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Shiraz 2009 - 1st EAGE International Petroleum Conference and Exhibition
- Conference date: 04 May 2009 - 09 May 2009
- Location: Shiraz, Iran
- ISBN: 978-90-73781-65-8
- Published: 04 May 2009
81 - 100 of 140 results
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Noise, the What, the Where and the How To
Authors S. Taylor, T. Ulrych, B. Nedilko and I. Weir-JonesThe ability to deliver drastic improvements in signal to noise ratio are a key step to enhancing the results of passive seismic surveys - whether short or long term; carbonate or clastic formation; deep or shallow; and fluid or steam stimulated. Across the board noise is the primary enemy of passive seismic. The authors detail advances in noise filtering and reduction techniques and detail the journey to automation of this technique as an embedded DSP routines directly onto the data acquisition system. Selected case studies will be detailed and explained in terms of data fidelity and the practical relevancy of associated benefits.
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Detection of Micro Faults in Dipping Layers in 3D Seismic Data by Coherency Attributes
Authors A. Hashemi Gazar and A. JavaherianCoherency attribute is a measure of lateral changes in acoustic impedance caused by variations in structure, stratigraphy, lithology, porosity, and fluid content. When coherency attributes are applied to seismic data, they might indicate the continuity between two or more traces within a seismic window. The rate of seismic continuity is an index of geological continuity. Areas of traces that change with a fault or other geological phenomena have lower coherency in contrast with the adjacent traces. There are three solutions to calculate coherency attributes that include cross-correlation, semblance and eigenstructure. To study the ability of coherency attributes in delineating micro faults, we generated several 3-D synthetic seismic cubes including horizontal, dipping, and cross dipping layers with micro faults. We also studied the effect of the dominant frequency and the size of analysis cube in calculating coherency attributes using MATLAB. We applied all three approaches of coherency attributes to 3-D real data. Coherency attributes proved to be very effective in defining micro geological discontinuities even up to 4 ms.
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Relationship Between Velocity and Permeability Using Hydraulic Flow Units
Authors A. Pouladi, E. Kazemzadeh, G. Norouzi and M. ShabanEstimation of Relationships between velocity of P-wave and permeability by using usual method is difficult. In this study that is first research in Iranian oilfield we show that by grouping and sorting rocks into hydraulic units, we can establish relationships between velocity and permeability. We can determine the hydraulic units by using measured porosity and permeability values from core analysis. Correlation between velocity and permeability is significant within each hydraulic unit. In the first part of study we determine this relation and the correlation coefficient (R2) lies in the range 0.67–0.80. We know that the compaction and cementation history of sediment can have effects on porosity and permeability and velocity of P-wave. At this study we determine relation between permeability and velocity within specific case study and then by comparison to one wave theory (Biot model of wave) we demonstrate that the good match is between them. This relation can be used to predict permeability from velocity in well logs by zoning the data from training wells into hydraulic units.
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Application of Artificial Neural Network for Estimation of Formation Permeability in an Iranian Reservoir
Authors M. Yeganeh, M. Masihi and S. FatholahiThe permeability is one of the most important reservoir parameters and its accurate prediction is necessary for reservoir management and enhancement. Although many empirical formulas are derived regarding permeability and porosity in sandstone reservoirs [1], these correlations cannot be modified accurately in carbonate reservoir for the wells which are not cored and there is no welltest data. Therefore estimation of these parameters is a challenge in reservoirs with no coring sample and welltest data. One of the most powerful tools to estimate permeability from well logs is Artificial Neural Network (ANN) whose advantages and disadvantages have been discussed by several authors [2]. In this paper, 767 core data sets and their corresponding well logs were taken from five wells of a reservoir in south west of IRAN. Depth, NPHI, PHOB, DT and total porosity were used as the input data and horizontal permeability obtained by coring was as target data. 60% of these data points were used for training and the remaining for predicting the permeability (validation and test).An ANN was developed and a correlation coefficient of 0.965 was obtained by comparing permeability predictions and the actual measurements. Data sets are well log and core data of a reservoir.
