The paper describes a problem of the quality of reservoir engineering mathematical modeling. It also gives the criteria for the models quality and six case studies based on real fields. The authors show that the practical value of the models is not high; therefore, the quality of mathematical modeling of reservoir engineering should be improved. To solve this problem, the authors suggest to use a new concept of mathematical modeling. This concept is based on hierarchical modeling and it takes into account the different scales of mathematical models and their specific features. Within the framework of the proposed modeling concept, it is assumed that the initial stage of it is to obtain data using the Digital Core technology, and then a gradual transition from one level of modeling to another takes place. The final stage of the concept is modeling the reservoir engineering process using the material balance equations. In the transition between the modeling levels, the obtained data are analyzed and transformed for the next level. Analysis and transformation of data at different levels of modeling implies that their form should reflect the models nature, i.e. spatial dimension, scale of heterogeneity, assumptions used, and other features. The importance of honoring the model features for the formation of a practically valuable result is demonstrated by a synthetic example of evaluating the mutual influence of production and injection wells. A solution to such an inverse problem allows to achieve similarity of the estimated and “actual” profiles, but this is achieved due to distortions of the mutual influence of wells relative to their true values. A capacitance resistive model (CRM) is used to show that the use of analytical models is an effective way to address complex challenges of reservoir engineering.
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