Estimation of Formation Shear and its Radial Profile from Sonic Dispersions in Well-Bonded Cased Boreholes
Sonic logging through casing is of increasing interest in the oil and gas
industry, because accurate estimation of formation shear slowness is necessary
in the mechanical characterization and lithological interpretation of the
formation, while most of the production and observation wells are cased.
Processing and interpretation of sonic data can be challenging in the presence
of a steel casing that has a strong influence on the elastic waves propagating
along a cased borehole. In this presentation, we first assume the formation is
homogeneous. A new technique is developed to invert for the formation shear
using borehole dispersions that have been already estimated from the recorded
waveforms. Secondly, we consider radially heterogeneous formations, and
describe a parameterized model-based technique based on a modified perturbation
approach to estimate formation shear radial variation from estimated
dispersions. Numerical results using synthetic Stoneley and dipole flexural
dispersion for a fast formation are presented to demonstrate the validity of
these proposed methodologies.
Jiaqi Yang received a B.S. in Pure and Applied Mathematics from Fudan
University. She earned a M.S. in Biostatistics and a Ph.D. in Applied
Mathematics from University of Minnesota, Twin Cities in 2008. She is currently
a research scientist at Schlumberger-Doll Research in Cambridge, Massachusetts.
Her research interests include modeling and simulation of acoustic and elastic
wave propagation in fluids and solids, guided wave dispersion analysis with
applications to borehole and reservoir geophysics, ultrasonic measurement
modeling and inversion for cement evaluation, and deterministic and statistical
approaches to parametric inversion and optimization. She is a member of SEG and
SIAM. She holds a WIPO patent and has published a book chapter, and nine
scientific articles in refereed journals.