Ahmad Ashtari

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Andrej Dujella

University of Zagreb

Hemin Koyi

Uppsala University

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University of East London

Graham Martin

University of Leicester

Gwen Robbins Schug

University of North Carolina at Greensboro

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University of Salamanca

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Macquarie University

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Universidade Federal do Rio Grande do Sul

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Swansea University

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University of Copenhagen

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Papers by Ahmad Ashtari

Image processing of sharp boundaries in 2D electrical tomography of faults

Automatic detection of boundaries between different geological bodies in 2D electrical tomography... more Automatic detection of boundaries between different geological bodies in 2D electrical tomography, using Image processing techniques is proposed here. This method is especially efficient for detection of faulting regions, which variation of resistivity values is sharp in one direction. Direction and intensity of faulting are found out by the way of an image processing method. The method is based on calculation of gradient of model resistivity data. Gradient of model resistivity values are calculated in four directions. Direction of maximum gradient vector is proposed as normal to the fault plane. Intensity of faulting is proportional to the magnitude of gradient vector. This method is applied for two synthetic models and one real data set of a faulted region in Iran. The synthetic data are representative of vertical and oblique faults. The result of applying this technique to the real data set is in well agreement with geological evidences. This method is applicable on various geoph...

Reservoir rock typing of the Asmari Formation using integrating geological and petrophysical data for unraveling the reservoir heterogeneity: a case study from the Ramshir oilfield, southwest Iran

The Asmari Formation with Oligo-Miocene in age and a carbonate-siliciclastic lithology is conside... more The Asmari Formation with Oligo-Miocene in age and a carbonate-siliciclastic lithology is considered as one of the main hydrocarbon reservoirs in the Zagros Basin of Iran. In this research, with the target of unraveling the reservoir heterogeneity, a comprehensive rock typing was performed using all available geological and petrophysical data. The procedure for reservoir rock typing was started with the identifying of sedimentary rock types derived from the description of cored intervals and the study of thin sections from 7 cored wells. These studies led to the identifying and classification of 12 sedimentary facies related to the inner, middle, and outer parts of a carbonate ramp platform. The statistical clustering algorithms were applied using Multi-Resolution Graph-based Clustering approach on well log data, resulting in the recognition of five electrofacies (EFs). Accordingly, five hydraulic flow units (HFUs), based on the flow zone indicator method were defined in the reservo...

Seismic spectral decomposition and inversion for buried channels delineation: a case study from the Asmari Reservoir, southwestern Iran

Dense data sampling in 3D seismic surveys provides a clear image from subsurface layers, but it m... more Dense data sampling in 3D seismic surveys provides a clear image from subsurface layers, but it may fail in the cases where the thickness of a layer is below seismic resolution (e.g. thin beds and channels). Seismic spectral decomposition and inversion are among methods that can help us to delineate and study the sub-seismic resolution features. This paper shows how the buried channels of the Asmari formation in an oil field located in southwest Iran were delineated and are studied using seismic spectral decomposition and inversion. The Gabor wavelet transform was used to divide seismic frequency spectra into eight bands out of which three frequency bands with central frequencies of 24, 29, and 35 Hz have been selected for RGB blending for its perfectness in exposing the channels. Several distinct channels were detected at 15ms interval below the top of the Asmari formation. The P-impedance data coincide with the findings further giving information on lithological aspects. Detailed ...

Safety assessment of landslide by 2D and 3D electrical tomography

Occurrence of landslides depends on several factors such as the composition and structure of eart... more Occurrence of landslides depends on several factors such as the composition and structure of earth materials, rainfall level, temperature, groundwater regime and cover crops. Landslides are a main natural hazard in Iran, because of its special geological conditions and its mountainous active tectonic regime. Linear civil structures, such as roads, highways and railways, face serious problems in Iran, because of their long length which exposes them to several various geological features. For analyzing the stability of these structures, several geophysical methods, such as electrical tomography methods are frequently used. The main purposes of geophysical surveys are reconstruction of landslide geometry, detection of sliding surface (between sliding mass and bed rock), and exploration of the groundwater flow regime which is a stimulant factor before landslide occurrence.

