F. Hormozzade; M. Baniassadi; F. Sahabi; H. Izadi; H. Memarian
Abstract
The determination of Petrophysical rock properties has always been an important part of geological modeling and also is used in reservoir engineering studies. Permeability (k) is one of the most important properties of porous media which is the measure of a porous material to allow fluids to pass through ...
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The determination of Petrophysical rock properties has always been an important part of geological modeling and also is used in reservoir engineering studies. Permeability (k) is one of the most important properties of porous media which is the measure of a porous material to allow fluids to pass through it. Permeability can be determined from both experimental tests and numerical simulations. Numerical simulations should be performed on geometries determined from advanced imaging techniques. Digital rock physics (DRP) is an approach for studying rocks nondestructively. In this paper, 10 carbonate rock plugs from the oil fields in South-West of Iran were imaged by medical CT scan and the outputs were used for image processing and permeability determination. We evaluated the use of Navier-Stokes equations to perform fluid flow simulation through the pore spaces geometry. The permeability of the samples were calculated and compared with laboratory-derived values. The results indicated a trend between the permeability values reported by the laboratory and medical CT images with R2=90%.
F Kamranzad; E Mohasel Afshar; M Mojarab; H Memarian
Abstract
Landslide is one of the natural phenomena which can cause catastrophic losses or damages in life and property each year. Hence, it is very important to recognize landslide-prone areas and apply methods to prevent or reduce slope instabilities and landslide hazard and risk. For this purpose, landslide ...
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Landslide is one of the natural phenomena which can cause catastrophic losses or damages in life and property each year. Hence, it is very important to recognize landslide-prone areas and apply methods to prevent or reduce slope instabilities and landslide hazard and risk. For this purpose, landslide hazard zonation is one of the indirect and efficient methods. This study aims to apply data-driven and AHP methods to provide a zonation map of landslide hazard potential in the Tehranprovince of Iran. First, six essential and available factors including slope, slope direction, geologic background, distance from faults, earthquake acceleration and rainfall were selected to be classified in GIS based on engineering judgment. By superposing data layers over landslide distribution map in data-driven method and expert judgment in AHP method, layers and sub-layers were weighted and combined. The landslide-hazard zonation map was then produced for each of the methods in GIS. Results showed that in data-driven method 92.9% of landslides fall into the perilous zone (i.e. hazardous and very hazardous zones) having an area of 7135.15 km2, which is 37.2% of total area of Tehran province. For the AHP method, 96.47% of the landslides were in perilous zone with an area of 10344.7 km2, which is 53.9% of the total area of the province. Finally, the ratio of percentage of landslides in the perilous zone to the percentage of total area of the zone was calculated. The ratio is 2.5 for the data-driven and 1.79 for the AHP method. The larger ratio in the data-driven method indicates its better consistency than the AHP method, implying more coverage of landslides in a smaller perilous area by the data-driven method. This result represents better accuracy of the data-driven method than the AHP method in landslide hazard zonation.
S Angornai; H Memarian; M Shariat Panahi; M.J Bolourchi
Abstract
Land subsidence is an environmental phenomenon that involves gradual or sudden settlement of the land surface because of compaction of underground material. Groundwater withdrawal, which occurs due to excessive use of water resources, is among the most important reasons for this phenomenon. Therefore, ...
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Land subsidence is an environmental phenomenon that involves gradual or sudden settlement of the land surface because of compaction of underground material. Groundwater withdrawal, which occurs due to excessive use of water resources, is among the most important reasons for this phenomenon. Therefore, land subsidence can lead to destructive results in residential, industrial and agricultural areas. As a result, subsidence caused by excessive use of groundwater resources has occurred in many countries in the world. Tehran metropolitan plain in Iran is one of the most obvious examples, where land subsidence is happening. Although the relationship between land subsidence, groundwater level decline and changes in the physical properties of subsurface material is broadly understood, a comprehensive and precise model to predict land subsidence remains unconstrained. Land subsidence modeling is a complicated matter in geological engineering but can help to better understand subsidence and possibly prevent damages. The commonly used numerical methods for modeling land subsidence are generally based on simple assumptions, which make the model results to be associated with some errors. In this study, artificial intelligent methods such as Artificial Neural Networks (ANN) were used to propose a new method to predict land subsidence. The efficiency of this method was then tested in the South Tehran plain as a case study. We have used hydrological, geotechnical, remote sensing and ambient vibrations for site effect investigations. First, the collected data was studied statistically. Then, the delay between groundwater withdrawal and subsidence was computed by genetic algorithms using available hydrographs and GPS data in a period of 27 months. Model input parameters include changes in groundwater level, natural frequency of soil, alluvial thickness, defined geographic coordinates and time. The model output was an estimated subsidence measured by radar interferometry method. The model was built in 15 time steps using a set of data having 4 months of time difference with the data used to create the model. The comparison between the predicted (modeled) and real (measured by remote sensing) subsidence shows a good correlation, which makes the proposed model reliable.
