Gravity surveying is a geophysical method for detecting subsurface density variations in mining and mining - related endeavours, such as mineral exploration, mine planning, and infrastructure siting. Such density variations can be produced by a variety of subsurface features, including orebodies, cavities, large water-bearing fissures, karst profiles, etc. Gravity surveys can also augment mining safety and risk management, e.g., as a tool for the early detection if incipient sinkholes in opencast operations.
To be useful, the raw gravity field data require several reduction and processing steps, one of which is gravity terrain correction (GTC) processing. The latter step is often omitted owing mainly to its computational demand, thereby diminishing the value of the final survey data.
This paper describes how recent advances in modern desktop computing technology with features such as hyper - and multithreading, multicore central processing units, instruction set extensions, and more, have made exhaustive GTC processing hugely more practicable. A resultant GTC processing code derived, prototyped, and developed in-house is briefly described. Finally, a synthetic example of a gravity survey conducted in a hypothetical open pit mine to detect subsurface cavities is presented, which illustrates the difference that proper GTC processing can make to a gravity survey's target delineation, definition, and contrast.
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