scholarly journals Adjustment of the Exploration Grids and its use to increase the Reliability of Geological Models of Coal Deposits

2020 ◽  
Vol 174 ◽  
pp. 01063
Author(s):  
Tamara Rogova ◽  
Sergey Shaklein
Keyword(s):  
Extreme Values ◽  
Data Interpretation ◽  
New Method ◽  
Geological Data ◽  
Geodetic Networks ◽  
Specific Measurement ◽  
Geological Modelling ◽  
Coal Deposits ◽  
Geological Models ◽  
Current Procedure

The current procedure for determining the boundaries of geological domains, the allocation of which is the mandatory element of digital geological modelling, does not entirely take into account the specifics of coal deposits. Without its improvement, it is impossible to increase the reliability of geological models used in the implementation of the “Industry 4.0ˮ strategy. A new method for analysis of geological data is supposed – the adjustment of the exploration grids method. It is to determine the corrections for values of measured parameters, the use of which eliminates the uncertainty of geological data interpretation. The correction values determined by the method of conditional measurements, which used at equalization geodetic networks. Corrections are considered as an indicator of the significance of measurement and interpolation errors which occurs in the vicinity of specific measurement points. The measured values of parameters are not corrected. Geological domains are the areas with close in values corrections, whose boundaries are corrections isolines. Separate single corrections of anomalous magnitude indicate the presence of extreme values parameters.

Design of Four-Bar Function Generators With Mini-Max Transmission Angle

1977 ◽  
Vol 99 (2) ◽  
pp. 360-365 ◽  
Author(s):  
K. C. Gupta
Keyword(s):  
Extreme Values ◽  
New Method ◽  
Numerical Examples ◽  
Transmission Angle ◽  
Function Generators ◽  
Synthesis Procedure

A new method of designing four-bar function generators with optimum transmission angle is presented. Transmission angles are considered optimum, in a mini-max sense, when their extreme values deviate equally from 90 deg. Numerical examples are given to illustrate the synthesis procedure.

scholarly journals Detailed geological models of V. N. Vinogradov oil field productive reservoirs

2019 ◽  
pp. 22-29
Author(s):  
Elena V. Panina ◽  
Svetlana V. Lagutina ◽  
Vladimir F. Grishkevich ◽  
Evgenia A. Arzhilovskaya
Keyword(s):  
Structural Model ◽  
Regional Analysis ◽  
Oil Field ◽  
Reservoir Properties ◽  
Geological Modelling ◽  
Geological Models ◽  
Resources Evaluation ◽  
Oil Water ◽  
Well Data

The article is devoted to the issue of geological modelling. The sedimentational environment of Tyumenand Frolov suites productive deposits is reconstructed using complex regional analysis of seismic and well data. Detailed facial models are built for UKand AS3 reservoir group. Concordant structural model, reservoir properties mapping, saturation recognition, oil-water contacts estimation, and pool contouring are made for oil initial resources evaluation.

Geological data interpretation at the stage of operational exploration of gold-bearing ore deposits

2021 ◽  
pp. 29-41
Author(s):  
P.A. Smirnov ◽  
I.A. Vorotyntseva ◽  
N.N. Barabanov ◽  
A.A. Lagutina ◽  
M.O. Lozhkin
Keyword(s):  
Data Interpretation ◽  
Ore Deposits ◽  
Geological Data ◽  
Gold Bearing

Abstract P402: A Rapid Automated Method Detects Probable Errors Among Sequential Clinical Measures Recorded During Clinical Care

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Dawn C Schwenke
Keyword(s):  
Extreme Values ◽  
Clinical Care ◽  
New Method ◽  
Individual Values ◽  
Cut Points ◽  
Automated Method ◽  
Blood Pressures ◽  
The Mean ◽  
Va Health Care System ◽  
Clinical Measures

