Geophysical Prospecting - 7 Special Issue: Mineral Exploration and Mining Geophysics, 2023

Established 2D seismic data processing methods such as Kirchhoff pre‐stack time migration and Kirchhoff pre‐stack depth migration function relatively well for regular acquisition geometries and well‐constrained velocity models. Recently developed focusing pre‐stack depth migration methods have the potential to enhance image quality in the case of sparse and non‐regular source–receiver distribution. We have tested the performance of the coherency migration method as one of these focusing migration approaches in comparison to standard dip‐moveout and Kirchhoff pre‐stack time migration techniques by applying them to the Swayze East seismic profile acquired in the Abitibi greenstone belt of Canada. This seismic profile represents a crooked‐line survey that intersects several metal‐bearing deformation zones, providing good target geometries to examine various pre‐stack migration methods. Analysis of the seismic data indicates reflectivity associated with shallowly dipping reflections appears relatively well preserved over the entire 0–6 km offset range for the frequency range between 20 to 90 Hz. Although most reflections are visible already in either the dip‐moveout or the Kirchhoff pre‐stack time migration results, the coherency migration method delivers the most improved image showing all reflective structures inferred for this area. The comparisons suggest the coherency migration method can be considered as superior in terms of resulting seismic image quality compared with conventional approaches for this type of crooked‐line seismic survey in such a complex geological setting.

Three‐dimensional reflection seismic data from the Neves‐Corvo area, southern Portugal, were reprocessed with the main objective of improving the seismic signature of the Lombador and Semblana volcanogenic massive sulphide deposits. The sensitivity for choosing adequate parameters for targeted imaging, even during the pre‐processing stage, such as common‐depth point binning size, was studied in detail before the main processing work began helping to optimize bin size parameters; preliminary stacking results from this analysis presented severe acquisition footprint, and seismic targets were not clearly identifiable. Processing results using pre‐stack dip move‐out and post‐stack migration methods show strong moderate to steeply dipping reflections. Several of the observed reflections can be correlated with known lithological contacts, some of which are interpreted to originate from the Semblana and Lombador deposits. Despite the mixed signal‐to‐noise ratio, the seismic cube reveals both shallow and deep three‐dimensional structures, allowing to account for the deposits’ lateral extension beyond the capabilities of two‐dimensional seismic imaging alone. Given the data processing approach taken it was possible to distinguish strong diffraction patterns, interpreted as originating from faults and edges of the Lombador deposit, illustrating the usefulness of diffraction patterns for better interpretation of geological features in hard‐rock environments.

Mineral exploration is facing greater challenges nowadays because of the increasing demand for raw materials and the lesser chance of finding large deposits at shallow depths. To be efficient and address new exploration challenges, high‐resolution and sensitive methods that are cost‐effective and environmentally friendly are required. In this work, we present the results of a sparse 3D seismic survey that was conducted in the Zinkgruvan mining area, in the Bergslagen mineral district of central Sweden. The survey covers an area of 10.5 km² for deep targeting of massive sulphides in a polyphasic tectonic setting. A total of 1311 receivers and 950 shot points in a fixed 3D geometry setup were employed for the survey. Nine 2D profiles and a smaller 3D mesh were used. Shots were generated at every 10 m, and receivers were placed at every 10–20 m, along the 2D profiles, and 40–80 m in the mesh area. An analysis of the seismic fold coverage at depth was used to determine the potential resolving power of this sparse 3D setup. The data processing had to account for cultural noise from the operating mine and strong source‐generated surface waves, which were attenuated during both pre‐ and post‐stack processing steps. The processing workflow employed a combination of 2D and 3D refraction static corrections, and post‐stack FK filters along inlines and crosslines. The resulting 3D seismic volume is correlated with downhole data (density and P‐wave, acoustic impedance, reflection coefficient), synthetic seismograms, surface geology and a 3D model of mineral‐bearing horizons in order to suggest new exploration targets at depth. The overall geological architecture at Zinkgruvan is interpreted as two EW overturn folds, an antiform and a synform, affected by later NS‐trending folding. Two strong sets of shallow reflections, associated with the Zn–Pb mineralization, are located at the hinge of an EW‐trending antiform, while a strong set of reflections, associated with the main mineralization, is located at the overturned apex of the EW synform. The NS Knalla fault that crosses the study area terminates the continuation of the mineral‐bearing deposits at depth towards the west, a conclusion solely based on the reflectivity character of the seismic volume. This study illustrates that sparse 3D data acquisition, while it has its own challenges, can be a suitable replacement for 2D profiles while line cutting, and environmental footprints can totally be avoided.

