Vaca Muerta Sequence Stratigraphy and Volcanic Intrusions: Impact on Unconventional Project Development

Fantin, Manuel; Tomassini, Federico González; Hernán, .; Reijenstein,; Christopher, Lipinski

doi:10.15530/urtec-2014-1923793

Cited by 5 publications

(1 citation statement)

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“…Based on the subsurface data from the electrical and acoustic log curves, mud-logging data, and borehole images, extensive facies studies have been carried out in the Neuquén Basin. It has been found that the Vaca Muerta (VM) Formation comprises a variety of lithologies that include organic-rich calcareous shales, marls, carbonates, calcareous sandstones, and sandstones (Fantin et al, 2014;Ortiz Sagasti et al, 2014;Sylwan, 2014).…”

Section: Introductionmentioning

confidence: 99%

Reducing uncertainty in characterization of Vaca Muerta Formation Shale with poststack seismic data

Sharma

Chopra

Vernengo³

et al. 2015

The Leading Edge

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The Late Jurassic-Early Cretaceous Vaca Muerta (VM) Formation in the Neuquén Basin has served as an important source rock for many of the conventional oil and gas fields in Argentina. With the interest in developing and exploiting shale resources in the country, many companies there have undertaken characterization of the VM Formation in terms of the elements of shale plays. Among other characteristics, shale plays can be identified based on the total-organic-carbon (TOC) content; better TOC leads to better production. However, there is no way of measuring it directly using seismic data, and it can be estimated only indirectly. Considering the influence of TOC on compressional and shear velocities and density, geoscientists have attempted to compute it using the linear or nonlinear relationship it might have with P-impedance. Understanding the uncertainty in using such a relationship for characterizing the VM Formation, a different approach has been followed for characterizing it. Because a linear relationship seems to exist between gamma ray (GR) and TOC, in addition to P-impedance, gamma ray is another parameter of interest for characterizing the VM Formation. Using P-impedance and GR volumes, a Bayesian classification approach has been followed to obtain a reservoir model with different facies based on TOC and the associated uncertainty with it. As the first step, different facies were defined, based on the cutoff values for GR and P-impedance computed from well-log data. Then Gaussian ellipses were used to capture the distribution of data in a crossplot of GR versus P-impedance. Next, 2D probability density functions (PDFs) were created from the ellipses for each of the facies. Combining these PDFs with GR and P-impedance volumes, different facies were identified on the 3D volume. Poststack model-based inversion was used to compute the P-impedance volume, and the probabilistic neural-network (PNN) approach was used to compute GR volume. Derived P-impedance and GR volumes correlated nicely at blind wells on the 3D volume, which gave confidence in the characterization of the VM Formation. An overlay of the discontinuity detail in terms of curvature lineaments on the determined TOC content at the level of interest helps in obtaining a more complete picture, which is useful for the planning of horizontal wells.

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Section: Introductionmentioning

confidence: 99%

Reducing uncertainty in characterization of Vaca Muerta Formation Shale with poststack seismic data

Sharma

Chopra

Vernengo³

et al. 2015

The Leading Edge

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Elastic parameter estimation for the identification of sweet spots, Vaca Muerta Formation, Neuquén Basin, Argentina

Convers

Hanitzsch²,

Curia³

et al. 2017

The Leading Edge

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Early identification of zones with possible good production (“sweet spots”) in shale plays is important to optimize the return on capital investment. Analyzing elastic rock properties helps in the identification of sweet spots in the Vaca Muerta Formation. The vertical and lateral heterogeneity of total organic carbon (TOC) and carbonate content are two critical factors that partly control the geomechanical response of the rock. Unconventional reservoirs have low permeability, making it necessary to define brittle zones to stimulate the rock and induce fractures to produce. This leads to the definition of mineralogy ranges that help discriminate brittle and ductile rock based on rock properties. This study is based on a 3D seismic survey and several vertical pilot wells with full log suites. Horizon interpretations and logs are used to build a low-frequency model that together with prestack seismic data is input for seismic inversion. Inversion results predict Poisson's ratio (v) directly, and TOC, carbonate content, density (ρ), and Young's modulus (E) are obtained through a neural network approach. The product (Eρ) is an alternative parameter to describe brittle rock when ρ cannot be obtained reliably. As elastic parameters, E and v are related to the geomechanical response of the rock, aiding in the discrimination of brittle and ductile rock. An inverse relationship between TOC and E is observed and quantified, but the relationship is very poor with v. Likewise, a direct relationship between carbonate content and E is identified but not with v. E plays the largest role in the identification of brittle rock within the Vaca Muerta Formation. Rock-physics relationships to describe sweet spots (zones with hydrocarbon presence and brittle rock) differ between shale plays around the world. The detailed 3D model from seismic inversion and clustering makes it possible to determine the best zones for placement of schematic horizontal wells.

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Where is the Vaca Muerta Sweet Spot? The Importance of Regional Facies trends, Thickness Variations and Thermal Maturity in Generating Play Concepts

Reijenstein

Christopher

Fantin³

et al. 2015

Proceedings of the 3rd Unconventional Resources Technology Conference

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Vaca Muerta Sequence Stratigraphy and Volcanic Intrusions: Impact on Unconventional Project Development

Cited by 5 publications

References 0 publications

Reducing uncertainty in characterization of Vaca Muerta Formation Shale with poststack seismic data

Reducing uncertainty in characterization of Vaca Muerta Formation Shale with poststack seismic data

Elastic parameter estimation for the identification of sweet spots, Vaca Muerta Formation, Neuquén Basin, Argentina

Where is the Vaca Muerta Sweet Spot? The Importance of Regional Facies trends, Thickness Variations and Thermal Maturity in Generating Play Concepts

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