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The AAPG/Datapages Combined Publications Database
Showing 185 Results. Searched 200,293 documents.
Data-Driven Approach to Optimize Stimulation Design in Eagle Ford Formation
Francisco Herrero Clar, Agustin Monaco
Unconventional Resources Technology Conference (URTEC)
...: prediction and inference. In the first case both error types are important and both contribute to prediction uncertainty. In the later case, the objective...
2019
Case of Study: Applying Data Analytics to Reveal Most Important Parameters Impacting Well Production Performance in Vaca Muerta Unconventional Formation
Alejandro Lerza, Juan Jose Fernandez, Ana Marlats, Diego Gallart
Unconventional Resources Technology Conference (URTEC)
... consist on measuring the increase in prediction error after permuting the features value, while others might quantify importance as the error...
2020
Multi-Detector, Pulsed Neutron-Based Synthetic Openhole Logs- An Unconventional Gas Reservoir Case Study
Yonghwee Kim, David Chace
Unconventional Resources Technology Conference (URTEC)
... minimizing the overall convergence error. Each weight shares contribution to any prediction error with other weights. A back-propagation algorithm decides...
2013
Optical Methods for Monitoring Treating Chemicals in Oilfield Water Systems
Dale F. Brost, Frank M. Rexach, Gregory A. Winslow
Indonesian Petroleum Association
... was 54.7%. Results for the corrosion inhibitor were somewhat better, with an average relative error of 22.2%. Table 2. Univariate Prediction Results...
1991
Petroleum Analytics Learning Machine to Forecast Production in the Wet Gas Marcellus Shale
Roger N. Anderson, Boyi Xie, Leon Wu, Arthur A. Kressner, Joseph H. Frantz Jr., Matthew A. Ockree, Kenneth G. Brown
Unconventional Resources Technology Conference (URTEC)
... production (Blue). PALM Production-Prediction Error Figure 11 quantitatively shows the increase in accuracy as the number of attribute Importance Weights...
2016
The Petrophysical Integration of Four Volumetric End Points Applied to an Indonesian Carbonate
Mark Deakin, David R. Smith
Indonesian Petroleum Association
... hydrocarbon saturation end point. If the Ro prediction is in error, hydrocarbon saturation (Sh) will also be in error, particularly in the low Sh region close...
2003
Rate of Penetration (ROP) Modeling Using Hybrid Models: Deterministic and Machine Learning
Chiranth Hegde, Cesar Soares, K. E. Gray
Unconventional Resources Technology Conference (URTEC)
... for prediction of ROP ahead of the bit (colored green in Figure 2). It is important to ensure that test error is low (not just the training error) since low...
2018
Evaluation and Optimization of Completion Design using Machine Learning in an Unconventional Light Oil Play
Luisa Porras, Christopher Hawkes, Arshad Islam
Unconventional Resources Technology Conference (URTEC)
... is not important if, when shuffling the values, the error remains the same because this means that the model avoided the feature during the prediction...
2020
Transfer Learning with Recurrent Neural Networks for Long-term Production Forecasting in Unconventional Reservoirs
Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Unconventional Resources Technology Conference (URTEC)
... as the features in ๐, we observe larger prediction error for the latitude and longitude scenarios. Figure 11. RMSE of the training set, testing set, testing set...
2021
Synthetic Data-driven Hybrid Deep Learning Methodology for Predicting Remaining Useful Life of Sensors in Downhole Drilling Equipment
Aamir Bader Shah, Yu Wen, Jiefu Chen, Xuqing Wu, Renjie Hu, Xin Fu
Unconventional Resources Technology Conference (URTEC)
... at time ๐ก. ๐ฆ The learning objective is to find the optimal parameters ๐ that minimize the expected prediction error over the distribution of possible...
2025
Intelligent Prediction of Shale Oil Fracturing Curves Based on A Sequence-to-Sequence Model
Leyi Zheng, Tianbo Liang, Yunjin Wang, Fujian Zhou, Junlin Wu, Bin Wang, Jiaming Zhang, Maoqin Yang, Gong Chen, Xingyuan Liang
Unconventional Resources Technology Conference (URTEC)
... prediction accuracy. Existing methods for predicting the wellhead pressure during hydraulic fracturing suffer from three primary limitations: error...
2025
Advanced Seismic-stratigraphic Imaging of Depositional Elements in a Lower Cretaceous (Mannville) Heavy Oil Reservoir, West-central Saskatchewan, Canada
Sabrina E. Sarzalejo Silva, Bruce S. Hart
AAPG Special Volumes
... for the application of neural networks to predict the GR was 0.90, and the prediction error was 13 API units (6.5%). Figure 8 shows the result...