A.A Morshedy; H Memarian
Abstract
Various interpolation and estimation tools are used to spatially model a regional variable across an area or site. This paper presents a new interpolation method, using the progressive radial basis function network and taking into account the spatial coordinates of the input data. The procedure starts ...
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Various interpolation and estimation tools are used to spatially model a regional variable across an area or site. This paper presents a new interpolation method, using the progressive radial basis function network and taking into account the spatial coordinates of the input data. The procedure starts with the study of the spatial structure and anisotropy of the data, to perform interpolation and determining the radiuses and rotation angles based on the directional variography. Next, the neighborhood radius and neighboring points of each node of hidden unit are determined, using the ellipsoidal anisotropy and the covariance matrix. Then, a shape factor is computed based on half the average distance of all the neighboring sample points. The progressive kernel matrix includes the corrected kernel functions and the coordinates of the nodes in the hidden units utilized to solve the weight matrix. The interpolation was finally performed at each point of regular network (unsampled points). The steps of this interpolation algorithm were evaluated by a synthetic data set, having an irregular 3D pattern. The Cross validation between actual and estimated values have a correlation coefficient of about 0.78 and the fitted line passing through the actual and estimated values is close to 45 degrees.
M Javid; H Memarian; S.M Mazhari; R Zorofi; B Tokhmechi; F Khoshbakht
Abstract
In the oilreservoirsof the ZagrosBasin, fractures play a major role in hydrocarbon migration and production. Borehole image log is a powerful tool to study and identify fractures around the wells. These logs provide critical information about orientation, depth and type of natural fractures. Since thereis ...
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In the oilreservoirsof the ZagrosBasin, fractures play a major role in hydrocarbon migration and production. Borehole image log is a powerful tool to study and identify fractures around the wells. These logs provide critical information about orientation, depth and type of natural fractures. Since thereis noaccuratealgorithmfor automaticidentification of fracture parametersonimage logs of the carbonatereservoirsin Iran, interpretation of theselogsisoftendone manually. This process may become erroneous if the interpreter is not sufficiently experienced. Aimed at automatic detecting of fractures in image logs, this paper presents a new implemented method, which is based upon image processingandoptimization techniques,as well as Artificial Bee Colony Algorithm. According to this approach, points related to fractures arefirst extracted from images using classification methods. Then, the Artificial Bee Colony Algorithmis used to determine the number, depth, dip and dip directionof fractureson extracted points. The proposed method is performed on FMS image log ofonewell located in an oilfield in southernIran. Results areshownindensity log, rose diagramandstereogramfor the identified fractures, and the obtained resultsshow efficiency of the proposedmethod.
F Kamranzad; L Moussavi; M Mojarab; H Memarian
Abstract
In this study,attenuation behavior of moderate to large earthquake aftershock sequences occurred in Iranian plateauhas been investigated according to the empirical Omori Law. Due to proper recordings of instrumental earthquakes from 1990 to 2012, important earthquakes of this period were selected. After ...
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In this study,attenuation behavior of moderate to large earthquake aftershock sequences occurred in Iranian plateauhas been investigated according to the empirical Omori Law. Due to proper recordings of instrumental earthquakes from 1990 to 2012, important earthquakes of this period were selected. After determination of aftershock sequences using temporal-spatial window defined by Gardner &Knopoff (1974), 14 sequenceshaving enough recordings and appropriately distributed over the Iranian plateau were investigated in terms of attenuation behavior curve.Therefore, the Omori curve and parameters (p, c and k)were plotted and calculated for each sequence. Results show that for the Iranian plateau earthquakes, p-values range between 0.39 and 2.7, parameter c values vary from 0.01 to 5, and paremeter k shows values in the range of 10 to 1427.4. This high variability is taken to indicate not only a variety of aftershock occurrence patterns in the Iranian plateau, but also an incomplete and inhomogeneous earthquake catalog.By using the present database, therefore, it is not easily possible to have a zonation based on temporal attenuation behavior of aftershock activitiesover the Iranian plateau. However, the estimations of aftershock attenuation rate for each locality can be used to analyze seismic hazard. Present study showed that the p-values and hence the aftershock attenuation rates in the Alborz and Zagros regions are greater than those in the eastern and central parts of Iran. The higher the rate, the greaterthe energy release, which means a shorter time to gain background seismicity. This result is comparable and consistentwith the amount of energy released in theseismotectonic zones of the Iranian Plateau. Moreover, 7 out of 14 earthquake sequences have secondary aftershocks, which give two values for each Omori parameters. Results demonstrated that with a higher earthquake magnitude, the occurrence of the next big event as well as secondary aftershocks is more likely. Furthermore, for the 7 sequences with secondary aftershocks, a trend of P2 variations is observable. P2 is more than 2.5 for 3 of these sequences that have magnitudes above 7 and occurred along the Iranian plate boundaries. For the other 4 intraplate events, which have magnitudes less than 7, P2 is less than 2. This might be due to a magnitude change or tectonic setting and distance of hypocenter to the main fault nodes. Resultsalso showed that the c and k parameters are highly affected by number of recordings in the catalog. A more complete and homogeneouscatalog would produce well-constrained values for these parameters,which in turnmakes the analysis of the seismicity and physics of the fault zone more accurate.
