Role of the Cluster Analysis in Logfacies and Depositional

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International Journal of Engineering Research Science IJOER ISSN 2395 6992 Vol 3 Issue 12 December 2017 . Electrofacies are primarily observational in nature and the classification procedure is based on three steps principal. component analysis cluster analysis and discriminant analysis Principal component analysis is used to summarize the data. and to reduce the dimensionality of the data without any significant loss of information The method displays the data as a. function of new variables called principal components that are simple linear combination of the well logs The aim of. cluster analysis is to classify the well log data into groups that are internally homogeneous and externally isolated on the. basis of a measure of similarity or dissimilarity between the groups The clusters define electrofacies on the basis of the. unique characteristics of well log measurements reflecting minerals and lithofacies within the loggedinterval Once the. electrofacies are identified we can use discrimi nant analysis a multivariate statistical method to assign an individual. observation vector to one of the predefined electrofacies Perez Datta Gupta Mishra 2005 . II BASIC CONCEPTS, Cluster analysis includes a broad suite of techniques designed to find groups of similar items within a data set Partitioning. methods divide the data set into a number of groups predesignated by the user Hierarchical cluster methods produce a. hierarchy of clusters from small clusters of very similar items to large clusters that include more dissimilar items . Hierarchical methods usually produce a graphical output known as a dendrogram or tree that shows this hierarchical. clustering structure Some hierarchical methods are divisive that progressively divide the one large cluster comprising all of. the data into two smaller clusters and repeat this process until all clusters have been divided Other hierarchical methods are. agglomerative and work in the opposite direction by first finding the clusters of the most similar items and progressively. adding less similar items until all items have been included into a single large cluster Cluster analysis can be run in the Q . mode in which clusters of samples are sought or in the R mode where clusters of variables are desired Holland 2006 . The clusters define electrofacies on the basis of the unique characteristics of well log measurements reflecting minerals and. lithofacies within the logged interval Once the electrofacies are identified we can use discriminant analysis a multivariate. statistical method to assign an individual observation vector to one of the predefined electrofacies Perez et al 2005 . The Cluster Analysis module uses standard statistical routines to allow the user to cluster the data into groups to produce an. electrical facies log This log can then hopefully be used to correlate to geological facies Senergy 2008 . III METHODOLOGY, The theory of Cluster Analysis is the module works in two stages Firstly the data is divided up into manageable data. clusters The number of clusters should be enough to cover all the different data ranges seen on the logs 15 to 20 clusters. would appear to be a reasonable number for most data sets The second step which is more manual is to take these 15 to 20. clusters and group them into a manageable number of geological facies This may involve reducing the data to 4 to 5 clusters . Stage 1 K mean clustering The first stage of Facies Clustering uses the K mean statistical technique to cluster the data into. a known entered number of clusters For this to work an initial guess has to be made of the mean value of each cluster for. each input log The initial guess can affect the results and in order to get good results the initial values should cover the total. range of the logs K mean clustering works by assigning each input data point to a cluster The routine tries to minimize the. within cluster sums of squares of the difference between the data point and the cluster mean value The routine works by. calculating the sum of the squares difference for a data point and each cluster mean and assigning the point to the cluster with. the minimum difference Once all the data points have been assigned to the clusters the new mean values in each cluster are. calculated Using the new mean values the routines starts again re assigning the data to the clusters This loop continues until. the mean values do not change between loops These then become the results . Page 36, International Journal of Engineering Research Science IJOER ISSN 2395 6992 Vol 3 Issue 12 December 2017 . FIGURE 1 CROSSPLOTS AND HISTOGRAMS BETWEEN RHOB NPHI DT GR LLD AND MSFL AS. GENERATED BY K MEANS CLUSTER ANALYSIS FOR GROUPS OF MISHRIF FORMATION. Stage 2 Cluster Consolidation Cluster consolidation can be done completely manually by using the crossplot and log plot. output to group data or a hierarchical cluster technique can be used to group the data Hierarchical clustering works by. computing the distances between all clusters and then merging the two clusters closest together The new cluster distance to. all other clusters is then recomputed and the two closest clusters merged again This process continues until you have only. one cluster The results can be plotted as a dendrogram which IP displays The dendrogram shows how the clusters were. merged and the order they were merged Senergy 2010 . Cluster grouping dendrogram, FIGURE 2 CLUSTER GROUPING DENDROGRAM OF MISHRIF FORMATION. Page 37, International Journal of Engineering Research Science IJOER ISSN 2395 6992 Vol 3 Issue 12 December 2017 .
