Author/EditorMOHAMMAD, RAHMAN ARDHIANSYAH
Alternative Title鉱山開発プロジェクトの評価における経済的，地質的および技術的不確実性を結合させたリアルオプション分析
Note (General)The selling of examined metal is the only mining company revenue generator. It implies a certain amount of metal and selling price would grow their revenue. Before mining, the company should estimate the reserves with tremendous uncertainty. In addition, fluctuation of the metal price as economic uncertainty forces the company to deal with an advanced strategy to gain optimum value because profit is very sensitive to the selling price. Nevertheless, the cost of mining operations is unstable due to both local and global economic conditions. Cost instability represents the technical uncertainty of the process that consists of mining and processing-related expenditure.Geology and mining operations need excessive capital expenditure to run the project. In contrast, finance has to press the expense to guarantee profit. A balance between them is the crucial success of mining. Exploration is necessary to estimate the resource. The estimation is detailed with core drilling at a considerable cost and yielded a certain confidence level of reserves with inherent uncertainty. Sales prices and expenses are commonly assumed in constant or constant growth without compromising their fluctuation. However, project evaluation cannot ignore those uncertainties to get the project value.A standard method to evaluate a project value, Discounted Cash Flow (DCF), could not adequately account for the future risk. Net Present Value (NPV) as the decision parameter of the DCF method theoretically only generates two decision areas that are accepted and declined. While in reality, management commonly takes no action to wait for a reasonable commodity price, stable cost and ensure the number of reserves by collecting more exploration data. As a result, recent study dedicated to accounting for uncertainty, real options (RO) valuation, adapt financial option theory to be practiced in a real business. On the other hand, uncertainty in reserves is modelled by geostatistics methodology, kriging, and conditional simulation, which captures the spatial variability of the deposits.There are three approaches in RO methodology: Black Scholes (BS) Valuation, Binomial Lattice (BL) Valuation, and simulation. The complexity of RO in BS and BL approach arises when considering multi uncertainties in project evaluation. On the other hand, simulation approach in RO is not well developed. As a result, RO studies often only consider price as an uncertainty driver. This research combined price, grade and cost uncertainty in a mining project evaluation through the simulation approach, namely Multistage Stratified Stage Aggregation (MSSA), which would be the study's originality. Conditional simulation methods in geostatistics will be utilized to account for grade uncertainty. Thus, the expected reserve and the deviation are incorporated with commodity price and cost uncertainties.This study demonstrated a project evaluation method covering resource estimation, mine planning, economic evaluation, and uncertainty assessment. The data was collected from PT Timah, Tbk, the most significant world tin producer in 2020, located in Indonesia. The data consisted of drill hole exploration and historical operation costs, while price data was recorded from the S&P 500. Those data were followed by resource estimation using conditional simulation, particularly Sequential Gaussian Simulation, which was run with the GEOVIA Surpac mining program. Mine planning and project evaluation were conducted with the GEOVIA Whittle mining program and converted to a monthly cash flow model. Finally, the uncertainty assessment was done with the real options method, especially MSSA, which utilized java programming language. The originality of the methodology was the development of path generation through java which is an essential step in the MSSA method.Our research was a pilot method that demonstrated a combination of advances in resource estimation and economic evaluation. The conditional simulation method indicated that each reserve location had its geological uncertainty. Furthermore, Geometric Brownian Model (GBM) was used to make price simulations and get the price uncertainty. Lastly, we utilized the Mean Reverting Process to model cost uncertainty. The three uncertainties represented geological, economic, and technical uncertainties, respectively. MSSA is an alternative method to get project value considering those three uncertainties. A benchmark comparison of the MSSA result with BS and BL approaches resulted in a slight difference.In summary, we developed a project evaluation methodology that considered geological, economic, and technical uncertainties represented by grade, price and cost, respectively. In our case study, the manager can run the project, but they must ensure the project cost. In addition, the price and geological uncertainties will not be revealed until they decide to mine its reserve; thus, controlling the production and price is essential to guarantee project profitability.
Collection (particular)国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
Date Accepted (W3CDTF)2023-04-07T23:08:37+09:00
Data Provider (Database)国立国会図書館 : 国立国会図書館デジタルコレクション