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Reservoir characterization of petroleum reservoirs can be claimed as one of the most important parts of reservoir management for optimized production and future developments. Through reservoir evaluation, geological zoning for a better comprehension of subsurface structure is needed. For developing a model, porosity plays a vital role; there are two common methods for obtaining this parameter, core samples and well logging. However, the results of these methods are in well scale which cannot be used through field scale modeling. A solution can be the combining seismic field data well log data, which makes it possible to estimate the reservoir properties in field scale. In this study, multi-attribute analyses were applied based on multilayer perceptron to determine the reservoir facies alteration and heterogeneity in the Ghar reservoir of the Hendijan oil field located in the Persian Gulf. Facies modeling was done through the sequential indicator simulation (SIS) algorithm which coupled with the possible trend and indicator kriging (IK) as geostatistical methods. Within the comparison of these two generated models with core facies, the obtained accuracy of SIS algorithm coupled with the possible trend and indicator kriging are 94% and 72%, respectively. Porosity distribution was also done by the sequential Gaussian simulation (SGS) algorithm which resulted the average porosity of 18% in Ghar formation. The SIS method results are compatible with the porosity distribution model obtained from the SGS simulation. The final results prove the robustness of the applied methods for facies and porosity modeling. [ABSTRACT FROM AUTHOR]

Shale and clay minerals as common constitute in the sandstones can be distributed in various scenarios which in turn can result in different reservoir and elastic properties. A new classification with distinct subclasses for clay distribution has been proposed based on the plausible configuration of shale/clay particles within the sandstone reservoirs. These subclasses give more quantitative insights into laminated, structural and dispersed clay scenarios by taking into account more details of the shale and clay microstructures. Some rock physics-based workflows were proposed and implemented on a real dataset to validate the given strategies to model different clay distribution types. These workflows can be used to generate a template in the elastic domain in order to differentiate various clay distributions. Accordingly, our dataset which was taken from a shaly sandstone in the Persian Gulf, was investigated in more details using the generated template for detecting different clay distribution types as well as observing different elastic and reservoir properties when clay distribution type is changed. We observed that there are four different classes (class I, II, III and IV) of properties with different trends in the crossplot of P-wave velocity versus porosity. Class I includes properties which their P-wave velocity increased when porosity is reduced. In contrast, class II includes properties which show a decreasing trend for P-wave velocity when porosity is reduced. Class III belongs to the properties with two different trends towards structural and dispersed clays. These properties do not follow the same trends for P-wave velocity changes versus porosity similar to classes I and II. However, when the given property decreases or increase by moving toward dispersed clay or structural clay, their P-wave may increase or decrease, respectively. Finally, class IV includes properties which their values do not show any particular trend within the given clay distribution types template. [Display omitted] • New topological classification for clay distribution based on plausible configuration of shale/clay particles. • Applicable in reservoir characterization workflows. • Several rock physics-based approaches proposed according to new classification. • A new rock physics template to differentiate various clay distribution. • Four different classes of reservoir and elastic properties of the rock as delineation attributes in sand-clay mixtures. [ABSTRACT FROM AUTHOR]

Facies modeling of Albian-Turonian successions at Tang-e-Bijar gas field in the Lurestan Province, NW of the Zagros region, Iran is the main objective of this study. The sedimentary environment and biozones of the Sarvak and Garau formations (Albian-Turonian time) are different in Lurestan Province when compared with the south Zagros and the Persian Gulf ranges. Synchronous successions of the formations with different lithofacies and laterally changing of biofacies are always controversial. The primary objectives of this paper is to determine the concurrency of the Sarvak and Garau successions using the correlation of foraminifera biozones and subsequent modeling of simultaneous lithofacies via employing the Truncated Gaussian Simulation with a trend (TGSim) algorithm. In this regard, the Tang-e-Bijar and nearby field data such as core data and petrophysical logs, paleontological and stratigraphy studies were taken into consideration. The stratigraphic ranges of the two formations were determined as Albian-Turonian age. Based on these biostratigraphic data, the tongue of the Garau Formation was clarified. The sequence stratigraphy zonation has been used for the entire Tang-e-Bijar field wells, based on Integrated Prediction Error Filter Analysis (INPEFA) logs and core data. In order to capture the heterogeneity of deep sea lithofacies, MRGC clustering method with supervising lithofacies was implemented in this study and five electrofacies were generated and coded from 1 to 5. They correspond to Rudist-Oncoids, packstone to grainstone (RO), Orbitolinid peloid packstone (OP), Fine Orbitolinid wackestone to packstone (FO), Bioturbated echinoderm mudstone to wackestone (BM), and Oligosteginid Mudstone (OM) lithofacies, respectively. The facies modeling in the reservoir such as Tang-e-Bijar where synchronous successions and laterally transient heterogeneous has occurred has always been challenging. To address this challenge, a new workflow has been implemented in this paper. • Facies Modeling of Albian-Turonian successions in Lurestan province at the northwest of the Zagros fold-thrust belt, Iran is the main objective of this study. • Multi Resolution Graph Based Clustering (MRGC) techniques have been used for identifying electrofacies in reservoirs. • Sequence stratigraphy and age determination have been done based INPEFA log and the Zagros biozonation. • The Truncated Gaussian with Trend method has been used to distribute facies parameters. [ABSTRACT FROM AUTHOR]