• Geomechanics and Engineering
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• v.13 no.1
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• pp.99-117
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• 2017

Rock physics modeling of sandstone reservoir from gas fields of Krishna-Godavari basin represents the link between reservoir parameters and seismic properties. The rock physics diagnostic models such as contact cement, constant cement and friable sand are chosen to characterize reservoir sands of two wells in this basin. Cementation is affected by the grain sorting and cement coating on the surface of the grain. The models show that the reservoir sands in two wells under examination have varying cementation from 2 to more than 6%. Distinct and separate velocity-porosity and elastic moduli-porosity trends are observed for reservoir zones of two wells. A methodology is adopted for generation of Rock Physics Template (RPT) based on fluid replacement modeling for Raghavapuram Shale and Gollapalli Sandstones of Early Cretaceous. The ratio of P-wave velocity to S-wave velocity (Vp/Vs) and P-impedance template, generated for this above formations is able to detect shale, brine sand and gas sand with varying water saturation and porosity from wells in the Endamuru and Suryaraopeta gas fields having same shallow marine depositional characters. This RPT predicted detection of water and gas sands are matched well with conventional neutron-density cross plot analysis.

• Economic and Environmental Geology
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• v.49 no.3
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• pp.225-242
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• 2016

Rock physics serves as a useful tool for seismic reservoir characterization and monitoring by providing quantitative relationships between rock properties and seismic data. Rock physics models can predict effective moduli for reservoirs with different mineral components and pore fluids from well-log data. The distribution of reservoirs and fluids for the entire seismic volume can also be estimated from rock physics models. The first part of this report discusses the Voigt, Reuss, and Hashin-Shtrikman bounds for effective elastic moduli and the Gassmann fluid substitution. The second part reviews various contact models for moderate- to high-porosity sands. In the third part, constant-cement model, known to work well for the sand that gradually loses porosity with deteriorating sorting, was applied to the well-log data from an oil field in the North Sea. Lastly, the rock physics template constructed from the constant-cement model and the results from the prestack inversion of 2D seismic data were combined to predict the lithology and fluid types for the sand reservoir of this oil field.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.173-178
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• 2008

In this paper, we will introduce rock physics modeling technique, which interrelate reservoir properties with seismic properties, and apply the technique to the Donghae-1 gas reservoir. From well-log data analysis, we obtained velocityporosity (Vp-$\phi$) relations for each formation. These relations can used to predict porosity from seismic data. In addition, we analyzed permeability data, which were obtained from core measurements and computational rock physics simulations. We then obtained permeability-porosity ($\kappa-\phi$) relations. Combining $\kappa-\phi$ with Vp-$\phi$ relations, we finally present quantitative Vp-$\kappa$ relations. As to Vp-$\phi$ modeling, we found that the degree of diagenesis and clay contents increase with depth. As to Vp-$\kappa$ relations, though \kappa-\phi relations are almost identical for all formations, we could obtain distinct Vp-$\kappa$ relations due to Vp-$\phi$ variations. In conclusion, the rock physics modeling, which bridges between seismic properties and reservoir properties, can be a very robust tool for quantitative reservoir characterization with less uncertainty.

• 한국지구물리탐사학회:학술대회논문집
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• 2011.10a
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• pp.183-186
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• 2011

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1747-1753
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• 2024

The accurate determination of formation density and the physical properties of rocks is the most critical logging tasks which can be obtained using gamma-ray transport and detection tools. Though the simulation works published so far have considerably improved the knowledge of the parameters that govern the responses of the detectors in these tools, recent studies have found considerable differences between the results of using a conventional model of a homogeneous mixture of formation and fluid and an inhomogeneous fractured medium. It has increased concerns about the importance of the complexity of the model used for the medium in simulation works. In the present study, we have suggested two various models for the flow of the fluid in porous media and fractured rock to be used for logging purposes. For a typical gamma-gamma logging tool containing a ¹³⁷Cs source and two NaI detectors, simulated by using the MCNPX code, a simplified porous (SP) model in which the formation is filled with elongated rectangular cubes loaded with either mineral material or oil was investigated. In this model, the oil directly reaches the top of the medium and the connection between the pores is not guaranteed. In the other model, the medium is a large 3-D matrix of 1 cm³ randomly filled cubes. The designed algorithm to fill the matrix sites is so that this realistic random (RR) model provides the continuum growth of oil flow in various disordered directions and, therefore, fulfills the concerns about modeling the rock textures consist of extremely complex pore structures. For an arbitrary set of oil concentrations and various formation materials, the response of the detectors in the logging tool has been considered as a criterion to assess the effect of modeling for the distribution of pores in the formation on simulation studies. The results show that defining a RR model for describing heterogeneities of a porous medium does not effectively improve the prediction of the responses of logging tools. Taking into account the computational cost of the particle transport in the complex geometries in the Monte Carlo method, the SP model can be satisfactory for gamma-gamma logging purposes.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.201-206
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• 2006

