ORIGINAL ARTICLE 3D static reservoir modeling by geostatistical techniques used for reservoir characterization and data integration Mehrdad Soleimani • Behshad Jodeiri Shokri Received: 17 August 2014 / Accepted: 29 January 2015 Ó Springer-Verlag Berlin Heidelberg 2015 Abstract To remove some of the ambiguities in a heterogeneous oil reservoir, a three dimensional model of the reservoir would be constructed by application of newly introduced methods. The aim of this study is to define an accurate and efficient model of a complex reservoir in southwest of Iran and accurately derive the geological and geometrical properties of the reservoir for well location proposal. Seismic data in addition to well logs were used for that purpose. A corner point grid was used in this study, and a generic global scale-up method was combined with previous result for reservoir simulation. The final model pointed out the heterogeneous characterization of the reservoir and proved the advantage of combining these methods in constructing accurate and efficient reservoir models. According to these models, it is concluded that the reservoir has different productive zones in different mem- bers that was not cleared in the previous models. Keywords Reservoir modeling  Grid adaptation  Global scale-up  Reservoir zonation  Time–depth conversion  Depth map Introduction Understanding subsurface structure is an essential task in any reservoir characterization study (Al Bulushi et al. 2012). Various technologies are used to understand a prospective reservoir and provide information at many different scales (Chen and Durlofsky 2006). Most often, geologic interpretation based on seismic information is used to interpolate or extrapolate the measured data in sparse well locations in order to yield complete reservoir descriptions. Reservoir characterization and modeling ob- tained by this information are keys to match the production profile and well planning in oil fields (Aarnes 2004). However, reservoir modeling has become a crucial step in field development, as it provides a venue to integrate and reconcile all available data and geologic concepts (Branets et al. 2009). One of the key challenges in reservoir modeling is ac- curate representation of reservoir geometry, including the structural framework and detailed stratigraphic layers (Novak et al. 2014). The structural frameworks delineate major compartments of a reservoir and often provide the first-order controls on in-place fluid volumes and fluid movement during production. Thus, it is important to model the structural frameworks as accurate as possible. To construct a model, it is necessary to use geostatistic methods. These are considered as the study of phenomena variation using collection of numerical techniques to de- scribe the spatial continuity by a model in a petroleum reservoir (Cornish and King 1988). A typical study in reservoir modeling contains classification and zonation of the reservoir, followed by structural construction and petrophysical models. Finally, 3D geo-model grid, water saturation, porosity, and permeability distributions map are made (Nikravesh and Aminzadeh 2001; Harris and Weber 2006). However, despite decades of advances in grid generation across many disciplines, grid generation for practical reservoir modeling and simulation remains a daunting task. Specific challenges in grid generation for M. Soleimani (&) Faculty of Mining, Petroleum and Geophysics, University of Shahrood, Shahrood, Iran e-mail: msoleimani@shahroodut.ac.ir B. Jodeiri Shokri Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran 123 Environ Earth Sci DOI 10.1007/s12665-015-4130-3