期刊
AAPG BULLETIN
卷 103, 期 6, 页码 1383-1400出版社
AMER ASSOC PETROLEUM GEOLOGIST
DOI: 10.1306/12131818054
关键词
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资金
- National Natural Science Foundation of China [41502124, U1562214]
- Natural Science Foundation of Heilongjiang Province [QC2018043]
- Young Innovative Talents Training Program for Universities in Heilongjiang Province [UNPYSCT-2018043]
- Cultivating Fund of Northeast Petroleum University [SCXHB201705, 2017PYQZL-14]
Natural fractures provide the main path for fluid flow in tight oil reservoirs and can control the flow direction in the subsurface. Tight sandstones commonly have intense mechanical anisotropy, which means that fracture development in such tight formations may vary widely with respect to fracture orientations. However, the prediction of the degree of fracture development for each orientation is challenging. Focusing on the tight sandstones of the Chang 4 and 5 Member in the Jiyuan oil field, Ordos Basin, China, a new approach was presented for better prediction of the tectonic fracture occurrence in different directions based on fracture characterization, controlling factor, and formation mechanism analysis. First, fracture types, characteristics, formation time, and controlling factors were determined using data from outcrops, cores, and image logs. Then, triaxial tests were conducted to measure the mechanical parameters of rock samples in different directions that assessed the mechanical anisotropy of the formation and its impact on the development of fracture networks in the basin. Next, finite element numerical simulations of the paleotectonic stress field during fracturing were performed based on the fracture formation mechanism and controlling factors (lithology, bed thickness, sedimentary microfacies, and rock anisotropy). Finally, according to the failure criteria established using the measured mechanical parameters, the failure ratio and strain energy were calculated. These criteria could be employed to predict the fracture occurrence and the degree of development of each fracture network. The simulation predictions in this work are in good agreement with observed data from outcrops, cores, and image logs.
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