A high‐resolution seismic reflection transect was acquired over a hard‐rock geological setting along an existing roadway in the Larder Lake area of the Superior Craton of Canada for the Metal Earth project in 2017. This profile, as well as other Metal earth transects, primarily aims to enhance the knowledge and to better understand the subsurface geology of the Abitibi Greenstone Belt within the Canadian Shield. The complex geological settings of the study area as well as the tribulations caused by the survey geometry have made the imaging and velocity field estimation more challenging. A recently introduced 2.5D multifocusing stacking method is one potential solution for processing crooked‐line seismic data with a poor signal‐to‐noise ratio. The 2.5D multifocusing approach offers more realistic modelling of the zero‐offset wavefield by explicitly accounting for the midpoint dispersion and cross‐dip effects. The main practical problem of the 2.5D multifocusing implementation is the simultaneous determination of the optimal wavefield parameters for each image point and time location. We address this optimization problem using a multidimensional constrained differential evolution global optimization algorithm, as this improves the efficiency and accuracy of the estimation. We have also designed an efficient processing sequence for multifocusing seismic imaging. The performance of the 2.5D multifocusing procedure has been examined on a synthetic model, generated using the same real acquisition geometry. Numerical tests demonstrate that the 2.5D multifocusing technique can produce a more focused stack with the primary reflections appearing at their poststack correct locations, and the procedure can also provide reliable estimates of interface dips. Due to the importance and difficulty of imaging the data, several conventional and advanced processing strategies have been attempted on the transect, specifically: 2D phase‐shift time migration of a dip moveout corrected stack; 2D prestack Kirchhoff time migration; swath 3D poststack migration; and our 2.5D multifocusing imaging algorithm. We found that applying the 2.5D multifocusing stacking algorithm followed by a poststack time migration approach improved the resolution of the image significantly compared to all the conventional and advanced methods and identified new reflections. The 2.5D multifocusing method also focused the steeply dipping reflections more coherently, which resolved ambiguities in geological architecture by understanding the location and continuity of structures. The method also accurately extracts 3D structural information and results in an improved signal‐to‐noise ratio.

Two legacy reflection seismic profiles were acquired in 1988, north of the Kloof–Driefontein Complex East Mine in the West Rand goldfield (South Africa), for the purpose of gold exploration and mine planning. These legacy 2D seismic data have been reprocessed using the latest processing tools to improve imaging. Special interest is given to the Black Reef Formation, which hosts a known gold orebody. The original legacy data are of poor quality, especially in areas that are dominated by dolomitic outcrops. To improve the quality of the data, special attention was given to the refraction static correction to enhance the continuity of the reflections below dolomitic rocks. Refraction seismic tomograms from both profiles exhibit three‐layer P‐wave velocity models: (1) topsoil (1000–2000 m/s), (2) a weathered layer ranging from ca. 100 to 300 m in thickness (2000–5000 m/s) and (3) bedrock (> 5000 m/s). Seismic profile OK‐212 shows poor imaging of the Black Reef Formation because of the scattering of seismic energy in the near‐surface due to dolomites from the Transvaal Supergroup, while seismic profile OK‐213 exhibits south‐dipping reflections that are associated with the Black Reef Formation. To improve the structural imaging resolution, we tried pre‐stack time migration, pre‐stack depth migration and post‐stack time migration using the Kirchhoff algorithm. PreSDM most improved the imaging of deeper reflections due to its ability to honour complex lateral variations in the velocity field. Both pre‐stack time migration and post‐stack time migration enhanced the continuity of the near‐surface reflections below the dolomitic rocks.