Information collected during clinical care is increasingly used for research. Such data include errors and a rapid automated method for identifying likely errors is needed. This study aimed to develop a rapid automated method for identifying extreme values among sequential measures recorded during clinical care and to compare this method with the extreme studentized deviate many outlier procedure (ESD). Data were weights (W, n=1,151,434), heights (H, n=760,924), pulses (P, n=1,369,484), and systolic (S, n=1,680,583) and diastolic (D, n=1,680,503) blood pressures for 88,068 Veterans (82,874 men and 5,194 women) receiving care from the Phoenix VA Health Care System who had ≥5 five sequential values for these measures recorded in the electronic medical record during primary care visits from October 1999- September 2013. The new method identified extreme values by comparing individual values with three within-person metrics: 1. median (PMed), 2. interquartile range (PIQR), and 3. modified IQR [ModPIQR: PMed + / - smaller of (PMed - 25th percentile) and (75th percentile - PMed)]. These measures were selected because they were expected to be less perturbed by extreme values than the mean and standard deviation. Values exceeding cut-points (> 99th or < 1st population percentile) for ≥ 2 metrics were considered errors. High errors (0.46% W, 0.40% H, 0.55% P, 0.48% S, 0.50% D) were median 125%, 107%, 156%, 135% and 140% of PMed; median 3.3, 2.3, 2.8, 2.0 and 2.1 fold above PIQR; and median 5.0, 20, 3.4, 2.6, and 2.6 fold above ModPIQR for W, H, P, S, and D, respectively. Low errors (0.48% W, 0.43% H, 0.48% P, 0.46% S, 0.47% D) were 73%, 86%, 62%, 70%, and 65% of PMed; median 4.3, 5.0, 2.0, 1.8, and 2.1 fold below PIQR; and median 6.4, 50, 2.6, 2.3, and 2.4 fold below ModPIQR for W, H, P, S, and D. Compared with the new method, ESD (alpha = 0.01) identified fewer total (high+low) outliers for D (0.21% vs. 0.97%), P (0.58% vs. 1.03%), and S (0.14% vs. 0.94%), more outliers for H (2.40% vs. 0.83%), and similar numbers for W (0.70% vs. 0.94%). Both high (> 99th population percentile) and low (< 1st population percentile) extreme values for percent of PMed were detected with greater sensitivity by the new method (39%, 39%, 50%, 45%, and 46%; 41%, 40%, 43%, 41%, and 42%, respectively for high and low extremes for W, H, P, S, D) than by ESD (19%, 20%, 22%, 6%, 9% and 27%, 31%, 11%, 3%, 7%, respectively) while specificity was equally high (>98%) for both methods. The new method can be easily implemented and effectively identifies extreme values likely to be errors from among sequential clinical measures and could help reveal underlying longitudinal trends in weight/BMI, blood pressure or other clinical measures.

scholarly journals Uncertainty assessment in 3-D geological models of increasing complexity

Solid Earth ◽  
2017 ◽  
Vol 8 (2) ◽  
pp. 515-530 ◽  
Author(s):  
Daniel Schweizer ◽  
Philipp Blum ◽  
Christoph Butscher
Keyword(s):  
Information Entropy ◽  
Model Uncertainty ◽  
Model Space ◽  
Distance Measures ◽  
Geological Model ◽  
Multiple Model ◽  
Geological Data ◽  
Geological Models ◽  
Different Types ◽  
Model Geometry

Abstract. The quality of a 3-D geological model strongly depends on the type of integrated geological data, their interpretation and associated uncertainties. In order to improve an existing geological model and effectively plan further site investigation, it is of paramount importance to identify existing uncertainties within the model space. Information entropy, a voxel-based measure, provides a method for assessing structural uncertainties, comparing multiple model interpretations and tracking changes across consecutively built models. The aim of this study is to evaluate the effect of data integration (i.e., update of an existing model through successive addition of different types of geological data) on model uncertainty, model geometry and overall structural understanding. Several geological 3-D models of increasing complexity, incorporating different input data categories, were built for the study site Staufen (Germany). We applied the concept of information entropy in order to visualize and quantify changes in uncertainty between these models. Furthermore, we propose two measures, the Jaccard and the city-block distance, to directly compare dissimilarities between the models. The study shows that different types of geological data have disparate effects on model uncertainty and model geometry. The presented approach using both information entropy and distance measures can be a major help in the optimization of 3-D geological models.

scholarly journals A NEW METHOD OF INTERPRETATION OF SELF‐POTENTIAL FIELD DATA

Geophysics ◽  
1948 ◽  
Vol 13 (4) ◽  
pp. 600-608 ◽  
Author(s):  
L. de Witte
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Field Work ◽  
Data Interpretation ◽  
New Method ◽  
Positive Maximum ◽  
Potential Field Data ◽  
Negative Center ◽  
Location Depth ◽  
Self Potential

In this paper a new, efficient method is worked out for the interpretation of self‐potential field data. Interpretation of location, depth and dip of the ore body is made, using a pattern of equipotential lines. The negative center and the positive maximum of the potential are found and also the so‐called “mid‐value” point. The dip α, can be determined accurately for values between 5° and 85°. The method cannot be used for vertical polarization. The depth and location can be found with relative accuracy for α>10°. The main advantage of this new method is the ease of interpretation and a greater accuracy for the high‐dip angles. It should be stressed that, for correct and accurate interpretation, the positive maximum is as important as the negative center. Therefore, it should be carefully sought during the field work, and mapped to its full extent.

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