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Full-Text Articles in Engineering
Subsurface Analytics: Contribution Of Artificial Intelligence And Machine Learning To Reservoir Engineering, Reservoir Modeling, And Reservoir Management, Shahab D. Mohaghegh
Subsurface Analytics: Contribution Of Artificial Intelligence And Machine Learning To Reservoir Engineering, Reservoir Modeling, And Reservoir Management, Shahab D. Mohaghegh
Faculty & Staff Scholarship
Subsurface Analytics is a new technology that changes the way reservoir simulation and modeling is performed. Instead of starting with the construction of mathematical equations to model the physics of the fluid flow through porous media and then modification of the geological models in order to achieve history match, Subsurface Analytics that is a completely AI-based reservoir simulation and modeling technology takes a completely different approach. In AI-based reservoir modeling, field measurements form the foundation of the reservoir model. Using data-driven, pattern recognition technologies; the physics of the fluid flow through porous media is modeled through discovering the best, most …
Top-Down Model Development Using Data Generated From A Complex Numerical Reservoir Simulation With Water Injection, Yvon Andrea Martinez
Top-Down Model Development Using Data Generated From A Complex Numerical Reservoir Simulation With Water Injection, Yvon Andrea Martinez
Graduate Theses, Dissertations, and Problem Reports
Numerical simulation and data-driven modeling are two current approaches in engineering reservoir modeling. Numerical reservoir simulation attempts to match past production history by modifying reservoir properties of the model. After multiple computationally intensive trial and error efforts, accurate history matches are identified. These history matches are used by project management for production forecasting purposes. Data-driven reservoir modeling utilizes measured data and is, therefore, free of assumptions that are often included in numerical reservoir simulations. Artificial intelligence and machine learning algorithms are technologies implemented in the development of a data-driven reservoir model with efforts to learn fluid flow through porous media …
Utilization Of A Numerical Reservoir Simulation With Water And Gas Injection For Verification Of Top Down Modeling, Ashley Konya
Utilization Of A Numerical Reservoir Simulation With Water And Gas Injection For Verification Of Top Down Modeling, Ashley Konya
Graduate Theses, Dissertations, and Problem Reports
The primary purpose of this thesis was to confirm the capabilities of artificial intelligence and machine learning through Top Down Modeling in history matching and predicting the oil, gas, and water production rates, reservoir pressure, and water saturation, of one limb of an anticline with water and gas injection. Several other characteristics were also applied to make the model more realistic to industry standards. The second purpose of this thesis was to determine the minimum amount of training and calibration data required in order to obtain good results for this particular dataset by increasing the blind validation in one year …