... learning data mining shale gas directional drilling energy economics production control artificial intelligence complex reservoir unconventional resource economics well performance reservoir characterization reservoir surveillance hydraulic fracturing drilling operation reserves evaluation...

... with completion sensitivity performed on a multithreaded cluster environment on these wells. Advanced machine learning and data mining algorithms of data analytics such as random forest, gradient boost, linear regression, etc. were applied on the data points to create a proxy model for the fracturing...

... in assessing properties for acquisition or farmout opportunities. The central idea of the work is that completions optimization is an ever-changing process. This implies the areas that were previously overlooked could potentially benefit from recent advances in completions and be more profitable. Data mining...

..., it is important to consider alternative methods, and to this end, we have developed two new methods of forecasting production. The first method uses data mining techniques, which allow the analysis of large quantities of data to discover meaningful pattern and relationships. These can subsequently be used...

... analyses and forecasting, which in turn decreases the time required for a complete field simulation study. data mining flow in porous media coal bed methane coalbed methane Artificial Intelligence shale gas machine learning Modeling & Simulation Fluid Dynamics gas reservoir...

... is presented. In this approach, data mining and pattern recognition techniques were used to initiate modeling of the hydrocarbon production (dray gas and condensate) from Marcellus Shale. Instead of imposing our understanding of flow and transport in shale gas media, which is a very complex and non-linear...