Atif Ismail | University of Engineering and Technology Lahore (original) (raw)

Papers by Atif Ismail

This paper describes a fracture characterization and modeling project in China. The fracture char... more This paper describes a fracture characterization and modeling project in China. The fracture characterization uses different sources and different scales of fracture-related data including outcrop, core, log, seismic, drilling, well test and production data for fracture recognition and analysis (Prioul et al (2009) and Hirata, (1989)). Subsequently, in the fracture modeling phase, a geostatistical method-the discrete modeling approach-is utilized to integrate the data from the various fracture characterization results. The fracture modeling uses the fracture characteristic parameters and their corresponding distribution under the guidance of the regional fracture development background to build a discrete fracture network (DFN) (Figure 1). Figure 1: Fracture Characterization and Modeling Workflow Fracture Parameters Analysis A detailed analysis of multiple fracture-related data types was conducted to characterize the fracture properties. These results are presented below. Outcrop data Outcrop data can provide regional scale features in terms of fracture density, length, aperture, dip, azimuth, sets, type and connectivity. Fracture aperture was found to be mostly <0.5 mm and more than 50% were not filled. Fractures were of the types tensile, shear and tensile-shear, and had good connectivity. Core data Fracture aperture, dip, type, density, length, sets, connectivity, porosity and permeability information for the sampled zones at the well locations can be obtained from core data (Aguilera (1988) and Nelson (2000)). In the study area, the apertures were mainly half-filled or unfilled, high angle and secondarily oblique and net-shaped. All apertures were <1.0 mm. Image log analysis This unconventional log has the advantage of directly detecting the fracture properties. It could provide details of the fracture azimuth, dip, aperture, density, and types surrounding the wellbore (Hirata (1989)). It also determines the locations and depths for identified fractures. Interpretation results of the imaging log in the study area show that the target layer is fracture-developed, which effectively improves the reservoir permeability. Seismic data analysis Seismic data are usually used for characterizing the fracture information between the wells. These data can be used to identify faults and large fractures. The fracture orientation and density may be characterized through the extraction of attributes or curvature from the 3D seismic (Murray (1977), Wang et al (2014)). The seismic data for the study area are relatively poor in quality, but because of spatial coverage, they could be helpful in understanding the fractures in-between the wells. Therefore, seismic data are corrected using well data. Horizons are also corrected by reflection events and wells. Based on the corrections, various seismic curvature attributes are extracted. Using a combination of multi-attributes and other information such as faults and well data, the fractures are characterized in-between the wells. This will provide a constraint for the subsequent the three-dimensional fracture density distribution volume and ultimately for the discrete fracture model. In addition, according to the current interpretation of the boundary faults and the internal secondary faults in the study area, the impact of the large boundary faults and the small internal faults on the fractures is analyzed (Zhou (1998)) (Figure 2 and Figure 3). Drilling data analysis Information from drilling such as mud loss, oil content in cuttings, exceptionally high permeability or wellbore collapse information may indicate the presence and stress orientation of a fracture-developed zone. Although drilling information is merely qualitative, it provides first-hand information that indicates the fractures. Well testing data analysis Fluid and pressure tests reveal fracture information, especially indicating fluid conductivity of the fracture and matrix systems. Tracer tests can determine the total effective permeability, fracture permeability, skin effect and connectivity. Pressure buildup test or interference tests can decide the fracture length and connectivity.