In 2019, a nationwide airborne geophysical survey of Sierra Leone was flown at 150 m nominal line spacing and 50 m nominal terrain clearance. Contractual deliverables included magnetic, radiometric and supporting data streams. The primary aim of the geophysical survey was to provide a national geoscientific benchmark for resource management by the National Minerals Agency and to encourage foreign investment in the rich mining potential of Sierra Leone. Geophysical interpretation is often highly subjective. This can be helpful when an interpreter is skilled in the project area and exploration targets being sought but can be constraining and even dangerous when exploring new areas, and for new commodities. Objective classification tools can challenge interpretive bias and enhance geological understanding, both locally and regionally. We present self‐organizing maps and neural network products generated from the Sierra Leone geophysical dataset which both confirm and challenge the validity of conventional, subjective interpretation workflows. We demonstrate the usefulness of self‐organizing maps as a tool for inferring complementary geological information and show some initial results of convolution neural network classification of a reduced‐to‐equator grid to locate magnetic lineaments in plan and in depth. Moreover, we show initial results of self‐organizing map clustering as a tool for joint analysis of multiphysics datasets and construction of a pseudolithological cluster map.

Diffraction wavefield contains valuable information on subsurface composition through velocity extraction and sometimes anisotropy estimation. It can also be used for the delineation of geological features, such as faults, fractures and mineral deposits. Diffraction recognition is, therefore, crucial for improved interpretation of seismic data. To date, many workflows for diffraction denoising, including deep‐learning applications, have been provided, however, with a major focus on sedimentary settings or for ground‐penetrating radar data. In this study, we have developed a workflow for a self‐supervised learning technique, an autoencoder, for diffraction denoising on synthetic seismic, ground‐penetrating radar and hardrock seismic datasets. The autoencoder provides promising results especially for the ground‐penetrating radar data. Depending on the target of the studies, diffraction signals can be tackled using the autoencoder both as the signal and/or noise when, for example, a reflection is a target. The real hardrock seismic data required additional pre‐ and post‐autoencoder image processing steps to improve automatic delineation of the diffraction. Here, we also coupled the autoencoder with Hough transform and pixel edge detection filters. Along inlines and crosslines, diffraction signals have sometimes a similar character as the reflection and may spatially be correlated making the denoising workflow unsuccessful. Coupled with additional image processing steps, we successfully isolated diffraction that is generated from a known volcanogenic massive sulphide deposit. These encouraging results suggest that the self‐supervised learning techniques such as the autoencoder can be used also for seismic mineral exploration purposes and are worthy to be implemented as additional tools for data processing and target detections.

Near‐surface boulders can pose serious challenges to opencast mining. They often introduce complexities, delays in drilling, blasting and excavation programmes, which subsequently decrease mining efficiency, increase mining risks and costs. The location of subsurface boulders and the identification of other geological features that may impact mining activities (e.g. fractures, the presence of iron‐rich ultramafic pegmatites and the variation in weathering across a mining region) are necessary to reduce the challenges posed by these geological features, therefore optimizing mining efficiency. In this study, magnetics, electrical resistivity tomography, seismic refraction tomography, ground penetrating radar and borehole data are integrated for boulder delineation and mapping of other geological features that may impact mining using an unmined section at Tharisa Mine, Bushveld Complex (South Africa), as a test site. The results obtained from the different geophysical techniques are found to complement each other and successfully delineate boulders, fractures, iron‐rich ultramafic pegmatites and the variation in weathering and layering across the area. The incorporation of geophysical results can thus improve mining efficiency, while reducing mining risks and costs.

Critical minerals are an integral part of the energy transition because of their important and, sometimes irreplaceable, uses in solar panels, wind turbines, electrical vehicles, etc. Mapping critical mineral resources is, therefore, essential to achieving the net‐zero emission goal by 2050. We present a case study on using airborne geophysical data, borehole and physical property measurements to characterize the Elk Creek Carbonatite complex located in the southeast of Nebraska, USA. It hosts the largest known niobium deposit in the United States and contains a high level of rare earth element mineralization. Our goal is to develop a better understanding of the three‐dimensional structures and composition of the Elk Creek Carbonatite complex as well as its critical mineral resource potential. We performed three‐dimensional joint inversion of the airborne gravity gradiometry and magnetic data to produce structurally similar density and susceptibility models. We carried out geology differentiation, a process of classifying recovered physical property values into distinct units, and obtained a three‐dimensional quasi‐geology model for the Elk Creek Carbonatite complex. We identified 12 geologic units, each of which is characterized by a distinct range of physical property values. Our quasi‐geology model, especially Units 9 and 11, shows a remarkable consistency with the borehole assay measurements. Unit 9 is spatially coincident with the known niobium ore zone. Unit 11 represents a significant volume of highly dense and magnetic materials below the deepest boreholes. These materials are likely associated with unexplored niobium mineralization. Our study demonstrates the added value of three‐dimensional geophysical joint inversions and geology differentiation in the context of critical mineral exploration under a thick sedimentary overburden.

