Reservoir Simulation Design Strategy for Next-Generation Multi-level Assisted History Matching

2014 ◽  
Author(s):  
S. Mirzadeh ◽  
R. Chambers ◽  
G. A. Carvajal ◽  
A. P. Singh ◽  
M. Maucec ◽  
...  
Keyword(s):  
Reservoir Simulation ◽  
History Matching ◽  
Design Strategy ◽  
Next Generation ◽  
Simulation Design ◽  
Assisted History Matching ◽  
Multi Level

Reservoir Simulation Design Strategy for Next-Generation Multi-level Assisted History Matching

2014 ◽  
Author(s):  
S. Mirzadeh ◽  
R. Chambers ◽  
G. A. Carvajal ◽  
A. P. Singh ◽  
M. Maucec ◽  
...  
Keyword(s):  
Reservoir Simulation ◽  
History Matching ◽  
Design Strategy ◽  
Next Generation ◽  
Simulation Design ◽  
Assisted History Matching ◽  
Multi Level

Next-Generation Workflow for Multi-level Assisted History Matching: Visualization and Collaboration

2014 ◽  
Author(s):  
G. A. Carvajal ◽  
M. Maucec ◽  
A. Singh ◽  
A. Mahajan ◽  
J. Dhar ◽  
...  
Keyword(s):  
History Matching ◽  
Next Generation ◽  
Assisted History Matching ◽  
Multi Level

Next-Generation Workflow for Multi-level Assisted History Matching: Visualization and Collaboration

2014 ◽  
Author(s):  
G. A. Carvajal ◽  
M. Maucec ◽  
A. Singh ◽  
A. Mahajan ◽  
J. Dhar ◽  
...  
Keyword(s):  
History Matching ◽  
Next Generation ◽  
Assisted History Matching ◽  
Multi Level

Next Generation of Workflows for Multilevel Assisted History Matching and Production Forecasting: Concept, Implementation and Visualization

2013 ◽  
Author(s):  
Marko Maucec ◽  
Ajay Pratap Singh ◽  
Gustavo A Carvajal ◽  
Seyed Mohammad Mirzadeh ◽  
Steven Patton Knabe ◽  
...  
Keyword(s):  
History Matching ◽  
Next Generation ◽  
Production Forecasting ◽  
Assisted History Matching

A Fast Gridding Method for Capturing Geological Complexity and Uncertainty

2021 ◽  
Author(s):  
Yifei Xu ◽  
Priyesh Srivastava ◽  
Xiao Ma ◽  
Karan Kaul ◽  
Hao Huang
Keyword(s):  
Efficient Method ◽  
Reservoir Simulation ◽  
History Matching ◽  
Mapping Method ◽  
Reservoir Properties ◽  
Structural Framework ◽  
Assisted History Matching ◽  
Grid Topology ◽  
Geological Complexity ◽  
Complex Channel

Abstract In this paper, we introduce an efficient method to generate reservoir simulation grids and modify the fault juxtaposition on the generated grids. Both processes are based on a mapping method to displace vertices of a grid to desired locations without changing the grid topology. In the gridding process, a grid that can capture stratigraphical complexity is first generated in an unfaulted space. The vertices of the grid are then displaced back to the original faulted space to become a reservoir simulation grid. The resulting reversely mapped grid has a mapping structure that allows fast and easy fault juxtaposition modification. This feature avoids the process of updating the structural framework and regenerating the reservoir properties, which may be time-consuming. To facilitate juxtaposition updates within an assisted history matching workflow, several parameterized fault throw adjustment methods are introduced. Grid examples are given for reservoirs with Y-faults, overturned bed, and complex channel-lobe systems.

Next-Generation Workflow for Multilevel Assisted History Matching: Visualization and Collaboration

2014 ◽  
Author(s):  
G.A. Carvajal ◽  
M. Maučec ◽  
A. Singh ◽  
A. Mahajan ◽  
J. Dhar ◽  
...  
Keyword(s):  
History Matching ◽  
Next Generation ◽  
Assisted History Matching

Successful Application of Honey-Bee Optimization Technique in Reservoir Engineering Assisted History Matching: Case Study

2021 ◽  
Author(s):  
Mohamed Shams
Keyword(s):  
Simulation Model ◽  
Reservoir Simulation ◽  
Optimization Algorithm ◽  
History Matching ◽  
Optimization Technique ◽  
Food Sources ◽  
Bee Colony ◽  
Assisted History Matching ◽  
Bee Colony Optimization ◽  
Reservoir Simulation Model

Abstract This paper provides the field application of the bee colony optimization algorithm in assisting the history match of a real reservoir simulation model. Bee colony optimization algorithm is an optimization technique inspired by the natural optimization behavior shown by honeybees during searching for food. The way that honeybees search for food sources in the vicinity of their nest inspired computer science researchers to utilize and apply same principles to create optimization models and techniques. In this work the bee colony optimization mechanism is used as the optimization algorithm in the assisted the history matching workflow applied to a reservoir simulation model of WD-X field producing since 2004. The resultant history matched model is compared with with those obtained using one the most widely applied commercial AHM software tool. The results of this work indicate that using the bee colony algorithm as the optimization technique in the assisted history matching workflow provides noticeable enhancement in terms of match quality and time required to achieve a reasonable match.

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