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Keywords: machine learning
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Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210297-MS
... media saturation separator fluid dynamics artificial intelligence journal viscosity upstream oil & gas machine learning pressure brine injection porosity petroleum technology flooding permeability modeling & simulation relative permeability experiment permeability curve...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210255-MS
... intelligence screen selection sand control production control production monitoring machine learning contour survival dataset drillstem testing completion cofactor application breakthrough petroleum engineer percentile probability exhibition th percentile producer information spe annual...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210290-MS
... knowledge management enhanced recovery evaluation information ptd demo machine learning weighting probability deployment project management strategic planning and management progression small demo consideration author sensitivity reduction technology development framework scenario quad...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210296-MS
... against the internal components, providing a unique signature of the internal state of the housing using anonintrusive method. The reflected signals are digitally recorded and analyzed using a binary classification network that was trained through machine learning to confirm correct installations...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210350-MS
... recovery factor in the Marcellus shale wells. permeability hydraulic fracturing upstream oil & gas shale gas complex reservoir fracture unstimulated matrix permeability marcellus shale machine learning patzek fracture permeability artificial intelligence variation reservoir simulator...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210295-MS
... reservoirs providing a sustainable way to minimize carbon footprint while delivering energy. upstream oil & gas complex reservoir machine learning reservoir optimization problem taranaki basin neural network reservoir characterization architecture deep learning artificial intelligence...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210287-MS
... was successful in mitigating potential seismicity risks, which can be applied to other regions to guide seismicity-free fracturing operations in unconventional plays. upstream oil & gas artificial intelligence complex reservoir reservoir characterization hydraulic fracturing machine learning...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210369-MS
... wellbore integrity wellbore design artificial intelligence cuttings detection shaker classification shale shaker wellbore instability deployment inspection accuracy drilling operation ai cuttings load classification drilling engineer machine learning sle information increase...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210337-MS
..., we provide new insight to successfully deliver virtual training and promote the adoption of cloud solutions in the digital transformation of the exploration and production industry. student machine learning upstream oil & gas cloud computing tryme tenant overcoming virtual training...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210277-MS
... Abstract Production optimization of oil, gas and geothermal wells suffering from unstable multiphase flow phenomena such as slugging is a challenging task due to their complexity and unpredictable dynamics. In this work, reinforcement learning which is a novel machine learning based control...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210345-MS
... artificial intelligence machine learning sequestration burghardt geomechanical risk analysis arbuckle group petroleum engineer probability evaluation arbuckle 36 information subsurface engineering uncertainty quantification arbuckle 35 Introduction There are many ways to ensure...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210318-MS
... Abstract This work provides an advanced prototype for pipeline and wellbore tube inspection using electromagnetic (EM) resonance coupling, electromagnetic (EM) coupling, and machine learning. Utilizing only two transmitters and eight sensor coils, the described device can detect...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210336-MS
... and gas industry, particularly for petrophysical evaluation. This study aims to develop machine learning models to identify mineralogy by applying six different machine learning methods and using real field data from the upper, middle, and lower members of the Bakken Formation. Efficient pre-processing...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210309-MS
... workflow for the spatial and temporal migration of the CO 2 plume. The efficiency and flexibility of the data-driven workflow make our approach suitable for field-scale applications. deep learning united states government reservoir surveillance machine learning architecture artificial...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-209958-MS
... a specific potential suboptimal pump working condition. For three alarms, a data-driven approach is adopted with the application of multiple classical machine learning models such as logistics regression, K-Means clustering, continuous linear regression, etc. The workflow also uses hybrid pipelines when...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-209959-MS
... conference deep learning machine learning accuracy international petroleum technology conference santoso neural network leakage prediction hoteit proc spatial information artificial intelligence information cnn-bilstm leakage detection bayesian optimization 1. Introduction To satisfy...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-209961-MS
..., highlighting the strength of combining data and leveraging the main insights without having to read through all the RMP documents. upstream oil & gas machine learning artificial intelligence resminder information workflow caption detection reservoir management natural language processing...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-209998-MS
... flooding methods efficiency artificial intelligence injector producer polymer injector upstream oil & gas enhanced recovery implementation onepetro polymer injection constraint operational constraint allocation mangala field india optimization problem machine learning streamline...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-209999-MS
... Abstract This paper presents a physics based and data driven machine learning approach for chemical treatment candidate well selection in fields producing heavy oil. In heavy oil fields, cyclic steam is often used to not only to stimulate the formation around a wellbore but also to open...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210008-MS
... Abstract It is essential to meet climate goals outlined in the Paris Agreement that the Oil and Gas industry reduces carbon emissions along with achieving production targets. The described body of work herein provided a machine learning (ML) framework to predict upcoming shutdown events which...

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