Exploration Geophysics - Volume 50, Issue 3, 2019

The main goal of this research was to develop a simple method to observe the effects of electromagnetic induction in conductors proximal to drillholes at the Pyhäsalmi volcanogenic massive sulphide (VMS) copper − zinc deposit located in central Finland, using electromagnetic fields generated by electrical power lines (50 Hz). The idea is that the mine geologist could interpret the 50 Hz measurements from several holes and infer the boundaries between rock types based on rock samples and the 50 Hz measurements. Three-component dB/dt coils were used to measure the time derivatives of the total electromagnetic field in deep drillholes. Thus, the primary field was present while taking measurements, or the induced field was not separated from the inducing field. Time-domain data were transformed to the frequency domain and three components (x, y, z) of the total 50 Hz magnetic field were extracted. The electromagnetic field down drillholes indicates anomalies, although the difference between the primary and secondary fields is difficult to distinguish. We compared the results of the power line method with those measured using the time- and frequency-domain electromagnetic methods. According to spatial variations in the total field profiles, a strong correlation with electromagnetic data from controlled source methods was observed. The results demonstrate that the electromagnetic field generated by the primary field of power lines in an active mining area can be used to identify conductive targets in the area.

Seismic wavelet estimation is the bedrock of seismic-well tying and seismic inversion but remains a challenge. Huge amounts of effort have been expended on seismic wavelet estimation and determining the amplitude and phase spectrum is a time-consuming task. In this article, we develop a workflow to determine automatically the constant phase of an estimated wavelet. This workflow begins with statistical wavelet estimation and seismic-well tying. We then extract a new seismic wavelet with a constant phase by using the well and seismic data together. To obtain the best phase for the extracted wavelet using well and seismic data, we rotate the phase of the wavelet by a user-defined increment and perform automatic seismic-well tying for each phase-rotated wavelet. The phase that reaches the maximum correlation coefficient between the synthetic and seismic data is regarded as the best phase for wavelets in each iteration. We next update the time–depth relation using the best seismic-well tie (the maximum correlation coefficient). We repeat the wavelet estimation using well and seismic data, phase rotation, automatic seismic-well tying and time–depth updating until the difference between wavelets, and time–depth relationships, in the current and previous iterations is below a user-defined threshold.

We applied advanced surface wave analysis for multichannel and multishot seismic data to estimate S-wave velocity structure with high lateral resolution. Although a horizontally layered structure is typically assumed in surface wave analysis, this assumption might be violated in environments such as geothermal fields because of their heterogeneous geological formation. The lateral variation of phase velocity can be effectively estimated with common midpoint (CMP) cross-correlation (CMPCC) analysis. In this study, we introduced two additional approaches into the CMPCC analysis workflow, to further improve lateral resolution of phase velocity estimates. One approach is window-controlled CMPCC analysis, which applies a spatial window for the CMP gathers while maintaining the accuracy of the phase velocity estimates. In this analysis, we found that it is difficult to improve phase velocity estimates at lower frequencies, as a wider spatial window must be kept to maintain the accuracy of the dispersion curve. Therefore, we introduced another approach in which we consider the direction of surface wave propagation from sources to receivers. Selection of cross-correlations based on source–CMP direction provides a significant improvement in dispersion curve resolution in the presence of lateral velocity variations, for a wide frequency range. We applied direction-controlled CMPCC analysis to seismic data acquired in the Yamagawa geothermal field, Kyushu Island, southwest Japan, and obtained dispersion curves in the heterogeneous geological setting. We then obtained S-wave velocity profiles by applying genetic algorithm inversion to the dispersion curves. The S-wave velocity profiles in the geothermal field resolve shallow and local heterogeneous structures (e.g. volcanic ash, pumice and igneous intrusions) that cannot be identified on reflection seismic profiles.

Multi-attribute analysis of multi-component seismic data can provide abundant information on seismic hydrocarbon reservoirs. It can exploit the different responses of compressional and shear waves to the reservoir, in conjunction with colour blending and fusion technology applied to seismic images, to enable the human eye to better discriminate features in seismic data, thereby improving the accuracy of reservoir characterisation. The integration of multi-component data and sophisticated visualisation techniques helps to reduce the number of possible models of the reservoir. Thus, we designed a reservoir prediction method based on unsupervised learning and colour feature blending. First, a large number of compressional and shear wave seismic attributes were extracted using cluster analysis to conduct unsupervised learning to optimise the attributes. Then, using the different responses of compressional and shear waves to oil and gas, and an understanding of rock physics, three types of composite attribute were constructed to highlight oil and gas anomalies by multi-component seismic attributes. Finally, the three composite attributes were transformed to the colour space by a first-order linear transformation and RGB colour blending. Applying this scheme to reservoir prediction shows that unsupervised learning and colour blending techniques could help the human eye perceive geological anomalies, highlight common hydrocarbon characteristics, reduce differences and decrease interpretation ambiguity. The prediction results are essentially consistent with actual data and can be used to predict favourable exploration areas.

