Rock Flow Dynamics, Moscow, Russia

A. Yu. Degterev, Leading Geologist, Candidate of Engineering Sciences, anton.degterev@rfdyn.ru

Siberian Coal Energy Company, Moscow, Russia
S. V. Kuzmin, Head of Geomechanics at Mining Planning Management, Candidate of Engineering Sciences

The article presents a case study of multivariate block geomechanical modeling in the domestic software system tNavigator. The concept of multivariate modeling in Workflow (graph of modeling) allows automation of model updating and construction of sister models. The prerequisites of transition from the deterministic to multivariate model and the main factors which earlier prevented the use of the technology in the mining industry are listed. The described tools of the spatial data interpolation in the conditions of statistical instability ensures the automated multivariate modeling. The technology of the multivariate block geomechanical modeling is demonstrated as a case study of a mineral deposit. All major stages of operation, tools and application of the obtained results are discussed. The tools of the automated interpolation of geomechanical characteristics in the conditions of statistical instability when the geostatistical approach is inapplicable are described. The automated prediction without delineation of domains and other manual manipulations with data as well as concordant automated prediction of a number of parameters are illustrated. An example of lithological modeling is given, and the possibility of realistic prediction of geomechanical characteristics directly, without lithological modeling is demonstrated. The authors describe the methods of the initial data analysis and the modeling data control, which allow substantiation of the model correctness. The principal points are that the model is updated with new data automatically without extra labor cost and that the model is multivariate, which enables stability assessment and any parameter prediction for any block of the model.

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24. Degterev A. Yu. Multivariate spatial temporal model of gas dynamic in underground gas storage based on saturation parameter from well logging data. SPE Russian Petroleum Technology Conference. 2020. DOI: 10.2118/201952-MS
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