NIOC Exploration Directorate

Tehrān, Iran

NIOC Exploration Directorate

Tehrān, Iran
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Gharibi M.,Sahand University of Technology | Shadmanaman N.,Sahand University of Technology | Kazemi K.,NIOC Exploration Directorate | Zagros P.P.,NIOC Exploration Directorate | Mirzakhanian M.,NIOC Exploration Directorate
SEG Technical Program Expanded Abstracts | Year: 2015

Deconvolution is one of the main steps in seismic data processing. It compresses the wavelet in order to improving resolution. Wiener deconvolution is one of the famous deconvolution method that uses the early part of autocorrelation of seismic trace as a representation of seismic wavelet. The smoothed amplitude spectrum of seismic data assumed to be the amplitude spectrum of seismic wavelet. Each trace can be assumed to be a linear combination of a number of Ricker wavelet with different peak frequency, center time and phase (Liu and marfurt, 2007), therefore its amplitude spectrum is a function of or depends on significant Ricker wavelets. The result of deconvolution greatly depends on the wavelet estimation. Here, we aim to introduce an alternative way for wavelet estimation based on fitting Ricker wavelet spectra on the seismic spectrum. Separable nonlinear least square (SNLS) method is applied to optimum determination of peak frequencies of main Ricker wavelets in order to fit seismic spectrum. Results of our synthetic and real tests indicate that proposed method have significant improvements on deconvolution outputs, comparing with Wiener deconvolution. © 2015 SEG.

Pireh A.,Research Institute of Petroleum Industry RIPI | Alavi S.A.,Shahid Beheshti University | Ghassemi M.R.,Geological Survey of Iran | Shaban A.,NIOC Exploration Directorate
Journal of Petroleum Science and Engineering | Year: 2015

Shale-gas production depends on natural and hydraulic fractures to flow it to well. A major part of source rocks in the Zagros Fold Belt was deposited during Neocomian time; the lowermost part of the Garau Formation has charged the Early Cretaceous Petroleum System of the Lurestan subzone, which has a potential of being as a shale-gas resource. These source rocks are widely distributed in the Lurestan Depression and in the NW part of the Dezful Embayment. Knowing factors which control fracture intensity and fracture length in each area are important in drilling into shale-gas resources. In this regard, a very dense and accurate field data acquisition on fracture sets, orientation, length, as well as bedding thickness, texture and lithology was carried out in Early Cretaceous Garau Formation and basal Sarvak Formation within two anticlines with different structural settings (Kabir-Kuh and Khoram-Abad). According to our analyses, we have identified 2 fracture systems: (1) an orthogonal fracture system: set A in Khoram-Abad anticline and sets A and B in the Kabir-Kuh anticline and a longitudinal fracture set: set B in Khoram-Abad anticline and sets C and D in the Kabir-Kuh anticline, (2) an oblique fracture system: sets C and D in Khoram-Abad anticline and set E in the Kabir-Kuh anticline. The normal faults and stylolites (prior to stylolitization) in the study area of Kabir-Kuh anticline had formed in response to extension stress regime and the transverse fractures in the study area of Khoram-Abad anticline are Early Cretaceous to Late Oligocene in age, then the transverse fractures and their orthogonal stylolites in Kabir-Kuh anticline and longitudinal and oblique fracture systems in the Khoram-Abad anticline have formed from Early Miocene to Middle Late Miocene, while longitudinal and oblique fracture sets in the Kabir-Kuh anticline have formed since Middle Late Miocene. We suggest that there have been two phases of counterclockwise rotations in orientation of the stress fields that had produced these fractures. The rotations in the stress field have probably occurred due to rotation of the Arabian plate during its convergence to the Eurasian plate which had changed the orientation of fractures. These rotations forming some range of fractures with different attitudes, that now with recent direction of impression apply by the Arabian plate those fractures which generate in the past would have shown different reaction. In our study area in addition to transverse fracture sets which originated near parallel to maximum horizontal stress, one set of oblique fractures is the second normal fracture set which is reactivated in response to fluid pressures, prior to origination of new hydraulic fractures. In the Lurestan structural province, deformation intensity is increased from the Kabir-Kuh anticline in the southern part of the Lurestan structural province to the Khoram-Abad anticline in the northeastern part of the province. In the Kabir-Kuh anticline, lithology has played the most important role in fracture intensity, so that in some places even with increasing bedding thickness, we observe an increase in fracture intensity instead of the expected decreasing fracture intensity. While in Khoram-Abad anticline bedding thickness has the most important effect on fracture intensity, and lithology has a minor role. In both investigated areas, fracture length is increased with changing texture from mudstone to wackstone and also from wackstone to packstone. © 2014 Elsevier B.V.

