On Knowledge-Based Forecasting Approach for Predicting the Effects of Oil Spills on the Ground

D. Kalibatiene (), A. Burmakova () and V. Smelov ()

Digital Transformation, 2021, issue 4

Abstract: The oil industry carries enormous environmental risks and can cause consequences at different levels: water, air, soil, and, therefore, all living things on our planet. In this regard, forecasting the environmental consequences of oil spill accidents becomes relevant. Moreover, forecasting of oil spill accidents can be used to quickly assess the consequences of an accident that has already occurred, as well as to develop a plan of operational measures to eliminate possible accidents, facilities under construction, associated with the transportation, storage or processing of petroleum products. Consequently, the aim of this paper is to present a knowledge-based approach and its implementing system for forecasting the consequences of an accidental oil spills on the ground and groundwater. The novelty of the proposed approach is that it allows us to forecast the oil spill in a complex and systematic way. It consists of components for modelling geological environment (i.e., geological layers, oil spill form, the oil migration with groundwater), forecasting component for an oil spill and pollution mitigation component. Moreover, the forecasting component is based on experts’ knowledge on oil spill. In addition, the paper presents a general architecture for the implementation of the proposed knowledge-based approach and its implementation into a prototype named SoS-Ground.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:abx:journl:y:2021:id:558

DOI: 10.38086/2522-9613-2020-4-44-56

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