Seismic Characterization of the Eagle Ford Shale Based on Rock Physics
Seismic Characterization of the Eagle Ford Shale Based on Rock Physics

Author: Ricardo Zavala-Torres

Publisher:

Published: 2014

Total Pages:

ISBN-13:

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The findings of this dissertation on seismic characterization of the Eagle Ford Shale based on rock physics using actual well-log data from productive and unproductive wells in Mexico can be immediately and effectively applied to avoid future failures and can be corroborated with current and new locations for exploration and production. It was found that basic sequence stratigraphy techniques developed for unconventional reservoirs can be applied to the case of the Eagle Ford Shale in Mexico. Using well log correlation and petrophysical techniques to estimate reservoir properties, it was concluded that the zone where the horizontal well was drilled at Montanes-1 was located above the condensed sequence, bypassing the pay zone below the maximum flooding surface in the transgressive system track. It is verified that the productive well Emergente-1 was drilled in the correct zone with hydrocarbon saturation at the transgressive system track below the maximum flooding surface. It was found that using mineral assessment methods to compute brittleness, and the proper geosteering analysis is a consistent approach for placement of future horizontals. Based on that, it is concluded that any estimation of rock physics and anisotropic parameters derived from well logs at the source rock interval will be deceiving and will give a false estimation. It was concluded that the isotropic rock physic model known as friable-sand or modified friable-shale (unconsolidated sand or unconsolidated shale), or most recently called “soft-sand model”, was proved to match the data better than any other rock physic model tested to predict velocity and density. The term “non-source rock model” will be used instead for the rock physic model because it is more consistent with the Eagle Ford Shale case analyzed here. For the orientation of maximum horizontal stress, it is concluded by integrating VSP, microseismic and borehole data, that a straight north-south orientation of future horizontals is needed in order to generate the fractures in the straight east-west azimuth correlating with the maximum horizontal stress orientation.

Anisotropic Seismic Characterization of the Eagle Ford Shale
Anisotropic Seismic Characterization of the Eagle Ford Shale

Author: Qi Ren

Publisher:

Published: 2016

Total Pages: 214

ISBN-13:

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Quantitative reservoir characterization using integrated seismic data and well log data is important in sweet spot identification, well planning, and reservoir development. The process includes building up the relations between rock properties and elastic properties through rock physics modeling, inverting for elastic properties from seismic data, and inverting for rock properties from both seismic data and rock physics models. Many quantitative reservoir characterization techniques have been developed for conventional reservoirs. However, challenges remain when extending these methods to unconventional reservoirs because of their complexity, such as anisotropy, micro-scale fabric, and thin beds issues. This dissertation focuses on developing anisotropic rock physics modeling method and seismic inversion method that are appliable for unconventional reservoir characterization. The micro-scale fabric, including the complex composition, shape and alignment of clay minerals, pore space, and kerogen, significantly influences the anisotropic elastic properties. I developed a comprehensive three-step rock-physics approach to model the anisotropic elastic properties, accounting for the micro-scale fabric. In addition, my method accounts for the different pressure-dependent behaviors of P-waves and S-waves. The modeling provides anisotropic stiffnesses and pseudo logs of anisotropy parameters. The application of this method on the Upper Eagle Ford Shale shows that the clay content kerogen content and porosity decrease the rock stiffness. The anisotropy increases with kerogen content, but the influence of clay content is more complex. Comparing the anisotropy parameter pseudo logs with clay content shows that clay content increases the anisotropy at small concentrations; however, the anisotropy stays constant, or even slightly decreases, as clay content continues to increase. Thin beds and anisotropy are two important limitation of the application of seismic characterization on unconventional reservoirs. I introduced the geostatistics into stochastic seismic inversion. The geostatistical models, based on well log data, simulate small-scale vertical variations that are beyond seismic resolution. This additional information compensates the seismic data for its band-limited nature. I applied this method on the Eagle Ford Shale, using greedy annealing importance sampling as inversion algorithm. The thin Lower Eagle Ford Formation, which cannot be resolved by conventional inversion method, is clearly resolved in the inverted impedance volume using my method. In addition, because anisotropy is accounted for in the forward modeling, the accuracy of inverted S-impedance is significantly improved.

