... assessment infrastructure upstream oil & gas installation analytical model maintenance digitalization platform production facility machine learning deepwater facility panel session operation south america Aggarwal , R. K. , DoIan , D. K. , & Cornell , C. A. ( 1996...

... Abstract The objective of the paper is to demonstrate the Machine Learning (ML) based Structural Integrity Management (SIM) Methodology and its application for the life extension of the offshore structure. This paper also illustrates how the sensor data are used to generate an ML based...

... corpus machine learning representation natural language neural network application upstream oil & gas artificial intelligence offshore technology conference natural language processing algorithm vector space model Ashton , W. B. , and Stacey , G. 1995 . Technical...

... upstream oil & gas surfactant oil recovery enhanced oil recovery material artificial intelligence machine learning effectiveness polymer concentration technology conference screening criteria enhanced oil recovery recommendation 10-fold cross validation alkaline test data...

... correlated to the core description. The method provides pattern recognition and facies prediction with higher resolution and accuracy than conventional Machine Learning methods based on the clustering of petrophysical properties. offshore technology conference information pattern recognition...

... permeability estimation porosity log analysis tomographic image machine learning spectrum atomic number formation fluid permeability decomposition drilling mud relaxation upstream oil & gas absolute permeability artificial intelligence original formation fluid Aster , R. C...

... violation safety vest usage hardhat ppe artificial intelligence application information machine learning detection classification pipeline supervision database upstream oil & gas neural network protective equipment annotation dataset computer vision accident backend...

... hole drilling applications, e. g. conductor casing design. To the authors’ knowledge, few papers perform this comparative analysis. statistical characterization undrained shear strength statistical evaluation standard deviation linear regression offshore technology conference machine...

... machine learning capillary pressure id card Amaefule , J. O. , Altunbay , M. , Tiab , D. , Kersey , D. G. and Keelan , D. K. 1993 . Enhanced Reservoir Description: Using Core and Log Data to Identify Hydraulic (Flow) Units and Predict Permeability in Uncored Intervals...

... . historical data input variable prediction input data simple regression machine learning classification artificial intelligence regular fishing information offshore technology conference bha application regression training data incidence fishing service upstream oil & gas operation...

... drilling operation accuracy well drilling performance mechanical drilling parameter plastic viscosity mud property machine learning Abdulmalek , A. Elkatatny S. , A. Abdulraheem , M. Mahmoud , A. Z. Ali , and I. M Mohamed ( 2018 , August 16 ). Prediction...

... smart well production proxy dataset prediction reservoir architecture offshore technology conference optimization artificial intelligence machine learning upstream oil & gas simulator lstm network reservoir simulation case study information deep learning technology conference...

... information operation dataset operation name upstream oil & gas scenario sequence ddr entry artificial intelligence drilling report machine learning classification prediction model dataset sequence prediction application algorithm experiment classification task prediction...

... drone offshore technology conference machine learning fracture structural geology neural network algorithm identify igneous rock complex reservoir deep learning technique dyke artificial intelligence Bemis , S.P. , Micklethwaite , S. , Turner , D. , James , M.R...

... model pixelization approach feature vector structural geology small multiple approach machine learning Abstract Providing an overview of an ensemble of oil reservoir models could help users compare and analyze their characteristics. Approaches that show a single model at a time may hamper...

... reservoir simulation goldstein machine learning reduction Abstract When performing classic uncertainty reduction based on dynamic data, a large number of reservoir simulations need to be evaluated at high computational cost. As an alternative, we construct Bayesian emulators that mimic...

... of the output model. The best combination was the one using the PReLU activation function with the Adamax optimizer. machine learning deep learning variation seismic modeling seismic data rmsprop leaky relu relu upstream oil & gas neural network activation function velocity model...

... Abstract In this paper, we propose an alternative approach to the problem of oil-production forecast based on the most straightforward feature-based machine-learning algorithm: the linear model. The method can be successfully applied to forecast both oil-rate and liquid-rate in oil fields under...

... to propose an optimal brine composition to maximize the oil recovery. oil component machine learning mechanism wettability alteration mineral enhanced recovery composition calculation calcite upstream oil & gas reservoir sol reaction interface waterflooding oil recovery artificial...

... evaluation of the ROP capability, bit wear, motor fatigue life, and BHA shock and vibration. At the end, we can perform fast drilling without compromising durability or reliability. drill bit stability differential pressure elastomer simulation machine learning durability directional drilling...