Improved target illumination at Ludvika mines of Sweden through seismic-interferometric surface-wave suppression

In mineral exploration, new methods to improve the delineation of ore deposits at depth are in demand. For this purpose, increasing the signal-to-noise ratio through suitable data processing is an important requirement. Seismic reflection methods have proven to be useful to image mineral deposits. However, in most hard rock environments, surface waves constitute the most undesirable source-generated or ambient noise in the data that, especially given their typical broadband nature, often mask the events of interest like body-wave reflections and diffractions. In this study, we show the efficacy of a two-step procedure to suppress surface waves in an active-source reflection seismic dataset acquired in the Ludvika mining area of Sweden. First, we use seismic interferometry to estimate the surface-wave energy between receivers, given that they are the most energetic arrivals in the dataset. Second, we adaptively subtract the retrieved surface waves from the original shot gathers, checking the quality of the unveiled reflections. We see that several reflections, judged to be from the mineralization zone, are enhanced and better visualized after this two-step procedure. Our comparison with results from frequency-wavenumber filtering verifies the effectiveness of our scheme, since the presence of linear artefacts is reduced. The results are encouraging, as they open up new possibilities for denoising hard rock seismic data and, in particular, for imaging of deep mineral deposits using seismic reflections. This approach is purely data driven and does not require significant judgment on the dip and frequency content of present surface waves, which often vary from place to place.     

Delineation of riparian vegetation from Landsat multi‐temporal imagery using PCA

A deficiency in crucial digital data, such as vegetation cover, in remote regions is a challenging issue for water management and planning, especially for areas undergoing rapid development, such as mining in the Pilbara, Western Australia. This is particularly relevant to riparian vegetation, which provides important ecological services and, as such, requires regional protection. The objective of this research was to develop an approach to riparian vegetation mapping at a regional scale using remotely sensed data. The proposed method was based on principal component analysis applied to multi‐temporal Normalized Difference Vegetation Index datasets derived from Landsat TM 5 imagery. To delimit the spatial extent of riparian vegetation, a thresholding method was required and various thresholding algorithms were tested. The accuracy of results was estimated for various Normalized Difference Vegetation Index multi‐temporal datasets using available ground‐truth data. The combination of a 14‐dry‐date dataset and Kittler's thresholding method provided the most accurate delineation of riparian vegetation.     

Roadheader performance prediction using genetic programming (GP) and gene expression programming (GEP) techniques

Roadheading machines play a vital role in excavation operation in tunneling and mining industries notably when selective mining is required. Roadheaders are more effective in soft to medium rock formations due to a higher cutting rate in such strata. A precise prediction of machine’s performance is a crucial issue, as it has considerable effects on excavation planning, project’s cost estimation, machine specification selection as well as safety of the project. In this research, a database of machine performance and some geomechanical parameters of rock formations from Tabas coal mine project, the largest and fully mechanized coal mine in Iran, has been established, including instantaneous cutting rate (ICR), uniaxial compressive strength, Brazilian tensile strength, rock quality designation, influence of discontinuity orientation (Alpha angle) and specific energy. Afterward, the parameters were analyzed through genetic programming (GP) and gene expression programming (GEP) approaches to yield more accurate models to predict the performance of roadheaders. As statistical indices, coefficient of determination, root mean square error and variance account were used to evaluate the efficiency of the developed models. According to the obtained results, it was observed that developed models can effectively be implemented for prediction of roadheader performance. Moreover, it was concluded that performance of the GEP model is better than the GP model. A high conformity was observed between predicted and measured roadheader ICR for GEP model.     

Robust Automatic Reduction of Multibeam Bathymetric Data Based on M-estimators

Multibeam echosounders have commonly been employed for a wide range of applications including offshore survey, navigation, hydrogeology, and oceanography. Because the tremendous volume of the bathymetric data is demanding for some purposes and requires significant storage space, the data reduction plays a prominent role in practice. Additionally, the multibeam soundings are inevitably contaminated with sporadic outliers, and as such, the data cleaning can be challenging especially in shallow waters. We present a speedily robust method for reliably reducing the volume of the bathymetric data within grid cells. In this respect, robust M-estimators are recursively applied to the data in a patch-wise manner to alleviate the undesirable effects of the outlying observations. Accordingly, the reduced bathymetry is automatically made unaffected by the possible outliers once their equivalent weights have been downweighted. The performance of the presented method has been demonstrated by synthetic datasets and an experimental dataset collected by an ATLAS FS 20/100 kHz shallow-water multibeam echosounder in the offshore waters of Kish wharf. The reliability, efficiency, and capability of the proposed method have been verified, which makes it quite possible to meet the IHO requirements for special-order seafloor mapping.     