Seismic Petrophysics in Quantitative Interpretation
Seismic Petrophysics in Quantitative Interpretation

Author: Lev Vernik

Publisher: SEG Books

Published: 2016-10-15

Total Pages: 227

ISBN-13: 156080324X

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Exploration and characterization of conventional and unconventional reservoirs using seismic technologies are among the main activities of upstream technology groups and business units of oil and gas operators. However, these activities frequently encounter difficulties in quantitative seismic interpretation due to remaining confusion and new challenges in the fast developing field of seismic petrophysics. Seismic Petrophysics in Quantitative Interpretation shows how seismic interpretation can be made simple and robust by integration of the rock physics principles with seismic and petrophysical attributes bearing on the properties of both conventional (thickness, net/gross, lithology, porosity, permeability, and saturation) and unconventional (thickness, lithology, organic richness, thermal maturity) reservoirs. Practical solutions to existing interpretation problems in rock physics-based amplitude versus offset (AVO) analysis and inversion are addressed in the book to streamline the workflows in subsurface characterization. Although the book is aimed at oil and gas industry professionals and academics concerned with utilization of seismic data in petroleum exploration and production, it could also prove helpful for geotechnical and completion engineers and drillers seeking to better understand how seismic and sonic data can be more thoroughly utilized.

Seismic Reservoir Characterization of the Haynesville Shale
Seismic Reservoir Characterization of the Haynesville Shale

Author: Meijuan Jiang

Publisher:

Published: 2014

Total Pages: 0

ISBN-13:

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This dissertation focuses on interpreting the spatial variations of seismic amplitude data as a function of rock properties for the Haynesville Shale. To achieve this goal, I investigate the relationships between the rock properties and elastic properties, and calibrate rock-physics models by constraining both P- and S-wave velocities from well log data. I build a workflow to estimate the rock properties along with uncertainties from the P- and S-wave information. I correlate the estimated rock properties with the seismic amplitude data quantitatively. The rock properties, such as porosity, pore shape and composition, provide very useful information in determining locations with relatively high porosities and large fractions of brittle components favorable for hydraulic fracturing. Here the brittle components will have the fractures remain opened for longer time than the other components. Porosity helps to determine gas capacity and the estimated ultimate recovery (EUR); composition contributes to understand the brittle/ductile strength of shales, and pore shape provides additional information to determine the brittle/ductile strength of the shale. I use effective medium models to constrain P- and S-wave information. The rock-physics model includes an isotropic and an anisotropic effective medium model. The isotropic effective medium model provides a porous rock matrix with multiple mineral phases and pores with different aspect ratios. The anisotropic effective medium model provides frequency- and pore-pressure-dependent anisotropy. I estimate the rock properties with uncertainties using grid searching, conditioned by the calibrated rock-physics models. At well locations, I use the sonic log as input in the rock-physics models. At areas away from the well locations, I use the prestack seismic inverted P- and S-impedances as input in the rock-physics models. The estimated rock properties are correlated with the seismic amplitude data and help to interpret the spatial variations observed from seismic data. I check the accuracy of the estimated rock properties by comparing the elastic properties from seismic inversion and the ones derived from estimated rock properties. Furthermore, I link the estimated rock properties to the microstructure images and interpret the modeling results using observations from microstructure images. The characterization contributes to understand what causes the seismic amplitude variations for the Haynesville Shale. The same seismic reservoir characterization procedure could be applied to other unconventional gas shales.

