... critical. To do so, conducting fracture and reservoir simulations in the cloud and analyzing the results using data analytics and machine learning algorithms can help to develop a powerful solution that creates "proxy" models for fast and effective completion optimization. In the present work, three...

... to discard uninformative parameters and retain parameters that may be tightly linked with desired and observed responses (e.g., pressures, production rates). With the advent of new algorithms in multivariate statistical analysis and machine learning (Theodoridis, 2015; Mohaghegh, 2017), the possibility...

... keeping the total mass constant. In this manner, we will estimate the volume contacted by the chemicals. machine learning thermal method reservoir characterization sagd reservoir simulation concentration enhanced recovery hydraulic fracturing artificial intelligence viscosity structural...

... complex reservoir artificial intelligence unconventional resource economics hydraulic fracturing pressure data completion clasificación ypf well head pressure variation confidencial detection interference real time series analysis well interference time series analysis machine learning...

... Abstract The main objective of this work is to identify and enable automatic online optimization actions in wells with plunger lift systems using machine learning. For this purpose, a fault classification model has been developed for plunger lift systems using neural networks focused...

... reservoir production control production forecasting urtec 1518 machine learning artificial intelligence reserves evaluation production monitoring complex reservoir dca model oil well production data reservoir surveillance upstream oil & gas hyperbolic equation application reservoir...

... utilizes data from different disciplines to explain how different parameters can impact the production behavior of a well. machine learning reservoir characterization reservoir surveillance drillstem testing reservoir geomechanics production control completion installation and operations...

... negatively to water cut and positively to lateral length, proppant-per-foot, and resistivity. In child wells, proppant-per-foot and depth were more important than in parent wells. Fluid-per-foot was of relatively low importance in all models. complex reservoir machine learning artificial intelligence...

... for performing this task, and subsequently were the methods used for this study. Over the last decade, and specially during the last 5 years, there has been a significant increase in the application of advanced data analytics methods used in the oil & gas industry. These global trends of machine learning , big...

... reservoir machine learning shale gas artificial intelligence hydraulic fracturing shale oil oil shale field development optimization and planning well head pressure information head pressure fabric structure whp fh certain rock fabric structure interference relative landing zone position...