Body‐wave reflections are sensitive to sharp velocity contrasts, making them useful for lithological imaging. We analysed seismic data from natural earthquake, ambient noise and mine blasts to map P‐wave reflection profiles at the Hishikari mine area by autocorrelation analysis. Because fissure‐filled gold veins are dominant in this area, we evaluated the potential of autocorrelation analysis for investigating the shallow subsurface, including the ore deposits. Seismic interferometry is commonly performed based on the autocorrelation of ambient noise or natural earthquake signals; here, we instead used blasting in the mine because blast events include high‐frequency signals that boost the spatial resolution of the imaging. To effectively extract P‐wave reflections from seismic signals including blast events, we applied Gaussian smoothing and spectral whitening to remove source effects and then investigated the optimum frequency band. We successfully obtained auto‐correlograms showing high‐resolution seismic reflectors at shallow formation depths. These reflections are interpreted to be lithological boundaries shallower than 500 m. A comparison with profiles obtained from ambient noise and earthquake data showed that blasting signals yielded highly spatially consistent reflections that would not be achievable with natural or ambient seismic sources. This study highlights the potential of using blast autocorrelation seismic analysis during short survey periods. By using single‐blast shots and dense seismic station spacings, we successfully achieved higher resolution 3D reflection images of lithological interfaces, possibly including ore veins.

Rockbursts pose a significant risk in deep gold mines in the Witwatersrand Basin of South Africa as they may damage the excavation, injure workers, and delay production. We analysed the source mechanisms of 75 large mining‐related seismic events (ML 1.5–2.7) that caused damage to stopes in Kloof Gold Mine and used legacy 3D reflection seismic data to delineate the ore body and geological structures that may be correlated with mining‐related seismic events. The 75 seismic events took place at depths of 1600–4200 m below surface. Most events were located close to stopes mining the Ventersdorp Contact Reef ore body. The S‐to‐P‐wave energy ratio (Es/Ep) from the analysed seismic events ranged from 1.1 to 19.9. The source mechanisms of mining‐induced seismic events aid in understanding the dominant modes of failure. Planes of weakness may be the result of mining‐induced stresses or pre‐existing geological structures such as faults and dykes. The Es/Ep ratio, focal mechanism and moment tensor solutions were correlated to the underground mapped and seismically defined geological structures. Approximately 44% of the events showed strong correlation with the known underground mapped and seismically imaged geological structures (faults and dykes), whereas 56% of the events were related to elements of the mining geometry (dip pillars, abutments and remnants). This information enables mining layouts to be modified to minimize the risk of rockbursting.

Predicting the peak ground velocity of vibrations is essential to blast mining operations in order to design the charge weights so as not to exceed certain thresholds that prevent damage to buildings and other infrastructure. The problem is usually marred by a large scatter of observed peak ground velocity due to unknown complexities of seismic wave propagation. Classic peak ground velocity prediction methods employ empirical formulas, the most widespread being the scaled distance approach that has the least parameters to calibrate and works for a single sensor. In this study, we used data from 55 mining production blasts recorded by an array of 81 seismic sensors in an open pit iron ore mine in Austria. We evaluated and compared different methods for predicting peak ground velocity. The large data set provides sufficient constraint to independently resolve the charge weight exponent c, the radial decay constant b and local site factors. The c/b‐ratio of 0.2 that we find for our site is far smaller than that implied by the US Bureau of Mining scaled distance method, and peak ground velocity predictions made with the latter approach are significantly worse. This highlights the importance of using site‐specific data to calibrate predictive models and suggests that relying on arbitrary priors may lead to inaccurate predictions. For the charge weight exponent, we find a value of 0.5 which we interpret as expression of the physical relationship among charge weight, energy and amplitude, suggesting that this may be a global, site‐independent, value. This result has probable a broader relevance beyond our specific location and could improve prediction outcomes on other sites.

