... geological subdiscipline dataset input variable ann model ml model algorithm gradient output variable input parameter ARMA 23 860 A Data-driven Intelligent Approach to Predict Shear Wave Velocity in Shale Formations Ayyaz Mustafa Civil and Environmental Engineering Department, University...

.... Rockburst data consisting of 254 case histories were compiled and used to model the RDP scale. The dataset was divided into two parts: a training set, which accounted for 80% of the dataset, and a separate test set, which accounted for the remaining 20%. Cross-validation technique was applied...

... government bp-ann model evaluation indicator neural network correlation data-driven model penetration dataset hyperparameter combination prediction indicator validation model performance prediction model rf model coefficient engineering rop prediction ARMA 23 0327 Data-driven Models...

... this uncertainty while making business decisions. This work aims at replacing these time-consuming fracture simulations by a proxy model, running in only a few seconds, into the Monte Carlo workflow. The proxy model is developed by training a Machine Learning (ML) based algorithm with a dataset made out of high...

... well logging reservoir geomechanics stability ann model svm model exhibition wellbore design wellbore integrity machine learning onepetro dataset neural network neuron wellbore instability correlation coefficient kernel artificial neural network ARMA 23-0598 Application of Artificial...

... information gru network accuracy engineering technology research institute drilling process efficiency petro china xinjiang oilfield company wear state bit selection algorithm dataset drilling data wear level ARMA 23 195 Real-time monitoring model of PDC bit wear based on GRU neural network...

... the early-stage, near-field rock blasting process and forms a synthetic dataset based on realistic explosive data to train a machine learning model. Key parameters, such as expanded hole diameter, burden velocity, and time-dependent gas pressure, are readily obtained from the constructed machine learning...

... pressure rock type reservoir geomechanics geological subdiscipline ann 4 10 horizontal stress zoback wellbore design wellbore integrity machine learning drilling fluids and materials prediction ann 6 10 dataset predict pore pressure reservoir characterization drilling parameter correlation...

.... geology artificial intelligence united states government metals & mining upstream oil & gas sensor machine learning wave velocity dataset seismic wave velocity algorithm productivity geologist seismicity velocity model neural network reservoir characterization diameter monitoring...

... geomechanical parameter geological fault asia government reservoir geomechanics displacement dataset geomechanical property pontifical catholic university damage zone neural network reservoir characterization janeiro numerical model rio zhang histogram correlation ARMA 23 0473 Prediction...

... in a ternary system of basaltic rocks, CO 2 , and brine under different operating conditions. To gain higher accuracy of the machine learning models, a sufficient dataset was utilized that was recorded by conducting a large number of laboratory experiments under a realistic pressure range, 0 – 25 MPa...

... government geological subdiscipline upstream oil & gas asia government breakdown pressure machine learning sedimentary rock abdulraheem prediction tensile strength enhancing breakdown pressure prediction tariq dataset prediction model geology neural network rock type coefficient...

... trapping mechanisms using a physics-based numerical reservoir simulator and creating a dataset based on uncertainty variables. The study used a numerical reservoir simulator to simulate CO 2 trapping mechanisms over 170 years, with uncertainty variables like petrophysical properties, reservoir physical...

... to estimate event location, magnitude, and source mechanism. The performance of the developed algorithm is tested using two field datasets from the Utah FORGE project. The results demonstrate the potential of the algorithm to achieve automatic real-time microseismic event detection for downhole DAS systems...

.... artificial intelligence dataset neural network machine learning probability correspond algorithm revisiting rockburst upstream oil & gas metals & mining classification rockburst engineering reservoir characterization adoko accuracy heal prediction underground space technology...

... that they could take advantage of the data more efficiently. The application of artificial intelligence (AI) and specifically machine learning (ML) along with big data analytics have known an enormous surge. deep learning well logging outlier equation dataset algorithm reservoir characterization...

... to regular inference, which allows the quantification of uncertainty in model prediction without having to significantly increase the model’s computational complexity. We survey the performance of all models using two well log datasets, one set of well logs is taken from a relatively homogenous rock...

... amanbek gradient recovery kazakhstan us rock mechanic geomechanics symposium wavelet transformation algorithm lightgbm debit accuracy artificial intelligence dataset simulation maintenance optimization ARMA 22-415 Time-series event prediction for the uranium production wells using machine...

... the dataset according to its mineral compositions, which are derived from the spectral matching of energy-dispersive spectroscopy data through the modular automated processing system (MAPS) platform. We observe that grouping our dataset into five clusters yields the best accuracy as well as a reasonable...

... into a 3D point cloud for various purposes (e.g. 3D map construction, quality inspection for huge parts). upstream oil & gas machine learning barton terrestrial laser scanner roughness estimation dataset algorithm artificial intelligence noise specimen joint roughness neural network...