G Jozanikohan; F Sahabi; G.H Norouzi; H Memarian
Abstract
Clay minerals reduce the reservoir quality in different ways. They may cause mechanical problems in drilling and lead to petrophysicalmisinterpretations.Therefore,Clay typing is necessary for upstream petroleum exploration and production industry. In this paper, type, amount and distribution patterns ...
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Clay minerals reduce the reservoir quality in different ways. They may cause mechanical problems in drilling and lead to petrophysicalmisinterpretations.Therefore,Clay typing is necessary for upstream petroleum exploration and production industry. In this paper, type, amount and distribution patterns of different clay minerals in 76 core samples from two producing and non- producing wells inthe ShurijehFormation, aging early cretaceous,were identifiedby six different instrumental analytical methods such as X-Ray diffraction (XRD), X- Ray fluorescence, thin section studies, thermal analysis (DTA-TGA), scanning electron microscopy (SEM) and measuring the cation exchange capacity (CEC). The results proved that the dominant clay minerals are illite, magnesium rich chlorite andkaolinite. The minor clays are glauconite (in the both wells), montmorillonite (in producing well) and mixed layers of illite-montmorillonite and chlorite-montmorillonite. The average amount of each clay minerals in non-producing well is more than producing one. Then clay minerals were classified on the percentage basis into five classes (less than 10%, 10-15%, 15-20%, 20-25% and more than 25%).According to quantityof samples in each class, the producing and non-producing wells were recognized as clean and shaly sand respectively. An increase in glauconite and Illite amounts and also an increase in illite and chlorite layers of mixed-layered clayswith increasing burial depth and temperature is an obvious sign of burial diagenesis in this formation. The best correlation was observed between percentages of clay minerals and iron, aluminum, potassium and magnesium.The clay minerals in the ShurijehFormation are diagenetic alteration of rock fragments, plagioclase and alkali feldspar in origin and in some cases they originate from outside with layered distribution. Distribution pattern of the autogenic clays are pore filling, pore coating and pore bridging, which cause the porosity and permeability reduction in this formation.
M Mojarab; H Memarian; M Zare; V Kossobokov
Abstract
The earthquake of 23 October 2011, near the Turkish city of Van, had 600 victims and caused great damages in Van, Argis, Moradiyeh and Caldiran. Review of 20th century and historical earthquakes in eastern Anatolian plate and west of Iranian plateau confirmed the activity of this area with the notable ...
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The earthquake of 23 October 2011, near the Turkish city of Van, had 600 victims and caused great damages in Van, Argis, Moradiyeh and Caldiran. Review of 20th century and historical earthquakes in eastern Anatolian plate and west of Iranian plateau confirmed the activity of this area with the notable earthquake of 24 November 1976 in Caldiran. The main objective of this paper is evaluation of predictability of earthquakes in this region. Presently, the two main approaches for predicting extreme events are precursory and pattern recognition algorithms. For this study, we applied M8 algorithm that is based on pattern recognition. In this respect,a 49 point network were designed around the epicenter of Van earthquake and M8 algorithm applied to this network. The end result was four zones with some overlaps that were proposed as CTIP (current time of increase probability). This study could predict the Van earthquake with 1/1/2008 to 30/12/2012 time window, 281 km local radius and magnitude of more than 7. In addition, forward prediction in this area shows there is no alarm for magnitude 7+ in next 5 years. This study showed the strength of M8 algorithm for predicting earthquakes in the Middle East. It can be concluded that using algorithms based on pattern recognition can play an important role for mitigation of damages in seismic events.
B Tokhmechi; H Azizi; H Memarian
Abstract
Estimation of rock type, porosity and saturation are the main applications of petrophysical logs. Several equations are presented for mentioned estimations, and deficiencies of these equations are widely investigated. In this paper, general deficiency of well logs processing methods is discussed. In ...
