Geraldine-Winston / Petroleum-Reservoir-Property-Prediction-using-LSTM-networks-on-well-log-data.Links
This project uses LSTM networks to predict reservoir properties like porosity from sequential well log data, enabling improved reservoir characterization and aiding petroleum engineers in making better exploration and production decisions.
☆2Updated last month
Alternatives and similar repositories for Petroleum-Reservoir-Property-Prediction-using-LSTM-networks-on-well-log-data.
Users that are interested in Petroleum-Reservoir-Property-Prediction-using-LSTM-networks-on-well-log-data. are comparing it to the libraries listed below
Sorting:
- ☆1Updated last month
- ☆1Updated last month
- ☆2Updated last month
- ☆2Updated last month
- ☆2Updated last month
- ☆2Updated last month
- ☆7Updated 3 months ago
- Geraldine-Winston / Energy-Efficient-Building-Design-Recommendations-using-deep-reinforcement-learning.This project develops a deep reinforcement learning agent to recommend energy-efficient building designs by optimizing parameters like wi…☆2Updated last month
- A WhatsApp bot designed to provide Nigerian farmers with real-time agricultural information including weather forecasts, crop prices, pe…☆2Updated last month
- A Chart for Water Parameters is a visual representation of key water quality indicators, such as pH, turbidity, dissolved oxygen, conduct…☆7Updated 5 months ago
- This project forecasts building energy consumption using LSTM models, incorporating climate variables like temperature and humidity. It e…☆2Updated last month
- ☆2Updated last month
- ☆1Updated last month
- Hello Digital World this is my Profile☆7Updated 7 months ago
- ☆1Updated last month
- ☆1Updated last month
- ☆2Updated last month
- ☆1Updated last month
- ☆2Updated last month
- This project uses Recurrent Neural Networks (RNNs) to model and predict coastal shoreline changes over time. By training on historical sa…☆2Updated last month
- ☆2Updated last month
- ☆1Updated last month
- Geraldine-Winston / Prediction-of-Salinity-Intrusion-in-Coastal-Aquifers-using-ML-time-series-forecasting.☆1Updated last month
- ☆1Updated last month
- ☆1Updated last month
- Harnessing LSTM neural networks, this project forecasts carbon emissions from historical data. Through streamlined preprocessing, dynamic…☆2Updated last month
- ☆2Updated last month
- This project uses reinforcement learning to optimize renewable energy grid operations, balancing energy demand, solar and wind generation…☆3Updated last month
- ☆1Updated last month
- ☆1Updated last month