2013
Thermal Conductivity of Wilcox and Frio Sandstones in South Texas (Gulf of Mexico Basin)
Thomas E. McKenna, John M. Sharp Jr., F. Leo Lynch
AAPG Bulletin
...------------------------------ sandstones; the large prediction error for the nonquartzose samples is evident in Figure 5a. The multicomponent, geometric mixing...
1996
Analysis of Recent and Historical Salt-Crust Thickness Measurements and Assessment of their Relationship to the Salt Laydown Project, Bonneville Salt Flats, Tooele County, Utah
W. W. White III, Moises Terrazas
Utah Geological Association
... bore-hole data are in parentheses): 1) mean prediction error should be near zero (0.00129); 2) average standard error should be close to the root-mean...
2006
A Deep Learning-Based Surrogate Model for Rapid Assessment of Geomechanical Risks in Geologic CO2 Storage
Fangning Zheng, Birendra Jha, Behnam Jafarpour
Carbon Capture, Utilization and Storage (CCUS)
... the prediction error of the effective plastic strain. In summary, our study demonstrated the effectiveness of the proposed U-Net model in predicting various...
2024
Optimising CO2 storage resource utilisation: insights from the Otway Stage 4 field program
Max Watson, Hadi Nourollah, David Bason, Scott Higgs, Sally Benson, Peter Cook, Yong-Chan Park, Mitch Allison, Ziqiu Xue
Australian Energy Producers Journal
..., will be reviewed considering the collected data and predictive models. To assess the performance improvement and to account for any prediction error, a forward model...
2024
Averaging Predictions of Rate-Time Models Using Bayesian Leave-Future-Out Cross-Validation and the Bayesian Bootstrap in Probabilistic Unconventional Production Forecasting
Leopoldo M. Ruiz Maraggi, Larry W. Lake, Mark P. Walsh
Unconventional Resources Technology Conference (URTEC)
... Cross-Validation We rarely have access to out-of-sample data (new realizations of the data). One attempt to capture outof-sample prediction error...
2021
Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs
Nguyen T. Le, Roman J. Shor, Zhuoheng Chen
Unconventional Resources Technology Conference (URTEC)
... for multi-step ahead prediction, but the accumulation of error makes it more and more unstable as more and more estimated values of the target...
2021
Using Bayesian Leave-One-Out and Leave-Future-Out Cross- Validation to Evaluate the Performance of Rate-Time Models to Forecast Production of Tight-Oil Wells
Leopoldo M. Ruiz Maraggi, Larry W. Lake, Mark P. Walsh
Unconventional Resources Technology Conference (URTEC)
...n (CV) One attempt to capture out-of-sample prediction error is by splitting the sample data set into training and testing (hold-out) sets. The model...
2021
Machine Learning Approach to Improve Calculated Bottom-hole Pressure
Esmail Eltahan, Reza Ganjdanesh, Wei Yu, Kamy Sepehrnoori, Ryan Williams, Jack Nohavitsa
Unconventional Resources Technology Conference (URTEC)
... , ๐). ๐ is either inherited from the uncertainty model or defined based on the average error of the predictive method. If the replaced prediction violates...
2021
Chapter 13: Linking Cognitive Science and Disciplinary Geoscience Practice: The Importance of the Conceptual Model
Thomas F. Shipley, Basil Tikoff
AAPG Special Volumes
...-section prediction error is reporting the perspective shape of the 3-D solid at the cut location (Cohen and Hegarty, 2014). Students often misunderstand...
2016
Pilot Phase of the Aguada Federal Block, Black-Oil Window
Osvaldo Nielsen, David Curia, Pablo Pateti, Javier Caniggia, Alexis Ortega, Morten Slinde
AAPG Special Volumes
... that provides the best possible combination with the lowest prediction error (Figure 17). Seismic TOC prediction solely on density and compressional...
2020
A Comparative Analysis of Machine Learning Techniques for Geothermal Wellsย Drilling Rate of Penetration (ROP) Prediction
Taha Yehia, Moamen Gasser, Hossam Ebaid, Nathan Meehan, Esuru Rita Okoroafor
Unconventional Resources Technology Conference (URTEC)
... (Vapnik, 2000). Definitely, following a robust ML workflow contributes to URTeC: 4044244 5 minimizing the prediction error of the ML models...
2024
Multidisciplinary thermal maturity studies using vitrinite reflectance and fluid inclusion microthermometry: A new calibration of old techniques
Rick C. Tobin, Brenda L. Claxton
AAPG Bulletin
... is relatively constant from about 0.6 to 1.5% Ro, the actual prediction error is more significant at lower levels of thermal maturity than it is at higher levels...
2000
Benchmarking exploration predictions and performance using 20+ yr of drilling results: One companyโs experience
Kurt W. Rudolph, and Frank J. Goulding
AAPG Bulletin
... that exceeded 7% error, three were in areas of poor seismic imaging related to subsalt or onshore fold belts. Figure 18. Frequency plot of depth prediction...
2017