Articles written in Journal of Earth System Science

    • Laboratory measurements of ultrasonic wave velocities of rock samples and their relation to log data: A case study from Mumbai offshore


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      The characterization of the reservoir rock's geomechanical properties is critical to address wellbore instabilities and subsidence-related issues. To address these issues, lab-derived dynamic and static elastic properties are essential to match the in-situ rock properties. In this study, as part of a new integrated workflow P-wave and S-wave velocities are congregated using ultrasonic transducers for the core plugs, which constitutes mainly carbonates, shales, and both. Mineral composition, shale anisotropy, seismic velocities, and cross plots are studied to understand shear wave splitting. During this study, as a part of 1D mechanical Earth models, rock elastic properties are calculated for 60 wells using petrophysical logs (gamma, density, acoustic and caliper). Also, triaxial loading tests are conducted on 14 specimens collected from the same wells, static Poisson's ratio and static Young's modulus are computed from the stress-strain curves. The major differences are observed between static and dynamic elastic properties calculated from well logs and lab tests. Cohesion and friction angle for rock samples are estimated from the triaxial tests under different confining pressures. The objective of this study is to compare the elastic properties derived from the ultrasonic method with well logs and fill the gaps in the 1D geomechanical model. The combined analysis of elastic properties from different methods provides exciting insights on wellbore stability in anisotropic rock.

    • Lithofacies and Cuid prediction of a sandstone reservoir using pre-stack inversion and non-parametric statistical classification: A case study


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      This paper describes a case study that converts pre-stack seismic data into meaningful rock properties by employing non-parametric probability density functions through a probabilistic modelling approach. This study used the simultaneous pre-stack inversion method to transform pre-stack seismic data into seismic attributes like compressional impedance, shear impedance, density, and V$_P$/V$_S$ ratio. Then cross plot analysis was conducted on selected wireline log data to identify reservoir lithofacies zones based on the ranges of properties like P-impedance and V$_P$/V$_S$ ratio. Hydrocarbon zone was identified with the range of V$_P$/V$_S$ ratio between 1.15 and 1.82 and ZP from 3800 to 12400 ((m/s) 9 (g/cc)).Water bearing sand zone was separated with V$_P$/V$_S$ ratio with 1.85–2.12 and ZP with 3500–14900 ((m/s)9 (g/cc)), and 3500–14900 ((m/s)9(g/cc)) of Z$_P$, V$_P$/V$_S$ ratio between 2.14 and 3.1 was used to characterize the shale zone. A non-parametric kernel density estimator is used on cross-plot data points to generate a probability density function for each lithofacies. These non-parametric PDFs were incorporated with seismic attributes using a probabilistic modelling approach based on Bayes’ classification to generate a lithofacies model. The application of methodology provides a better insight into predicting and discriminating lithofacies in the study area.


      $\bullet$ Applied seismic inversion to obtain seismic elastic attributes such as compressional impedance (ZP), shear impedance (ZS), VP/VS ratio, and density.

      $\bullet$ Shale, water-bearing zone, and hydrocarbon zone were identified using the cross plot analysis of well log data.

      $\bullet$ Probability density functions (PDFs) for lithologies were generated on cross-plot space using the non-parameter statistical classification.

      $\bullet$ Finally, hydrocarbon zones were identified using the Bayes' rule by combining the seismic data with PDFs.

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