Fracture mapping and modelling in shale-gas target in the Cooper Basin, South Australia

Abstract

The success story of a shale-gas reserve development in the United States is triggering a strong industry focus towards similar plays in Australia. The Cooper Basin (located at the border of South Australia and Queensland) and the Otway Basin (extending both onshore and offshore South Australia and Victoria) could be prime targets to develop shale-gas projects. The Cooper Basin, a late-Carboniferous to mid-Triassic basin, is the largest onshore sedimentary basin producing oil and gas from tight conventional reservoirs with low permeability. Fracture stimulation programs are used extensively to produce the oil and gas. Furthermore, new exploration strategies are now targeting possible commercial gas hosted in low-permeability Permian shale units. To maximise production, the development of shale-gas prospects requires a good understanding of the: 1. structure of the reservoirs; 2. mechanical properties of the stratigraphy; 3. fracture geometry and density; 4. in-situ stress field; and, 5. fracture stimulation strategies. In this study, we use a combination of seismic mapping techniques–including horizon and attribute mapping, and an analysis of wellbore geophysical logs–to best constrain the existing fracture network in the basins. This study is based on the processing and analysis of a 3D seismic cube–the Moomba Big Lake survey–which is located in the southwestern part of the Cooper Basin. This dataset covers an area encompassing both a structurally complex setting in the vicinity of a major fault to the SE of the survey, and an area of more subtle deformation corresponding to the southernmost part of the Nappamerri Trough. Structural fabrics trending ˜NW–SE and NE–SW, which are not visible on the amplitude seismic data, are revealed by the analysis of the seismic attributes–namely a similarity (equivalent to a coherency cube), dip steering and maximum curvature attributes. These orientations are similar to those of natural fractures mapped from borehole images logs, and can therefore be interpreted as imaging natural fractures across the Moomba-Big Lake area. This study is the first of its kind able to detect possible fractures from seismic data in the Cooper Basin. The methodology developed here can offer new insights into the structure of sedimentary basins and provide crucial parameters for the development of tight reservoirs. In parallel, a tentative forward model of the generation of a fracture network following a restoration of the Top Roseneath horizon was carried out. The relatively good correlation between the fracture orientations generated by the model and the fractures mapped from geophysical data shows that fractures in the Moomba-Big Lake area may have formed during either a N–S compressive principal horizontal stress, or an E–W compressive principal horizontal tectonic stress regime. In addition, the orientations of the fracture interpreted through this study are also compatible with a generation under the present day stress regime described in this part of the basin, with an maximal horizontal stress trending E–W.

Relating permeability and electrical resistivity in fractures using random resistor network models

“…Unconventional oil and gas reservoirs are also often contained in low‐permeability rocks and therefore often rely on fractures for permeability. However, while larger faults (with lengths on the scale of several meters or more) can be detected using methods such as seismic reflection, they are not always permeable, and it can be difficult to determine their permeability without using drilling data [e.g., Backé et al , ; Bailey et al , ]. Moreover, it is often the minor faults, and the damage zones around major faults, which are not easily imaged using geophysical methods that provide much of the permeability [e.g., Caine et al , ].…”

Basement structural architecture and hydrocarbon conduit potential of polygonal faults in the Cooper‐Eromanga Basin, Australia

“…This research exploits a commonly used seismic attribute called incoherency, which was first introduced by Bahorich and Farmer (1995) and further developed by Gersztenkorn and Marfurt (1999). Incoherency visually emphasises the discrepancy between adjacent seismic traces along any given horizon or time slice that may otherwise be overlooked (Neves et al 2004;Mai et al 2009;Backé et al 2011;Basir et al 2013). Incoherency is most useful for structural interpretation because of its ability to highlight abrupt changes in amplitude along a reflector typically corresponding to faults.…”

“…Incoherency (also referred to as coherency and similarity) has become the most widely used seismic attribute due to its ability to visually enhance the discrepancies of adjacent seismic traces along a horizon, or time-slice, to infer the presence of faults (Neves, Zahrani and Bremkamp 2004;Mai, Marfurt and Chávez-Pérez 2009;Backé et al 2011;Basir, Javaherian and Yaraki 2013;Kulikowski et al 2016b). Improvements in seismic time-to-depth conversion methods have also enabled more accurate interpretation of faults and structural closures.…”

“…Seismic attribute analyses have developed to become a formidable tool in effective hydrocarbon exploration by highlighting subtle changes in seismic data that are not visible from the standard vertical section. Incoherency (also referred to as coherency and similarity) has become the most widely used seismic attribute due to its ability to visually enhance the discrepancies of adjacent seismic traces along a horizon, or time-slice, to infer the presence of faults (Neves, Zahrani and Bremkamp 2004;Mai, Marfurt and Chávez-Pérez 2009;Backé et al 2011;Basir, Javaherian and Yaraki 2013;Kulikowski et al 2016b). Following this rapid improvement in seismic imaging, this research revisits low-resolution seismic data to develop a modern structural model of the Cooper-Eromanga Basin consisting of basement faults that were previously difficult to identify and interpret.…”

Remote sensing of subsurface fractures in the Otway Basin, South Australia

“…Several methods exist for identifying natural fractures in the subsurface, most notably various wellbore geophysical and image logs, recovered core, and surface analogues [ Barton et al ., ]. Both 2‐D and 3‐D seismic amplitude data are also commonly used to identify geological structures, which are likely to be fractured; and recently, 3‐D seismic attribute analysis has been applied to identify zones of fractured rock [ Roberts , ; Backé et al ., , ]. However, while identifying natural fractures can often be relatively simple with basic oilfield data such as wellbore image logs, accurately characterizing the transport properties of fractures within rock is another matter entirely and is one fraught with uncertainty.…”