scholarly journals 3D Reservoir Rock Type Model Based on Cluster Analysis Technique for Rumaila Formation in the Ahdeb Oil Field, Central Ira

2021 ◽  
Vol 11 (2) ◽  
pp. 49-73
Author(s):  
Buraq Adnan Hussein Al-Baldawi
Keyword(s):  
Cluster Analysis ◽  
Rock Type ◽  
Oil Field ◽  
Reservoir Rock ◽  
Type Model ◽  
Shale Volume ◽  
Rock Types ◽  
Analysis Technique ◽  
Cluster Analysis Technique

This study presents is a classification of reservoir properties (porosity and shale volume) into rock types for carbonate Rumaila reservoir in Central Iraq (Ahdeb Field). The Cluster analysis method is used to identify rock types and to recognize well log clusters of similar characteristics. For most subsurface research, the determination of the rock type (lithofacies and petrofacies) is not adequate enough because of a lack of cores and cuttings. An interactive petrophysics software program was used to get the results of a cluster analysis technique, in order to determine the rock typing (log facies) in Rumaila formation units in the Ahdeb oil field. Initially, petrophysical parameters such as porosity, shale volume and quantity of various reservoir minerals were determined using the probabilistic evaluation process. In the second stage, the multi-resolution graphic clustering method was employed to separate the sequential electrofacies which resulted in the identification of four electrofacies with different geological reservoir properties. The vertical variations of the rock type for Rumaila formation are based on four log facial groups. These log groups are categorized according to porosity and shale volume of formation based on responses to well logs after division of Rumaila formation into four units (Ru-1, Ru-2, Ru-3, and Ru-4).A 3D rock type model for Rumaila Formation was performed using Petrel software in order to illustrate the horizontal distribution of rock type along the Ahdeb field and showing the best characterized of reservoir rock type in any unit of Rumaila Formation. Cluster analysis technique classified porosity and shale volume, which were calculated for Rumaila Formation using well logs, into four similar characteristics rock types: rocktype-1, rock type-2, rock type-3 and rock type-4. A 3D Petrel model of rock type shows that rock type-2 has better reservoir quality than other rock types in Rumaila Formation which is characterized by high porosity and low shale volume. The model clarifies the distribution of rock type-2 in the Ahdeb field at units Ru-1 and Ru-3 of Rumaila Formation

scholarly journals Numerical Simulation Modeling of Carbonate Reservoir Based on Rock Type

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Peiqing Lian ◽  
Cuiyu Ma ◽  
Bingyu Ji ◽  
Taizhong Duan ◽  
Xuequn Tan
Keyword(s):  
History Matching ◽  
Water Saturation ◽  
Rock Type ◽  
Carbonate Reservoir ◽  
Reservoir Rock ◽  
Column Height ◽  
Fluid Distribution ◽  
Type Model ◽  
Type Curves ◽  
Rock Types

There are many types of carbonate reservoir rock spaces with complex shapes, and their primary pore structure changes dramatically. In order to describe the heterogeneity of K carbonate reservoir, equations of porosity, permeability and pore throat radii under different mercury injection saturations are fitted, and it shows that 30% is the best percentile. R30 method is presented for rock typing, and six rock types are divided according to R30 value of plugs. The porosity-permeability relationship is established for each rock type, and their relevant flow characteristics of each rock type have been studied. Logs are utilized to predict rock types of noncored wells, and a three-dimensional (3D) rock type model has been established based on the well rock type curves and the sedimentary facies constraint. Based on the relationship between J function and water saturation, the formula of water saturation, porosity, permeability, and oil column height can be obtained by multiple regressions for each rock type. Then, the water saturation is calculated for each grid, and a 3D water saturation model is established. The model can reflect the formation heterogeneity and the fluid distribution, and its accuracy is verified by the history matching.

Ten-Year Results of a Ponderosa Pine Progeny Test in the Black Hills

1986 ◽  
Vol 1 (3) ◽  
pp. 79-83 ◽  
Author(s):  
Wayne D. Shepperd ◽  
Sue E. McElderry
Keyword(s):  
Cluster Analysis ◽  
Ponderosa Pine ◽  
Black Hills ◽  
Progeny Test ◽  
Poor Survival ◽  
Analysis Technique ◽  
Survival And Growth ◽  
Cluster Analysis Technique ◽  
Growth Of Seedlings