Dehbozorgi M.,University of Tehran | Pourkermani M.,University of Tehran | Arian M.,University of Tehran | Matkan A.A.,University of Tehran | And 2 more authors.
Geomorphology | Year: 2010

Neotectonics is a major factor controlling landform development in tectonically active regions, and it has significantly affected fluvial systems and mountain-front landscapes in the Sarvestan area of the central Zagros, Iran. The area is located along the simply folded belt of the Zagros, and is an outcome of the SW-NE oriented tectonic conversion that initiated in the Late Cretaceous and strengthened during the Early Miocene due to the collision of the Arabian and Eurasian plates. To assess tectonic activities in the area, we analyzed geomorphic indices: the stream-gradient index (SL), drainage basin asymmetry (Af), hypsometric integral (Hi), valley floor width-valley height ratio (Vf), drainage basin shape (Bs), and mountain-front sinuosity (J). These indices were combined to yield the relative active tectonics index (Iat) using geographic information systems (GIS). Based on Iat values, the study area was divided into four parts: Class 1 (very high relative tectonic activity, 1.0% in area); Class 2 (high, 20.0%); Class 3 (moderate, 67.0%), and Class 4 (low, 12.0%). The results are consistent with field observations on landforms and geology. © 2010.

Khoshdel H.,NIOC exploration Directorate | Riahi M.A.,University of Tehran
Journal of Petroleum Science and Engineering | Year: 2011

This study focuses on one of the marine oil fields in the Southwest Iran. The main reservoir unit in the interested area is composed of an alternation of thin dolomite and anhydrite layers. In the available 3D seismic data, these layers cannot be resolved. Because of a composite detectable seismic response, it is difficult to make reservoir characterization by conventional seismic attribute analysis. In addition to resolving the major reservoir rock units, the main aim of this study is to predict accurate porosity and make 3D porosity cube. For this purpose, at first, the 3D seismic volume was inverted to obtain acoustic impedance cube. In the next step, the acoustic impedance attribute besides other attributes extracted from seismic volume was analyzed by multiple attribute regression and neural networks to predict porosity. These linear or non-linear combinations of attributes for porosity prediction result in improved match between the actual porosity and predicted (in comparison with using only single attribute to predict porosity). An error of 1.1% in porosity prediction causes a change of 1500000 STBO in oil reserves in the oil reservoir. This shows the importance of using a better prediction method. To estimate the reliability of the derived multi attribute transforms, cross validation is used; according to the results it is found that the cross correlation between actual porosity and predicted porosity increased from 80% in the case of using a single attribute to 88% in the other case using multiple regression transform. Also, neural networks provide higher cross correlation values than both previous cases. Finally, according to the cross validation results, multiple regression transform is used for porosity prediction. Using implemented estimation technique, porosity slices prepared from the producing rock unit (A3 layer) provided a reliable result from lateral and vertical heterogeneities inside the A3 layer. © 2011 Elsevier B.V.

