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In‐situ stress determination and fracture characterization using image logs: The Paleogene Dongying Formation in Nanpu Sag, Bohai Bay Basin, China
Author(s) -
Niu Huapeng,
Liu Shichen,
Lai Jin,
Wang Guiwen,
Liu Bingchang,
Xie Yuqiang,
Xie Weibiao
Publication year - 2020
Publication title -
energy science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 29
ISSN - 2050-0505
DOI - 10.1002/ese3.529
Subject(s) - geology , borehole , paleogene , fracture (geology) , structural basin , petrology , well logging , geotechnical engineering , geomorphology , petroleum engineering
Fracture detection and in‐situ stress determination via well logs are important for exploration and exploitation of subsurface hydrocarbons. Cores, thin sections, and image logs are used to describe and interpret the subsurface fractures and in‐situ stress in the Paleogene Dongying sandstones in Nanpu Sag, Bohai Bay Basin, China. The maximum horizontal stress (SH max ) indicates a nearly east‐west trend according to the borehole breakouts and drilling‐induced fractures. Natural fractures in the Dongying sandstones are classified into: (1) open fractures and (2) closed fractures. The cement‐filled (closed) fractures are commonly detected by image logs as bright discontinuous sinusoidal waves due to resistive filling materials, while the open fractures are evident on image logs appearing as dark sine waves. The open fractures are of dominantly high dip angles, and the rose diagrams confirm the presences of two sets of fractures: northwest‐southeast and northwest‐southeast orientation. Fractures with strikes approximately parallel to the SH max have good connectedness, making a significant contribution in hydrocarbon production. In addition, the oil‐bearing layers are mainly associated with the intervals with open fractures. The presence of natural fractures provides important pore spaces and fluid flow conduits. Insights can be provided into the subsurface fracture (natural and induced) detection and characterization using image logs.

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