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... wells. The aim is to develop a correlation that is simple and easy to incorporate yet providing robust answers on a global scale. Multiple machine learning tools are employed. These include; Artificial Neural Network (ANN), Functional Network (FN), and Adaptive Neuro Fuzzy Inference System (ANFIS...

... for the production engineers to forecast the FBHP in a real time. Methodology Reservoir Surveillance Brill annual technical symposium production monitoring abdulraheem correlation FBHP Exhibition production control Upstream Oil & Gas intelligent solution pressure drop machine learning...

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.... This technique develops a relationship with a much better fit between permeability and porosity in respective ranges and thereby creating a higher cue-efficient of determination i.e. R squared value. machine learning Fluid Dynamics Upstream Oil & Gas flow in porous media permeability porosity...

... is accurate enough and can serve as a handy tool for the production engineers to forecast the productivity of wells drilled in a naturally fractured dual porosity-dual permeability saturated oil reservoirs. machine learning reservoir simulation Artificial Intelligence inflow performance storativity...

... formations. Based on these approaches, potential risks can be mitigated which help to boost drilling performance and provides effective parameters for drilling of future wells in Kohat region. drilling optimization machine learning Artificial Intelligence optimization problem Engineering logic...

... and production forecast can be made. flow in porous media machine learning Artificial Intelligence probabilistic model random error linear model confidence interval society of petroleum engineers linearity Fluid Dynamics prediction outlier null hypothesis Predict Permeability Upstream Oil...

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