Markov expert logical analysis for energy reserves probabilistic evaluation
The paper focuses on the probabilistic evaluation of oil and gas resources with the models and methods of AHP/ANP analysis. The AHP/ANP models are shown to be the particular cases of finite Markov chains, i.e. discrete random processes with Markov property. An integrated method (Markov expert logical analysis (МELA)) is proposed. The method is based on the models, methods and algorithms of Markov chains theory. This basis will stimulate the progress in research on multi-criteria decision-making problems that arise in various spheres. The paper presents different methods using MELA to allow for the uncertainty of numeric and nonnumeric data on gas reserves as methods of transformation of expert estimations into the probability distributions. Typical logical schemes are proposed for multi-criteria comparison of analogous objects, to take account of possible errors in porosity evaluation and to estimate project life.
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