The data sources used in microseismic locating include mainly the arrival time or waveform (wavefield value) in the microseismic record, and the algorithms used are mainly inversion or reverse time imaging. In terms of data source and algorithm, previously available methods generally fall into three categories: travel time inversion, waveform inversion, and reverse time imaging based on the wavefield. In this study, we propose a new reverse imaging method based on travel time. Starting with time invariance, we use the travel time of the back-propagated wavefield as a data source for imaging source location. We calculate the travel times from one receiver to all grid points directly rather than pick arrival times, and refer to this as the reverse travel time field (RTTF). The method of using the RTTFs of all receivers for imaging is called reverse travel time imaging (RTTI). RTTI images the whole research area and so overcomes the problem of a local minimum in travel time inversion. RTTI pre-prepares RTTF and there is no need to calculate travel time during imaging, which helps maintain the high computational efficiency as travel time inversion. The effectiveness, adaptability and resistance to some interfering factors in RTTI are tested using 2D acoustic numerical experiments.

To date, studies of elastic reverse time migration (RTM) have undergone much improvement, but mainly focus on isotropic media. Because anisotropic media is widespread, it is necessary to explore the application of elastic RTM in anisotropic media. We extend the wavefield decomposition method, which is based on decoupled propagation, and three vector imaging conditions to transversely isotropic media with vertical symmetry isotropy (VTI). Two of the imaging conditions are based on the excitation amplitude (EA) and the third is based on source-normalized cross-correlation. First, the wavefield decomposition method is extended to VTI media. This is then tested in a two-layer model. The results show that this extension cannot decompose P- and S-waves perfectly in VTI media; some weak residuals remain. However, the results of a simple model test show that no obvious crosstalk is generated by these weak residuals. Finally, a Hess VTI model is adopted to test the adaptive use of this method in complex media. Many subsurface structures can be clearly recognized in the migrated result, for example, the high-velocity rock body, a fault and two low-velocity interlayers. Compared with PP images, converted PS images have many merits, such as clearer imaging of the anisotropic body, higher resolution and a wider migration aperture. We conclude that the vector decomposition method and three vector imaging conditions can be applied to prestack elastic RTM for VTI media and satisfactory results obtained.

As part of the Natural Sciences and Engineering Research Council of Canada–Canada Mining Innovation Council (NSERC-CMIC) Mineral Exploration Footprints project, three selected magnetic inversion programs (VPmg, MAG3D and VINV) were used to process the same aeromagnetic data set from the Highland Valley Copper district, British Columbia, Canada. In each case, the inversion was constrained using available geological and physical property constraints. Analysis of magnetic susceptibility data suggests that the observed aeromagnetic anomaly pattern includes effects associated with boundaries between lithological units and fault zone alteration resulting from removal of magnetite. Susceptibility contrast associated with alteration is greater than that associated with changes in lithology. The inversions seek to define the three-dimensional geometry of geological boundaries and the fractures are treated as high-frequency noise. Results from the three programs, although similar, are sensitive to attributes of the different algorithms. VPmg emphasises physical boundaries between geological domains, MAG3D produces a more blurred image, whereas VINV produces reasonable geological images. Computer performance using the different programs ranges from reasonable for VPmg to computer intensive for MAG3D and VINV. Differences in the results reflect the inherent uncertainty in producing inversions from “noisy” aeromagnetic data.

Using the stress–strain oscillation method, we conducted experiments on a sandstone over a frequency range of 1–100 Hz at a differential pressure of 5 MPa to investigate the effects of oil saturation and oil/water substitution on modulus dispersion and attenuation. We first saturated the sandstone with a low viscosity oil (2#) at different saturation degrees, then replaced the 2# oil with a more viscous oil (68#) and finally injected distilled water in the oil-saturated sample. Young’s modulus, Poisson’s ratio and extensional attenuation were measured during these saturation processes. The measured moduli of this sandstone, when saturated with the 2# oil at different saturation degrees (0% to 100%) or when fully saturated with the 68# oil, manifest little dispersion over the frequency range of 1–100 Hz, and low attenuation was observed. The measured bulk modulus for the oil-saturated sandstone agrees well with the prediction of Gassmann’s fluid-substitution theory, suggesting that wave-induced fluid flow (WIFF) plays an insignificant role in control of the bulk modulus when the sandstone is filled with oil. However, as oil saturation and viscosity increase, the shear modulus keeps increasing, violating the Gassmann’s fluid-substitution theory, which may be caused by the viscous coupling mechanism. When water was injected into sandstone fully saturated with the 68# oil, distinct modulus dispersion and attenuation were observed. The characteristics of the modulus dispersion and attenuation are consistent with mesoscopic WIFF theory, indicating that mesoscopic WIFF is the main cause of modulus dispersion and attenuation for this sandstone saturated with oil–water mixture at seismic frequencies.