In this study, we review the principles of blast array design for vibration reduction and we present a parametric Laplace‐domain model to predict source time functions for mine blasts that accounts for the relation between charge weight and frequency. We developed the model for one of Europe's largest iron ore mines, Mt. Erzberg, Austria, where we repeatedly monitored production blasts with arrays of 80–125 seismic sensors. Our model enables us to simulate not only resonance modes and Doppler shifts but also time‐domain waveforms. We use the normalized cross‐correlation coefficient of observed and synthetic waveforms to calibrate the model. The overall good match of our predictions suggests that our modelling of the source time functions could be used for more advanced predictions of the peak ground velocity, which is essential to designing charge weight distributions in modern mining operations.

The undesired drill‐bit deviation is a source of drilling risks and requires monitoring. Seismic‐while‐drilling is one potential method to achieve this and has been tested in a number of previous studies. In August 2020 in Örebro, Sweden, we conducted an experiment to test the feasibility of seismic‐while‐drilling drill‐bit positioning and other applications of the method. We used the hammer drill‐bit signal generated while drilling a 200 m deep well in hardrock conditions and implemented vertical stacking of the subsequent impulsive signals from the hammer source, generating enhanced direct arrivals from the drill‐bit. Then, we used the relative arrival times to estimate the drill‐bit position for selected bit depths, confirming our methodology with two numerical studies. We successfully estimated the position of the drill‐bit for the numerical examples and for several of the real data examples, with the accuracy dependent on the receiver array geometry and the quality of the data. We conclude that this drill‐bit positioning method shows potential for near‐real‐time monitoring in drilling operations that could be applicable for both impulsive and noise‐retrieved drill‐bit signals.

Following ambient noise seismic interferometry principles, we retrieved virtual zero‐offset vertical seismic profile shot gather using continuous seismic records obtained simultaneously during an active‐source data acquisition study from Soma coal basin, Western Turkey. We treated the data to include pure ambient noise by eliminating earthquakes, surface sweeps and quarry explosions due to mining activities. We have implemented a series of data processing steps, including spectral normalization and filtering to increase the signal‐to‐noise ratio. We produced a zero‐offset virtual shot gather by cross‐correlation and cross‐coherence methods in a coal basin for the first time and we observed the P‐wave first arrivals and reflections from the deepest coal layer (km2). Our results demonstrate that the ambient noise seismic interferometry method can serve as an alternative approach for seismic imaging and monitoring in areas where the use of active seismic sources is limited due to field conditions, provided that there are sufficient and appropriate noise sources at the wellhead.

Cavity due to underground old mine workings is one of the major threats to the coal mines and the overlying subsurface and surface properties, which need to be protected. The detection of old mine workings and stability assessment of overlying strata are common problems in most of the Indian coalfields. Several coal mines in India are loss‐making, mainly due to different types of mine hazards. Khandra mine is one such mine at Raniganj Coalfield, Eastern Coalfields Ltd., a subsidiary of Coal India Limited. In the present study, 2‐dimensional and 3‐dimensional electrical resistivity tomography were carried out for detailed subsurface characterization. It supports delineating underground workings, including the nature of voids/cavities (air or water‐filled). Excessive distortions were reported in electrical resistivity tomography application, especially at the near‐surface, owing to large resistivity variations. Refinement of the model by half‐unit electrode spacing was attempted here to reduce the distortions with minimum possible absolute errors. 3‐Dimensional resistivity volumetric model was also developed with the help of five electrical resistivity tomography parallel profiles for better apprehension of the subsurface. Analysis provided important inputs for stability analysis using 3‐dimensional numerical modelling. The physico‐mechanical properties of the overlying strata, pre‐excavation in situ stresses, boundary conditions and the mine geometry simulation were incorporated for understanding the stability analysis. Stability analysis was carried out using the finite difference technique. The analysis of 3‐dimensional numerical modelling indicated that two distinct layers comprising (i) laterite/part of the course to medium‐grained sandstone and (ii) developed galleries of R‐IX seam exhibited a very low safety factor below 1.0, indicating potholing/subsidence susceptibility. The other three layers comprising parts of fine‐grained sandstone exhibited a relatively higher safety factor of around 2.0, indicating moderately stable zones, but not on a long‐term basis. Parts of Siduli stream embankments need suitable retaining walls to avoid water inundation for the stability of the area.