The Invention and Application of Typical Points-Based Well Log Correlation and Picking Up Technology

2021 ◽  
Author(s):  
Ya Deng ◽  
Yong Li ◽  
Wenqi Zhang ◽  
Dandan Hu ◽  
Zhongyuan Tian ◽  
...  
Keyword(s):  
Characteristic Point ◽  
Free Water ◽  
Water Levels ◽  
New Method ◽  
Quality Analysis ◽  
Stratigraphic Correlation ◽  
Well Log ◽  
Data Set ◽  
Characteristic Points ◽  
Dynamic Performance Analysis

Abstract This paper proposes a new method called typical points-based well log correlation and picking up technology and provides several related application examples based on this method. The new method firstly determines representative extreme points, typical or characteristic points by analyzing the characteristics of logging curves and lithology of different wells, which are generally representative points with special geological significance, including the points with the best physical properties or tight points. (For example, the maximum flooding surface or exposed surface in a sedimentary cycle, etc.). On the basis of these characteristic points, we carry out stratigraphic correlation and tracking between wells to obtain a data set of a series of characteristic points. From the same characteristic point, all points have the same or similar petrophysical properties, and the logging curve values of these characteristic points are extracted. And then analyze the change trend, distribution characteristics and the internal relationship of the parameters of the data set of each feature point. Based on the data set obtained from the method above, we extended it to the following application areas: 1) Through mathematical theoretical models, two free water level distribution modes and their determination workflows were established, including horizontal and tilted free water levels. 2) Perform data quality analysis and control, especially logging data analysis. 3) Exploratory application in the standardization of logging curves.4) Application in dynamic performance analysis The new method is developed on the traditional stratigraphic correlation method and stratal slicing method (Zeng Hongliu, 1998) and then used for well log data extraction and analysis. It is a practical means and technique for geological analysis. The application effect shows that the it is reliable, convenient and practical.

Detecting and Determining the Characteristic Points on the Parametric Surface/Surface Intersection

1995 ◽  
Author(s):  
Xianglin Zeng ◽  
Qifu Wang ◽  
Ji Zhou ◽  
Jun Yu
Keyword(s):  
Characteristic Point ◽  
New Method ◽  
Parametric Surface ◽  
Initial Interval ◽  
Surface Modelling ◽  
Surface Intersection ◽  
Characteristic Points ◽  
Numeric Solution ◽  
Modelling System ◽  
Significant Point

Abstract In this paper we present a new method for detecting and determining characteristic points on the surface/surface intersection while marching along the intersections. The initial interval which contains a potential characteristic point is first determined by certain criteria, then a numeric solution of the significant point is obtained by the binary subdivision method. Based on these ideas, a new marching algorithm is constructed, and it has been implemented in a surface modelling system (SurfCADM V1.0). Examples are also presented for illustrating the capability of our algorithm.

A New Approach for the Analysis of Mixture Toxicity Data

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2345-2348 ◽  
Author(s):  
C. N. Haas
Keyword(s):  
Quantitative Analysis ◽  
Mixture Toxicity ◽  
New Method ◽  
Metal Exposure ◽  
Positive Interactions ◽  
Toxicity Data ◽  
Data Set ◽  
New Approach ◽  
Negative Interactions

A new method for the quantitative analysis of multiple toxicity data is described and illustrated using a data set on metal exposure to copepods. Positive interactions are observed for Ni-Pb and Pb-Cr, with weak negative interactions observed for Ni-Cr.

scholarly journals A New Method for Landmark-Based Studies of the Dynamic Stability of Growth, with Implications for Evolutionary Analyses

2021 ◽  
Author(s):  
Fred L. Bookstein
Keyword(s):  
Growth Regulation ◽  
Pattern Analysis ◽  
Developmental Time ◽  
Dynamical Stability ◽  
New Method ◽  
Data Sets ◽  
Data Set ◽  
Landmark Data ◽  
Study Designs ◽  
Changes Over Time

