Gas Reservoir

Gas reservoir research focuses on accurately predicting the location and extent of subsurface gas deposits to optimize extraction and resource management. Current research heavily utilizes machine learning, employing ensemble methods like NGBoost, Random Forest, and gradient boosting algorithms, to integrate diverse data sources such as 3D seismic surveys and well logs for improved reservoir characterization and prediction. These data-driven approaches aim to reduce uncertainty in reservoir modeling, enhance well placement strategies, and ultimately improve the efficiency and profitability of gas production. The resulting advancements contribute to more sustainable and economically viable hydrocarbon exploration and development.

Papers

January 23, 2024

Gas trap prediction from 3D seismic and well test data using machine learning
Dmitry Ivlev
Machine Learning Test Data Reservoir Pressure Well Data Seismic Wavefield 3D Seismic Gas Reservoir

August 24, 2023

Uncertainty and Explainable Analysis of Machine Learning Model for Reconstruction of Sonic Slowness Logs
Hua Wang, Yuqiong Wu, Yushun Zhang, Fuqiang Lai, Zhou Feng, Bing Xie, Ailin Zhao
Machine Learning Model High Uncertainty Anticipation Full State Reconstruction Borehole Description Gas Reservoir

April 6, 2023

Generalization with Reverse-Calibration of Well and Seismic Data Using Machine Learning Methods for Complex Reservoirs Predicting During Early-Stage Geological Exploration Oil Field
Dmitry Ivlev
Machine Learning Strong Generalization Human Prediction Self Calibration Geophysical Data Seismic Wavefield Gas Reservoir

June 7, 2022

Data-driven evolutionary algorithm for oil reservoir well-placement and control optimization
Guodong Chen, Xin Luo, Jimmy Jiu Jiao, Xiaoming Xue
Data Driven Evolutionary Algorithm Differential Evolution Optimal Controller Reservoir Dynamic Well Control Gas Reservoir

June 4, 2022

Forecasting the production of Distillate Fuel Oil Refinery and Propane Blender net production by using Time Series Algorithms
Akshansh Mishra, Rakesh Morisetty, Rajat Sarawagi
Production Incident Oil Well Reservoir Pressure Oil Price Production Data Label Refinery Gas Reservoir

Gas Reservoir

Papers

Gas trap prediction from 3D seismic and well test data using machine learning

Uncertainty and Explainable Analysis of Machine Learning Model for Reconstruction of Sonic Slowness Logs

Generalization with Reverse-Calibration of Well and Seismic Data Using Machine Learning Methods for Complex Reservoirs Predicting During Early-Stage Geological Exploration Oil Field

Data-driven evolutionary algorithm for oil reservoir well-placement and control optimization

Forecasting the production of Distillate Fuel Oil Refinery and Propane Blender net production by using Time Series Algorithms