Tutorial: Petrophysics of Thinly Bedded Formations

Author(s):  
Rick Aldred ◽  

This paper was written in response to a personal request from the Editor to contribute a “tutorial” on thin-bed petrophysics. The paper is not intended to be an exhaustive review of all the work that has been done regarding thin-bed petrophysics. Instead, it is an introduction to the different types of methods available, with some discussion on the strengths and weaknesses of each. Thin beds have posed problems for petrophysicists for many decades, mostly because conventional interpretation techniques in thin beds tend to overestimate water saturation, owing to the very low resistivities often seen in hydrocarbon-bearing intervals. There are a number of different techniques available to the petrophysicist for evaluating thin beds, including conventional “bulk volume” techniques, various types of high-resolution modeling, and different low-resolution modeling techniques, both with and without triaxial resistivity measurements. There is no single best technique to use. Instead, the most appropriate method is dependent on the formation complexity and the types of data available. Generally, it is very useful to have triaxial resistivity measurements to understand the formation anisotropy better. However, in some cases, simple “triple-combo” logging suites may be sufficient, provided the interpretation can be improved and verified with core data. In other cases, complex formation modeling is required to provide the best results with low uncertainty. If using either low- or high-resolution modeling, the reporting of evaluation results is not straightforward. Net reservoir and net pay cutoffs require special consideration, and the results are specific to the formation components rather than the bulk volume formation, as they are with conventional reservoir summaries. Furthermore, the quantification of petrophysical uncertainties in formation modeling of thinly bedded formations is better done using scenario modeling rather than Monte Carlo processing, which is commonly applied with bulk volume techniques.

Author(s):  
Kazumichi Ogura ◽  
Michael M. Kersker

Backscattered electron (BE) images of GaAs/AlGaAs super lattice structures were observed with an ultra high resolution (UHR) SEM JSM-890 with an ultra high sensitivity BE detector. Three different types of super lattice structures of GaAs/AlGaAs were examined. Each GaAs/AlGaAs wafer was cleaved by a razor after it was heated for approximately 1 minute and its crosssectional plane was observed.First, a multi-layer structure of GaAs (100nm)/AlGaAs (lOOnm) where A1 content was successively changed from 0.4 to 0.03 was observed. Figures 1 (a) and (b) are BE images taken at an accelerating voltage of 15kV with an electron beam current of 20pA. Figure 1 (c) is a sketch of this multi-layer structure corresponding to the BE images. The various layers are clearly observed. The differences in A1 content between A1 0.35 Ga 0.65 As, A1 0.4 Ga 0.6 As, and A1 0.31 Ga 0.69 As were clearly observed in the contrast of the BE image.


Author(s):  
Wei Huang ◽  
Xiaoshu Zhou ◽  
Mingchao Dong ◽  
Huaiyu Xu

AbstractRobust and high-performance visual multi-object tracking is a big challenge in computer vision, especially in a drone scenario. In this paper, an online Multi-Object Tracking (MOT) approach in the UAV system is proposed to handle small target detections and class imbalance challenges, which integrates the merits of deep high-resolution representation network and data association method in a unified framework. Specifically, while applying tracking-by-detection architecture to our tracking framework, a Hierarchical Deep High-resolution network (HDHNet) is proposed, which encourages the model to handle different types and scales of targets, and extract more effective and comprehensive features during online learning. After that, the extracted features are fed into different prediction networks for interesting targets recognition. Besides, an adjustable fusion loss function is proposed by combining focal loss and GIoU loss to solve the problems of class imbalance and hard samples. During the tracking process, these detection results are applied to an improved DeepSORT MOT algorithm in each frame, which is available to make full use of the target appearance features to match one by one on a practical basis. The experimental results on the VisDrone2019 MOT benchmark show that the proposed UAV MOT system achieves the highest accuracy and the best robustness compared with state-of-the-art methods.


2021 ◽  
Vol 35 (3) ◽  
pp. 406-414
Author(s):  
Yoko Satoh ◽  
Masami Kawamoto ◽  
Kazunori Kubota ◽  
Koji Murakami ◽  
Makoto Hosono ◽  
...  

