103 citations · 150 across the 7 of their papers we have counts for
8 papers
A Deep Learning-Aided Approach for Estimating Field Permeability Map by Fusing Well Logs, Well Tests, and Seismic Data
Grigoriy Shutov, Viktor Duplyakov, Shadfar Davoodi +11
Obtaining reliable permeability maps of oil reservoirs is crucial for building a robust and accurate reservoir simulation model and, therefore, designing effective recovery strateg…
CO2 storage in deep saline aquifers: evaluation of geomechanical risks using integrated modeling workflow
Evgenii Kanin, Igor Garagash, Sergei Boronin +5
CO2 injection into a saline aquifer crossed by a tectonic fault is studied with coupled fluid mechanics - geomechanics modeling. The simulation approach is based on coupling of the…
Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements
E. A. Kanin, A. A. Garipova, S. A. Boronin +5
We propose a new method for construction of the absolute permeability map consistent with the interpreted results of well logging and well test measurements in oil reservoirs. Nada…
Development of Deep Transformer-Based Models for Long-Term Prediction of Transient Production of Oil Wells
Ildar Abdrakhmanov, Evgenii Kanin, Sergei Boronin +2
We propose a novel approach to data-driven modeling of a transient production of oil wells. We apply the transformer-based neural networks trained on the multivariate time series c…
Data-driven model for hydraulic fracturing design optimization. Part II: Inverse problem
Viktor Duplyakov, Anton Morozov, Dmitriy Popkov +5
We describe a stacked model for predicting the cumulative fluid production for an oil well with a multistage-fracture completion based on a combination of Ridge Regression and CatB…
Data-driven model for hydraulic fracturing design optimization: focus on building digital database and production forecast
A. D. Morozov, D. O. Popkov, V. M. Duplyakov +6
Growing amount of hydraulic fracturing (HF) jobs in the recent two decades resulted in a significant amount of measured data available for development of predictive models via mach…