...Abstract Abstract The application of Artificial Intelligence for planning has received increased attention in the energy industry in the past few years, particularly for the increased production efficiency requirements and environmental standards. The objective of this paper is to show...

... lessons from established tight oil plays that will underpin planned activities at a Field Laboratory Test Site in the southern Powder River Basin. energy economics core analysis reservoir characterization artificial intelligence wellbore integrity us government hydraulic fracturing...

... rock is reduce by 10 2 to 10 4 times as porosity decreases from 0.1 to 0.03. complex reservoir liquid phase co 2 Artificial Intelligence critical property shift enhanced recovery Upstream Oil & Gas shale gas diffusivity psia tortuosity factor correlation coefficient effective...

... to operators. log analysis downhole intervention completion installation and operations well intervention debris well logging hydraulic fracturing production enhancement traditional method drilling operation tractor artificial intelligence coiled tubing operations upstream oil & gas...

... poisson independent data machine learning artificial intelligence neural network model neutron porosity actual poisson brittleness poisson ratio geomechanical property well logging relation society of petroleum engineers well 1 well 2 gradient Introduction B I = V Q u...

... in unconventional horizontal wells over the past few decades. The purpose is to apprise the industry and academic researchers on the various AL optimization approaches that have been used and suggest AL optimization areas where new technologies can be developed. Artificial Intelligence Upstream Oil & Gas...

... analysis ensures that this estimation is robust and repeatable by adding prior information on the parameters to the model and by calibrating the estimates to the data. production forecasting diagnostic plot artificial intelligence data distribution inverse problem production data machine...

... Approach (VFMA) ( Esmaili, 2013 ). ( Hao Sun, 2018 ) proposed that a dual porosity, dual permeability (DPDP) model with Knudsen diffusion, which is considered to be adequate to model shale gas reservoir production. complex reservoir artificial intelligence machine learning shale gas upstream oil...

... strategy. shale oil artificial intelligence machine learning complex reservoir refrac kpis shale play re-fracturing unconventional resource economics correlation hydraulic fracturing upstream oil & gas energy economics refrac shale gas oil shale barnett 3-month production gain...

... artificial intelligence coefficient fracture treatment regression coefficient algorithm multinomial regression hydraulic fracturing supervised learning technique classification simulation fracture network numerical simulation validation unconventional reservoir random forest reservoir...

... to predict the cumulative gas production in 24 months. This manuscript demonstrated the application of artificial intelligence in simulating hydraulic fracturing design. In this study, database of more than 150 Marcellus shale wells were developed, hydraulic fracturing properties such as total stage...

... to achieve the required Q for any increase in YP/PV. machine learning drilling fluid chemistry well control wellbore pressure management annular pressure drilling pearson correlation particle turbulent flow data mining artificial intelligence drilling fluids and materials plastic viscosity...

... unconventional reservoir matrix form machine learning Upstream Oil & Gas deconvolution pressure response pressure map matrix permeability Artificial Intelligence Simulation training feature flow regime pressure drawdown leesn deconvolved response reservoir property noise permeability...

... dynamics simulation heterogeneous model heterogeneous simulation water cut assumption ntg different value artificial intelligence upstream oil & gas heterogeneity porosity effective permeability permeability ntg value spatial correlation equation Introduction Net-to-Gross (NTG...

... shale gas upstream oil & gas gas well artificial intelligence complex reservoir taleghani 2016 hydraulic fracturing oil well production rate appalachian basin cumulative probability distribution economic analysis fracture undiscounted npv re-fracturing program confidence interval...

...-established ML and data mining algorithms in computer sciences and statistical literature. This approach enables safe operations and handling of extremely large data bases, hence, facilitating tough decision-making processes. machine learning google patent node Artificial Intelligence Exhibition...

.... We build these set of tools by utilizing the pattern recognition abilities of machine learning algorithms and public data from the Southwestern Pennsylvania region of the Marcellus Shale. By means of artificial intelligence and data mining techniques, we studied a database that includes public data...

.... The laboratory workflow must also prove that the stimulation fluid chemistry satisfies the stimulation intensity objectives of high rate, high sand concentration, and reduced fluid volumes while enabling reliable field execution. formation damage rock-fluid incompatibility chemical treatment Artificial...

..., compared to conventional methods. asset and portfolio management field development optimization and planning Simulation optimization problem fracture half-length multiplier Artificial Intelligence complex reservoir machine learning completion design optimization economic analysis workflow...

... modeling machine learning Upstream Oil & Gas bottomhole gauge data child well fracture proppant Drillstem Testing communication marcellus well parent well Artificial Intelligence drillstem/well testing frac stage statistical analysis roc curve Completion Operation frac production...