FIGURE 3 CLUSTER GROUPS RANDOMNESS OF MISHRIF FORMATION. TABLE 1, THE PROPERTIES FOR GROUPS OF CLUSTERS AND ENVIRONMENT. Zones Clusters of group Environment, MISHRIF 6 Lagoon. MA 4 Rudist Biostrome Shoal, BAR 2 3 Lagoon, MB11 2 3 Rudist Biostrome Shoal. BAR 3 3 4 Lagoon, MB12 3 2 Rudist Biostrome, BAR 4 4 2 3 Lagoon. MB13 2 3 Back Shoal, BAR 5 6 Basin, MB21 1 2 Slope.
BAR 6 6 5 3 Basin, MC1 2 1 3 Slope, BAR 7 3 2 Basin. MC2 3 2 Slope, IV RESULTS AND DISCUSSIONS, The method has tested on a 398 5 m thick interval of Carbonate deposits in a vertical well from Amara field located in. southeast Iraq Modal data have collected from both core and cutting samples Cluster analysis and electrofacies. classification have performed using advance interpretation in Interactive Petrophysics software version 3 6 . Page 38, International Journal of Engineering Research Science IJOER ISSN 2395 6992 Vol 3 Issue 12 December 2017 . Recognition of Logfacies is a common practice in drilled wells where suitable well logs and core samples are available . Cluster analysis techniques such as hierarchical and k means cluster analysis can be used for classifying well log data into. discrete classes , However studying this part was made through two trends The first trend includes the petrography and microfacies analysis. of Mishrif Formation have been studied on the basis more than 120 thin sections of core samples and the previous. microfacies studies for Mishrif Formation The second trend includes the Mishrif depositional environments in studied wells. depending on the available well logs utilizing cluster analysis technique . 4 1 Carbonate Microfacies and Depositional Environments. Carbonate microfacies and marine depositional environments studied for Mishrif Formation depended on the available thin. sections though they were not enough to cover all the depositional environments of Mishrif Formation Therefore previous. studies and well logs were also depended in this study . 4 2 Mishrif Facies Associations, The Mishrif Formation carbonates were classified following Dunham s 1962 classification modified by Embry and.
Klovan 1971 into mud or grain supported textural types Each type consists of three principal microfacies Aqrawi . Thehni Sherwani Kareem 1998 as follows ,4 2 1 Mud supported microfacies. 4 2 1 1 Pelagic mudstone wackestone, This microfacies occurs at various levels in Mishrif Formation but was existing in the lower parts Micrite is the main. component but planktonic foraminifera also occur in various proportions usually less than 5O This microfacies. dominates the underlying Rumaila Formation Aqrawi 1983 Aqrawi and Khaiwka 1986 and 1989 Pelagic lime. mudstone wackestones are usually interpreted as outer shelf or basinal deposits Wilson 1975 . 4 2 1 2 Bioclastic wackestone, Bioclastic wackestones comprise one of the most common microfacies in the Mishrif Formation carbonates Bioclasts such. as Praealveolinids algae and echinoderms comprise between 10 and 40 of the lithology and limited pelagic foraminifera. also occur The microfacies is characteristic of shallow open marine environments Flugel 1982 . 4 2 1 3 Wackestone packstone, Wackestones packstones are quite common in Mshrif formation Benthic foraminifera such as Miliolids and Textularia . sponge spicules algae small mollusc fragments and echinoderms occur in this microfacies in proportions up to about 50 . The microfacies is typical of lagoons Flugel 1982 or restricted subtidal zones with warm shallow waters and moderate. circulation Tucker 1985 ,4 2 2 Grain supported microfacies.
