Forecasting of Coalbed Methane Daily Production Based on T-LSTM Neural Networks
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Forecasting of Coalbed Methane Daily Production Based on T-LSTM Neural Networks
Authors
Keywords
-
Journal
Symmetry-Basel
Volume 12, Issue 5, Pages 861
Publisher
MDPI AG
Online
2020-05-25
DOI
10.3390/sym12050861
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks
- (2020) Zhuyun Chen et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Color image chaos encryption algorithm combining CRC and nine palace map
- (2019) Zenggang Xiong et al. MULTIMEDIA TOOLS AND APPLICATIONS
- An ensemble long short-term memory neural network for hourly PM2.5 concentration forecasting
- (2019) Yun Bai et al. CHEMOSPHERE
- Effective Long short-term Memory with Differential Evolution Algorithm for Electricity Price Prediction
- (2018) Lu Peng et al. ENERGY
- Deep learning with long short-term memory networks for financial market predictions
- (2018) Thomas Fischer et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models
- (2018) Ha Young Kim et al. EXPERT SYSTEMS WITH APPLICATIONS
- An architecture for emergency event prediction using LSTM recurrent neural networks
- (2018) Bitzel Cortez et al. EXPERT SYSTEMS WITH APPLICATIONS
- Long Short-Term Memory Networks for Accurate State-of-Charge Estimation of Li-ion Batteries
- (2018) Ephrem Chemali et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Development of material balance equations for coalbed methane reservoirs considering dewatering process, gas solubility, pore compressibility and matrix shrinkage
- (2018) Juntai Shi et al. INTERNATIONAL JOURNAL OF COAL GEOLOGY
- The modified gas-water two phase version flowing material balance equation for low permeability CBM reservoirs
- (2018) Zheng Sun et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- A model for pseudo-steady and non-equilibrium sorption in coalbed methane reservoir simulation and its application
- (2018) Myong Guk Yun et al. Journal of Natural Gas Science and Engineering
- LSTM-based traffic flow prediction with missing data
- (2018) Yan Tian et al. NEUROCOMPUTING
- Time series forecasting of petroleum production using deep LSTM recurrent networks
- (2018) Alaa Sagheer et al. NEUROCOMPUTING
- A novel spatiotemporal convolutional long short-term neural network for air pollution prediction
- (2018) Congcong Wen et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Long short-term memory - Fully connected (LSTM-FC) neural network for PM2.5 concentration prediction
- (2018) Jiachen Zhao et al. CHEMOSPHERE
- Multi-output bus travel time prediction with convolutional LSTM neural network
- (2018) Niklas Christoffer Petersen et al. EXPERT SYSTEMS WITH APPLICATIONS
- Numerical simulation of multi-seam coalbed methane production using a gray lattice Boltzmann method
- (2018) Yan-long Zhao et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation
- (2017) Xiang Li et al. ENVIRONMENTAL POLLUTION
- LSTM network: a deep learning approach for short-term traffic forecast
- (2017) Zheng Zhao et al. IET Intelligent Transport Systems
- Long short-term memory neural network for traffic speed prediction using remote microwave sensor data
- (2015) Xiaolei Ma et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Production data analysis of unconventional gas wells: Review of theory and best practices
- (2013) C.R. Clarkson INTERNATIONAL JOURNAL OF COAL GEOLOGY
- On the use of cross-validation for time series predictor evaluation
- (2012) Christoph Bergmeir et al. INFORMATION SCIENCES
- History matching and production prediction of a horizontal coalbed methane well
- (2012) Fengde Zhou JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Productivity matching and quantitative prediction of coalbed methane wells based on BP neural network
- (2011) YuMin Lü et al. Science China-Technological Sciences
- Reservoir Modeling in Shale-Gas Reservoirs
- (2010) Craig L. Cipolla et al. SPE RESERVOIR EVALUATION & ENGINEERING
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now