Rock-physics and 3C-3D Seismic Analysis for Reservoir Characterization
Rock-physics and 3C-3D Seismic Analysis for Reservoir Characterization

Author: Fabiola Del Valle Ruiz Pelayo

Publisher:

Published: 2016

Total Pages:

ISBN-13:

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The elastic properties (density and velocity) of organic shales are largely controlled by kerogen content, porosity, clay content, and e ective pressure. Since surface-seismic measurements can have a complicated dependence on rock properties, it is essential to understand the relationship between the elastic response and variations in rock properties to correctly assess the target reservoir. In this sense, a combination of rock-physics and seismic modeling is applied to relate variations in key properties, such as kerogen content and porosity, to di erences in the elastic response of a 3C-3D seismic volume in the Marcellus Shale (Bradford County, Pennsylvania). Well log analysis and rock physics modeling indicate that density is more sensitive to kerogen content than Vp/Vs or P impedance. Organic-rich intervals (kerogen content > 6 wt. %) are characterized by densities lower than 2.5 g/cc. Vp/Vs and P-impedance are more sensitive to variations in clay content than density; Vp/Vs values lower than 1.6 are attached to clay content lower than 25 %. The interplay between mineralogy and kerogen content causes an increase in velocity in the organic-rich interval, where the e ect of kerogen on the elastic moduli seems to be masked by a decrease in clay content and increase in quartz and calcite. Elastic AVA modeling shows that the sensitivity to the presence of the organic-rich facies increases with angle for both PP and PS (converted-wave) reflections. Additionally, the compressibility seems to be more sensitive to the organic-rich facies than the rigidity. A comparison between PP and PP-PS inversions show that the addition of PS data decreases the P-impedance, S-impedance and density estimation errors by 58, 80, and 17 %, respectively. We used this procedure to create 3D-density maps to indicate promising reservoir quality. These predictions suggest good reservoirs where two gas wells (not used in the analysis) are producing.

Rock Properties, Seismic Modeling, and 3C Seismic Analysis in the Bakken Shale, North Dakota
Rock Properties, Seismic Modeling, and 3C Seismic Analysis in the Bakken Shale, North Dakota

Author: Andrea Gloreinaldy Paris Castellano

Publisher:

Published: 2017

Total Pages:

ISBN-13:

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A solid understanding of the factors that affect the seismic velocity and the amplitude variation with offset (AVO) is imperative for a reliable interpretation of seismic data and related prospect de‐risking. To understand the relationship between rock properties and their elastic response (i.e. velocity and density), petrophysical properties, rock‐physics, seismic modeling, and fluid substitution are analyzed. Seismic inversions and statistical predictions of rock properties are integrated to delimit prospective intervals and areas with high total organic carbon (TOC) content within the Bakken Formation, North Dakota. The shale intervals can be recognized by cross‐plotting well logs velocities versus density. The hydrocarbon potential is observed on logs as low densities, high gamma‐ray response, low P and S‐wave velocities, and high neutron porosities. Organicrich intervals with TOC content higher than 10 wt. % deviate from the ones that have lower TOC in the density domain, and exhibit slightly lower velocities, lower densities ( 2.3 g/cc), and a generally higher shale content ( 40%). Within the study area, Well V‐1 shows the highest TOC content, especially at the Upper Bakken depths with approximately 50% of clay volume. TOC is considered to be the principal factor affecting changes in density and P and S‐wave velocities in the Bakken shales. Vp/Vs ranges between 1.65 and 1.75. Synthetic seismic data are generated using the anisotropic version of Zoeppritz equations including estimated Thomsen parameters. For the tops of Upper and Lower Bakken, the amplitude becomes less negative with offset showing a negative intercept and a positive gradient which correspond to an AVO Class IV. A comparison between PP and PP‐PS joint inversions shows that the P‐impedance error decreases by 14% when incorporating the converted‐wave information in the inversion process. A statistical approach using multi‐attribute analysis and neural networks allows to delimit the zones of interest in terms of P‐impedance, density, TOC content, and brittleness. The inverted and predicted results show fair correlations with the original well logs. The integration between well‐log analysis, rock‐physics, seismic modeling, constrained inversions and statistical predictions contribute in identifying the vertical distribution of good reservoir quality areas within the Bakken Formation.