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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 5–7, 2024
Paper Number: SPE-217700-MS
... to the industry and details some of the challenges to adopting LLMs. artificial intelligence large language model natural language chatbot machine learning construction operation gpt llm rag thetford information retrieval international drilling conference onepetro exhibition behounek platform...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217699-MS
... solution gamification technique workforce personnel competence well control training engagement competency maintenance machine learning university khan academy well control course learner baylor university Introduction Historically, the oil and gas industry has delivered much of its...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217671-MS
... intelligence large language model openai application experiment evaluation database api completion api machine learning retrieved template arxiv accuracy llm dataset benchmark in-context learning knowledge enhancing information retrieval Introduction Rapid access to critical...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217689-MS
... the creation of digital twins of full-scale rigs and to verify and validate interoperability of third-party apps prior to field release on land and offshore rigs. geologist drilling equipment machine learning drilling operation procedure well control objective algorithm information module...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217697-MS
... and false-positive rates to enhance and evaluate the performance of early stuck sign detection methods. drilling fluids and materials drilling fluid management & disposal profitability machine learning drilling operation wellbore integrity npt presented frequency detection early stuck...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217661-MS
... and the liner and casing running success rate. A machine learning model has been developed which predicts the likelihood of successfully running the casing or liner to the target depth. This information is used to compliment the Wellbore Quality Score for informing operational decisions. wellbore design...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217729-MS
... for later stages of the slurry design process. Furthermore, smart selection of slurries saves many hours of expensive laboratory testing. cement chemistry machine learning casing and cementing cement property algorithm information artificial intelligence database slurry vector application...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217739-MS
... solution for a traditionally manual-oriented workflow. The system comprises a rig site software application for creating and managing mix sheets, a machine learning algorithm that suggests chemical mixes based on fluid properties, a real-time sensor system for monitoring fluid properties, and an OPC-UA...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217738-MS
... collected dataset containing detailed information on 1047 wells in the San Juan Basin in the State of New Mexico. The inputs considered for the risk assessment model based on machine learning (ML) included well longitude, latitude, total injected or produced fluid throughout the well's lifetime, distance...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217736-MS
... events. sedimentary rock geologist wellbore design drilling operation clastic rock cuttings artificial intelligence wellbore integrity segmentation geological subdiscipline reservoir geomechanics characterization geology rock type machine learning algorithm characteristic accuracy...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217724-MS
... drilling equipment machine learning diffp hkld differential pressure measurement recognition algorithm connection automation system spp consistency driller accuracy drilling operation drillstring design automation wob note drilling conference Introduction Doing more with less has...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217722-MS
.... This opens doors to make advanced data science modeling, such as machine learning and online learning, available directly to existing rig control systems that do not have these capabilities. The flexibility of this system offers significant opportunity for applying advanced analytics and data science tools...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217717-MS
... Abstract Detecting when the entirety of a drillstring is moving—referred to as breakover—is necessary for automating several tasks in the drilling process. This paper provides an overview of how cross-industry application of machine learning (ML) technology helped solve challenges related...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217737-MS
... in recent studies and represent the taxonomy of machine-learning-based anomaly detection algorithms. Specifically, we utilized recurrent neural networks, autoencoders, and clustering. Finally, a comparison between the two approaches was performed in terms of the fidelity of the warnings they generated. We...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217733-MS
... more reward factors in the drilling optimization such as whirl and high frequency torsional oscillation (HFTO), stuck pipe, tool temperature and so on. The RL model can be applied for both pre-well drilling planning and real-time drilling optimization. drilling operation machine learning deep...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217741-MS
.... The validation log provides a strong degree of confidence in the dual-string evaluation results. Data from the dual-string evaluation and single-casing log will be used to generate a machine learning model for this well geometry, fluids, cement, and formation and is expected to give another high-resolution...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217954-MS
... Abstract Data is one of the most important limiting factors of deep machine learning (ML) model in drilling applications. Though a big size of historical data can be available, high-quality cleaned and labeled data is usually limited. In this case study, we show that with limited labeled data...
Proceedings Papers

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217750-MS
... these approaches. It does so by employing appropriate data normalization methods, transfer learning, and the inclusion of physics-based features. Using historical offset well data, this paper presents trained and tested machine learning models capable of predicting the stick-slip index (SSI) using sequences...

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