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Estimate of Porosity Distribution by Using Seismic Inversion and Geostatistics Methods in one of the Oil Fields of Iran
Authors Z. Farajpour, M. Nabi-Bidhendi and M.R. TorabiWe analyse data acquired over a part of studied field how 3D seismic inversion and 3D geostatistical analysis can be used to predict porosity. The adopted techniques in this study are ordinary kriging and cokriging using well to well, well to seismic and seismic to seismic variograms. The result is a set of porosity simulations, all of which are equally probable. The simulations, computed as 3D volumes, are constrained to be in agreement with both log and seismic data and the geologic model for the reservoir. Summary maps can be used to view the average porosity in any layer or combination of layers. The integration of 3D geologic modelling and high resolution constrained model based seismic inversion has proven to be a useful tool in the exploration for hydrocarbons (Pendrel and Van Riel, 1997). We use the constrained model based inversion cube corresponding to the project data as a co-simulator. This is computed using all of the available information seismic, interpreted horizons, geology and logs. We using the estimated probability density functions (pdf’s) and variograms, we do 3D sequential spherical co-simulation of the porosity logs with the inversion impedance cube as the secondary input.
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Seismic Inversion and Multi Attribute Analysis to Prediction of Porosity Distribution in an Oil Field in SW of Iran
Authors A. Rahimi Zeynal and M.A. RiahiThis paper describes a methodology for the integration of well logs and a series of grid-based attributes extracted from interpreted seismic data for prediction of porosity distributions. The studied area is located in the southwest Iran. Before finding a relationship between the target logs and predicted logs from 3D seismic data, we have interpreted the 3D seismic data in the studied area. Also we matched and combined well data with seismic for forward modeling and seismic inversion. Inversion produces a full band acoustic impedance model of earth which improves the vertical resolution. Then we have checked other different inversion methods such as spare spike and model based. Since the model based method resulted with a better resolution outcome, therefore we decided to apply model based inversion method in the reservoir level. In the next step we applied a linear and a non linear transforms between a group of seismic attributes and porosity logs. Then we obtained a relationship for estimating of a volume of the porosity at all locations of the seismic volumetric data. Finally we found an improvement in the porosity prediction from linear multi attribute transforms when using neural network methods.
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Petrophysical Evaluation and Sequence Stratigraphy of Upper Surmeh (Arab) Formation in Reshadat Field (Persian Gulf)
Authors S. Sohrabi and B. ArbabAbstract The upper Jurassic, Upper Surmeh (Arab) Formation in Block R in Iranian territorial Reshadat field in the Persian Gulf , subdivided into the A, A1, B, C and D members, is overlain by Hith formation and underlain by the Darb and Diyab formations. The Arab members consist of a thick sequence of carbonates and evaporites which is deposited in Shallow marine. The typical Parasequences consist of shoal Grainstone, representing Transgressive System Tracts, that pass upward into Thin-Bedded Lagoonal burrowed mud/Wackstone, representing the Maximum Flooding surface. Intercrystaline Porosity and moldic pores is recorded as very good, but locally decreasing because of the presence of large secondary Anhydrite Patches.The Porosity map shows a downflank deterioration In reservoir quality. Dolomitization process increased the porosity. The studies demonstrated 16 Shallowing-Upward Paresequences. It was recognized for Arab members as follows: A and A1 (6 Cycles), B (2Cycles), C (2Cycles) and D (6Cycles). Petrophysical Characters of each Microfacies are extracting from Log and Core Analysis in key wells. Microfacies modeling is done and petrophysical characters are populated into each facies bodies.
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Reservoir Characterization Using Local Linear Models (LLMs) Approach Applied on Seismic Attributes
Authors H. Jamali, N. Keshavarz Faraj Khah, S.M. Behrouz, G.H. Montazeri and I. MaddahiIn this research we used one of the most advanced neuro-fuzzy algorithms called Local Linear Models (LLMs) to estimate the resistivity log from seismic attributes in an oil field in south-west of Iran. Local Linear models belong to the class of intelligent Neuro-Fuzzy approaches which are based on a neuron growing strategy. This method has been developed primarily for the purpose of control in electronic engineering, as it has been shown here, it also can be used as a strong predictor of estimating reservoir characteristics by its application on seismic attributes. In addition, this method can act as an appropriate substitute for conventional methods that have been applied in petroleum industry previously. The input space dividing strategy, used in this method, makes it less affected by the choice of seismic attributes for multi-attribute analysis. Also, this approach can be applied when we have limited number of wells.
