A New Model for Determining the Radius of Mud Loss During Drilling Operation in a Radial Fractured Network

Author(s):  
M. Pordel Shahri ◽  
S.H. Zabihi
2020 ◽  
Vol 10 (8) ◽  
pp. 3389-3397 ◽  
Author(s):  
Nayem Ahmed ◽  
Md. Saiful Alam ◽  
M. A. Salam

Abstract Loss of drilling fluid commonly known as mud loss is considered as one of the critical issues during the drilling operation as it can cause severe formation damage. To minimize fluid loss, researchers introduced numerous additives but did not get the expected result. Recently, the use of nanoparticles (NPs) in drilling fluid gives a new hope to control the fluid loss. A basic KCl–Glycol–PHPA polymer-based mud is made, and six different concentrations of 0.1, 0.5, 1.0, 1.5, 2.0, 3.0 wt% iron (III) oxide or Hematite (Fe2O3) NPs are mixed with the basic mud. The experimental observations reveal that fluid loss of basic mud is 5.9 ml after 30 min and prepared nano-based drilling mud results in a less fluid loss at all concentrations. Nanoparticles with a concentration of 0.5 wt% result in a 5.1 ml fluid loss at the API LTLP filter press test. On the other hand, nanoparticles with a concentration of 3.0 wt% enhance the plastic viscosity, yield point, and 10 s gel strength by 15.0, 3.0, and 12.5%, respectively. The optimum concentration of hematite NPs is found to be 0.5 wt% which reduces the API LPLT filtrate volume and filter cake thickness by 13.6 and 40%, respectively, as well as an improvement of plastic viscosity by 10%.


2021 ◽  
Vol 196 ◽  
pp. 107984
Author(s):  
Saeed Shad ◽  
Soroush Salmanpour ◽  
Hossein Zamani ◽  
Davood Zivar

Author(s):  
H. Akabori ◽  
K. Nishiwaki ◽  
K. Yoneta

By improving the predecessor Model HS- 7 electron microscope for the purpose of easier operation, we have recently completed new Model HS-8 electron microscope featuring higher performance and ease of operation.


2005 ◽  
Vol 173 (4S) ◽  
pp. 140-141
Author(s):  
Mariana Lima ◽  
Celso D. Ramos ◽  
Sérgio Q. Brunetto ◽  
Marcelo Lopes de Lima ◽  
Carla R.M. Sansana ◽  
...  

Author(s):  
Thorsten Meiser

Stochastic dependence among cognitive processes can be modeled in different ways, and the family of multinomial processing tree models provides a flexible framework for analyzing stochastic dependence among discrete cognitive states. This article presents a multinomial model of multidimensional source recognition that specifies stochastic dependence by a parameter for the joint retrieval of multiple source attributes together with parameters for stochastically independent retrieval. The new model is equivalent to a previous multinomial model of multidimensional source memory for a subset of the parameter space. An empirical application illustrates the advantages of the new multinomial model of joint source recognition. The new model allows for a direct comparison of joint source retrieval across conditions, it avoids statistical problems due to inflated confidence intervals and does not imply a conceptual imbalance between source dimensions. Model selection criteria that take model complexity into account corroborate the new model of joint source recognition.


1986 ◽  
Vol 31 (2) ◽  
pp. 108-109
Author(s):  
Alexandra G. Kaplan
Keyword(s):  

PsycCRITIQUES ◽  
2004 ◽  
Vol 49 (Supplement 13) ◽  
Author(s):  
Paul E. Priester
Keyword(s):  

1993 ◽  
Vol 38 (4) ◽  
pp. 406-407
Author(s):  
Donald B. Yarbrough ◽  
Monika Schaffner

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