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Estimation of rock type, porosity and saturation are the main applications of petrophysical logs. Several equations are presented for mentioned estimations, and deficiencies of these equations are widely investigated. In this paper, general deficiency of well logs processing methods is discussed. In general, because of smoothing trait of estimators, variability of estimated data is less than raw data. Since rock type, porosity and saturation are estimated from various well logs, it is anticipated that they have less variability in comparison with raw well logs. Therefore, it seems that energy (equal to information) of Fourier transform of estimated well logs in low frequency bands have to be more than similar energy of raw well logs. This study has been done on raw and estimated well logs of more than 100 wells of Iranian south and southwest oil fields. The results showed that estimated well logs have more variability, which confirms a fundamental deficiency in current well log processing methods.
A. Hossein Morshedy; H. Memarian
Abstract
Zoning is an important practice in earth sciences. In zonation, the study area is divided into separate parts and by compiling the results of these parts, a unique model is obtained. In this study, clustering methods are applied for zoning of Semilan dam site. Optimal number of clusters are measured ...
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Zoning is an important practice in earth sciences. In zonation, the study area is divided into separate parts and by compiling the results of these parts, a unique model is obtained. In this study, clustering methods are applied for zoning of Semilan dam site. Optimal number of clusters are measured based on geotechnical parameters (lugeon, RQD), the importance of various dam structures and lithology indicators. By ranking of 7 clustering validity indexes, the optimum number of clusters found to be 4. In this paper, clustering was performed by faults locations and self-organizing neural network. In the former case, the study area was divided into four zones based on faults. This two dimensional zoning is independed of the third dimension (depth) and each sample belonged to a cluster. In the later case, a self-organizing map (SOM), which is a kind of neural network capable of clustering, was used. The SOM input data consists of, three dimensional parameters (X,Y,Z), geotechnical parameters (lugeon, RQD) and finally indicators of importance of various dam structures and lithology. Then, 7 input parameters were normalized between 0 to 1 and entered the network for training.The output data were allocated to four zones (clusters). For RQD spatial distribution realization, variography and anisotropy parameters for all four zones were calculated for both cases, Based on the main principal of clustering method which is maximum difference between clusters and maximum similarity between members of each cluster, performance and validation of two cases of clustering, RQD data were defined. Clustering quality index defined as sum of mean differences between two clusters divided by sum of standard deviation of clusters. Maximizing of this index is optimal solution. This study showed that clustering by SOM gives more accurate results than clustering by faults.
F. Khoshbakht; H. Memarian; M. Mohammadnia
Abstract
Natural fractures are the main factor which control hydraulic behavior of oil and gas reservoir in naturaly fractured reservoirs. Thus it is important to fully characterize these features in fractured reservoirs. Image logs are one of powerful tools in fracture study in wells. Image log is high ...
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Natural fractures are the main factor which control hydraulic behavior of oil and gas reservoir in naturaly fractured reservoirs. Thus it is important to fully characterize these features in fractured reservoirs. Image logs are one of powerful tools in fracture study in wells. Image log is high resolution “pseudo picture” of borehole wall which records properties of fractures. In present study, FMI (Formation Micro Scanner) of two wells located in the same structural setting of a naturally fractured carbonate are considered. Well A and B drilled through three formations (Asmari, Pabdeh and Gurpi) and fracture data of these formations were acquired from these wells. Both wells located in the same structural setting near each other. We compared fractures of each formation in well A with well B to find out similarity and dissimilarity of fractures occurd in the same formation in different wells. This study shows that density and orientation of bedding planes of well A is completely similar to well B. Density of open fractures of well A is totally different from well B but orientations of open fractures are same in two wells. Density and orientation of filled fractures of well A are similar to well B. Pattern of fractures of Asmari and Pabdeh formations are similar but in Gurpi fractures are different. Comparison of density of bedding planes and fractures show that high fracture frequency occurred in the thin beds, for example FMI show that laminar intervals of Pabdeh coincide with highly fractured intervals.
B. Tokhmechi; H. Memarian; H. Ahmadi Noubari; B. Moshiri
Abstract
Joint study is one of the primary jobs in many geological, mining, geotechnical and petroleum exploration projects. Up to 10 features of joints are gathered during each field survey, while only two of them (dip and dip direction) are normally used to classify these complex features. This paper proposes ...
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Joint study is one of the primary jobs in many geological, mining, geotechnical and petroleum exploration projects. Up to 10 features of joints are gathered during each field survey, while only two of them (dip and dip direction) are normally used to classify these complex features. This paper proposes a new method for joint set classification which can use more than two surveyed features. A synthetic set of 8 joint set, each joint defined with 4 features (dip, dip direction, type of infilling and amount of infilling), created in a way that with two features (dip and dip direction) sets could not be differentiated. Necessary program developed to use Bayesian classifier to sort 8 synthetic joint sets in 4D space. Present study showed that all 8 sets can be successfully differentiated by using Bayesian method.