Robust rock properties through PP-PS processing and interpretation—Marcellus Shale

Chaveste, Alvaro; Zhao, Zhiyong; Altan, Suat; Gaiser, J.E.

doi:10.1190/tle32010086.1

Cited by 12 publications

(6 citation statements)

References 5 publications

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“…Figure 1 Illustrates the location of a 3D-3C survey acquired by Geokinetics Inc., and Geophysical Pursuit Inc. using dynamite sources covering 12.3 mi 2 (Chaveste et al, 2013). A subset of the processed PP (P-wave to P-wave) component is used.…”

Section: Geological Settingmentioning

confidence: 99%

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A novel prestack sparse azimuthal AVO inversion

Lasscock,

Sansal

2017

Preprint

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In this paper we demonstrate a new algorithm for sparse prestack azimuthal AVO inversion. A novel Euclidean prior model is developed to at once respect sparseness in the layered earth and smoothness in the model of reflectivity. Recognizing that methods of artificial intelligence and Bayesian computation are finding an every increasing role in augmenting the process of interpretation and analysis of geophysical data, we derive a generalized matrix-variate model of reflectivity in terms of orthogonal basis functions, subject to sparse constraints. This supports a direct application of machine learning methods, in a way that can be mapped back onto the physical principles known to govern reflection seismology. As a demonstration we present an application of these methods to the Marcellus shale. Attributes extracted using the azimuthal inversion are clustered using an unsupervised learning algorithm. Interpretation of the clusters is performed in the context of the Ruger model of azimuthal AVO.

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Section: Geological Settingmentioning

confidence: 99%

“…The complete group is decoupled from the deeper structures by the Silurian Salina salt formation. This produces shorter wavelength folds than deeper formations (Chaveste et al, 2013). The average gross thickness of the Marcellus is approximated to be around 80 ft.…”

Section: Geological Settingmentioning

confidence: 99%

A novel prestack sparse azimuthal AVO inversion

Lasscock,

Sansal

2017

Preprint

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“…Additionally, density is also the key to time-lapse monitoring of the carbon dioxide (CO 2 ) sequestrated reservoirs (Mukhopadhyay et al 2010). As the primary focus of the oil and gas industry is shifting from conventional to the unconventional reservoirs where the density is primarily related to the total organic content or TOC (Chaveste et al 2013), an accurate estimation of density in addition to P-and S-wave velocities/impedances is important. Because the mode-converted (P-SV) reflections are more sensitive to the variations in density compared to P-P reflections (Aki & Richards 2002), combining P-P with P-SV reflections in a multicomponent seismic inversion has been shown to estimate density better than the single component inversion (Mallick 2000;Padhi & Mallick 2013, among others).…”

Section: Introductionmentioning

confidence: 99%

Multicomponent pre-stack seismic waveform inversion in transversely isotropic media using a non-dominated sorting genetic algorithm

Padhi

Mallick

2013

Geophysical Journal International

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Inversion of band-and offset-limited single component (P wave) seismic data does not provide robust estimates of subsurface elastic parameters and density. Multicomponent seismic data can, in principle, circumvent this limitation but adds to the complexity of the inversion algorithm because it requires simultaneous optimization of multiple objective functions, one for each data component. In seismology, these multiple objectives are typically handled by constructing a single objective given as a weighted sum of the objectives of individual data components and sometimes with additional regularization terms reflecting their interdependence; which is then followed by a single objective optimization. Multi-objective problems, inclusive of the multicomponent seismic inversion are however non-linear. They have nonunique solutions, known as the Pareto-optimal solutions. Therefore, casting such problems as a single objective optimization provides one out of the entire set of the Pareto-optimal solutions, which in turn, may be biased by the choice of the weights. To handle multiple objectives, it is thus appropriate to treat the objective as a vector and simultaneously optimize each of its components so that the entire Pareto-optimal set of solutions could be estimated. This paper proposes such a novel multi-objective methodology using a non-dominated sorting genetic algorithm for waveform inversion of multicomponent seismic data. The applicability of the method is demonstrated using synthetic data generated from multilayer models based on a real well log. We document that the proposed method can reliably extract subsurface elastic parameters and density from multicomponent seismic data both when the subsurface is considered isotropic and transversely isotropic with a vertical symmetry axis. We also compute approximate uncertainty values in the derived parameters. Although we restrict our inversion applications to horizontally stratified models, we outline a practical procedure of extending the method to approximately include local dips for each source-receiver offset pair. Finally, the applicability of the proposed method is not just limited to seismic inversion but it could be used to invert different data types not only requiring multiple objectives but also multiple physics to describe them.

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“…August 21-24, 2016, Adelaide, Australia Chaveste et al (2013) estimate rock properties through P-and PS joint inversion from the Marcellus shale in Pennsylvania. They illustrate the potential risk reduction in qualitative estimation of total organic content (TOC) and fracture characterization.…”

Section: Aseg-pesa-aig 2016mentioning

confidence: 99%

P- and PS-wave vector wavefields for anisotropic petrophysics

Gaiser¹

2016

ASEG Extended Abstracts

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SUMMARYPredicting petrophysical properties of lithology, density and fractures using seismic data is an essential part of reservoir evaluation. In addition to lithology characterization, "frackability" has become a very important area of investigation for high-grading locations for drilling and hydraulic fracture stimulation. Most seismic studies that estimate P-and S-wave impedance, density and brittleness or formation strength use conventional P-wave data and isotropic elastic inversion methods. However, converted-wave (PS-wave) joint inversion and S-wave splitting methods have successfully been used to improve determination of seismic properties for shale plays as well as other unconventional resource plays.Anisotropic behaviour related to layered media (VTI), fracture properties, stress direction and the geomechanics of shales are increasingly more important for seismic analysis, imaging and reservoir characterization. Vector wavefields are sensitive to these properties and can help identify optimal drilling and stimulation locations. Also, it has been shown that use of conventional elastic parameters for characterizing "brittleness" should include anisotropic corrections to obtain a more accurate response. Including PSwave seismic data is beneficial for isotropic elastic inversion and should improve anisotropy estimates for identification of potential fracture locations.Elastic inversion of azimuthally anisotropic amplitude variations (AVAz) is also becoming more important. When layered media are fractured, orthorhombic symmetry of P-wave amplitude depends on S-wave birefringence. PS-waves are ideal for determining this Swave splitting information from layerstripping and their reflectivity provides additional equations for joint inversion with P-waves. Two coefficients, a radial R PSV and transverse R PSH reinforce anisotropic signatures similar to P-wave reflectivity R P . Vector wavefields contain all the necessary information for S-wave anisotropy from short wavelength AVAz as well as from long wavelength moveout behaviour.

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Robust rock properties through PP-PS processing and interpretation—Marcellus Shale

Cited by 12 publications

References 5 publications

A novel prestack sparse azimuthal AVO inversion

A novel prestack sparse azimuthal AVO inversion

Multicomponent pre-stack seismic waveform inversion in transversely isotropic media using a non-dominated sorting genetic algorithm

P- and PS-wave vector wavefields for anisotropic petrophysics

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