The effects of hydrometer reading times on the spatial variability of soil textures in southeast Iran

Soil texture is an important physical soil property that may contribute to variations in many soil functions as well as nutrient storage and availability, water retention, and soil erosion. Although several methods for determining the texture classes of soil particles have been proposed, differences among hydrometer reading times have presented challenges in determining the precise soil texture classes. Therefore, this study was conducted to evaluate the effects of hydrometer reading time on the spatial variability of soil textures in the Rafsanjan area, southeast Iran. To accomplish this, 77 soil samples were collected on a 500-m square sampling grid from depths of 0–40, 40–80, and 80–120 cm, and their particle sizes were determined through analysis for 40 s, 2 h, 6.5 h, and 8 h using the Bouyoucos hydrometer method. The results showed a strong spatial correlation in the soil particles among sampling soil layers and across the study area. Moreover, the differences among hydrometer reading times did not have a significant impact on determination of coarse soil texture classes, although they did influence determination of the finer classes. Although the 8 h reading time provided the most accurate response with respect to mechanical analysis of a soil, after 6.5 h the hydrometer could also largely (more than 80.0 %, on average) achieve this goal. Additionally, the 2 h hydrometer reading time could also be useful for the initial assessment or general overview of the soil texture in a certain region; however, it is not recommended for precision agriculture or site-specific management.     

Paleopedology and magnetic properties of Sari loess-paleosol sequence in Caspian lowland,northern Iran

The objective of this study was to characterize the morphological and magnetic properties of Sari loess-paleosol section in northern Iran for paleopedologic and paleoenvironmental interpretation. The section consisted of a modern soil(MS) and three paleosols(PS_1, PS_2, PS_3) separated by loess layers(LS_1, LS_2 and LS_3). Based on particle size distribution, clay mineralogy, carbonates distribution and size of secondary carbonates, pedogenic development of the soils was in order of PS_3PS_2PS_1=MS. Presence of redoximorphic features in PS_3 was attributed to alternate stagnic saturation due to local water or high precipitation. Dominance of smectite and vermiculite as well as large carbonated dolls in PS_3 indicated suitable environment and sufficient time for pedogenic development. Magnetic properties(χ~(lf) and χ~(fd)%) were distinctly higher in MS, PS_1 and PS_2 when compared to loess layers. The Lowest magnetic properties values were observed in PS_3 which can be the result of ferrimagnetic minerals destruction under hydromorphic conditions. The highest Fe_d content occurred in PS_3, however, low χ~(lf)/Fe_d ratio indicated that majority of the iron minerals in PS_3 are not magnetic. In conclusion, the particle size distribution, clay mineralogy and carbonates features were indicative of pedogenesis intensity, whereas, magnetic properties were useful to characterize the pedogenic environment.     

Ellipsoidal Neumann geodetic boundary-value problem based on surface gravity disturbances: case study of Iran

An ellipsoidal Neumann type geodetic boundary-value problem (GBVP) for the computation of disturbing potential on the surface of the Earth based on the surface gravity disturbance as the boundary data is formulated. The solution methodology of the GBVP can be algorithmically summarized as follows: (i) using global navigation satellite systems (GNSS) coordinates of the gravity stations, the surface gravity disturbances are generated as the boundary data. (ii) Applying the deflection correction to the gravity disturbances to arrive at the derivative of the surface disturbing potential along the ellipsoidal normal. (iii) Removing the low frequencies part of the gravity field using harmonic expansion to degree and order 110. (iv) Using the short wavelength part of the corrected gravity disturbances derived in the previous section as the boundary data within the constructed GBVP to derive the short wavelength disturbing potential over the Earth surface. (v) The computed shortwave length signals of disturbing potentials are converted to disturbing potential values by restoring the removed effects.     

Hydrocarbon Vertical Continuity Evaluation in the Cretaceous Reservoirs of Azadegan Oilfield,Southwest of Iran: Implications for Reservoir Geochemistry

A collection of data obtained from analytical methods in geochemistry along with the reservoir engineering and geologic data were used to investigate the reservoir continuity in the Cretaceous Fahliyan, Gadavan, Kazhdumi and Sarvak reservoirs of the super-giant Azadegan oilfield, SW Iran. The geochemical data indicate that the oil samples, with medium to high level of thermal maturity, have been generated from the anoxic marine marl/carbonate source rock(s). The Sargelu(Jurassic) and Garau(Creta...     

Comparison of conventional and Monte Carlo simulation-based probabilistic seismic hazard analyses for Shiraz city,southern Iran

Estimation of ground-motion amplitudes of different hazard levels is of paramount importance in planning of urban development of any metropolis. Such estimation can be computed through a probabilistic seismic hazard analysis (PSHA). This paper concentrates on the PSHA of an area located in Shiraz city, southern Iran. The area includes whole of Shiraz city (i.e., one of the largest and most populous cities of Iran) and its outskirts. Conventional and Monte Carlo simulation-based approaches are utilized to perform the PSHA of the studied area. Two areal seismic source models are delineated, and thence seismicity parameters of all zones associated with their corresponding uncertainties are computed. Uncertainties in ground-motion prediction are accounted for via three ground-motion prediction equations (GMPEs) within the logic tree framework. These GMPEs are applied to estimate bedrock ground shaking (V_s30?=?760 m/s) for several return periods (i.e., 75, 475, 975, and 2475 years). In general, the results of the two abovementioned PSHA approaches show relatively similar results. However, the Monte Carlo simulation-based approach overpredicts bedrock spectral accelerations at periods of 0.4–2.5 s compared to the conventional PSHA approach for return periods of 475, 975, and 2475 years.