... a representative dataset out of numerous data obtained in an oil-field is an essential task for the sand control design. Introduction machine learning clustering algorithm descriptor artificial intelligence particle sieve size sand control minimum similarity threshold psd alberta cascade...

.... Artificial Intelligence risk management reserves evaluation intervention Upstream Oil & Gas initial rate machine learning reservoir simulation subsurface outcome production forecasting subsurface uncertainty operational risk society of petroleum engineers distribution function development...

... and transmissibility for proper application of EOR schemes. reservoir simulation fault transmissibility fault throw Reservoir Characterization Upstream Oil & Gas SSF Artificial Intelligence injector Capacitance Model machine learning structural geology algorithm kaviani permeability Thickness...

... the importance of an integrated workflow in predicting future well performance in gas condensate fields. The study demonstrates how to implement the workflow in managing or developing these types of reservoirs. machine learning Drillstem Testing condensate reservoir empirical method drillstem/well...

... reservoirs are the U and T sandstones, Fig.2 . The value of the information log analysis well logging machine learning hydraulic fracturing inflow performance sandstone evaluation Upstream Oil & Gas information producer Artificial Intelligence drillstem/well testing oil production...

... regression uncertainty range central composite design Artificial Intelligence Fluid Dynamics Monte Carlo simulation experiment machine learning Upstream Oil & Gas uncertainty analysis oil water contact plackett-burman design society of petroleum engineers NPV experimental design d-optimal...

... and recommend proxy models to estimate RF and NPV versus reservoir parameters. Artificial Intelligence chemical flooding methods enhanced recovery Simulation viscosity sensitivity region Oil Viscosity Oil Recovery machine learning Upstream Oil & Gas viscosity NPV reservoir permeability...

... efficient way. Reservoir Surveillance production control production forecasting production monitoring shale gas shale reservoir coefficient complex reservoir analysis model nanopore diffusion Knudsen diffusion Petroleum Science horizontal well multiple fracture machine learning...

... Artificial Intelligence oiled wildlife management plan incident machine learning Upstream Oil & Gas programme contingency planning Wildlife Preparedness bpTT operator Trinidad and Tobago society of petroleum engineers chemical spill oil spill response stakeholder Noscp...

... control of decision variables in varying ranges of uncertainty that will be useful in analyzing prospective assets. thermal method machine learning enhanced recovery steam-assisted gravity drainage optimization application recovery method Experiment Run SAGD viscosity light crude heavy...

... enables continued learning from historical well-data in a systematic, data-driven method that has not existed in the past. machine learning real time system shale oil complex reservoir Upstream Oil & Gas real-time decision-making dashboard knowledge hypothesis Energy Economics shale gas...

... on lifting costs. progressing cavity pump supplier machine learning sucker rod PTO progressive cavity pump artificial lift system Upstream Oil & Gas Soldado Field rod string drivehead petrotrin trinmar operation downhole pump society of petroleum engineers Artificial Intelligence...

... posterior range of uncertainties and volumes, even where a large initial uncertainty was believed to exist. These results were successful in achieving the objective by largely reducing the volumetric uncertainty and re-confirming the initial view. machine learning Artificial Intelligence mismatch...

... other fault-block reservoirs. In this work, several development methods demonstrate a significant effect to enhance oil recovery for complex fault-block reservoir, which can give a good guidance for other similar reservoirs. optimization problem development effect machine learning...

... using True Vertical Depth (TVD) as a correlation parameter for the first time, and it can generally be used to estimate both the dynamic and static rock mechanical properties of the Cruse Formation for future oilfield operations. machine learning Reservoir Characterization log analysis Upstream...

... water cut period improved remaining oil sweeping efficiency and enhanced oil recovery. machine learning Artificial Intelligence flow in porous media waterflooding Fluid Dynamics flow pattern classification enhanced recovery Upstream Oil & Gas coordination number columnar stream...

... for Hybrid EOR techniques utilizing CO 2 and LSW. machine learning waterflooding correlation enhanced recovery Upstream Oil & Gas water saturation Modeling & Simulation salinity experiment Brine co 2 Artificial Intelligence low salinity pressure drop fine migration saturation...

..., a correlation with molecular weights and reservoir temperature can give an estimation of CO 2 MMP. Furthermore, for tight oil reservoirs, taking the confinement effect into consideration, CO 2 MMP is reduced and a solubility method can incorporate a pore radius into evaluation. machine learning...

... for the low-salinity waterflooding. Artificial Intelligence enhanced recovery waterflooding Brine PPM relative permeability experiment water saturation salinity machine learning Upstream Oil & Gas OOIP water relative permeability water saturation distribution Oil Recovery connate...

... the ‘blind' drilling eliminated several gyroscopic runs, saving time and money for the client. well planning dogleg severity information drilling dynamic tool machine learning trajectory design original wellbore BHA drilling operation well tool face correlation case study Artificial...