Earth Modeling
TGS has the technology, expertise
Though present over large areas, optimization of well location and completion and stimulation designs remain critical to successful exploitation. Reservoir characterization, encompassing rock properties, petrophysical, geological, geochemical, geomechanical, measurements, maturity
The goals for seismic characterization of resource plays include the determination of lateral variations of elastic and petrophysical properties within rock units. The understanding of how these relate to
Any shale resource characterization exercise beings with a discussion on requirements for the different available data types that would be employed in the workflow, including seismic, rock properties, petrophysical, geological, geochemical, geomechanical, measurements, maturity
Correlation of W-2
For a shale resource play to be successful, an optimum combination of depth, maturation, organic content, thickness, mineralogy, permeability, pore-pressure
Most of the above key elements may be determined easily at the location of the wells, but the challenge is to determine them from seismic data to understand their spatial variation.
Crossplot between E-rho and Poisson’s ratio for well W-1 broadly covering the Duvernay interval. The cluster of points enclosed by the red polygon appears to be anomalous and its back projection to the
Crossplot of E-rho versus Poisson’s ratio attributes derived from P- and S-impedance values derived using prestack joint inversion, for data selected along
Effective propagation of complex fractures in the formations of interest is dependent on the rock’s ability to fail in a brittle manner. Consequently, various methods for
A combination of Young’s modulus (
Usually, determination of density from seismic data is difficult due to the requirement of large offsets or angles. With this in mind, a new attribute E-rho (product of Young’s modulus and density) was developed at TGS, which eliminates the requirement of long offsets. As both Young’s modulus and density are expected to be high for a brittle rock, E-rho should also exhibit a high value for such a rock.
Crossplots of E-rho and Poisson’s ratio are first plotted from well log data for the zone of interest, and a cluster of points corresponding to high E-rho and low Poisson’s ratio
Back-projection of marked off clusters on the
At TGS, various projects have been carried out that span most of the prominent shale formations in North America and Argentina. If the
In addition, analysis and comparison of such
A more meaningful way out of such a confusing scenario is to describe shale zones in terms of their resistance to fracture growth. Such a measure of rock resistance to fracture growth is referred to as fracture toughness. A rock with low fracture toughness would promote fracture propagation.
Horizon slice from a volume of inverse fracture toughness measure from the Duvernay formation in the Fox Creek area in central Alberta, Canada. Notice the high values of inverse fracture toughness measure or low values of fracture toughness measure correlate well with the induced seismicity data overlaid on the display. Induced seismicity data is courtesy of Repsol Oil and Gas, Canada.
Once the desired attribute has been obtained after use of the appropriate transform, it can be visualized for capturing the sweet spots. Such an exercise includes determination of sweet spots corresponding to organic richness.
Crossplots of ΔlogR with (a) P-impedance, (b) μρ, (c) λρ, (d) λ/λ+2μ. A large scatter of data points is seen on three of the
In the display below,
Horizon slice from the ΔlogR volume 10 ms interval below the Duvernay top marker. High values of
Usually, when pairs of attributes derived from well log data are evaluated in
Crossplot between AI and Gamma Ray attributes for the Vaca Muerta shale in Neuquén Basin in Argentina. Probability density functions for three
Usually, when pairs of attributes derived from well log data are evaluated in
An arbitrary line through the acoustic impedance volume passing through five wells. The acoustic impedance volume
(Above):
(Below):
(a) The TOC values obtained from measurements on core samples over the zone of interest are shown in the form of a curve (red). This was a blind well test. Overlaid on this curve is the ΔlogR curve (blue) obtained by inversion of the seismic data. The match is seen as good as the increasing and decreasing trends follow each other reasonably well; (b) a
References
Al-Dossary, S., and K. J. Marfurt, 2006, 3-D volumetric multispectral estimates of reflector curvature and rotation: Geophysics, 71, 41–51.
Chopra, S., and K. J. Marfurt, 2007, Seismic attributes for prospect identification and reservoir characterization, Geophysical Development Series, SEG.
Fatti, J. L., P. J. Vail, G. C. Smith, P. J. Strauss, and P. R. Levitt, 1994, Detection of gas in sandstone reservoirs using AVO analysis: A 3-D seismic case history using the
Goodway, B., T. Chen, and J. Downton, 1997, Improved AVO fluid detection and lithology discrimination using Lame petrophysical parameters; 'λρ, 'μρ', & 'λ/μ’ fluid stack' from P and S inversions: 67th Annual International Meeting, SEG, Expanded Abstracts, 183-186.
Goodway, B., 2001, AVO and Lame' constants for rock parameterization and fluid detection: Recorder, 26, no. 6, 39–60.
Roberts, A., 2001, Curvature attributes and their application to 3D interpreted horizons. First Break, 19, 85–99.
TGS has the technology, expertise
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