Dipole Sonic Log Calibration using Walkaway VSP data

Karrenbach, Martin; Primiero, P.; Donald, Adam; Knight, Edward J.; Sayers, Colin M.; Koster, Klaas; Keir, Donald

doi:10.1190/1.3513777

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…Anisotropy parameters are computed utilizing different methods such as core velocity measurement at different angles (0, 45 and 90 degrees), sonic logs from deviated wells, walkaway vertical seismic profiling (VSP) and Backus averaging using well logs (Li, 2006;Liner and Fei, 2006;Horne et al, 2010). Backus (1962) proposed methodology to calculate effective stiffness parameters for a horizontally fine layered medium comprising isotropic or anisotropic elastic layers.…”

Section: A N I S Ot Ro P I C Pa R a M E T E R S E S T I M At I O N ( mentioning

confidence: 99%

Lithology‐dependent seismic anisotropic amplitude variation with offset correction in transversely isotropic media

Babasafari

Ghosh

Salim

et al. 2020

Geophysical Prospecting

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Analysis of amplitude variation with offset is an essential step for reservoir characterization. For an accurate reservoir characterization, the amplitude obtained with an isotropic assumption of the reservoir must be corrected for the anisotropic effects. The objective is seismic anisotropic amplitude correction in an effective medium, and, to this end, values and signs of anisotropic parameter differences (Δδ and Δε) across the reflection interfaces are needed. These parameters can be identified by seismic and well log data. A new technique for anisotropic amplitude correction was developed to modify amplitude changes in seismic data in transversely isotropic media with a vertical axis of symmetry. The results show that characteristics of pre‐stack seismic data, that is, amplitude variation with offset gradient, can be potentially related to the sign of anisotropic parameter differences (Δδ and Δε) between two layers of the reflection boundary. The proposed methodology is designed to attain a proper fit between modelled and observed amplitude variation with offset responses, after anisotropic correction, for all possible lithofacies at the reservoir boundary. We first estimate anisotropic parameters, that is, δ and ε, away from the wells through Backus averaging of elastic properties resulted from the first pass of isotropic pre‐stack seismic inversion, on input data with no amplitude correction. Next, we estimate the anisotropic parameter differences at reflection interfaces (values and signs of Δδ and Δε). We then generate seismic angle gather data after anisotropic amplitude correction using Rüger's equation for the P‐P reflection coefficient. The second pass of isotropic pre‐stack seismic inversion is then performed on the amplitude‐corrected data, and elastic properties are estimated. Final outcome demonstrates how introduced methodology helps to reduce the uncertainty of elastic property prediction. Pre‐stack seismic inversion on amplitude‐corrected seismic data results in more accurate elastic property prediction than what can be obtained from non‐corrected data. Moreover, a new anisotropy attribute (ν) is presented for improvement of lithology identification.

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Section: A N I S Ot Ro P I C Pa R a M E T E R S E S T I M At I O N ( mentioning

confidence: 99%

Lithology‐dependent seismic anisotropic amplitude variation with offset correction in transversely isotropic media

Babasafari

Ghosh

Salim

et al. 2020

Geophysical Prospecting

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Integrated rock classification in the Wolfcamp Shale based on reservoir quality and anisotropic stress profile estimated from well logs

2016

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Reliable rock classification is the key to identify target zones for successful hydraulic fracturing stimulation treatment in unconventional reservoirs such as organic-rich mudrocks. Such a rock classification scheme should take into account geologic attributes, petrophysical, and geomechanical properties (i.e., in situ stress gradient and elastic properties) to improve the likelihood of successful fracture treatment. However, conventional rock classification methods do not take into account stress gradients in the formation. We have developed a new rock classification technique that integrates four rock classification schemes based on the (1) geologic facies, (2) reservoir quality, (3) stress profile, and (4) completion quality. The techniques applied in these classification schemes include core description and thin section analysis, well-log-based depth-by-depth petrophysical and compositional characterization, and analysis of geomechanical measurements. Geomechanical analysis of core measurements and well logs provide a depth-by-depth assessment of minimum horizontal stress assuming vertical transverse isotropy in the formation. We have performed the geologic facies and reservoir quality classifications using an artificial neural network analysis, in which well logs and well-log-based estimates of the petrophysical and compositional properties were inputs to the network. Our technique was applied to a well located in the Wolfcamp Shale in the Delaware Basin. Based on the integrated rock classification results, we recommend the middle of the upper Wolfcamp and the bottom of the lower Wolfcamp depth intervals as the best candidates for fracture initiation and fracture containment zones, respectively. The selection of these zones was based on the reservoir quality and average minimum horizontal stress gradient calculated in these intervals. Our integrated rock classification technique can improve the planning and execution of completions design for hydraulic fracture treatments.

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Dipole Sonic Log Calibration using Walkaway VSP data

Cited by 2 publications

References 10 publications

Lithology‐dependent seismic anisotropic amplitude variation with offset correction in transversely isotropic media

Lithology‐dependent seismic anisotropic amplitude variation with offset correction in transversely isotropic media

Integrated rock classification in the Wolfcamp Shale based on reservoir quality and anisotropic stress profile estimated from well logs

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