Seismic solutions utilizing existing in-mine infrastructure for mineral exploration: A case study from Maseve platinum mine, South Africa

We demonstrate the application of seismic methods using in-mine infrastructure such as exploration tunnels to image platinum deposits and geologic structures using different acquisition configurations. In 2020, seismic experiments were conducted underground at the Maseve platinum mine in the Bushveld Complex of South Africa. These seismic experiments were part of the Advanced Orebody Knowledge project titled “Developing technologies that will be used to obtain information ahead of the mine face.” In these experiments, we recorded active and passive seismic data using surface nodal arrays and an in-mine seismic land streamer. We focus on analyzing only the in-mine active seismic portion of the survey. The tunnel seismic survey consisted of seven 2D profiles in exploration tunnels, located approximately 550 m below ground surface and a few meters above known platinum deposits. A careful data-processing approach was adopted to enhance high-quality reflections and suppress infrastructure-generated noise. Despite challenges presented by the in-mine noisy environment, we successfully imaged the platinum deposits with the aid of borehole data and geologic models. The results open opportunities to adapt surface-based geophysical instruments to address challenging in-mine environments for mineral exploration.

Unsupervised Clustering of Continuous Ambient Noise Data to Get Higher Signal Quality in Seismic Surveys

Seismic interferometry has been shown to extract body wave arrivals from ambient noise seismic data. However, surface waves dominate ambient noise data, so cross-correlating and stacking all available data may not succeed in extracting body wave arrivals. A better strategy is to find portions of the data in which body wave energy dominates and to process only those portions. One challenge is that passive seismic recordings comprise huge volumes of data, so identifying portions with strong body-wave energy could be difficult or time-consuming. We use spatio-temporal features, calculated with data recorded by all receivers together, to perform unsupervised clustering. Using data recorded by a dense seismic array in Sweetwater, TX we were able to identify five clusters, representing a subsets of the complete dataset that contain similar features, and extract a 7 km/s body wave arrival from one cluster. This arrival did not emerge when we performed the same cross-correlation and stacking regimen on the entire dataset.

Imaging crustal structures through a passive seismic imaging approach in a mining area in Saxony, Germany

We have used several flooding-induced microseismic events that occurred in an abandoned mining area to image geological structures close to the hypocentres in the vicinity of the mine. The events have been located using a migration-based localization approach. We used the recorded full waveforms of these localized microseismic events and have processed these passive source data as if they resulted from active sources at the known hypocentre location and origin time defined by the applied location approach. The imaging was then performed using a focusing 3D prestack depth migration approach for the secondary P-wave arrivals. The needed 3D migration velocity model was taken from a recent 3D active (controlled-source) seismic survey in that area. We observed several clear and pronounced reflectors in our obtained 3D seismic image cube, some of them related to a major fault zone in that area and some correlating well with information from the nearby mining activities. We compared our results to the 3D seismic image cube obtained directly from the 3D active seismic survey and have found new structures with our approach that were not known yet, probably because of their steep dips which the 3D active seismic survey had not illuminated. The location of the hypocentres at depth with respect to the illumination angles of those structures proved to be favourable in that case, and our 3D passive image complements the 3D active seismic image in an elegant way, thereby revealing new structures that cannot be imaged otherwise with surface seismic configurations alone.

Stability Assessment and Geomorphological Evolution of Sea Natural Arches by Geophysical Measurement: The Case Study of Wied Il-Mielah Window (Gozo, Malta)

The Wied il-Mielaħ Window (Gozo–Malta) is a limestone natural arch on the north-western coast of the island of Gozo in Malta. It is located at the end of the Wied il-Mielaħ valley north of the village of Għarb. This natural arch is less well known than the Azure Window, which collapsed in March 2017 following a heavy storm, but notwithstanding, it is an imposing and important natural monument too. In the past, the Wied il-Mielah valley was responsible for discharging wastewater from the surrounding localities to the Mediterranean directly at the Wied il-Mielah Window. The sewage flag was often clearly visible underneath the archway into the open sea. The natural features of the arch provide an outstanding touristic attraction. To avoid what happened to the Azure Window, a methodology for the evaluation of the collapse hazard, combining passive seismic, ground penetrating radar (GPR), geological/geomorphological surveys and mine engineering methods, is here proposed. In this study, a methodological approach was applied, based on the following: (i) passive seismic method to study the physical–mechanical characteristics of the rock mass that constitutes the window; (ii) GPR method in order to demonstrate the conservation state (i.e., the intensity of fracturing); (iii) geological/geomorphological surveys in order to obtain a crack pattern; and (iv) scaled span empirical analysis in order to evaluate the stability of the arch. The calculation of the safety factor, with a static method, gave a value equal to 3.75 with a probability of collapse of the marine arch within 50 and 100 years.