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Keywords: machine learning
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Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208726-MS
... easily find out the causes of NPT and ILT and optimize drilling operations to realize the well GQ-6 the fastest well in the block The system also save much of manual work for data record of rig jobs. real time system machine learning well logging log analysis drilling data acquisition deep...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208787-MS
... ( McGehee et. al. 1992 ) and more recently proposed for other cutting tools ( Ulvedal et. al. 2011 ). It has held up well, however with the introduction of automated systems, machine learning, evolving products, and requirement for more detailed analysis, there is a substantial need to improve the system...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208743-MS
... scientists where using multilayer perceptron models and random forest techniques allow determination of the ranking of features that affect ROP the most. The top tier features are then used to train a machine learning (ML) model to determine the average threshold of historic performance. Once the threshold...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208745-MS
... Petroleum Engineering Conference , Buenos Aires, Argentina , May 2017 . doi: https://doi.org/10.2118/185562-MS Cornel , Simon , and Gonzalo Vazquez . " Use of Big Data and Machine Learning to Optimise Operational Performance and Drill Bit Design. " Paper presented at the SPE Asia Pacific...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208794-MS
... an active ecosystem that promotes progress. artificial intelligence clojure machine learning optimization problem drillstring design cobol python drillstring dynamics yplcalibrationfromrheometer api value 5 rheological behavior software open-source community implementation algorithm...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208754-MS
... solutions that capture and describe the generation of drilling data through multi-disciplinary workflows, and how they relate in terms of uncertainty propagation. drilling measurement data mining machine learning information management upstream oil & gas semantic graph data quality...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208795-MS
... vibration sensors. A surrogate regression model between reamer vibration and sensor vibration is built using machine learning. This surrogate model is implemented in a drilling monitoring software platform as a process digital twin. During drilling, the surrogate model uses downhole measurement while...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208736-MS
... agent multi-agent decision planned trajectory ddnet validation agent virtual environment total reward etr simulated environment single agent machine learning directional drilling validation environment international drilling conference average score action proposal agent human operator...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208769-MS
... models for MPC using machine learning techniques and analytical equations. Advantages of the proposed method are discussed, such as the ability to take advantage of estimated future formation types and rates of penetration for improved prediction of future fluid properties and the ability to implement...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208741-MS
... to it being more widely deployable. The trained machine-learning algorithm in the test setup provided an accuracy greater than 90% in detecting the damaged state of the valve and piston. Only the characterization of the normal (i.e., non-damaged) state data was required to train the model. This is a very...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208779-MS
... knowledge for interpretation. Here, we aim to develop a machine learning algorithm to automatically detect events of interest and convert this information into a structured format. Several unscheduled events, such as losses, influx and stuck pipe, were selected to develop a prototype of our natural language...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208760-MS
... leverages the physics models of drillstring systems and reinforces it with machine-learning models, such as fully connected neural networks, recurrent neural networks (RNN) (e.g. long short-term memory (LSTM), and Markov Recurrent Neural Network (MarkovRNN)), and different ensembles of these approaches...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208773-MS
... cameras was used to create a monitoring dashboard where supervisors could receive alerts at the worksite level or drill down to the specific events. New technology for training machine learning models which result in faster training times over traditional methods was used. Operators and supervisors can...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208778-MS
... and modify itself to changes in the drilling operations. machine learning deep learning accuracy neural network classification model drilling operation stuck pipe incident classifier algorithm international association well 2 artificial intelligence international drilling conference...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208767-MS
... and cost-effectively, where the sequence is well defined. knowledge management drilling equipment machine learning artificial intelligence recognition procedure drilling conference digital procedure software engineering library digital operation procedure instruction shallow test...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208712-MS
... dysfunction under a particular set of conditions. These physics-informed processes are central to the development of machine learning algorithms and rig automation ( Mishra et al. 2021 ). Although extensive work has taken place over the years researching the different modes of drilling dysfunction there lacks...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208711-MS
... activity publication drilling knowledge management data quality upstream oil & gas operation code objective activity data wellbore machine learning artificial intelligence new code information operation abandonment well planning base plan work instruction requirement operator...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208693-MS
... records, cleaned and processed to enable data-driven decisions on drilling fluid type and family selection, and optimal fluid property ranges—improving drilling process efficiency. data mining drilling fluid property drilling fluid chemistry drilling fluid management & disposal machine...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208675-MS
... for preventing hole cleaning problems that may lead to a stuck pipe, and well pressure management more generally. In this work, we demonstrate a Machine Learning approach to estimating downhole ECD in real-time using a deep neural network. Surface measurements that are widely available from most rigs are used...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208676-MS
... automatically judges whether it is an anomaly or not. The algorithm has successfully demonstrated its applicability in the field data with better interpretability. data mining machine learning drilling operation upstream oil & gas benchmarking artificial intelligence anomaly mechanism...

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