The last two decades have seen a significant evolution in both the methods for and purposes of closure cost estimating. As part of this evolution, changes in the uses of closure cost estimates have resulted in coincident changes in the scope, methods employed and level of detail required.Prior to the development of regulatory requirements to prepare closure cost estimates, closure cost estimates were typically intended for planning, design and contracting of the actual closure, and were often developed late in the mine life cycle. The level of detail required was largely determined by the number of years remaining in the operational life of the mine at that time. The nearer to the time of closure, the more detailed the closure design and cost estimate became. These closure designs became the basis for construction contract bidding and tracking purposes.As mining laws changed and the need to provide financial surety for closure activities became a priority, the focus of closure cost estimating in many countries was to reduce the liability of the government that would assume responsibility should the operator abandon the site prior to planned closure. The latest evolution of closure cost estimating techniques has been focussed on improving closure cost estimating for the purpose of accurate reporting of financial liabilities to shareholders, lending institutions and governments. Requirements for reporting mine closure liabilities have added a new dimension to the scope and detail of closure cost estimating.This paper documents the history of mine closure cost estimating since the 1970s and discusses the influence that different purposes for mine closure cost estimates have had on the evolution of methods used to develop those estimates. Several examples of successes and failures in closure cost estimates for actual mine sites and the regulatory programmes that oversee the closure of these mine sites are presented as illustrations of the progression of closure cost estimating and demonstrate the importance of this discipline in the mining life cycle process. Current trends in the current best practice and their probable impact on the future of closure cost estimating are also discussed.
Mine closure relies on proof of best practice in both design and performance of rehabilitation. Field techniques have been the traditional approach for producing detailed supporting empirical evidence for mine closure. Although field sampling provides a detailed snapshot of key performance criteria within small areas, these areas themselves may not be representative of the overall performance of rehabilitation. Additionally, their limited scale may miss broader spatial characteristics that could further strengthen arguments for relinquishment. Remote sensing is a complimentary approach to field sampling that can produce an entire census of a rehabilitation site at a reduced scale. However, uncertainty still surrounds the adoption of a remote sensing approach, and whether such techniques can capture key performance indicators accurately and consistently. This paper provides both a demonstration of capacity, and quantification of accuracy, of remotely sensed data analytics for the production of empirical evidence to support mine closure management. Using rehabilitated landforms in the Western Australian Goldfields as case studies, remote sensing was adopted in two supporting roles: the validation of landform construction, and the ongoing monitoring of landform performance. The geometry of constructed landform surfaces was measured through photogrammetric techniques and assessed against design specifications. Ongoing monitoring assessed both vegetative colonisation and relative stability of established landform surfaces. Coupled together, the broader scale impact of non-compliant areas upon local rehabilitation performance was explored and discussed. Underpinning these data analytics is the accuracy of remotely sensed data. The quantification of uncertainty within the data was derived through a comparison against precision field measurements. Quantification of this uncertainty allowed the establishment of confidence intervals on derived measurements. Furthermore, the impact of changing environmental complexity upon analysis performance was quantified. This allowed for the modelling of compensation factors that dynamically counterbalance the increased uncertainty of complex environments. The result of the study demonstrates the capacity for a remote sensing approach to empirically support mine closure and relinquishment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.