... surveillance, the reservoir and oil wells will experience many dynamic changes, such as workover or power failure. Therefore, the obtained pressure data will be mixed with a large number of abnormal points and noise. decision tree learning artificial intelligence production monitoring waterflooding...

... driven approach decision tree learning modeling reservoir simulation upstream oil & gas artificial intelligence communication history matching machine learning prediction reservoir modeling data science workflow regression limitation data analytic approach platform proxy...

... assessment tool to evaluate the development prospect of unconventional tight rocks. upstream oil & gas neural network wellbore integrity petroleum engineer complex reservoir reservoir geomechanics tariq society decision tree learning prediction artificial intelligence strength machine...

... are expensive and, hence, it is also not economically viable to do more frequent well tests. decision tree learning deep learning neural network artificial intelligence production monitoring prediction machine learning uplift prediction recommendation information conference reservoir...

... in running the tedious and time-consuming experiments and helps to provide a good quick estimate of surfactant adsorption. This model will add a great value in the practical application of a chemical EOR project. upstream oil & gas fuzzy logic decision tree learning machine learning abu-khamsin...

... industries. data mining upstream oil & gas failure mode health & medicine quality data artificial intelligence dynamic prescriptive maintenance objective machine learning decision tree learning maintenance identification unsupervised approach justin time maintenance maintenance...

... method model water cut measurement dataset application classify water cut measurement classifier random forest fiber optic production monitoring decision tree learning classification model production zone simple decision tree model fiber optic data society of petroleum engineers water cut...

... abnormal reservoir behavior. risk management drillstem/well testing machine learning decision tree learning traditional method Drillstem Testing bottom hole pressure Artificial Intelligence analytic method algorithm decision tree algorithm reservoir pressure surveillance ARIMA model...

... failures caused by void pumping or long-time system stop. It could also greatly increase pumping and system efficiency and save more energy. production monitoring Reservoir Surveillance Upstream Oil & Gas decision tree learning machine learning Artificial Intelligence drillstem/well testing...

... - streamlining of proposed practice is key to drive robust engineering decisions in petroleum industry and enhance the value of decision process making it more flexible and accurate, and thus more attractive. machine learning Upstream Oil & Gas Decision analysis decision process decision tree...

... geomechanics enabler Efficiency machine learning decision tree learning Simulation average temperature electromagnetic wave tree model different rock type dielectric heating perforation society of petroleum engineers rock type enabler property heating mechanical property temperature value...

... learning Artificial Intelligence fracturing fluid hydraulic fracturing Upstream Oil & Gas fracture conductivity productivity fracture well productivity data proppant dimensionless fracture conductivity Gomaa conductivity reservoir permeability decision tree learning productivity index...