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Calibrating anisotropic velocity models for Vaca Muerta

DANIEL O. PÉREZ1,2,3 ,  SOLEDAD R. LAGOS1,2 ,  DANILO R. VELIS1,2 ,  JUAN C. SOLDO3
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1 Facultad de Ciencias Astronómicas y Geofísicas - Universidad Nacional de La Plata, La Plata, Argentina.,
2 CONICET, La Plata, Argentina.,
3 Ecopetrol, Bogota, Colombia.,
JSE 2019, 28(5), 495–511;
Submitted: 9 June 2025 | Revised: 9 June 2025 | Accepted: 9 June 2025 | Published: 9 June 2025
© 2025 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Pérez, D.O., Lagos, S.R., Velis, D.R. and Soldo, J.C., 2019. Calibrating anisotropic velocity models for Vaca Muerta. Journal of Seismic Exploration, 28: 495-511. We provide well-calibrated VTI velocity models useful to locate microseismic events in the Vaca Muerta shale formation, Neuquén, Argentina. Assuming layered models with weak anisotropy, we make use of the information provided by well logs and perforation shots of known position to estimate the layer velocities, depths and anisotropy. This leads to a constrained nonlinear inverse problem that consists of minimizing the discrepancies between the observed and calculated P- and S-wave arrival time differences. To avoid local minima and other convergence issues, we minimize the resulting objective function using very fast simulated annealing (VFSA). We test the proposed strategy on field data and estimate a set of velocity models that honor the observed data, which we validate carrying out a simulated microseismic event location. The results show that the proposed strategy is capable of estimating layered VTI velocity models suitable to accurately locate microseismic events during a hydraulic stimulation in the Vaca Muerta shale formation.

Keywords
VTI
Vaca Muerta
microseismic
calibration
velocity model
VFSA
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Journal of Seismic Exploration, Electronic ISSN: 0963-0651 Print ISSN: 0963-0651, Published by AccScience Publishing
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