AbstractA matrix manipulation new to the quantitative study of develomental stability reveals unexpected morphometric patterns in a classic data set of landmark-based calvarial growth. There are implications for evolutionary studies. Among organismal biology’s fundamental postulates is the assumption that most aspects of any higher animal’s growth trajectories are dynamically stable, resilient against the types of small but functionally pertinent transient perturbations that may have originated in genotype, morphogenesis, or ecophenotypy. We need an operationalization of this axiom for landmark data sets arising from longitudinal data designs. The present paper introduces a multivariate approach toward that goal: a method for identification and interpretation of patterns of dynamical stability in longitudinally collected landmark data. The new method is based in an application of eigenanalysis unfamiliar to most organismal biologists: analysis of a covariance matrix of Boas coordinates (Procrustes coordinates without the size standardization) against their changes over time. These eigenanalyses may yield complex eigenvalues and eigenvectors (terms involving $$i=\sqrt{-1}$$ i = - 1 ); the paper carefully explains how these are to be scattered, gridded, and interpreted by their real and imaginary canonical vectors. For the Vilmann neurocranial octagons, the classic morphometric data set used as the running example here, there result new empirical findings that offer a pattern analysis of the ways perturbations of growth are attenuated or otherwise modified over the course of developmental time. The main finding, dominance of a generalized version of dynamical stability (negative autoregressions, as announced by the negative real parts of their eigenvalues, often combined with shearing and rotation in a helpful canonical plane), is surprising in its strength and consistency. A closing discussion explores some implications of this novel pattern analysis of growth regulation. It differs in many respects from the usual way covariance matrices are wielded in geometric morphometrics, differences relevant to a variety of study designs for comparisons of development across species.

scholarly journals Blue as an Underrated Alternative to Green: Photoplethysmographic Heartbeat Intervals Estimation under Two Temperature Conditions

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4241
Author(s):  
Evgeniia Shchelkanova ◽  
Liia Shchapova ◽  
Alexander Shchelkanov ◽  
Tomohiro Shibata
Keyword(s):  
Blue Light ◽  
Characteristic Point ◽  
Biological Effects ◽  
Green Light ◽  
Estimation Accuracy ◽  
Lower Sensitivity ◽  
Light Spectrum ◽  
Cardiovascular Parameter ◽  
Temperature Conditions ◽  
Characteristic Points

Since photoplethysmography (PPG) sensors are usually placed on open skin areas, temperature interference can be an issue. Currently, green light is the most widely used in the reflectance PPG for its relatively low artifact susceptibility. However, it has been known that hemoglobin absorption peaks at the blue part of the spectrum. Despite this fact, blue light has received little attention in the PPG field. Blue wavelengths are commonly used in phototherapy. Combining blue light-based treatments with simultaneous blue PPG acquisition could be potentially used in patients monitoring and studying the biological effects of light. Previous studies examining the PPG in blue light compared to other wavelengths employed photodetectors with inherently lower sensitivity to blue, thereby biasing the results. The present study assessed the accuracy of heartbeat intervals (HBIs) estimation from blue and green PPG signals, acquired under baseline and cold temperature conditions. Our PPG system is based on TCS3472 Color Sensor with equal sensitivity to both parts of the light spectrum to ensure unbiased comparison. The accuracy of the HBIs estimates, calculated with five characteristic points (PPG systolic peak, maximum of the first PPG derivative, maximum of the second PPG derivative, minimum of the second PPG derivative, and intersecting tangents) on both PPG signal types, was evaluated based on the electrocardiographic values. The statistical analyses demonstrated that in all cases, the HBIs estimation accuracy of blue PPG was nearly equivalent to the G PPG irrespective of the characteristic point and measurement condition. Therefore, blue PPG can be used for cardiovascular parameter acquisition. This paper is an extension of work originally presented at the 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A Novel K-Harmonic Means Clustering Based on Multiple Initial Centers

