Exploration Geophysics - Volume 47, Issue 2, 2016

A new zero-cost method of correcting static shift in magnetotelluric data is proposed based on 3D forward modelling and field tests. The method has been verified using synthetic and real data.

To solve the problem of correction of magnetotelluric (MT) static shift, we quantise factors that influence geological environments and observation conditions and study MT static shift according to 3D MT numerical forward modelling and field tests with real data collection. We find that static shift distortions affect both the apparent resistivity and the impedance phase. The distortion results are also related to the frequency. On the basis of synthetic and real data analysis, we propose the concept of generalised static shift resistivity (GSSR) and a new method for correcting MT static shift. The approach is verified by studying 2D inversion models using synthetic and real data.

We have conducted the first application of wavelet-based denoising techniques for processing raw TDIP data. Our investigation included laboratory and field measurements to better understand the advantages and limitations of these techniques. It was found that distortions arising from conventional filtering can be significantly avoided with wavelet-based methods.

Time-domain induced polarisation (TDIP) methods are routinely used for near-surface evaluations in quasi-urban environments harbouring networks of buried civil infrastructure. A conventional technique for improving signal to noise ratio in such environments is by using analogue or digital low-pass filtering followed by stacking and rectification. However, this induces large distortions in the processed data. In this study, we have conducted the first application of wavelet based denoising techniques for processing raw TDIP data. Our investigation included laboratory and field measurements to better understand the advantages and limitations of this technique. It was found that distortions arising from conventional filtering can be significantly avoided with the use of wavelet based denoising techniques. With recent advances in full-waveform acquisition and analysis, incorporation of wavelet denoising techniques can further enhance surveying capabilities. In this work, we present the rationale for utilising wavelet denoising methods and discuss some important implications, which can positively influence TDIP methods.

Microtremors were analysed using the H/H and H/V methods to estimate site effects of the Cheongcheon earthen dam in Korea. The peak near 3 Hz may correspond to depth to the bedrock, whereas the other peaks at higher frequencies may reflect the geometrical effect of the dam or overtone responses.

Microtremors were analysed using the reference-dependent horizontal spectral (H/H) method and the horizontal-to-vertical spectral ratio (H/V) method to estimate site effects of the Cheongcheon earthen dam in Korea. Seismic vibrations were recorded on the dam’s crest, at the toe of the dam, and in a downstream borehole using three-component accelerometers. The H/H peaks for crest versus toe-of-dam accelerations occurred at 3.1, 6.7 and 13.1 Hz with ratios of 6.9, 11.4 and 8.9, respectively. The H/V peaks for the crest of the dam occurred at 3.0, 7.0 and 13.4 Hz with ratios of 6.7, 7.8 and 5.6, respectively. The peak near 3 Hz may correspond to depth to bedrock, whereas the other peaks at higher frequencies may reflect the geometrical effect of the dam or overtone responses to the thickness of dam fill overlying the clay core. For the toe data, from the H/V spectral ratio method, the basement boundary appeared as double peaks near 8 and 10 Hz with corresponding amplification factors of 5.2 and 6.2. These may indicate a gradual change in velocity across the basement boundary at ~10 m depth. The third resonance, which occurred at 15 Hz, may correlate with the refraction boundary at 5–6 m depth in the overburden layer. Both the frequencies and magnitudes of resonance derived from the H/H and H/V methods are reasonably well matched to the theoretical response curves computed by the reflection and transmission matrix and the two-dimensional finite difference methods.

We use seismic interferometry to process ambient noise recorded in measurement lines. The Rayleigh wave component of the Green’s Functions is obtained with a high S/N ratio. Using CMPCC analysis, we can identify lateral variations of phase velocity inside the seismic line with higher resolution compared to conventional analysis.

Determination of the shear-wave velocity structure at shallow depths is a constant necessity in engineering or environmental projects. Given the sensitivity of Rayleigh waves to shear-wave velocity, subsoil structure exploration using surface waves is frequently used. Methods such as the spectral analysis of surface waves (SASW) or multi-channel analysis of surface waves (MASW) determine phase velocity dispersion from surface waves generated by an active source recorded on a line of geophones. Using MASW, it is important that the receiver array be as long as possible to increase the precision at low frequencies. However, this implies that possible lateral variations are discarded. Hayashi and Suzuki (2004) proposed a different way of stacking shot gathers to increase lateral resolution. They combined strategies used in MASW with the common mid-point (CMP) summation currently used in reflection seismology. In their common mid-point with cross-correlation method (CMPCC), they cross-correlate traces sharing CMP locations before determining phase velocity dispersion. Another recent approach to subsoil structure exploration is based on seismic interferometry. It has been shown that cross-correlation of a diffuse field, such as seismic noise, allows the estimation of the Green’s Function between two receivers. Thus, a virtual-source seismic section may be constructed from the cross-correlation of seismic noise records obtained in a line of receivers.

In this paper, we use the seismic interferometry method to process seismic noise records obtained in seismic refraction lines of 24 geophones, and analyse the results using CMPCC to increase the lateral resolution of the results. Cross-correlation of the noise records allows reconstructing seismic sections with virtual sources at each receiver location. The Rayleigh wave component of the Green’s Functions is obtained with a high signal-to-noise ratio. Using CMPCC analysis of the virtual-source seismic lines, we are able to identify lateral variations of phase velocity inside the seismic line, and increase the lateral resolution compared with results of conventional analysis.

