and processing and degrades the quality of the final stacked or migrated image. In this study, this phenomenon is analysed for P-SV converted waves recorded at the sea-bed. Theoretical analysis shows that phase change does not occur if the converted shear waves always maintain raypaths that lie within the critical angle, provided the subsurface layering is horizontal. A phase change that is asymmetric with offset can readily be explained as being due to dipping layers at targets or the dipping sea-bed. This analysis is extended to multiple layers and anisotropic media and shows that the same conclusions hold. The analysis performed on two sets of ocean-bottom-cable seismic data shows that the majority of observations show little evidence of phase change, and occasionally display the asymmetric phase change with offset. This finding underlines the robustness of converted shear waves for imaging the horizontal subsurfaces and sea-bed as all of the offset information may be use

Parallel processing of prestack Kirchhoff time migration on a PC cluster

This paper discusses an approach that implements a parallel processing of 3-D Prestack Kirchhoff Time Migration (PKTM) on a low-cost PC Cluster by using the Message Passing Interface (MPI), and analyses its performance using a real seismic data as examples. The PC Cluster provides a significant acceleration of the migration processing with the exact same image quality. The ratio between the communication time and processing time is a critical indicator for determining the efficiency of the PC Cluster. If the processing time is longer than the communication time, using more CPUs can efficiently reduce the elapsed time. On the contrary, using more CPUs cannot reduce the elapsed time. Appling this approach to the Alba dataset on our PC Cluster up to 15 CPUs, the elapsed time of PKTM is inversely proportional to the number of CPUs used. The elapsed time for migrating a 2-D seismic line is reduced from 15 h using one CPU to 1 h using 15 CPUs. The elapsed time for migrating a 3-D image is reduced from 630 h using one CPU to 42 h using 15 CPUs. Further reduction can be achieved by using more CPUs. However, an optimal CPU number is expected for an application on large PC clusters with hundreds of nodes. Adapting existing algorithms to the cluster environment offers the potential to allow the application of more accurate algorithms for PKTM to construct a more accurate image. This work has proven that the PC Cluster is a powerful and scalable computing resource for oil and gas exploration organizations

Automatic picking of seismic arrivals in local earthquake data using an artificial neural network

A preliminary study is performed to test the ability of an artificial neural network (ANN) to detect and pick seismic arrivals from local earthquake data. This is achieved using three-component recordings by utilizing the vector modulus of these seismic records as the network input. A discriminant function, F(t), determined from the output of the trained ANN, is then employed to define the arrival onset. 877 pre-triggered recordings from two stations in a local earthquake network are analysed by an ANN trained with only nine P waves and nine noise segments. The data have a range of magnitudes (ML) from -0.3 to 1.0, and signal-to-noise ratios from 1 to 200. Comparing the results with manual picks, the ANN can accurately detect 93.9 per cent of the P waves and also 90.3 per cent of the S waves with a F(t) threshold set at 0.6 (maximum is 1.0). These statistics do not include false alarms due to other non-seismic signals or unusable records due to excessive noise. In 17.2 per cent of the cases the ANN detected false alarms prior to the event. Determining the onset times by using the local maximum of F(t), we find that 75.4 per cent of the P-wave estimates and 66.7 per cent of the S-wave estimates are within one sample increment (10 ms) of the reference data picked manually. Only 7.7 per cent of the P-wave estimates and 11.8 per cent of the S-wave estimates are inaccurate by more than five sample increments (50 ms). The majority of these records have distinct local P and S waves. The ANN also works for seismograms with low signal-to-noise ratios, where visual examination is difficult. The examples show the adaptive nature of the ANN, and that its ability to pick may be improved by adding or adjusting the training data. The ANN has potential as a tool to pick arrivals automatically. This algorithm has been adopted as a component in the early stages of our development of an automated subsystem to analyse local earthquake data. Further potential applications for the neural network include editing of poor traces (before present algorithm) and rejection of false alarms (after this present algorithm)