An improved method for predicting brittleness of rocks via well logs in tight oil reservoirs. (22nd March 2018)

• Record Type: Journal Article
• Authors: Wang, Zhenlin; Sun, Ting; Feng, Cheng; Wang, Wei; Han, Chuang
• Is Part Of: Journal of geophysics and engineering. Volume 15:Number 3(2018:Jun.)
• Page Start: 1042
• Page End: 1049
• Publication Date: 2018-03-22
• Subjects: brittleness prediction -- transformation of dynamic and static rock mechanics parameters -- correction of confining pressure -- tight oil -- well log; Geophysics -- Periodicals; Prospecting -- Geophysical methods -- Periodicals; Engineering -- Periodicals; 622.1505
• DOI: 10.1088/1742-2140/aaa935
• Languages: English
• ISSNs: 1742-2132

Abstract

Abstract: There can be no industrial oil production in tight oil reservoirs until fracturing is undertaken. Under such conditions, the brittleness of the rocks is a very important factor. However, it has so far been difficult to predict. In this paper, the selected study area is the tight oil reservoirs in Lucaogou formation, Permian, Jimusaer sag, Junggar basin. According to the transformation of dynamic and static rock mechanics parameters and the correction of confining pressure, an improved method is proposed for quantitatively predicting the brittleness of rocks via well logs in tight oil reservoirs. First, 19 typical tight oil core samples are selected in the study area. Their static Young's modulus, static Poisson's ratio and petrophysical parameters are measured. In addition, the static brittleness indices of four other tight oil cores are measured under different confining pressure conditions. Second, the dynamic Young's modulus, Poisson's ratio and brittleness index are calculated using the compressional and shear wave velocity. With combination of the measured and calculated results, the transformation model of dynamic and static brittleness index is built based on the influence of porosity and clay content. The comparison of the predicted brittleness indices and measured results shows that the model has high accuracy. Third, on the basis of the experimental data under different confining pressure conditions, the amplifying factor of brittleness index is proposed to correct for the influence of confining pressure on the brittleness index. Finally, the above improved models are applied to formation evaluation via well logs. Compared with the results before correction, the results of the improved models agree better with the experimental data, which indicates that the improved models have better application effects. The brittleness index prediction method of tight oil reservoirs is improved in this research. It is of great importance in the optimization of fracturing layer and fracturing construction schemes and the improvement of oil recovery.