In the analysis of field development processes, methods for assessing the mutual influence of wells within one development object and a model of the connectivity of reservoir systems, including the forecast of the spread of anisotropy of the geological properties of the productive layer of the studied reservoir, are especially in demand. There are several approaches to solving this problem, but they all have their limitations of applicability. The purpose of the study is to systematize and evaluate the effectiveness of various existing mathematical models, statistical algorithms for describing the geology of the reservoir, the connectivity of reservoir systems and field development processes. The main sources for the research search were the SPE database OnePetro, as well as Russian scientific library eLibrary.ru. The main selection criterion was the presence in the publication of a description of the study of the mutual influence of wells. After the selection of duplicate publications, a search for the full texts of the selected publications was carried out using Digital Object Identifier (DOI) and in the ResearchGate social network. The section "Classical Methods and Phenomenological Approaches" includes a review of 6 publications by Russian scientists describing the applicability of approaches based on hydrodynamic modeling of the material balance method and the mutual productivity matrix. In the section describing capacitive-resistive models, an analysis of 7 sources is carried out, describing the hydrodynamic connection of wells on the basis of material balance equations. The section "Statistical Methods and Machine Learning Methods" includes the analysis of 11 sources, which describe both approaches based on time series analysis and based on machine learning algorithms (support vector machine, decision tree algorithm, etc.), neural network models. A separate section contains 6 studies based on the applicability of geostatistical methods. This section discusses, in addition to traditional cricking and coking methods, methods based on spatial statistical modeling. The analysis of the sources allowed us to draw conclusions about the most promising use of hybrid approaches, since when building a model on the entire set of related time series (well productivity dynamics), it is important to support the study with synchronous analysis to identify the characteristic patterns of both each well and the existing time lag in the resulting mutual influence wells.
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