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Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0036
.... machine learning well logging Artificial Intelligence Reservoir Characterization neural network abdulraheem transit time wave velocity prediction correlation gamma ray log analysis Upstream Oil & Gas empirical correlation compressional resistivity wave transit time sonic wave transit...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0023
...; fluid type; hydraulic horsepower (HHP) per stage; lb/ft 2 of proppants per stage; number of stages, and lateral length (completed interval) of horizontal wells,. fracturing materials hydraulic fracturing machine learning Completion Installation and Operations Artificial Intelligence...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0106
... density inversion MEQ machine learning hydraulic fracturing stimulation fluid pressure seismicity probability Artificial Intelligence Fluid Dynamics Earthquake genetic algorithm riffault Dempsey cloud 1 1. INTRODUCTION Hydraulic stimulation is applied to wells to improve formation...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0092
... failure criteria. A machine learning algorithm is developed to generate cement parameters, such as cohesion and friction angle. The statistic value, Misfits, is used for the quantitative comparison of the accuracy of different failure criteria. Results show that using only the conventional triaxial...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0034
... discussed for each model showing the fine differences between the models. Artificial Intelligence exponent hydraulic conductivity 2-parameter model machine learning Fluid Dynamics pressure parameter sorptivity test Upstream Oil & Gas correspond sorptivity capillary pressure curve...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0101
... that many of these equations were developed for only one type of sandstone and tend to generalize poorly to the broader database. machine learning Artificial Intelligence wellbore integrity reservoir geomechanics strength zorlu Upstream Oil & Gas Reservoir Characterization Wellbore...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0130
... orientation stimulation microseismic data microseismicity DPA Reservoir Characterization baig geomechanical model dynamic parameter analysis dynamic parameter deformation machine learning Upstream Oil & Gas Simulation prediction evolution fracture geometry hydraulic fracturing...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0243
... better than existing correlations using different technics in optimization and agreement study. machine learning Reservoir Characterization reservoir geomechanics neural network correlation Artificial Intelligence neural network model lab test test data normal distribution agreement...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0208
... improve the effectiveness and reliability of geomechanical reservoir models. Artificial Intelligence Ferronato reservoir geomechanics displacement application Reservoir Characterization teatini covariance matrix machine learning Upstream Oil & Gas hydrocarbon reservoir probability...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0325
.... machine learning classification abutment angle knowledge management US government Artificial Intelligence calculation new abutment angle equation colwell stress measurement database fracability metals & mining proceedings pillar stability abutment angle equation Case History abutment...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0268
... analysis, a description method for the mechanical properties of carbonates with fractures and holes was established. The analysis results can be used to rock mechanics calculation of deep fractured carbonate rocks. Artificial Intelligence carbonate reservoir machine learning complex reservoir...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0362
... strong tendency to open the natural fracture. The scenarios predicted by the neural networks is in agreement with the rock mechanics concepts and with the expected tendencies, which gives more reliability to the neural network. neural network Simulation machine learning Upstream Oil & Gas...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0382
... adequately dealt with to still achieve the economic benefits. Reservoir Characterization drilling operation wellbore integrity annular pressure drilling loss event machine learning Artificial Intelligence Upstream Oil & Gas mechanism ECD monitoring failure mechanism well control...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0455
... simplified analytical model is presented to simulate the natural fractures' stress-sensitive effects on production. machine learning complex reservoir flow in porous media Fluid Dynamics Simulation modeling natural fracture hydraulic fracturing element method calculation Artificial...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0438
... ABSTRACT: Parameter calibration is an indirect problem in which responses of a system are known, but the properties of the said system are not. Often, trial and error strategies are used for parameter calibration. However, they can be labor intensive and time consuming. Machine learning...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0433
... control production logging production monitoring hydraulic fracturing Upstream Oil & Gas viscosity sensor machine learning Artificial Intelligence deep learning subsurface virtual fiberoptic sensor fracture height hydraulic fracture physics-informed deep neural network analysis dataset...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-1570
... data machine learning Upstream Oil & Gas seismic hazard assessment comprehensive assessment Velenje fractal dimension-based index information dimension dimension-based index application fractal dimension 1. INTRODUCTION Seismic hazard in mining is the probability of hazard events...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-1791
... class machine learning classification accuracy ratio Upstream Oil & Gas accuracy variation identification characteristic input parameter topology classification accuracy characterization limestone lithological classification p-wave velocity Visualization dataset information self...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-1863
... and cavities in the near-well formation can be analyzed through drilling data and fracturing data. machine learning reservoir reconstruction coefficient formation fracture Upstream Oil & Gas drilling data instability neuron Artificial Intelligence neural network displacement...
Proceedings Papers

Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-1917
... propagation anglogold ashanti minimum ppv serra grande accident vibration machine learning Upstream Oil & Gas cme excavation peak particle velocity maximum load unstable block wave attenuation 1. INTRODUCTION The vibrations caused by the drill and blats process are a matter of concern due...

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