2013 ◽  
Vol 321-324 ◽  
pp. 1947-1950
Author(s):  
Lei Gu ◽  
Xian Ling Lu
Keyword(s):  
New Method ◽  
Final Solution ◽  
Data Set ◽  
Number Of Clusters ◽  
Multiple Groups ◽  
Harmonic Means

In the initialization of the traditional k-harmonic means clustering, the initial centers are generated randomly and its number is equal to the number of clusters. Although the k-harmonic means clustering is insensitive to the initial centers, this initialization method cannot improve clustering performance. In this paper, a novel k-harmonic means clustering based on multiple initial centers is proposed. The number of the initial centers is more than the number of clusters in this new method. The new method with multiple initial centers can divide the whole data set into multiple groups and combine these groups into the final solution. Experiments show that the presented algorithm can increase the better clustering accuracies than the traditional k-means and k-harmonic methods.

Denoising of river surface photogrammetric DEMs using deep learning

2021 ◽  
Author(s):  
Radosław Szostak ◽  
Przemysław Wachniew ◽  
Mirosław Zimnoch ◽  
Paweł Ćwiąkała ◽  
Edyta Puniach ◽  
...  
Keyword(s):  
Higher Education ◽  
Deep Learning ◽  
Water Level ◽  
Water Surface ◽  
Research University ◽  
Static Characteristic ◽  
Water Levels ◽  
Training Dataset ◽  
Observation Data ◽  
Characteristic Points

<p>Unmanned Aerial Vehicles (UAVs) can be an excellent tool for environmental measurements due to their ability to reach inaccessible places and fast data acquisition over large areas. In particular drones may have a potential application in hydrology, as they can be used to create photogrammetric digital elevation models (DEM) of the terrain allowing to obtain high resolution spatial distribution of water level in the river to be fed into hydrological models. Nevertheless, photogrammetric algorithms generate distortions on the DEM at the water bodies. This is due to light penetration below the water surface and the lack of static characteristic points on water surface that can be distinguished by the photogrammetric algorithm. The correction of these disturbances could be achieved by applying deep learning methods. For this purpose, it is necessary to build a training dataset containing DEMs before and after water surfaces denoising. A method has been developed to prepare such a dataset. It is divided into several stages. In the first step a photogrammetric surveys and geodetic water level measurements are performed. The second one includes generation of DEMs and orthomosaics using photogrammetric software. Finally in the last one the interpolation of the measured water levels is done to obtain a plane of the water surface and apply it to the DEMs to correct the distortion. The resulting dataset was used to train deep learning model based on convolutional neural networks. The proposed method has been validated on observation data representing part of Kocinka river catchment located in the central Poland.</p><p>This research has been partly supported by the Ministry of Science and Higher Education Project “Initiative for Excellence – Research University” and Ministry of Science and Higher Education subsidy, project no. 16.16.220.842-B02 / 16.16.150.545.</p>

scholarly journals Technical note: Multiple wavelet coherence for untangling scale-specific and localized multivariate relationships in geosciences

2016 ◽  
Vol 20 (8) ◽  
pp. 3183-3191 ◽  
Author(s):  
Wei Hu ◽  
Bing Cheng Si
Keyword(s):  
Multiple Scales ◽  
Free Water ◽  
Wavelet Coherence ◽  
Predictor Variables ◽  
Water Evaporation ◽  
Multivariate Methods ◽  
Spectral Coherence ◽  
Data Set ◽  
Multivariate Relationships ◽  
Multiple Wavelet Coherence