AbstractBreast positron emission tomography (PET) has had insurance coverage when performed with conventional whole-body PET in Japan since 2013. Together with whole-body PET, accurate examination of breast cancer and diagnosis of metastatic disease are possible, and are expected to contribute significantly to its treatment planning. To facilitate a safer, smoother, and more appropriate examination, the Japanese Society of Nuclear Medicine published the first edition of practice guidelines for high-resolution breast PET in 2013. Subsequently, new types of breast PET have been developed and their clinical usefulness clarified. Therefore, the guidelines for breast PET were revised in 2019. This article updates readers as to what is new in the second edition. This edition supports two different types of breast PET depending on the placement of the detector: the opposite-type (positron emission mammography; PEM) and the ring-shaped type (dedicated breast PET; dbPET), providing an overview of these scanners and appropriate imaging methods, their clinical applications, and future prospects. The name “dedicated breast PET” from the first edition is widely used to refer to ring-shaped type breast PET. In this edition, “breast PET” has been defined as a term that refers to both opposite- and ring-shaped devices. Up-to-date breast PET practice guidelines would help provide useful information for evidence-based breast imaging.


2020 ◽  
Vol 500 (1) ◽  
pp. 548-557
Author(s):  
M Lisogorskyi ◽  
H R A Jones ◽  
F Feng ◽  
R P Butler ◽  
S Vogt

ABSTRACT We examine the influence of activity- and telluric-induced radial velocity (RV) signals on high-resolution spectra taken with an iodine absorption cell. We exclude 2-$\mathring{\rm A}$ spectral chunks containing active and telluric lines based on the well-characterized K1V star α Centauri B and illustrate the method on Epsilon Eridani – an active K2V star with a long-period, low-amplitude planetary signal. After removal of the activity- and telluric-sensitive parts of the spectrum from the RV calculation, the significance of the planetary signal is increased and the stellar rotation signal disappears. In order to assess the robustness of the procedure, we perform Monte Carlo simulations based on removing random chunks of the spectrum. Simulations confirm that the removal of lines impacted by activity and tellurics provides a method for checking the robustness of a given Keplerian signal. We also test the approach on HD 40979, which is an active F8V star with a large-amplitude planetary signal. Our Monte Carlo simulations reveal that the significance of the Keplerian signal in the F star is much more sensitive to wavelength. Unlike the K star, the removal of active lines from the F star greatly reduces the RV precision. In this case, our removal of a K star active line from an F star does not a provide a simple useful diagnostic because it has far less RV information and heavily relies on the strong active lines.


2021 ◽  
Vol 184 ◽  
pp. 106188
Author(s):  
Tahereh Azimpour-Ardakan ◽  
Reza Fotouhi-Ardakani ◽  
Nasser Hoghooghi-Rad ◽  
Nourdehr Rokni ◽  
Abbasali Motallebi

2018 ◽  
Vol 1012 ◽  
pp. 012002 ◽  
Author(s):  
Jiahao Xu ◽  
Alan M. Ferrenberg ◽  
David P. Landau

Author(s):  
Magnus Hölle ◽  
Christian Bartsch ◽  
Peter Jeschke

The subject of this paper is a statistical method for the accurate evaluation of the uncertainties for pneumatic multi-hole probe measurements. The method can be applied to different types of evaluation algorithms and is suitable for steady flowfield measurements in compressible flows. The evaluation of uncertainties is performed by a Monte Carlo method (MCM), which is based on the statistical law of large numbers. Each input quantity, including calibration and measurement quantities, is randomly varied on the basis of its corresponding probability density function (PDF) and propagated through the deterministic parameter evaluation algorithm. Other than linear Taylor series based uncertainty evaluation methods, MCM features several advantages. On the one hand, MCM does not suffer from lower-order expansion errors and can therefore reproduce nonlinearity effects. On the other hand, different types of PDFs can be assumed for the input quantities and the corresponding coverage intervals can be calculated for any coverage probability. To demonstrate the uncertainty evaluation, a calibration and subsequent measurements in the wake of an airfoil with a 5-hole probe are performed. MCM is applied to different parameter evaluation algorithms. It is found that the MCM approach presented cannot be applied to polynomial curve fits, if the differences between the calibration data and the polynomial curve fits are of the same order of magnitude compared to the calibration uncertainty. Since this method has not yet been used for the evaluation of measurement uncertainties for pneumatic multi-hole probes, the aim of the paper is to present a highly accurate and easy-to-implement uncertainty evaluation method.


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