Abstract Ten-year survival and growth of seedlings from 77 parent trees from throughout the Black Hills were compared, using a cluster-analysis technique. Five clusters were identified that account for most of the variability in survival and growth of the open-pollinated families. One cluster, containing 6 families, exhibited exceptional survival and growth. Another, containing 12 families, exhibited poor survival and growth. The performance of families in these two groups appears to be related to location and elevation of parent trees. West. J. Appl. For. 1:79-83, July 1986.

scholarly journals Comparing the utilities consumptions in Dubai per category and community: MANOVA and cluster analysis approaches

2021 ◽  
Vol 958 (1) ◽  
pp. 012022
Author(s):  
A Saihi ◽  
A Alzaatreh
Keyword(s):  
Cluster Analysis ◽  
Data Analysis ◽  
Water Desalination ◽  
Analysis Technique ◽  
Open Government Data ◽  
Government Data ◽  
Increasing Demand ◽  
And Cluster Analysis ◽  
Cluster Analysis Technique ◽  
Desalination Plants

Abstract UAE is marked by the increasing demand for water and electricity due to demographic, environmental and economic factors, coupled with the dependence on water desalination process, which is costly, consumes a lot of energy and is non-environmentally friendly. Like most of the authorities in UAE, Dubai Electricity and Water Authority is facing the challenges of balancing supply with demand and responding to consumer requirements, from one side, and addressing the continuously increasing consumption and slowing it down from another side. Therefore, policy makers can benefit from statistical data analysis in order to make informed decisions. This study aims to equip decision makers with useful tools and analysis to address some of their short- and long-term objectives related to production and consumption. The current study focused on three main objectives: (i) analysing the production of the desalination plants in Dubai, (ii) comparing the consumptions of water and electricity based on the four categories residential, commercial, industrial and others, and (iii) segmenting the various communities in Dubai depending on their consumption behavior. The data used for this study is collected from the open government data and SAS Programming is adopted for data analysis. The results of the analysis revealed that the desalinated water production follows an upward trend, yet still not in line with the consumption growth. Furthermore, there are significant differences between the four categories for both water and electricity consumptions. The highest levels of consumptions are associated with the residential and commercial categories. Finally, the cluster analysis technique revealed fifteen clusters of communities depending on the consumption levels.

scholarly journals Copper ore type definition from Sossego Mine using X-ray diffraction and cluster analysis technique

2012 ◽  
Vol 65 (4) ◽  
pp. 561-566 ◽  
Author(s):  
Viviane Kotani Shimizu ◽  
Henrique Kahn ◽  
Juliana L. Antoniassi ◽  
Carina Ulsen
Keyword(s):  
Cluster Analysis ◽  
Mineralogical Composition ◽  
X Ray Diffraction ◽  
Copper Ore ◽  
X Ray ◽  
Type Definition ◽  
Analysis Technique ◽  
And Cluster Analysis ◽  
Cluster Analysis Technique

This paper presents the classification of 110 copper ore samples from Sossego Mine, based on X-ray diffraction and cluster analysis. The comparison based on the position and the intensity of the diffracted peaks allowed the distinction of seven ore types, whose differences refer to the proportion of major minerals: quartz, feldspar, actinolite, iron oxides, mica and chlorite. There was a strong correlation between the grouping and the location of the samples in Sequeirinho and Sossego orebodies. This relationship is due to different types and intensities of hydrothermal alteration prevailing in each body, which reflect the mineralogical composition and thus the X-ray diffractograms of samples.

scholarly journals Igneous Rock Associations 14. The Volcanic Setting of VMS and SMS Deposits: A Review

2014 ◽  
Vol 41 (3) ◽  
pp. 365 ◽  
Author(s):  
Pierre-Simon Ross ◽  
Patrick Mercier-Langevin
Keyword(s):  
Igneous Rock ◽  
Rock Type ◽  
Massive Sulphide ◽  
Pyroclastic Deposits ◽  
Pyroclastic Rocks ◽  
Rock Types ◽  
Volcanogenic Massive Sulphide ◽  
Vms Deposits ◽  
Volcanic Succession

