Advanced Geophysics combined with Deep Directional Resistivity complementing in-fill well placement and successful Geosteering

Author(s):  
J. DePledge ◽  
M. Viandante
Keyword(s):  
2008 ◽  
Author(s):  
Roland E. Chemali ◽  
Michael S. Bittar ◽  
Frode Hveding ◽  
Min Wu ◽  
Michael Raymond Dautel

2009 ◽  
Author(s):  
Benny Poedjono ◽  
Erhan Isevcan ◽  
Guy Joseph Lombardo ◽  
John Richard Walker ◽  
Simon McCulloch

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 857
Author(s):  
Jahedul Islam ◽  
Md Shokor A. Rahaman ◽  
Pandian M. Vasant ◽  
Berihun Mamo Negash ◽  
Ahshanul Hoqe ◽  
...  

Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.


Author(s):  
Patrick Nwafor ◽  
Kelani Bello

A Well placement is a well-known technique in the oil and gas industry for production optimization and are generally classified into local and global methods. The use of simulation software often deployed under the direct optimization technique called global method. The production optimization of L-X field which is at primary recovery stage having five producing wells was the focus of this work. The attempt was to optimize L-X field using a well placement technique.The local methods are generally very efficient and require only a few forward simulations but can get stuck in a local optimal solution. The global methods avoid this problem but require many forward simulations. With the availability of simulator software, such problem can be reduced thus using the direct optimization method. After optimization an increase in recovery factor of over 20% was achieved. The results provided an improvement when compared with other existing methods from the literatures.


2006 ◽  
Author(s):  
Mike Parker ◽  
Robert N. Bradford ◽  
Laurence Ward Corbett ◽  
Robin Noel Heim ◽  
Christina Leigh Isakson ◽  
...  

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