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Keywords: machine learning
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Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, March 3–5, 2015
Paper Number: SPE-173394-MS
... system to enhance welltest data validation and reduce the uncertainties in production allocation. production control production logging multiphase choke performance prediction machine learning Artificial Intelligence Upstream Oil & Gas production monitoring flow metering input parameter...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, March 3–5, 2015
Paper Number: SPE-173429-MS
... of largely untapped collection of documents. The process can be automated to integrate pattern extraction and visualization with existing systems to empower engineering staff and technical specialists involved in the monitoring and analysis of well construction. machine learning Upstream Oil & Gas...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, March 3–5, 2015
Paper Number: SPE-173420-MS
... in the related field that can result in decreasing Non Productive Time. Artificial Intelligence machine learning Upstream Oil & Gas field data drilling parameter Efficiency simulation result prediction validation well 1 lowest validation error application subset neural network well 3...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, March 3–5, 2015
Paper Number: SPE-173455-MS
... of our knowledge this is the first time fPCA is applied to well log curves in the context of oil and gas exploration. machine learning Artificial Intelligence log analysis regression well logging principal component score interpolation well log data Reservoir Characterization Upstream Oil...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, March 3–5, 2015
Paper Number: SPE-173422-MS
... logging data. More than one hundred datasets were collected to build the artificial intelligence model used for this purpose. This paper unlocks a completely new application of artificial intelligence in the field of well integrity surveillance. machine learning well integrity Subsurface Corrosion...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, March 3–5, 2015
Paper Number: SPE-173405-MS
... for the model. The results of this study prove the cability of SRMs in assisting history matching process using population-based sampling algorithms and other computationally intensive operations in reservoir management workflows. Artificial Intelligence Upstream Oil & Gas machine learning...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, March 3–5, 2015
Paper Number: SPE-173391-MS
... generated and are described in the paper. The results show that the modified QPSO was able to produce an optimum realistic solution significant superior to current practices in the field. Artificial Intelligence Efficiency PSO Upstream Oil & Gas steam generator machine learning constraint...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, March 3–5, 2015
Paper Number: SPE-173415-MS
... Intelligence model order historian machine learning spike reconstruction detection algorithm principal component analysis data quality dpca model-based data threshold sensor detail coefficient synthetically erroneous data Introduction The data recorded in historians, particularly process...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference, March 5–7, 2013
Paper Number: SPE-163728-MS
... and hole pack-off. machine learning real time measurement Artificial Intelligence bit wear Upstream Oil & Gas decision support system circulation Exhibition pipe comprehensive decision netherlands incident operation drilling operation spe 163728 optimization rock strength sensor...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference, March 5–7, 2013
Paper Number: SPE-163684-MS
... it to develop Geo-technical markers and apply machine learning algorithms to these historical data sets. Nonclinical data used to be set aside after clinical trials began. Today there is interest in translating lessons back and forth across the two study regimes. Translational medicine is already re-purposing...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference, March 5–7, 2013
Paper Number: SPE-163702-MS
.... machine learning sensor fault detection original data Upstream Oil & Gas historian data reconstruction data quality detection application reconstruction validation DPCA model spe 163702 Artificial Intelligence input variable sensor validation diagnosis algorithm principal component...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference, March 5–7, 2013
Paper Number: SPE-163697-MS
... sp smart flow smart flow neural network machine learning Artificial Intelligence key performance indicator Upstream Oil & Gas Production Operation SPE Digital Energy Conference water cut the woodlands frequency correlation operation Production Surveillance society of petroleum...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference, March 5–7, 2013
Paper Number: SPE-163726-MS
... to greatly enhance the safety and the performance of well drilling and pave the path forward for more automated rig operations. machine learning Upstream Oil & Gas drilling fluid management & disposal Artificial Intelligence relational redundancy rig internal logic false alarm drill pipe...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference, March 5–7, 2013
Paper Number: SPE-163690-MS
... geomechanical logs on a subset of wells, but having the luxury of generating logs of similar quality for all the existing wells in a Shale asset can prove to be a sound reservoir management tool for better reservoir characterization, modeling and efficient production of Marcellus Shale reservoir. machine...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference, March 5–7, 2013
Paper Number: SPE-163691-MS
... averaging-technique. The history match results from both methods were compared based on the percentage error. This unique approach will benefit older fields with sparse data. flow in porous media Upstream Oil & Gas machine learning reservoir simulation Artificial Intelligence history matching...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, April 19–21, 2011
Paper Number: SPE-142799-MS
... with the stuck pipe problems in the well planning and drilling performance approach. drilling fluid selection and formulation neural network machine learning drilling fluids and materials drilling fluid chemistry drilling fluid property drilling time analysis spe 142799 reduction Upstream Oil...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, April 19–21, 2011
Paper Number: SPE-143179-MS
.... They have open data requirement architecture that can accommodate a wide variety of data from pressure tests to seismic. machine learning modeling history pattern recognition upstream oil & gas reservoir simulation model reservoir simulation static model reservoir characteristic srm...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, April 19–21, 2011
Paper Number: SPE-143873-MS
... to data from rotating and reciprocating equipment on the topsides of offshore assets to develop predictive models that can be used to prompt preemptive actions before a critical and economically expensive downtime event. best practice data stream application machine learning information...
Proceedings Papers

Paper presented at the SPE Digital Energy Conference and Exhibition, April 19–21, 2011
Paper Number: SPE-143842-MS
... of the influence areas has to be accounted for in the selection of the parameter values in each of the regression loops. A smart expert system that includes machine-learning techniques (cognitive agents) is used to drive the global history matching process, control the sub-domains and find the best parameter...

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