SPEAKER: Alberto Mendoza - Imperial College London
Alberto Mendoza is currently a Research
Scientist with the Department of Mathematics at Imperial College London. He received
a Ph.D. degree in Petroleum Engineering from the University of Texas at Austin
in 2008. From 2008 to 2014, he worked for ExxonMobil Corporation as a Formation
Evaluation Specialist in the USA and Russia, and during 2014-2016 he was a
Petrophysical Engineer with Shell | NAM in The Netherlands.
Abstract: Paper OOOO
We show that statistical methods enable the use of portable industrial
scanners (with sparse measurements), suitable for fast on-site whole-core X-ray
computerized tomography (CT), as opposed to conventional (medical) devices
(with dense measurements). This approach accelerates an informed first-stage
general assessment of core samples. To that end, we show that this novel industrial
tomographic measurement principle is feasible for rock sample imaging, in
conjunction with suitable forms of priors in Bayesian inversion algorithms. We assess
the performance of the inversion with Gaussian, Cauchy, and Total Variation
(TV) priors. In so doing, we consider, in discrete form, conditional mean (CM) estimators,
via Markov Chain Monte Carlo (MCMC) algorithms with noise-contaminated
To benchmark the reliability of whole-core imaging with sparse
radiograms via Bayesian inversion, in our study we include X-ray CT from
numerical simulations of synthetic and measurement-based whole-core samples. To
that end, we consider tomographic measurements of fine- to medium-grained
sandstone core samples, with igneous-rich pebbles from the Miocene, off the Shimokita
Peninsula in Japan, and fractured welded tuff from Big Bend National Park,
Texas. Bayesian inversion results show that with only 16 radiograms, natural
fractures with aperture of less than 2mm wide are detectable. Additionally,
images show approximately
concretions of 6mm diameter. We show that to achieve similar results, filtered
back projection (FBP) techniques require hundreds of radiograms, only possible
conventional (medical) laboratory scanners.
This paper shows that Bayesian inversion on whole-core X-ray CT is
capable of imaging coarse sedimentary features that, with faster, simplified
measurement principles, would aid in more efficient operational petrophysical
decisions for planning further core analysis.
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