Abstract. The scale-specific and localized bivariate relationships in geosciences can be revealed using bivariate wavelet coherence. The objective of this study was to develop a multiple wavelet coherence method for examining scale-specific and localized multivariate relationships. Stationary and non-stationary artificial data sets, generated with the response variable as the summation of five predictor variables (cosine waves) with different scales, were used to test the new method. Comparisons were also conducted using existing multivariate methods, including multiple spectral coherence and multivariate empirical mode decomposition (MEMD). Results show that multiple spectral coherence is unable to identify localized multivariate relationships, and underestimates the scale-specific multivariate relationships for non-stationary processes. The MEMD method was able to separate all variables into components at the same set of scales, revealing scale-specific relationships when combined with multiple correlation coefficients, but has the same weakness as multiple spectral coherence. However, multiple wavelet coherences are able to identify scale-specific and localized multivariate relationships, as they are close to 1 at multiple scales and locations corresponding to those of predictor variables. Therefore, multiple wavelet coherence outperforms other common multivariate methods. Multiple wavelet coherence was applied to a real data set and revealed the optimal combination of factors for explaining temporal variation of free water evaporation at the Changwu site in China at multiple scale-location domains. Matlab codes for multiple wavelet coherence were developed and are provided in the Supplement.

scholarly journals Dampak Limbah Penambangan Emas Tanpa Izin (Peti) Terhadap Kualitas Air Sungai Limun Kabupaten Sarolangun Propinsi Jambi - The Impact Of Illegal Gold Mining Activity To The Water Quality Of Limun River, Sarolangun District, Jambi Province

2017 ◽  
Vol 14 (3) ◽  
pp. 251
Author(s):  
Rita Yulianti ◽  
Emi Sukiyah ◽  
Nana Sulaksana
Keyword(s):  
Water Quality ◽  
Gold Mining ◽  
Quality Standard ◽  
Water Levels ◽  
Quality Analysis ◽  
Quality Data ◽  
Mining Activities ◽  
Water Quality Data ◽  
The Impact

Daerah penelitian terletak di desa Muaro Limun, Kecamatan Limun Kabupaten Sarolangun Provinsi Jambi. Sungai limun, salah satu sungai besar di daerah kabupaten sarolangun yang dimanfaatkan oleh mayarakat sekitarnya sebagai sumber penghidupan. Penelitian bertujuan untuk mengetahui pengaruh kegiatan penambangan terhadap kualitas air sungai Batang Limun, dan perubahan sifat fisik dan  kimia yang diakibatkan   kegiatan penambangan.Metode yang digunakan adalah  metode grab sampel, serta stream sedimen untuk dianalis di laboratorium. Sejumlah sampel diambil di beberapa lokasi Penambangan Emas berdasarkan Aliran Sub-DAS dan dibandingkan dengan beberapa sampel lain yang diambil pada lokasi yang belum terkontaminasi oleh kegiatan penambangan. Analisis kualitas air mengacu pada  SMEWWke 22 tahun 2012 dan standar baku mutu air kelas II dalam PP No 82 yang dikeluarkan oleh Menteri Kesehatan No. 492/Menkes/Per/IV/2010. Diketahui sungai Batang Limun telah mengalami perubahan karakteristik fisika dan kimia. Dari grafik  kosentrasi kekeruhan, pH, TSS, TDS  Cu, Pb, Zn, Mn, Hg terlihat bahwa penambang emas tanpa izin (PETI) dengan cara amalgamasi yang menyebabkan terjadinya penurunan kualitas air sungai. Sejak tahun 2009 sampai tahun 2015  sungai Limun dan sekitarnya terus mengalami penurunan kualitas air. Penurunan kualitas yang cukup tinggi terjadi  yaitu peningkatan nilai Rata-rata konsentrasi merkuri pada sungai Batang Limun dari 0,18ppb (0,00018 mg/l)  menjadi 0,3ppb (0,0003 mg/l), peningkatan tersebut dipengaruhi oleh proses kegiatan penambangan dan nilai tersebut masih dibawah standar baku mutu air kelas II  pp nomor 82 tahun 2010.Kata kunci :   Kualitas Air, Sungai Limun,TSS, Merkuri, PETI Limun river is one of the major rivers in the area of Sarolangun, which utilized by the society as a source of livelihood. The aim of study  to analyze the effect of mining activities on  the water quality of Batang Limun River, and the changes of physical and chemical properties of water. The method used are grab  and stream samples to  sediment analyzed in the laboratory. A number of samples were taken at several locations based Flow Gold Mining Sub-watershed and compared to some other samples taken at the location that has not been contaminated by mining activities. Water quality analysis referring to SMEWW, 22nd edition 2012 and refers to Regulation No 82 that issued by Minister of Health No. 492 / Menkes / Per / IV / 2010.The results showed that the Limun river has undergone chemical changes in physical characteristics. These symptoms can be seen from the discoloration of clear water in the river before the mine becomes brownish after mining, based on graphic of muddiness concentration: pH, TSS, TDS Cu, Pb, Zn, Mn, Hg have seen that  the illegal miner which used amalgamation caused deterioration in water quality, data from 2009 to 2015 Limun river and surrounding areas continue to experience a decrease in water quality. The decreasing of water quality showed in the TSS parameter which found in the area is to high based on  the standard of water quality class II pp number 82 of 2010. An increase in the value of average concentrations of mercury in the Batang Limun river before mine 0,18ppb (0.00018 mg / l) into 0,3ppb (0.0003 mg / l) on the river after the mine. The increase was affected by the mining activities and the value is still below the air quality standard Grade II pp numbers 82 years 2010, although the value is still below with the standards quality standard, the mercury levels in water should still be a major concern because if it accumulates continuously in the water levels will increase and will be bad for health. In contrast to the concentration of mercury in sediments that have a higher value is 153 ppb (0,513ppm ) .Key Words :   Water Quality, Limun River, Mercury, Illegal gold mining

