A Bayesian approach to cost estimation for offshore deepwater drilling - Gyasi, Evans Akwasi
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The global offshore oil and gas industry is constantly challenged with complex operational activities, increasing uncertainties, strict regulations and delicate health, safety and environmental issues. That has made offshore deepwater drilling operation the most time sensitive activity in the upstream oil and gas industry with high probabilities of cost and time overrun. Unfortunately, the current cost estimation models are not robust enough to deal with the multi-variables associated with cost overrun in the offshore deepwater drilling industry in the Sub-Sahara Africa. This study therefore…mehr

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Produktbeschreibung
The global offshore oil and gas industry is constantly challenged with complex operational activities, increasing uncertainties, strict regulations and delicate health, safety and environmental issues. That has made offshore deepwater drilling operation the most time sensitive activity in the upstream oil and gas industry with high probabilities of cost and time overrun. Unfortunately, the current cost estimation models are not robust enough to deal with the multi-variables associated with cost overrun in the offshore deepwater drilling industry in the Sub-Sahara Africa. This study therefore developed a mathematical model that gives accurate estimations with limited data, precisely capture risk elements and factor probability results of all the possible cost variables in the offshore deep-water drilling operations. The study combined Bayesian approach with Activity-based costing (ABC) model to address the limitations of most existing models using primary data collected and secondary data extrapolated from past literature, published official drilling data and companies' financial and operational reports.
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Autorenporträt
Dr. Evans Akwasi GYASI is an experienced Cost Control Engineer and PRINCE2 certified practitioner with exceptional skills and interest in cost estimation/forecasting. He is experienced in estimating, monitoring, and developing validated cost estimation models to help reduce project costs in the oil and gas industry.