Evaluation of Laminated Shaly Sand Sequences in Oil Fields Using Thomas Stieber Model and Conventional Logs

Document Type : Research Paper

Authors

1 Petroleum Engineering, Department of Petroleum & Gas Engineering, Sahand University of Technology, Tabriz, Iran

2 Department of Physics, Arak University, Iran

3 Petroleum Engineering, Petrophysist, Petrophysics Division of National Iranian South Oil Company, Ahwaz, Iran

Abstract

Thin layers of sand within clay are capable of producing hydrocarbons in the case of being carefully analyzed. These layers are often ignored because of their low thickness and low resolution of common reservoir petrophysical evaluation logging tools in conventional methods. These tools only calculate the average properties of these layers which make a wrong prediction of amount of oil and gas in layers. There are some methods for better analysis of the layers and increasing the production of reservoir which can accurately identify thin laminated shaly sand and calculated petrophysical parameters with high precision. In this paper, laminated shaly sand layers (LSS) are studied by using Thomas Stieber model and common reservoir petrophysical evaluation logs. Thomas Stieber model is applied to the desired layer by laminated shaly sand analysis module in Geolog 7.2 software, and the results of this model and the common reservoir petrophysical evaluation logs were analyzed by using this software. According to the results of the Thomas Stieber and conventional logs’ analyses without  implementing shear cut-offs, the amount of the porosity increased 6.5 % and 5.4 % for well A and B, respectively. Also, the amount of the water saturation for well A and B decreased 38.8 % and 16.3 %, respectively. Finally, by comparing the results of the analysis, it was concluded that Thomas Stieber model calculates properties of laminated shaly sand layers more accurate than the common reservoir petrophysical evaluation logs and this model can be used to study these sequences.
 

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References

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Journal of Petroleum Research
Volume 27, 96-3 - Serial Number 94
September and October 2017
Pages 165-176

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