Neural simulation-based analysis of the well wall stability while productive seam penetrating

Yuriy Katanov¹, Yuriy Vaganov¹, Matvey Cheymetov²

¹Industrial University of Tyumen, Tyumen, 625000, Russian Federation

²Saint Petersburg State University of Economics, Saint Petersburg, 191023, Russian Federation

Min. miner. depos. 2021, 15(4):91-98

https://doi.org/10.33271/mining15.04.091

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      ABSTRACT

      Purpose is the development of mathematical models to evaluate deformation of parameters of the rock mass-well geological and engineering system within the anisotropic media.

      Methods. Both mathematical and neural modeling of a stress state of the rock mass-well system under conditions of geological uncertainty has been applied for the studies. From the viewpoint of mathematical modeling, analysis of probability of factors, complicating drilling, should involve a number of assumptions for strength and deformation characteristics of rock mass layers corresponding to particular hole-making conditions.

      Findings. A mathematical model of horizontal wellbore and geological layers, occurring along the structure under the conditions of permanent comprehensive stresses, has been developed. An analytical and graphical form has been applied to implement one of the basic aspects of aggregation principles of strength changes in each particular lithological layer for identification of an ideal value of horizontal/inclined wellbore length relative to the rock mass depths scheduled by mining. Regularities of changes in deformation and spatial well stability within the complex reservoirs depending upon various process duties have been determined. A neural simulation-based model has been proposed to analyze deformation of rock mass layers having different strength characteristics.

      Originality. Interaction between geomechanical characteristics of rock mass as well as deformation and spatial stability of well design has been evaluated both qualitatively and quantitatively.

      Practical implications. An opportunity has been presented to forecast deformation of well walls taking into consideration different strength as well as structural and geological rock mass characteristics on the basis of neural simulation. The represented approach has been included on the register of the best scientific-based practices according to “Methods to recover low-pressure gas of Cenomanian producing complex” Project.

      Keywords: stress, neural network, deformation, rock pressure, transversely isotropic medium, forecasting, borehole, well

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