The Role of the Value of Information and Long Horizontal Wells in the Appraisal and Development Studies of a Brazilian Offshore Heavy Oil Reservoir

Author(s):  
Celso Cesar M. Branco ◽  
Antonio Carlos Capeleiro Pinto ◽  
Paulo Marcos Bastos Tinoco ◽  
Paulo Marcos F. Vieira ◽  
Alexandre Dutra Sayd ◽  
...  
2011 ◽  
Vol 38 (5) ◽  
pp. 600-605 ◽  
Author(s):  
Zhaomin Li ◽  
Teng Lu ◽  
Lei Tao ◽  
Binfei Li ◽  
Jiguo Zhang ◽  
...  

2014 ◽  
Vol 607 ◽  
pp. 886-893
Author(s):  
Ya Hui Li ◽  
Cai Zhen Peng

Due to its high viscosity, it is very difficult to develop heavy oil cost-effectively. Currently, CO2 huff and puff method is a better choice to develop heavy oil reservoir. The key to this method is to choose the suitable candidate target wells. However, it is now very difficult to judge the suitability of the horizontal target wells’ heavy oil reservoirs’ CO2 huff and puff. In according to such issue, this paper, based on the entropy weight method of fuzzy comprehensive evaluation, and used the established horizontal wells’ index in heavy oil reservoir CO2 huff and puff, evaluates the suitability of candidate wells comprehensively. Moreover, this paper presents a set of indicator system that suits the choice of horizontal wells with regard to its heavy oil reservoir CO2 huff and puff, and proposes a specific method and procedures to evaluate an individual candidate well. This project uses such method to calculate 19 horizontal wells in area G, and the evaluation results are consistent with the actual situations. Therefore, it proves that such proposed evaluation method and evaluation index system are feasible to a certain extent. Keyword:heavy oil reservoir;horizontal well;CO2 huff and puff;Well selection; entropy method;Fuzzy comprehensive evaluation。


2018 ◽  
pp. 57-63
Author(s):  
I. V. Kovalenko ◽  
S. K. Sokhoshko ◽  
D. A. Listoykin

The article presents the experience in the stage of experimental industrial exploitation and industrial exploitation of the field with a system for the development of horizontal wells with non-standard oil properties (high oil viscosity) and complex geological structure (gas cap and aquifer). The focus of the article is on the estimation of aquifer activity by using well tests.


Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8161
Author(s):  
Zehao Xie ◽  
Qihong Feng ◽  
Jiyuan Zhang ◽  
Xiaoxuan Shao ◽  
Xianmin Zhang ◽  
...  

Conformance control is an effective method to enhance heavy oil recovery for cyclic-steam-stimulated horizontal wells. The numerical simulation technique is frequently used prior to field applications to evaluate the incremental oil production with conformance control in order to ensure cost-efficiency. However, conventional numerical simulations require the use of specific thermal numerical simulators that are usually expensive and computationally inefficient. This paper proposed the use of the extreme gradient boosting (XGBoost) trees to estimate the incremental oil production of conformance control with N2-foam and gel for cyclic-steam-stimulated horizontal wells. A database consisting of 1000 data points was constructed using numerical simulations based on the geological and fluid properties of the heavy oil reservoir in the Chunfeng Oilfield, which was then used for training and validating the XGBoost model. Results show that the XGBoost model is capable of estimating the incremental oil production with relatively high accuracy. The mean absolute errors (MAEs), mean relative errors (MRE) and correlation coefficients are 12.37/80.89 t, 0.09%/0.059% and 0.99/0.98 for the training/validation sets, respectively. The validity of the prediction model was further confirmed by comparison with numerical simulations for six real production wells in the Chunfeng Oilfield. The permutation indices (PI) based on the XGBoost model indicate that net to gross ratio (NTG) and the cumulative injection of the plugging agent exerts the most significant effects on the enhanced oil production. The proposed method can be easily transferred to other heavy oil reservoirs, provided efficient training data are available.


2015 ◽  
Author(s):  
M. B. Gomez Gualdron ◽  
A. Florez Anaya ◽  
Y. E. Araujo ◽  
W. Parra ◽  
M. Uzcategui ◽  
...  

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