Machine Learning Techniques for Defect Depth Estimation in Oil and Gas Pipelines

2016 ◽  
Author(s):  
Abduljalil Mohamed ◽  
Mohamed Salah Hamdi ◽  
Sofiene Tahar ◽  
Osman Hasan
Keyword(s):  
Machine Learning ◽  
Oil And Gas ◽  
Depth Estimation ◽  
Machine Learning Techniques ◽  
Gas Pipelines ◽  
Defect Depth ◽  
Learning Techniques ◽  
Oil And Gas Pipelines

Application of Machine Learning Techniques in Reservoir Characterization

2021 ◽  
Author(s):  
Edet Ita Okon ◽  
Dulu Appah
Keyword(s):  
Machine Learning ◽  
Oil And Gas ◽  
Reservoir Characterization ◽  
Learning Algorithm ◽  
Oil And Gas Industry ◽  
Production Performance ◽  
Machine Learning Techniques ◽  
Gas Industry ◽  
Learning Techniques ◽  
Machine Learning Model

Abstract Application of artificial intelligence (AI) and machine learning (ML) is becoming a new addition to the traditional reservoir characterization, petrophysics and monitoring practice in oil and gas industry. Accurate reservoir characterization is the driver to optimize production performance throughout the life of a field. Developing physics-based data models are the key for applying ML techniques to solve complex reservoir problems. The main objective of this study is to apply machine learning techniques in reservoir Characterization. This was achieved via machine learning algorithm using permeability and porosity as the investigative variables. Permeability and porosity of a reservoir were predicted using machine learning technique with the aid of XLSTAT in Excel. The general performance and predictability of the technique as applied to permeability and porosity predictions were compared. From the results obtained, it was observed that the machine learning model used was able to predict about 98% of the permeability and 81% of the porosity. The results from Al and ML will reinforce reservoir engineers to carry out effective reservoir characterization with powerful algorithms based on machine learning techniques. Hence, it can therefore be inferred that machine learning approach has the ability to predict reservoir parameters.

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