Data-driven model for the identification of the rock type at a drilling bit

“Zhores” — Petaflops supercomputer for data-driven modeling, machine learning and artificial intelligence installed in Skolkovo Institute of Science and Technology

“…Skoltech CDISE Petaflops supercomputer "Zhores" named after the Nobel Laureate Zhores Alferov, is intended for cutting-edge multidisciplinary research in data-driven simulations and modeling, machine learning, Big Data and artificial intelligence (AI). It enables research in such important fields as Bio-medicine [46,44], Computer Vision [20,21,11,42,45,8], Remote Sensing and Data Processing [32,34,13], Oil/Gas [33,19], Internet of Things [37,38], High Performance Computing (HPC) [29,14], Quantum Computing [10,9], Agro-informatics [32], Chemical-informatics [39,35,16,15,17] and many more. Its architecture reflects the modern trend of convergence of "traditional" HPC, Big Data and AI.…”

“…Figure9: binary and ternary aggregation solvers on CPU, Ballistic-like kernels, 16 and 10 time-integration steps for N = 222 and N = 219 nonlinear ODEs, respectively. Parameter R denotes the rank of used matrix and tensor decompositions.…”

“…The experiments have been performed using Intel compilers and Intel MKL library. Computational times for 10 time-integration steps for parallel implementation of the algorithm for ternary aggregation equations with N = 219 nonlinear ODEs.…”

Gradient boosting to boost the efficiency of hydraulic fracturing

“…In many cases machine learning allow handling the forecasting problems for cases when the accuracy of physics-driven or empirical models is limited by uncertainties of their input parameters and can provide a fast approximation, or the so-called surrogate models, to estimate selected properties based on the results of real measurements (for details, see [4]). Surrogate models are a wellknown way of solving various industrial engineering problems including oil industry [2,3,9,13,17,18,20].…”