In this paper, I describe a new technique to determine the interval between P-waves in similar, overlapping microseismic events. The similar microseismic events that occur with overlapping waveforms are called ‘proximate microseismic doublets’ herein. Proximate microseismic doublets had been discarded in previous studies because we had not noticed their usefulness. Analysis of similar events can show relative locations of sources between them. Analysis of proximate microseismic doublets can provide more precise relative source locations because variation in the velocity structure has little influence on their relative travel times. It is necessary to measure the interval between the P-waves in the proximate microseismic doublets to determine their relative source locations.

A ‘proximate microseismic doublet’ is a pair of microseismic events in which the second event arrives before the attenuation of the first event. Cepstrum analysis can provide the interval even though the second event overlaps the first event. However, a cepstrum of a proximate microseismic doublet generally has two peaks, one representing the interval between the arrivals of the two P-waves, and the other representing the interval between the arrivals of the two S-waves. It is therefore difficult to determine the peak that represents the P-wave interval from the cepstrum alone. I used window functions in cepstrum analysis to isolate the first and second P-waves and to suppress the second S-wave. I change the length of the window function and calculate the cepstrum for each window length. The result is represented in a three-dimensional contour plot of length–quefrency–cepstrum data. The contour plot allows me to identify the cepstrum peak that represents the P-wave interval. The precise quefrency can be determined from a two-dimensional quefrency–cepstrum graph, provided that the length of the window is appropriately chosen. I have used both synthetic and field data to demonstrate that this method can be used to identify the cepstrum peak that represents the interval between the arrivals of successive P-waves.

This paper describes a cepstrum analysis using window functions to determine the interval between P-waves in similar, overlapping microseismic events. The window functions isolate the two P-waves and suppress the second S-wave. Applications of the method to both synthetic and field data show that it can identify the P-wave interval.

This paper describes the use of binary and multiclass support vector machine models with geophysical log data to estimate the volcanic lithology of the Liaohe Basin in China. A comparison between predicted data and actual data from four wells indicates that binary and multiclass support vector machine models are effective methods for classifying volcanic lithology.

Lithology estimation of rocks, especially volcanic lithology, is one of the major goals of geophysical exploration. In this paper, we propose the use of binary and multiclass support vector machine models with geophysical log data to estimate the volcanic lithology of the Liaohe Basin, China. Using neutron (CNL), density (DEN), acoustic (AC), deep lateral resistivity (RLLD), and gamma-ray (GR) log data from 40 wells (a total of 1200 log data points) in the Liaohe Basin, China, we first construct the binary support vector machine model to classify volcanic rock and non-volcanic rock. Then, we expand the binary model to a multiclass model using the approach of directed acyclic graphs, and construct multiclass models to classify six types of volcanic rocks: basalt, non-compacted basalt, trachyte, non-compacted trachyte, gabbro and diabase. To assess the accuracy of these two models, we compare their predictions with core data from four wells (at 800 different depth points in total). Results indicate that the accuracy of the binary and multiclass models are 98.4% and 87%, respectively, demonstrating that binary and multiclass support vector machine models are effective methods for classifying volcanic lithology.

We present a new method for the inversion of airborne gamma-ray spectrometric line data to a regular grid of radioelement concentration estimates on the ground. The method incorporates the height of the aircraft, the 3D terrain within the field of view of the spectrometer, the directional sensitivity of rectangular detectors, and a source model comprising vertical rectangular prisms with the same horizontal dimensions as the required grid cell size. The top of each prism is a plane surface derived from a best-fit plane to the digital elevation model of the earth’s surface within each grid cell area.

The method is a significant improvement on current methods, and gives superior interpolation between flight lines. It also eliminates terrain effects that would normally remain in the data after the conventional processing of these data assuming a flat-earth model.

A new method is presented for the inversion of airborne gamma-ray spectrometric line data to a regular grid of radioelement concentration estimates on the ground. The method incorporates the height of the aircraft and the topography. It eliminates terrain effects and improves the interpolation between flight lines.

Based on the phase velocity and attenuation propagation velocity, a method for performing numerical dispersion analysis of three-dimensional Laplace-Fourier-domain scalar wave equation is presented. This method is applied to a 27-point average-derivative optimal scheme and a 27-point finite-element scheme. Within the relative error of 1%, the 27-point average-derivative optimal scheme requires seven grid points per wavelength and pseudo-wavelength while the 27-point finite-element scheme requires 23 grid points per wavelength and pseudo-wavelength for equal and unequal directional sampling intervals. Numerical examples show that the 27-point Laplace-Fourier-domain average-derivative optimal scheme is more accurate than the 27-point Laplace-Fourier-domain finite-element scheme for the same computational cost. By using larger directional sampling intervals while maintaining accuracy, the 27-point Laplace-Fourier-domain average-derivative optimal scheme can greatly reduce the computational cost of three-dimensional Laplace-Fourier-domain modelling.

Based on the phase velocity and attenuation propagation velocity, a method for performing numerical dispersion analysis of three-dimensional Laplace-Fourier-domain scalar wave equation is presented. This method is applied to a 27-point average-derivative optimal scheme and a 27-point finite-element scheme.