Tavakoli M.,South Pars Gas Complex SPGC | Nejati Kalateh A.,University of Shahrood | Ghomi S.,NIOC Exploration Directorate
Journal of African Earth Sciences | Year: 2016

The thick sedimentary units in Central Iran contain structures that form oil traps and are underlain by a basaltic layer which is amenable for study using its magnetic susceptibility. The study and modeling of such sedimentary structures provide valuable exploratory information. In this study, we locate and interpret an underground magnetic susceptibility interface using 3D non-linear inverse modeling of magnetic data to make a better judgment in the context of hydrocarbon existence. The 3D structure is reconstructed by making it equal to a number of side by side rectangular hexahedrons or prisms and calculating their thicknesses such that the bottoms of the prisms are corresponding to the magnetic susceptibility interface. By one of the most important mathematical tool in computational science, Taylor series, the non-linear problem changes to a linear problem near to initial model. In many inverse problems, we often need to invert large size matrices. To find the inverse of these matrices we use Singular Value Decomposition (SVD) method. The algorithm by an iterative method comparing model response with actual data will modify the initial guess of model parameters. The efficiency of the method and subprograms, programmed in MATLAB, has been shown by inverse modeling of free noise and noise-contaminated synthetic data. Finally, we inverted magnetic field data from Garmsar area in Central Iran which the results were acceptable. © 2015 Elsevier Ltd.

Mahbaz S.,Petro Gostar Permayon Company | Sardar H.,Petro Gostar Permayon Company | Namjouyan M.,Petro Gostar Permayon Company | Mirzaahmadian Y.,NIOC Exploration Directorate
Petroleum Geoscience | Year: 2011

Although reservoir quality cut-off criteria have been used formore than 50 years as a guide for economic decisions, there is still no rationalprocedure for identifying and applying them in Iranian oil and gas fields. Inother words, there are different 'rules-of-thumb' in different sections of theNational Iranian Oil Companies for determination of cut-off values. Forinstance, in one section, values of 10%, 50% and 50% are used for porosity,water saturation and shale content cut-offs, respectively; in another section,cut-off criteria are not used at all, simply an estimate of the time when 20%of oil-in-place could be produced. This paper addresses the optimization ofcut-off value estimation from raw and processed petrophysical data based onextracting the most appropriate relationship for permeability as a functionof porosity, water saturation and shale content - k = $(φ, Sw, Vsh). Theprocedure starts by looking at permeability as the key parameter in choosinga cut-off value because sometimes the minimum value (the permeabilitycut-off) is directly related to economic circumstances and is defined by theclient. Regression analysis coefficients of 0.936 and 0.870 were achieved forrelationships of the form k = $ (φ, Sw, Vsh) in the two petrofacies intervalsstudied. This leads to specification of minimum k values of permeability anddetermination of optimum cut-off values for φ, Sw and Vsh. This method isthen used to determine optimum cut-off values for the Burgan Member(sandstone) in the Kazhdumi Formation in an offshore oil field in the PersianGulf. The calculated cut-off values for this case for k = 1.0 mD are φ = 12.5%,Sw = 60% and Vsh = 27%, as opposed to the 'standard' corporate values ofφ = 10%, Sw = 50% and Vsh = 50%. © 2011 EAGE/Geological Society of London.

Shaban A.,NIOC Exploration Directorate | Sherkati S.,NIOC Exploration Directorate | Miri S.A.,NIOC Exploration Directorate
Geological Magazine | Year: 2011

Most carbonate fractured reservoirs display complex behaviour in the simulation and production stages of their development, and this complexity is thought to be the result of the different fracture distributions and intensities within the reservoir. Accurate fracture characterization is therefore essential and the two techniques most commonly used for fracture prediction are 'strain analysis' and 'curvature analysis'. In this paper these two methods of fracture analysis are compared by applying them to the Gachsaran oil field in the Zagros folded belt and comparing the predictions of the two with the performance history of the reservoir. This reservoir is well suited for such a study as there is a large quantity of seismic data and over 350 wells have been drilled. Fracture intensity indicator maps have been produced using both methods and the results compared with production index data from the wells. The indicator map produced using the 3D strain analysis method in which special attention was given to the structural setting, structural evolution and the position of the fractures with respect to the local stress orientation, was found to be more compatible with the production index data than the map produced using the method of curvature analysis. In addition, the study also demonstrates that one of the great advantages of strain analysis compared to the curvature method is its ability to predict variations in the vertical direction and thus provide data related to a reservoir volume rather than simply to a surface. © 2011 Cambridge University Press.

