Examinando por Autor "Martínez Bernal, Margarita María"
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- ÍtemClasificación litológica a partir de registros eléctricos utilizando machine learning: caso de estudio formación otaraoa, Nueva Zelanda.(Fundación Universitaria Los Libertadores. Sede Bogotá., ) Martínez Bernal, Margarita María; González Veloza, José John FredyIn the oil industry, when exploration well drilling, the uncertainty is excessively high since it is necessary to determine the characteristics of the subsurface and thus the possibilities that oil or gas exists. Indirect methods such as well logs are what provide the basis for geological investigation studies (sedimentary facies, groundwater) which is a complex activity that requires time but allows the evaluator to make decisions. By applying an automatic learning model, we want to reduce this uncertainty and minimize the time in the analysis of well logs. In this study, lithology prediction is investigated using electrical logs (Gamma Rays, Neutron, Density and Photoelectric Effect (PEF)) taken at the Fm. Otaraoa in New Zealand. The training of a Supervised model is carried out where two problems are addressed: the first of identification of two labels (Sand and Clay) and the second of four labels (Sandy Clay, Calcareous Sandy Clay, Clayey Sand and Calcareous Clayey Sand). One well is used to train an algorithm for each case and then two complementary wells are used to test its performance. The results of the Extra Trees Classifier model show that for Problem 1 an Accuracy of 93% was obtained, exceeding the metrics of the model based on rules (Accuracy of 87%), while in Problem 2 the Accuracy was 86%. The model in Problem 1 will learn to recognize the lithology pre-established by the human expert and for Problem 2 it is important to continue feeding the model training with more data from other wells or with core descriptions.