Study of Oil Urban Fragmentation in the Vaca Muerta Region using Data Mining and Machine Learning

Abstract

The aim of this paper is to contribute to the studies of the urban fragmentation process by means of Oil&Gas activity in the Añelo region, center of Vaca Muerta (Neuquén). For this purpose, the data mining technique and model training were used to analyze the evolution of real estate prices. A time range was taken from June 2020 to June 2021, which allowed us to establish a model to predict the evolution of values for subsequent periods. The predictive model incorporated the investments made by more than ten companies engaged in exploration and production activities in Vaca Muerta. In this work we start from the premise that Añelo is an urban center that in the last 15 years has undergone urban transformations due to the increase of oil&gas activity associated with the exploitation of the Vaca Muerta geological formation, by non-conventional method. One of the objectives of this work is to present the possibility of incorporating Artificial Intelligence (AI) as a predictive tool to complement geographic works on spatial transformations caused by hydrocarbon extraction. Two results were obtained: on the one hand, the model developed is presented as a tool for individuals as well as public and private agents linked to urban planning and the real estate market. On the other hand, it is highlighted how the incorporation of AI to the analysis of urban alterations from geography allows the elaboration of predictive models for localities within areas of exploitation of strategic resources such as oil&gas.