Tolokonnikova Z.,Kuban State University | Yazdi-Moghadam M.,NIOC Exploration Directorate
Geologos | Year: 2013

Four bryozoan species are described from the upper member (Shishtu II) (Visean, Early Carboniferous=Mississippian) of the Shishtu Formation of central Iran: Nikiforovella ulbensis Nekhoroshev, 1956, Nicklesopora elegantulaformis (Nekhoroshev, 1956), Primorella cf. iranica Gorjunova, 2006, and Nikiforopora intermedia (Nikiforova, 1950). This Visean assemblage shows close palaeogeographical affinities of Iran with Kazakhstan and Russia (eastern Transbaikalia, Kurgan region).

Ghafouri A.,NIOC Exploration Directorate
32nd Asian Conference on Remote Sensing 2011, ACRS 2011 | Year: 2011

Imagery and remotely sensed data is one of the most efficient tools for the assessment and monitoring of earth resources. Since the advent of cheap and declassified satellite images in the late 1970s and early 1980s, mineral and hydrocarbon explorations have begun to use satellite imagery to map not only the visual light spectrum over exploration processes, but spectra which are beyond the visible. Satellite based spectroscopes allow the modern hydrocarbon explorations, in regions devoid of cover and vegetation, to map minerals and alteration directly. Improvement in the resolution of modern commercially based satellites has also improved the utility of satellite imagery. RADAR imagery which is one of remotely sensed data is an acronym for radio detection and ranging. This object-detection system which uses electromagnetic waves specifically radio waves to determine the range, altitude, direction, or speed of both moving and fixed objects. The radar dish, or antenna, transmits pulses of radio waves or microwaves which bounce off any object in their path. The object returns a tiny part of the wave's energy to a dish or antenna which is usually located at the same site as the transmitter. For example GPR which is a geophysical method that uses radar pulses to image the subsurface uses electromagnetic radiation in the microwave band (UHF/VHF frequencies) of the radio spectrum, and detects the reflected signals from subsurface structures. This system can be used in a variety of media, including rock, soil, ice, fresh water, pavements and structures. It can detect objects, changes in material, and voids and cracks. Using remotely sensed imagery in the process of hydrocarbon exploration accelerates whole the process enormously. The best situation that this method is highly recommended is in hydrocarbon exploration in vast areas as the basis of further studies.

Ghafouri A.,NIOC Exploration Directorate
32nd Asian Conference on Remote Sensing 2011, ACRS 2011 | Year: 2011

Remote sensing is an efficient tool for the assessment and monitoring of natural resources. Image classification is the most general method of information extraction through remotely sensed images. Mixed pixels, however may lead to inaccurate classification results in most conventional image classification algorithms. Subpixel image classification is a process which tries to extract the proportions of the pure components of each mixed pixel. In traditional image classification methods which are called pixel-based methods in this article, each pixel is assigned to a single class by assuming all pixels within the image are pure. Therefore, acknowledging surface heterogeneity during image classification is important. This can be done by using spectral unmixing techniques. It is a technique that has been developed to derive fractions of spectrally pure materials that contribute to observed spectral reflectance characteristics of a mixed pixel using endmember spectra. Image classification results is the basis of many judgments and decisions in remotely sensed projects, afterward its precision must be evaluated as well to remove any inaccuracy or errors that distorts accuracy and accurateness of process to get the process improved in further projects. There are many pixel unmixing and subpixel image classification methods however they have some common aspects in procedure. In this paper three methods of these methods are selected and applied. Using the aforementioned method makes the process of petroleum exploration faster and to some extents easier. The best situations that this method is highly recommended are: oil exploration in very large areas to make a general decision in the process of exploration and the other situation doubtlessly is in control procedure of the petroleum exploration process.

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