4 2 2 1 Peloidal packstone, This microfacies is principally composed of peloids of various sizes many of which have an uncertain internal structure In. addition benthic foraminifera rudist fragments and ostracods also occur The microfacies is common in the upper parts of. the Mishrif Formation and is interpreted to indicate shoals and subtidal zones . Page 39, International Journal of Engineering Research Science IJOER ISSN 2395 6992 Vol 3 Issue 12 December 2017 . 4 2 2 2 Rudistid packstone grainstone, This microfacies is characterised by a high content of rudist fragments which are associated with other bioclasts such as. algal debris benthic foraminifera and peloids in smaller proportions It is one of the two principal reservoir facies of the. Mishrif Formation Rudist grainstones are interpreted to be a reef bank or shoal deposit and rudist packstones to be a back . reef deposit ,4 2 2 3 Rudstone, Rudstones are composed of rudist fragments most of which are larger than sand grade in addition to coral fragments of a. similar size This microfacies is interpreted to be a fore reef slope deposit Wilson 1975 The rudstones and rudistid. packstone grainstones are generally over and underlain by subtidal and outer shelf facies respectively in the boreholes. studied These two microfacies are characterised by high primary and secondary porosities and permeabilities together they. form the most important reservoir units in the Mishrif Formation throughout the Mesopotamian Basin Aqrawi et al 1998 . FIGURE 4 HISTOGRAM OF LOGFACIES FOR ZONES OF MISHRIF FORMATION. Page 40, International Journal of Engineering Research Science IJOER ISSN 2395 6992 Vol 3 Issue 12 December 2017 .
Mishrif platform carbonates throughout the southern Iraq and especially in southeast Iraq can be divided into the following. facies associations Figure 4 , FIGURE 5 A SCHEMATIC CROSS SECTION OF MISHRIF PLATFORM SHOWING THE ENVIRONMENTS OF. DEPOSITION OF MICROFACIES ASSOCIATION B BLOCK DIAGRAM SHOWING DEPOSITIONAL ENVIRONMENTS. OF MISHRIF FORMATION AND THE DISTRIBUTION OF MICROFACIES ASSOCIATIONS CIRCLED NUMBERS . FIGURES A B ARE MODIFIED AFTER BURCHETTE 1993 ,4 3 Mishrif Depositional Environments. 4 3 1 Basin Environment, Basinal environment is simply the end of the marine environmental spectrum that began at the strandline and ended at the. deepest part of that particular sedimentary basin Figure 4 There is not even a rigid definition of basinal environment or. Page 41, International Journal of Engineering Research Science IJOER ISSN 2395 6992 Vol 3 Issue 12 December 2017 . basinal facies In fact the greatest depth that exists in one basin may be the same measured depth as the shallow subtidal. regime in another basin Ahr 2008 ,4 3 2 Slope Environment.
Slopes are commonly sites for upwelling initiation of density or turbidity currents and initiation of slumps rock falls and. debris flows triggered by slope failures Figure 4 Environmental processes on slopes are dominated by gravitational forces. and pounding from waves Upper slope zones in relatively shallow water may be subject to wind or storm waves oceanic. currents and tides Middle slope and base of slope zones are typically below fair weather wave base below the influence of. surface currents and relatively less influenced by tidal currents than the upper slope zone Deeper parts of slope zones are. sites where rocks and sediments swept off the slope by shallow water processes come to rest Ahr 2008 . The succession coarsening upward from basinal limestone to shallow marine packstone reflects shallowing of the. depositional environment in response to progradation of carbonate slope Burchette 1993 . 4 3 3 Shoal Environment, Shoal forms a barrier that absorbs most of the wave energy from the open ocean Nichols 2009 This is the most. widespread coarse grained facies association of Mishrif Formation The shoal association is composed of off white poorly. sorted bioclastic packstone grainstone and rudstone Bioclasts are predominantly molluscan mostly rudistid It represents. the deposits of low energy shoals and banks along the platform margin Burchette 1993 . 4 3 4 Rudist Biostrome Environment, This facies association represents the most important reservoir rock in Mishrif Formation The . Interactive Petrophysics software version 3 6 Carbonate microfacies and marine depositional environments studied for Mishrif Formation depended on the available thin sections though they were not enough to cover all the depositional environments of Mishrif Formation Therefore previous studies and well logs were also depended in this study

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