Earth sciences is undergoing a gradual but massive shift from description of the earth and earth systems, toward process modeling, simulation, and process visualization. This shift is very challenging because the underlying physical and chemical processes are often nonlinear and coupled. In addition, we are especially challenged when the processes take place in strongly heterogeneous systems. An example is two-phase fluid flow in rocks, which is a nonlinear, coupled and time-dependent problem and occurs in complex porous media. To understand and simulate these complex processes, the knowledge of underlying pore-scale processes is essential. This paper presents a new attempt to use pore-scale simulations for understanding physical properties of rocks. A rigorous pore-scale simulator requires three important traits: reliability, efficiency, and ability to handle complex microstructures. We use the Lattice-Boltzmann (LB) method for singleand two-phase flow properties, finite-element methods (FEM) for elastic and electrical properties of rocks. These rigorous pore-scale simulators can significantly complement the physical laboratory, with several distinct advantages: (1) rigorous prediction of the physical properties, (2) interrelations among the different rock properties in a given pore geometry, and (3) simulation of dynamic problems, which describe coupled, nonlinear, transient and complex behavior of Earth systems.

• Geomechanics and Engineering
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• v.17 no.4
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• pp.343-354
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• 2019

The present study demonstrates the application of seismic petrophysics and amplitude versus angle (AVA) forward modeling to identify the reservoir fluids, discriminate their saturation levels and natural gas composition. Two case studies of the Lumshiwal Formation (mainly sandstone) of the Lower Cretaceous age have been studied from the Kohat Sub-basin and the Middle Indus Basin of Pakistan. The conventional angle-dependent reflection amplitudes such as P converted P ($R_{PP}$) and S ($R_{PS}$), S converted S ($R_{SS}$) and P ($R_{SP}$) and newly developed AVA attributes (${\Delta}R_{PP}$, ${\Delta}R_{PS}$, ${\Delta}R_{SS}$ and ${\Delta}R_{SP}$) are analyzed at different gas saturation levels in the reservoir rock. These attributes are generated by taking the differences between the water wet reflection coefficient and the reflection coefficient at unknown gas saturation. Intercept (A) and gradient (B) attributes are also computed and cross-plotted at different gas compositions and gas/water scenarios to define the AVO class of reservoir sands. The numerical simulation reveals that ${\Delta}R_{PP}$, ${\Delta}R_{PS}$, ${\Delta}R_{SS}$ and ${\Delta}R_{SP}$ are good indicators and able to distinguish low and high gas saturation with a high level of confidence as compared to conventional reflection amplitudes such as P-P, P-S, S-S and S-P. In A-B cross-plots, the gas lines move towards the fluid (wet) lines as the proportion of heavier gases increase in the Lumshiwal Sands. Because of the upper contacts with different sedimentary rocks (Shale/Limestone) in both wells, the same reservoir sand exhibits different response similar to AVO classes like class I and class IV. This study will help to analyze gas sands by using amplitude based attributes as direct gas indicators in further gas drilling wells in clastic successions.

• Geophysics and Geophysical Exploration
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• v.18 no.3
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• pp.143-153
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• 2015

Polymer flooding for enhancing hydrocarbon production injects into a reservoir polymer solution that is viscous. It is very important to monitor the behavior pattern of the polymer solution in order to evaluate the effectiveness of polymer flooding. To monitor the distribution of polymer solution and thus fluid substitution within the reservoir, we first construct seismic and resistivity rock physics models (RPMs), which are functions of reservoir parameters such as rocks and type of fluid, fluid saturation. For the seismic and resistivity RPMs, responses of seismic and electromagnetic (EM) tomography are numerically simulated as polymer injection, using two dimensional (2D) staggered-grid finite difference elastic modeling and 2.5D finite element EM modeling algorithms, respectively. In constructing RPM for EM tomography, three different reservoir rocks are considered: clean-sand, dispersed shale-sand, and sand-shale lamination rocks. The polymer solution is assumed to have 2 wt% of polymer as normally generated, while water is freshwater or saltwater. Further, neutron logging is also considered to check its sensitivity to polymer flooding. The techniques discussed in the paper are important in monitoring not only hydrocarbon but also geothermal reservoirs.