ORIGINAL PAPER Applying the cluster analysis technique in logfacies determination for Mishrif Formation, Amara oil field, South Eastern Iraq Buraq Adnan Al-Baldawi Received: 5 April 2014 /Accepted: 23 May 2014 # Saudi Society for Geosciences 2014 Abstract Reservoir facies determination is the most impor- tant job in oil exploration which dominantly relies on the major properties of rocks. Fundamental properties of rocks are usually understood by their detailed description in the field (lithofacies analysis) and laboratory (petrofacies analysis). The facies (lithofacies and petrofacies) determination in most subsurface studies is impractical, due to lack of cores and cuttings. In such situations, where the wire line logs are the only data available, the logfacies or electrofacies are deter- mined instead. In this study, the available logs (gamma ray, density, Neutron, and sonic logs) for four wells (Am-1, Am-4, Am-5, and Am-6) were used to divide Mishrif Formation into seven units separated by barrier beds. Using cluster analysis in this study practiced the logfacies determination in each unit of Mishrif Formation in Amara oil field using Interactive Petrophysics software. The types of input data into Interactive Petrophysics software to determine logfacies are gamma ray log, porosity, and water saturation which are used to create 15 clusters and determine six groups of logfacies. In this paper, the vertical variations of logfacies for Mishrif Formation are carried out based on six groups of logfacies. These groups of logfacies are classified based on its reservoir properties such as porosity, water saturation, and shale content. In order to conclude the ability of application cluster analysis method, the logfacies of well Am-4 that predicated from cluster analysis were compared with the facies studied from examination of cutting samples. Keywords Logfacies . Cluster analysis . Mishrif Formation . Amara oil field Introduction Well logs are principal sources of subsurface geological infor- mation. They provide significant information on mineralogi- cal composition, texture, sedimentary structures, and petrophysical properties such as porosity and permeability. By compiling data from various well logs, one can discrimi- nate sedimentary units with comparable log characteristics. The sedimentary units which defined on this basis and char- acterized from wire line logs are known as electrofacies or logfacies in the literatures (Serra 1986). Logfacies analysis is the most important tool in petroleum industry, sedimentolog- ical, and depositional environment study of the bearing rocks, especially where wire line logs are only reliable data available (Serra 1986). Logfacies analysis can be carried out manually or automatically using mathematical techniques. Multivariate cluster analysis (as the best method of data grouping) is one of the most accurate and affective methods in oil bearing reser- voir. The method is applied in both detrital and carbonate rocks (Gill et al. 1993). The purpose of the present study is to classify the gamma ray, porosity, and water saturation into logfacies types. The cluster analysis method is used to perform the logfacies classification based on the attempts to identify clusters of well logs responses with similar characteristics. This classification does not require any artificial subdivision of the data population but follows naturally based on the unique characteristics of well-log measurements, reflecting minerals and lithofacies within the logged interval. This clas- sification of logfacies in my study is done by Interactive Petrophysics software. As well as, the vertical distribution of logfacies for Mishrif Formation in Amara oil field is carried out based on the classification of these clusters into six groups of logfacies. In order to obtain accurate logfacies zones of cluster analysis method, the logfacies of well Am-4 that predicated from cluster analysis were compared with the facies studied from examination of cutting samples. B. A. Al-Baldawi (*) Department of Geology, College of Science, University of Baghdad, Baghdad, Iraq e-mail: buraqaddnan@yahoo.com Arab J Geosci DOI 10.1007/s12517-014-1490-z