scholarly journals White-matter free-water diffusion MRI in schizophrenia: a systematic review and meta-analysis

2022 ◽  
Author(s):  
Inês Carreira Figueiredo ◽  
Faith Borgan ◽  
Ofer Pasternak ◽  
Federico E. Turkheimer ◽  
Oliver D. Howes
Keyword(s):  
White Matter ◽  
Healthy Volunteers ◽  
Diffusion Mri ◽  
Clinical Symptoms ◽  
Free Water ◽  
Brain Regions ◽  
Water Levels ◽  
First Episode ◽  
Whole Brain ◽  
Illness Duration

AbstractWhite-matter abnormalities, including increases in extracellular free-water, are implicated in the pathophysiology of schizophrenia. Recent advances in diffusion magnetic resonance imaging (MRI) enable free-water levels to be indexed. However, the brain levels in patients with schizophrenia have not yet been systematically investigated. We aimed to meta-analyse white-matter free-water levels in patients with schizophrenia compared to healthy volunteers. We performed a literature search in EMBASE, MEDLINE, and PsycINFO databases. Diffusion MRI studies reporting free-water in patients with schizophrenia compared to healthy controls were included. We investigated the effect of demographic variables, illness duration, chlorpromazine equivalents of antipsychotic medication, type of scanner, and clinical symptoms severity on free-water measures. Ten studies, including five of first episode of psychosis have investigated free-water levels in schizophrenia, with significantly higher levels reported in whole-brain and specific brain regions (including corona radiata, internal capsule, superior and inferior longitudinal fasciculus, cingulum bundle, and corpus callosum). Six studies, including a total of 614 participants met the inclusion criteria for quantitative analysis. Whole-brain free-water levels were significantly higher in patients relative to healthy volunteers (Hedge’s g = 0.38, 95% confidence interval (CI) 0.07–0.69, p = 0.02). Sex moderated this effect, such that smaller effects were seen in samples with more females (z = −2.54, p < 0.05), but antipsychotic dose, illness duration and symptom severity did not. Patients with schizophrenia have increased free-water compared to healthy volunteers. Future studies are necessary to determine the pathological sources of increased free-water, and its relationship with illness duration and severity.

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