Volcanogenic massive sulphide (VMS) deposits and seafloor massive sulphide (SMS) deposits have a spatial and genetic connection with contemporaneous volcanism. The control exerted by the volcanic succession (e.g. rock type, architecture and facies) on the nature and style of the ore and alteration (e.g. subsea-floor replacement vs. exhalative, or discordant vs. conformable) is significant, making it imperative to understand the local volcanology in developing better genetic and exploration models. Three VMS deposit groupings collectively represent a high proportion of cases: (1) deposits associated with complexes of submarine felsic domes, cryptodomes, lobe-hyaloclastite flows and/or blocky lavas, and their reworked equivalents; (2) deposits associated with thick piles of pumiceous felsic pyroclastic rocks, suggesting a caldera context; and (3) deposits associated with mafic volcanic footwalls and/or with sedimentary hosts, including significant deposits such as Windy Craggy (~300 Mt) in British Columbia. With regard to number (2) above, demonstrating the presence of a caldera in ancient successions can be difficult because silicic calderas tend to be large and exceed the limits of deposit-scale investigations. Furthermore, there is no consensus regarding what a large submarine caldera should look like, i.e., no accepted facies model exists showing the distribution of rock types. But without thick piles of pumiceous felsic pyroclastic deposits, arguing for a large submarine caldera is a challenge.SOMMAIRELes gisements de sulfures massifs volcanogènes (SMV) et leurs équivalents actuels au fonds des mers ont une connexion spatiale et génétique avec le volcanisme. La succession volcanique – composition, architecture, faciès – exerce un contrôle important sur la nature et le style de minéralisation et d’altération hydrothermale (p. ex. minéralisation mise en place par remplacement sous le fond marin vs. exhalative; altération discordante ou plus concordante). Il est donc impératif de connaître la volcanologie des roches encaissantes pour développer de meilleurs modèles génétiques et d’exploration. Trois groupes de gisements couvrant collectivement une grande proportion des cas sont discutés ici. Premièrement, plusieurs gisements sont associés à des complexes de dômes felsiques sous-marins, des cryptodômes, des coulées de type lobes-hyaloclastite et/ou des laves en blocs, ou leur équivalents resédimentés. Deuxièmement, certains gisements sont associés à d’épaisses séquences de roches pyroclastiques felsiques ponceuses, suggérant un contexte de caldeira. Troisièmement, plusieurs gisements sont associés avec des roches volcaniques mafiques et/ou avec des roches sédimentaires, par exemple l’important dépôt de Windy Craggy (~300 Mt) en Colombie-Britannique. Concernant les contextes de type 2, la démonstration d’une caldeira peut être difficile dans les successions anciennes, car les caldeiras felsiques sont de grandes dimensions, excédant les limites des études à l’échelle du gîte. De plus, il n’existe pas de consensus sur un modèle de faciès pour une grande caldeira sous-marine. Mais sans la présence d’épais empilements de roches pyroclastiques felsiques ponceuses, il est difficile d’argumenter en faveur d’une caldeira sous-marine.

Attribute Recognition of Buried Pipes Based on Multi-Trace Phase Features Using K-means Clustering for GPR Data Interpretation

2021 ◽  
Vol 26 (2) ◽  
pp. 117-132
Author(s):  
Deshan Feng ◽  
Xun Wang ◽  
Hua Zhang ◽  
Jun Yang ◽  
Zhongming Yuan ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Phase Difference ◽  
Laboratory Data ◽  
Object Identification ◽  
Connected Components ◽  
Pipe Material ◽  
Difference Analysis ◽  
Analysis Technique ◽  
Attribute Recognition ◽  
Cluster Analysis Technique

Accurate location and depth determination of underground pipes, especially the attribute recognition, are of great importance yet remake a challenging issue in municipal environments. Single-trace phase difference analysis remains a bottleneck due to its inherent and strong randomness in object identification. This paper developed a multi-trace phase difference analysis framework for ground-penetrating radar (GPR) data based on K-means cluster analysis technique and the theory of region of interest (ROI), which could serve as a new criterion for successful pipe attribute recognition. After improving signal-to-noise ratio of GPR data by using the preprocessing techniques, the connected components algorithms (CCA) based on image segmentation and morphological operation is performed to delineate the ROI. The K-means cluster analysis technique is further employed to efficiently extract the multi-trace phase statistical features for comprehensively evaluating the attributes of ROI. We verify this proposed framework by simulated GPR signals, laboratory data and field datasets. Results demonstrate that the proposed method can not only facilitate the attribute recognition of pipes, but also reduce the interpretation ambiguity of the pipe material even in the field site environment. Specifically, if the phase difference of pipe turns out to be even multiples of π, the target can be automatically identified as metallic-category pipes, whereas odd multiples of π, point to non-metallic-category pipes with a lower permittivity than that of the background. This criterion presents promising applicability in subsurface pipeline identification and attributes recognition, especially in constructing a more appropriate initial model of GPR full waveform inversion for survey in pipes.

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