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A stochastic characterization of a hydrocarbon reservoir, constituted by a sedimentary sequence of sandstones interbbeded with siltstones and shales, has been performed. The stratigraphic unit studied here mainly comprises the C4 sands of the Misoa Formation, located in the Lama Field, Maracaibo Lake (Venezuela). A Markov Chain algorithm, based on the definition of genetic lithofacies relationships along stratigraphic columns, was developed. The application of the Monte Carlo stochastic method using this algorithm, to log data from 11 wells, allowed the generation of pseudo sequences at 20 new locations. This algorithm was able to properly model pseudo stratigraphic sequences and to quantify the relative facies percentage, showing a 82% confidence level related to the proportional content of sediments at a test well. The net sand map obtained integrating the stratigraphic columns, derived from the well information, and the Markov pseudo-columns, suggests the presence of sand bodies with a northeast-southwest orientation that agree with previous geological studies in the area. This map could help in the definition of prospective zones in the field. The existence of stratigraphic memory along the evaluated columns was recognized after applying the algorithm. The embedded Markov method used in the cyclicity analysis of the whole area indicates cyclic transitions just from sandstones to siltstones and from shales to siltstones. Hence for the study area, on average, fining upward and coarsening upward processes can be identified with the Markovian approach, as was expected for the tide-dominated deltaic system associated to the analyzed reservoir

Stratigraphic Columns Modeling and Cyclicity Analysis of the Misoa Formation, Maracaibo Lake, Venezuela, using Markov Chains