Petrophysical evaluation and uncertainty analysis of Roseneath and Murteree shales reservoirs in Cooper Basin, Australia (a case study)

Abstract

This study investigates petrophysical characteristics of lacustrine Permian Murteree and Roseneath shales in relation to reservoir evaluation of the most prospective gas shale plays in the Cooper Basin, Australia. Both shales were investigated for gas volumes by employing unconventional petrophysical techniques through a combination of source rock parameters acquired by geochemical analysis, and integrating the extracted parameters into log interpretation and core studies. Modeling mineralogical composition using wireline logs require the selection of a proper mineral model. In this study, the mineral model was built in the Interactive Petrophysics (IP's) Mineral Solver module by integrating all regional sedimentological, petrographic, SEM (Scanning electronic microscope), pulse decay and X-ray diffraction data (XRD) from core and chip cutting samples. This study developed a mineral grouping framework to assist in the selection of a proper model to easily solve complex shale gas reservoirs for gas volumes. Furthermore, the permeability of both shales depends on insitu confining stress and permeability of these cores and can be calculated through decay rate of a pressure pulse applied to experimental data. Subsequent to the integrated study as explained above, it is concluded on the basis of extruded parameters (shale porosity, permeability, volume of kerogen, volume of brittle minerals and water saturation) that Murteree formation exhibits better potential than Roseneath formation in and around Nappameri, Patchawarra and Tenappera troughs, while poor potential is exhibited in the Allunga trough. The only location where Roseneath exhibits better potential is in Encounter-01 well.

Unconventional Reservoir Characterization of Patala Formation, Upper Indus Basin, Pakistan

“…Density, neutron, and other logs commonly can be used to calculate porosity, whereas shale and its organic component affect the density. 48 Estimating total porosity in shale gas reservoirs poses a challenge due to high clay minerals and fine-grained texture. 49 Log porosity was used to generate a distribution map and to understand the regional porosity behavior.…”

Quantitative Characterization of Elastic Parameters and Its Implications for Reservoir Evaluation: A Case Study on High Clay-rich Continental Shale

“…The application of an integrated petrophysical evaluation method, incorporating multiple advanced wireline logs and core data, has demonstrated successful implementation in the field of shale oil. 36 However, this method is excessively intricate, and it remains worthwhile to endeavor determining the optimal production layer in a more streamlined manner. In response to the limitations of the aforementioned research, this paper has undertaken three aspects of work: (1) applying experimental data of acoustic velocity anisotropy from Gulong shale and systematically analyzing the accuracy of different prediction models to select the most superior elastic coefficient prediction model for Gulong shale, (2) analyzing the causes of anisotropy and its impact on elastic parameters and geostress, and (3) establishing a methodology for evaluating sweet spots through elastic parameters.…”

“…Furthermore, while it is widely acknowledged that organic shale exhibits elastic anisotropy, the impact of this anisotropy on elastic parameters remains ambiguous. The application of an integrated petrophysical evaluation method, incorporating multiple advanced wireline logs and core data, has demonstrated successful implementation in the field of shale oil . However, this method is excessively intricate, and it remains worthwhile to endeavor determining the optimal production layer in a more streamlined manner.…”