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College Station, TX, United States

Heidari Z.,TexasAandiversity | Torres-Verdin C.,University of Texas at Austin
Proceedings - SPE Annual Technical Conference and Exhibition | Year: 2012

Petrophysical interpretation of well logs acquired in organic shales and carbonates is challenging because of the presence of thin beds and spatially complex lithology; conventional interpretation techniques often fail in such cases. Recently introduced methods for thin-bed interpretation enable corrections for shoulder-bed effects on well logs but remain sensitive to incorrectly picked bed boundaries. We introduce a new inversion-based method to detect bed boundaries and to estimate petrophysical and compositional properties of multi-layer formations from conventional well logs in the presence of thin beds, complex lithology/fluids, and kerogen. Bed boundaries and bed properties are updated in two serial inversion loops. Numerical simulation of well logs within both inversion loops explicitly takes into account differences in the volume of investigation of all well logs involved in the estimation, thereby enabling corrections for shoulder-bed effects. The successful application of the new interpretation method is documented with synthetic cases and field data acquired in thinly bedded carbonates and in the Haynesville shale-gas formation. Estimates of petrophysical/compositional properties obtained with the new interpretation method are compared to those obtained with (a) nonlinear inversion of well logs with inaccurate bed boundaries, (b) depth-by-depth inversion of well logs, and (c) core/X-Ray Diffraction (XRD) measurements. Results indicate that the new method improves the estimation of porosity of thin beds by more than 200% in the carbonate field example and by more than 40% in the shale-gas example, compared to depth-by-depth interpretation results obtained with commercial software. This improvement in the assessment of petrophysical/compositional properties reduces uncertainty in hydrocarbon reserves and aids in the selection of hydraulic fracture locations in organic shale. Copyright 2012, Society of Petroleum Engineers.


Zhong Y.,Wuhan University | Zhang S.,Wuhan University | Zhang S.,TexasAandiversity | Zhang L.,Wuhan University
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2013

Traditional automatic fuzzy clustering methods can obtain the optimal number of clusters by maximizing or minimizing one single-objective function using validity indexes. However, the effectiveness of these methods depends on the selection of the validity indexes, and one single-objective function may not provide satisfactory results because of the complexity of remote sensing images. For instance, the same land types may have different spectral curves, and different land types can have similar curves. To avoid this problem, this paper proposes a novel automatic fuzzy clustering method based on adaptive multi-objective differential evolution (AFCMDE) for remote sensing imagery. In AFCMDE, the automatic clustering problem is transformed into a multi-objective problem using two objective functions: Jm and the Xie-Beni index. AFCMDE is designed as a two-layer system comprising an optimization layer and a classification layer. In the optimization layer, AFCMDE searches for a feasible number of clusters by minimizing the Jm value and the Xie-Beni index. Based on the obtained number of clusters, AFCMDE utilizes non-dominated and crowd-distance sorting to obtain the optimal clustering centers and output the clustering results. In addition, a self-adaptive strategy without user-defined parameters is also used to improve the differential evolution. Experimental results using three different types of remote sensing image show that the AFCMDE algorithm consistently outperforms the other traditional clustering algorithms and the previous single-objective automatic fuzzy clustering algorithms. © 2008-2012 IEEE.


Hsiao E.Y.,University of Aarhus | Burns C.R.,Carnegie Observatories | Contreras C.,University of Aarhus | Hoflich P.,Florida State University | And 58 more authors.
Astronomy and Astrophysics | Year: 2015

We present near-infrared (NIR) time-series spectroscopy, as well as complementary ultraviolet (UV), optical, and NIR data, of the Type Ia supernova (SN Ia) iPTF13ebh, which was discovered within two days from the estimated time of explosion. The first NIR spectrum was taken merely 2.3 days after explosion and may be the earliest NIR spectrum yet obtained of a SN Ia. The most striking features in the spectrum are several NIR C i lines, and the C iλ1.0693 μm line is the strongest ever observed in a SN Ia. Interestingly, no strong optical C ii counterparts were found, even though the optical spectroscopic time series began early and is densely cadenced. Except at the very early epochs, within a few days from the time of explosion, we show that the strong NIR C i compared to the weaker optical C ii appears to be general in SNe Ia. iPTF13ebh is a fast decliner with Δm15(B) = 1.79 ± 0.01, and its absolute magnitude obeys the linear part of the width-luminosity relation. It is therefore categorized as a "transitional" event, on the fast-declining end of normal SNe Ia as opposed to subluminous/91bg-like objects. iPTF13ebh shows NIR spectroscopic properties that are distinct from both the normal and subluminous/91bg-like classes, bridging the observed characteristics of the two classes. These NIR observations suggest that composition and density of the inner core are similar to that of 91bg-like events, and that it has a deep-reaching carbon burning layer that is not observed in more slowly declining SNe Ia. There is also a substantial difference between the explosion times inferred from the early-time light curve and the velocity evolution of the Si iiλ0.6355 μm line, implying a long dark phase of ∼4 days. © 2015 ESO.


Handler R.A.,TexasAandiversity | Zhang Q.,TexasAandiversity
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2013

The fluid mechanics associated with the interface between two fluids, and in particular air and water, is of obvious importance in interpreting and determining surface signatures in the radar, infrared (IR), and visible wavelengths of the electromagnetic spectrum. These dynamics also play an important role in the determination of the interfacial flux of heat, mass, and momentum at the air-sea interface. Here we present results of direct numerical simulations (DNS) of an undeformed interface subject to a constant shear and constant outgoing heat flux at three Reynolds numbers. Particular attention is payed to the surface temperature field and its relation to the velocity and vorticity fields. The importance of these results to current problems in IR remote sensing is discussed. © 2013 IEEE.

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