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Keywords: machine learning
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Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214817-MS
... and analysis. Thus, a new methodology utilizing Machine Learning (ML) and Natural Language Processing (NLP) was used to create an advance model to automate this process. This study explores the process of automating exploring artificially lifted well data via the utilization of ML and NLP algorithms...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214984-MS
.... The major benefits of this workflow include reducing time for numerical simulations and saving overall monitoring and tracking costs for conventional techniques. The present work would provide a good illustration of the capability of practical integration of machine learning methods in solving engineering...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214985-MS
... Abstract Subsurface modeling is important for subsurface resource development, energy storage, and CO2 sequestration. Many geostatistical and machine learning methods are developed to quantify the subsurface uncertainty by generating subsurface model realizations. Good subsurface models should...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214991-MS
... testing united states government drilling fluid selection and formulation sampling drilling fluid chemistry algorithm fluid sampling artificial intelligence simulation prediction drilling fluid formulation drilling fluid property machine learning probe contamination prediction filtrate...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214996-MS
... for the commercial-scale deployment. In this paper, an innovative method comprising multi-tiered analysis has been developed to leverage advanced machine learning (ML) techniques to process passive seismic monitoring data acquired over the two-year injection period along with pumping/injection pressure and rate...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-215015-MS
.... wellbore design united states government upstream oil & gas erosion artificial intelligence production monitoring particle mclaury computational fluid dynamic cfd simulation production logging sand control machine learning simulation contour salama flow metering wellbore integrity...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-215019-MS
... & gas deep learning united states government semi-supervised learning approach dataset neural network machine learning u-net seismic reflectivity inversion petroleum engineer reservoir characterization geophysics seismogram complexity seismic inversion operator Introduction...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-215020-MS
... natural language architecture query ownership product data mining governance graph plane machine learning setup template system mesh platform modernizing data management mesh knowledge layer Introduction Throughout the decades in which data has been made available in Exploration...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-215028-MS
... information machine learning drilling operation conference mechanism prediction accuracy accuracy presented transformer application well control detection fine-tuning limitation model Introduction Anomalies in drilling operations can have severe consequences, such as equipment failure...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214769-MS
..., and machine learning techniques. Arps (1945) introduced a decline curve analysis method (DCA) method, which employs empirical equations to fit historical production data. However, one limitation of DCA decline analysis is its inability to account for operational constraints when generating production...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214773-MS
... be introduced to the seismic images, potentially impacting the accuracy of geological interpretation. In this paper, we leveraged the known correlations between drilling parameters (e.g., rate of penetration, weight on bit and torque) and mechanical properties of formation rocks to construct a machine-learning...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214777-MS
... management production monitoring sensitivity evolutionary algorithm spe annual technical conference permeability workflow production control streamline aquifer geologist geology drillstem testing reservoir surveillance machine learning exhibition calibration multiplier datta-gupta chen...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214783-MS
... drilled in Utah FORGE. This paper seeks to fill these gaps by using a hybrid approach to study these events, ultimately implementing a form of physics-informed machine learning (ML) for anomaly detection. Additionally, it provides guidelines derived from the analysis, to avoid stuck pipe incidents...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-214784-MS
...-well fracture hits that are characterized by the installed low-frequency DAS (LF-DAS) in the monitoring well. The target objectives are simultaneously and automatically matched through the calibration of hydraulic fracturing simulator by developing highly efficient and accurate machine learning (proxy...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-215047-MS
... Machine Learning (ML); an automated predictive analytics tool for model selection; and incorporating the predictive models into a prescriptive model that determines quantity of additives to use to achieve a desired set of drilling fluid properties. Given the initial product composition, a set of desired...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-215103-MS
... modeling & simulation numerical simulation history matching united states government neural network iran government machine learning geologist reservoir deep learning flow in porous media artificial intelligence neural operator society sagd geology reservoir simulation petroleum play...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-215091-MS
... government rock type geology deep learning production forecasting petroleum play type north america government production monitoring production control machine learning energy economics estimation unconventional resource technology conference united states government clastic rock complex...

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