Abstract
One of exploitation methods of liquid fossil fuel deposits depends on pumping chemicals to the geological formation and ‘sucking out’ the fuel that is pushed out by the solution. This method became particularly popular in the case of extraction of shale gases. A real problem here is however a natural environment contamination caused mainly by chemicals soaking through the geological formations to ground-waters.
The process of pumping the chemical fluid into the formation and extracting the oil/gas is modeled here as a non-stationary flow of the non-linear fluid in heterogeneous media.
The (poly)optimization problem of extracting oil in such a process is then defined as a multiobjetcive optimization problem with two contradictory objectives: maximizing the amount of the oil/gas extracted and minimizing the contamination of the ground-waters.
To solve the problem defined a hibridized solver of multiobjective optimization of liquid fossil fuel extraction (LFFEP) integrating population-based heuristic (i.e. NSGA-II algorithm for approaching the Pareto frontier) with isogeometric finite element method IGA-FEM method for modeling non-stationary flow of the non-linear fluid in heterogeneous media is presented along with some preliminary experimental results.
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The research presented in this paper was partially supported by the AGH University of Science and Technology Statutory Fund no. 11.11.230.124.
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Siwik, L., Los, M., Kisiel-Dorohinicki, M., Byrski, A. (2016). Evolutionary Multiobjective Optimization of Liquid Fossil Fuel Reserves Exploitation with Minimizing Natural Environment Contamination. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9693. Springer, Cham. https://doi.org/10.1007/978-3-319-39384-1_33
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