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Dingzhou Cao
Dingzhou Cao
WPX Energy
Verified email at wpxenergy.com - Homepage
Title
Cited by
Cited by
Year
Efficient exact optimization of multi-objective redundancy allocation problems in series-parallel systems
D Cao, A Murat, RB Chinnam
Reliability Engineering & System Safety 111, 154-163, 2013
682013
Forecasting exchange rate using support vector machines
DZ Cao, SL Pang, YH Bai
2005 international conference on machine learning and cybernetics 6, 3448-3452, 2005
512005
Approximation methods for hybrid diffusion systems with state-dependent switching processes: Numerical algorithms and existence and uniqueness of solutions
G Yin, X Mao, C Yuan, D Cao
SIAM Journal on Mathematical Analysis 41 (6), 2335-2352, 2010
482010
Real-time hydraulic fracturing pressure prediction with machine learning
Y Ben, M Perrotte, M Ezzatabadipour, I Ali, S Sankaran, C Harlin, D Cao
SPE Hydraulic Fracturing Technology Conference and Exhibition, D031S008R003, 2020
412020
Rapid development of real-time drilling analytics system
D Cao, C Loesel, S Paranji
SPE/IADC Drilling Conference and Exhibition, D021S012R003, 2018
252018
Development and Application of a Real-Time Drilling State Classification Algorithm with Machine Learning
Y Ben, C James, D Cao
Unconventional Resources Technology Conference, 2019
242019
Near real-time hydraulic fracturing event recognition using deep learning methods
Y Shen, D Cao, K Ruddy, LF Teixeira de Moraes
SPE Drilling & Completion 35 (03), 478-489, 2020
162020
Building a General and Sustainable Machine Learning Solution in a Real-Time Drilling System
Y Ben, W Han, C James, D Cao
SPE/IADC Drilling Conference and Exhibition, D101S014R002, 2020
142020
The development and application of real-time deep learning models to drive directional drilling efficiency
D Cao, D Hender, S Ariabod, C James, Y Ben, M Lee
SPE/IADC Drilling Conference and Exhibition, D082S000R003, 2020
142020
Novel models and algorithms for systems reliability modeling and optimization
D Cao
Wayne State University, 2011
142011
Developing an Integrated Real-Time Drilling Ecosystem to Provide a One-Stop Solution for Drilling Monitoring and Optimization
D Cao, Y Ben, C James, K Ruddy
SPE Annual Technical Conference and Exhibition?, D021S019R003, 2019
132019
Design of reliable system based on dynamic bayesian networks and genetic algorithm
D Cao, S Kan, Y Sun
2012 Proceedings Annual Reliability and Maintainability Symposium, 1-6, 2012
112012
Deep learning based hydraulic fracture event recognition enables real-time automated stage-wise analysis
Y Shen, D Cao, K Ruddy, LF Teixeira De Moraes
SPE Hydraulic Fracturing Technology Conference and Exhibition, D012S012R001, 2020
92020
Optimizing maintenance policies based on discrete event simulation and the OCBA mechanism
D Cao, Y Sun, H Guo
2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS), 1-6, 2013
92013
Digital transformation strategy enables automated real-time torque-and-drag modeling
D Cao, D Hender, S Ariabod, K Ruddy, C James
SPE/IADC Drilling Conference and Exhibition, D101S015R002, 2020
82020
Slide drilling guidance system for directional drilling path optimization
C Pehlivantürk, J D'Angelo, D Cao, D Chen, P Ashok, E Van Oort
SPE/IADC Drilling Conference and Exhibition, D021S007R002, 2019
72019
Development of a ball seat event recognition algorithm with convolutional neural network for the real-time hydraulic fracturing analytics system
Y Shen, D Cao
SPE Canada Unconventional Resources Conference?, D033S004R002, 2020
32020
Applications of Deep Learning Methodology in Real-Time Completion Event Recognition
Y Shen, D Cao, K Ruddy
Machine Learning and the Physical Sciences Workshop at the 33rd Conference …, 2019
22019
Spare Parts Strategy Based on RAM Analysis to Extend the Life of Drilling Supervisory and Control Systems: A Case Study
D Cao, N Moralez
SPE/IADC Drilling Conference and Exhibition, D031S024R003, 2016
22016
Real-Time Drilling and Completion Analytics: From Cloud Computing to Edge Computing and Their Machine Learning Applications
D Cao, J Xue, Y Sun
Machine Learning Applications in Subsurface Energy Resource Management, 73-90, 2022
2022
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