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Safety Assessment of Landslide by Electrical Tomography: A case study from Ardabil, Iran

Safety assessment of landslides in risk bearing areas over linear civil structures has an importa... more Safety assessment of landslides in risk bearing areas over linear civil structures has an important role in programming the following designs. As a part of a program, after a landslide in Saien, in June, 2005, which ruined a part of Nir-Sarab Road, electrical tomography has been performed to detect the unstable risk zones in order to make precautions to avoid

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Nearest Neighbor Based Seismic Attribute Selection for Effective Porosity Prediction

Proceedings, 2014

ABSTRACT We applied a non-linear, robust, attribute selection method called RGS (Regression, Grad... more ABSTRACT We applied a non-linear, robust, attribute selection method called RGS (Regression, Gradient guided, feature selection) to find an optimal subset of attributes for prediction of effective porosity in an oil field from south-west of Iran. This method utilizes a special kind of k-nearest-neighbor algorithm as predictor that makes attribute selection procedure fast and suitable for large scale problems. Comparing the results from this algorithm to common attribute selection methods indicated RGS is superior to other methods for reducing the curse of dimensionality by selecting lower number of attributes and resulting in the smallest validation error among all. Analyzing the results of this study indicated consideration of complex dependency of the target function on group of attributes helps RGS to achieve better performance.

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Neuro-Fuzzy estimation of permeability from SNMR and Electrical Tomography Methods: A case-study from Iran

Surface Nuclear Magnetic Resonance (SNMR) is a new geophysical method currently developed for sha... more Surface Nuclear Magnetic Resonance (SNMR) is a new geophysical method currently developed for shallow investigations of aquifers. Compared to the other geophysical methods, SNMR is a water selective method. Therefore, hydraulic properties of media are achievable through SNMR investigations. Relative to classical electrical methods, SNMR still costs much. In order to reduce the expense of the survey, it should be better to perform a sufficient electrical tomography in the region, and then few SNMR sounding for acquiring aquifer properties. Then it is possible to use the Neuro-fuzzy estimator for estimating permeability in the regions without SNMR data. Neuro-fuzzy estimator is tested on a 3D synthetic model. A case study is also presented to explain the applicability of the Method. The study area is located in Iran. The scope of the survey is determining the best well site for drilling. The transmisitivity map of the aquifer is contoured for selecting the best permeable site.

Safety assessment of landslide by 2D and 3D electrical tomography

Introduction: Occurrence of landslides depends on several factors such as the composition and str... more Introduction: Occurrence of landslides depends on several factors such as the composition and structure of earth materials, rainfall level, temperature, groundwater regime and cover crops. Landslides are a main natural hazard in Iran, because of its special geological conditions and its mountainous active tectonic regime. Linear civil structures, such as roads, highways and railways, face serious problems in Iran, because of their long length which exposes them to several various geological features. For analyzing the stability of these structures, several geophysical methods, such as electrical tomography methods are frequently used. The main purposes of geophysical surveys are reconstruction of landslide geometry, detection of sliding surface (between sliding mass and bed rock), and exploration of the groundwater flow regime which is a stimulant factor before landslide occurrence.

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Integration of 3D seismic attributes and well logs for Asmari reservoir characterization in the Ramshir oilfield, the Dezful Embayment, SW Iran

3D seismic attributes and well logs were used to estimated porosity and water saturation in the A... more 3D seismic attributes and well logs were used to estimated porosity and water saturation in the Asmari Formation in the Dezful Embayment, SW Iran. For this purpose, at first, the 3D seismic volume was inverted base on the model, to obtain acoustic impedance cube. Afterward, the impedance and other attributes extracted from seismic volume were analyzed by multiple attribute regression transform and neural networks to predict porosity and water saturation between wells. Then linear or non-linear combinations of attributes performed for porosity and water saturation prediction. The result shows that the match between the actual and predicted porosity and water saturation improved; using only a single attribute to the derived multi attribute transforms and neural networks model. Based on the results of neural networks, the highest cross-correlation was observed between seismic attributes and the observed target logs between seven wells in the study area. Based on our study, the cross-co...

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Image Processing of Sharp Boundaries in 2D Electrical Tomography of Faults

This was an innovative work of me and one of my classmates in master period. I have simulated the... more This was an innovative work of me and one of my classmates in master period. I have simulated the method on synthetic data as well as real case studies I have faced in my job in copper exploration. Automatic detection of boundaries between different geological bodies in 2D electrical tomography, using Image processing techniques is proposed here. This method is especially efficient for detection of faulting regions, which variation of resistivity values is sharp in one direction. Direction and intensity of faulting are found out by the way of an image processing method. The method is based on calculation of gradient of model resistivity data. Gradient of model resistivity values are calculated in four directions. Direction of maximum gradient vector is proposed as normal to the fault plane. Intensity of faulting is proportional to the magnitude of gradient vector. This method was applied for two synthetic models and one real data set of a faulted region in Iran. The synthetic data a...

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Image processing of sharp boundaries in 2D electrical tomography of faults