Fractured Reservoir Evaluation Using Production Testing

1990 ◽  
Author(s):  
Giovanni da Prat ◽  
Ricardo Jorquera ◽  
Suresh Puthigai
Keyword(s):  
Fractured Reservoir ◽  
Production Testing ◽  
Reservoir Evaluation

Characteristics of Fracture and Fractured Reservoir of Hailaer Basin Budart Group

2013 ◽  
Vol 316-317 ◽  
pp. 826-829
Author(s):  
Cui Ju Feng ◽  
Wei Lin Yan
Keyword(s):  
Oil And Gas ◽  
Low Permeability ◽  
Fractured Reservoir ◽  
Fracture Density ◽  
High Angle ◽  
Pore System ◽  
Reservoir Evaluation ◽  
Angle Fracture ◽  
Conventional Logs ◽  
Huge Challenge

The output of fracture pool is over half of the entire outout of oil and gas,and fracture pool is one of the important fields of oil inhancing yield in 21st Century. Fractured reservoir evaluation is always a huge challenge for the oil exploration and development. Budart Group of Sudert district in Hailaer Basin is a reservoir that has very low porosity、very low permeability、double pore system and it is rich of fracture. The paper summarized Hailaer Basin Budart Group reservoir’s characteristics, especially fractures’s characteristics in conventional logs,fracture’s parameters,such as fracture density,dip,width and filling and illustrate the response of low angle fracture and high angle fracture in logs.

Fractures and Flow Patterns Detection in Carbonate Reservoirs Using Intelligent Sensor Selection in a Deep Learning and Uncertainty Framework

2021 ◽  
Author(s):  
Klemens Katterbauer ◽  
Alberto Marsala ◽  
Abdallah Al Shehri ◽  
Ali Yousif
Keyword(s):  
Deep Learning ◽  
Industrial Revolution ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Sensor Selection ◽  
Sensor Data ◽  
Data Uncertainty ◽  
Fractured Reservoir ◽  
Sweep Efficiency ◽  
Reservoir Evaluation

Abstract 4th Industrial Revolution (4IR) technologies have assumed critical importance in the oil and gas industry, enabling data analysis and automation at unprecedented levels. Formation evaluation and reservoir monitoring are crucial areas for optimizing reservoir production, maximizing sweep efficiency and characterizing the reservoirs. Automation, robotics and artificial intelligence (AI) have led to tremendous transformations in these areas, in particular in subsurface sensing. We present a novel 4IR inspired framework for the real-time sensor selection for subsurface pressure and temperature monitoring, as well as reservoir evaluation. The framework encompasses a deep learning technique for sensor data uncertainty estimation, which is then integrated into an integer programming framework for the optimal selection of sensors to monitor the reservoir formation. The results are rather promising, showing that a relatively small numbers of sensors can be utilized to properly monitor the fractured reservoir structure.

Fracture Qualitative Identification Using Conventional Logging Data

2013 ◽  
Vol 316-317 ◽  
pp. 822-825
Author(s):  
Cui Ju Feng ◽  
Wei Lin Yan
Keyword(s):  
Oil Exploration ◽  
Fractured Reservoir ◽  
Reservoir Evaluation ◽  
Response Characteristics ◽  
Actual Production ◽  
Huge Challenge ◽  
Probability Index

Fractured reservoir evaluation is always a huge challenge for the oil exploration and development.The paper summarizes the response characteristics of fracture in conventional logging curves and gives 4 parameters which can identify fractures.Furthermore the paper proposes a comprehensive probability index of fracture which can integrate the 4 parameters above and indicate fracture develop rate qualitatively.In addition,the paper classified fracture developing level into three levels.Actual process shows that this method can indicate fracture develop rate,search fractured formation and guide actual production.

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