LIDAR-based fracture characterization and controlling factors analysis: An outcrop case from Kuqa Depression, NW China

• Published in: Journal of petroleum science & engineering 2018-02, Vol.161, p.445-457
• Main Authors: Zeng, Qinglu, Lu, Wenzhong, Zhang, Ronghu, Zhao, Jilong, Ren, Ping, Wang, Bo
• Format: Article
• Language: English
• Subjects: Controlling factors; Development characterization; Fracture; Kuqa Depression; LIDAR
• ISSN: 0920-4105; 1873-4715
• DOI: 10.1016/j.petrol.2017.12.002

Fracture is of primary importance to the natural gas production capacity from many tight sandstone reservoirs in the Kuqa foreland basin, NW China, but the orientation, size and plane porosity of the fractures in the subsurface is difficult to measure directly. Terrestrial light detection and ranging (LIDAR) surveys can offer factual information of outcrop-based research efforts to characterize fracture development laws and controlling factors. In this paper, utilizing a multi-level covering, we obtain the three dimensional (3D) point cloud data from a LIDAR survey launched at a typical outcrop. Matching with high-resolution digital photos and artificial measured information, the 3-D positions of natural fractures are extracted strictly in the data volume section. Furthermore, the fracture and reservoir model can be founded based on the systematic sampling and laboratory analysis, while a variety of accurate facture parameters can be obtained. It is founded that three groups of shear fractures are mainly developed in two periods with large inclination, short trace length and small spacing of normal distribution. Its patterns has provided a literal distribution of penetrating fracture zone and interlayer fracture zone with a single and a double set of advantage orientation respectively. It turned out that the fracture development scale is controlled by lithology, layer thickness, maximum principle paleostress and rock composition with a good exponential relationship. Our work could provide a workflow linking outcrop fracture observations to the 3D model of subsurface fracture prediction and extend modeling capability in other outcrop studies. •Qualitative distribution characteristics of fractures was studied using LIDAR technology and outcrop analogues.•A new means was used to understand fracture patterns and their macroscopic geometry features with a partition comparison.•Fracture controlling factors in foreland areas were represented qualitatively with a series of correlation formulas.•Fracture outcrop model enhances understanding and prediction of subsurface reservoirs.