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Permeability Prediction from Petrophysical Logs Using Fuzzy Logic in Clastic-Carbonate of Asmari Formation
Authors S. Zare, S.K. Shiroodi and B. NooriAboozar field is located approximately 72 km west of Khark Island in offshore Iran. Main reservoir of this field is an Oligo-Miocene stratum called Ghar which is a member of Asmari. Permeability plays important role in reservoir flow and always has much difficulty to be defined and modeled. This property is directly measured based on core analysis and drill stem test. This paper presents the use of fuzzy logic molding to prediction permeability from wireline log data in clastic-carbonate reservoirs of Asmari formation. Fuzzy logic allows quantifying qualitative information and modeling complex not linear relation. In essence, the problems consist in finding some explicit relation between log and core in well. After training the fuzzy model with subtractive clustering in a given well, permeability prediction were made for other layers in the same well. In subtractive clustering a one and quick way shall be selected for training which based on this a Takagi-Sugeno-Kang method can be generated. The number of membership functions and laws doesn’t need to be defined because inferring system is able to define those by using clustering input-output data. These predictions were in excellent agreement with permeability values obtained from core.
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Using NMR Log to Estimate Permeability in One of the Carbonate Formations in South of Iran
Authors M. Roustaie, M. Nabi-Bidhendi, M. Tadayoni and S. TorabiPermeability is an elusive parameter in hydrocarbon reservoirs as it is very difficult, if not impossible, to determine precisely and directly from current subsurface logging technologies. In this research, an attempt is made to test some methods for estimating permeability as a function of depth from Nuclear Magnetic Resonance (NMR) logging in one of carbonate reservoirs in south of Iran. For accurate permeability estimation, an Artificial Neural Network (ANN) model with two different inputs is applied. In the first case, NMR porosity has been used as input data but in the second case there is no NMR data as input and core porosity has been used. Also three NMR models such as average-T2, free-fluid and Swanson model, have been used for permeability estimation. The results of all these methods are compared with the core permeability. The trends of permeabilities obtained by NMR models have good compatibility with core permeability, so they can be used for in-situ permeability estimation. The results of ANN model shows that using NMR porosity, beside traditional log data, as input for ANN leads to considerably increase in correlation coefficient relative using core porosity. So it can be used as a reliable method for permeability prediction.
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Geostatistical Modeling of Reservoir Properties in an Iranian Oil Field from Upper Bangestan Group, Southwest of Iran
More LessIntegration of various data types available on different scales by using appropriate statistical tools is necessary for building an appropriate static reservoir model. It is very important prior to the reservoir simulation to estimate reservoir performance uncertainty and to aid reservoir management decisions. The oil field of this study is from upper Bangestan group in the SW of Iran which consists of several reservoirs, including Ilam and Sarvak. The information from 5 wells along with the acoustic impedance in time domain in the field was used to generate stochastic images of porosity and permeability with their inferred associated probability. Data from various scales including logs, cores and AI were available. We used AI to improve the reservoir characterization by providing information on the spatial variation of the reservoir porosity away from the existing well. The velocity model for depth conversion was developed by using first check shots in the wells and second Collocated Co-Kriging method with stacking velocity in the field and the check shots. Variogram contour maps of AI were generated to evaluate the underling anisotropy. These are then used in the framework of the various sequential simulation techniques to produce realizations of 3D porosity and permeability models.
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Pressure-volume-temperature Correlations For Iranian Crude Oils
Authors B. Moradi, E. Malekzadeh, R. Kharrat and P. MoradiABSTRACT Pressure-Volume-Temperature (PVT) properties are necessary to reservoir engineering calculations in porous media and it is important for calculations in pipeline as well. This work presents a new set of correlation for estimating Iranian Crude oils properties based on some experimental data. Whenever, these is no representative experimental PVT data, these correlations can be used for oils of API ranging between 19 to 42. New correlations was developed to calculate Oil Formation Volume Factor (Bo), Bubble point pressure (Pb) and solution Gas oil Ratio (Rs). Finally, a comparison is made between these correlations and other published correlations such as Standing, Vazquez & Beggs, Glaso, Farshad and et al, Al Marhoun, Petrosky & Farshad, Hanafi and et al and it is found out that these new correlation are more accurate then the other ones.
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Implementation of Ensemble Kalman Filter (EnKF) Technique in Well-test Analysis of Gas Condensate Reservoirs
Authors G.H. Montazeri, S.M. Behrouz and H. JamaliIn this paper the Ensemble Kalman Filtering technique (EnKF) is implemented to remove noise from well testing data of a gas condensate reservoir and estimate some important parameters such as critical condensate saturation, irreducible water saturation and distribution index which can be used in drawing relative permeability curves. In order to use EnKF, we developed a MATLAB computer program which dynamically interfaces with ECLIPSE300 numerical reservoir simulator. The conventional approches for interpretation of transient data in gas condensate reservoirs can be criticized in several ways. Because of complex nature of flow in such reservoirs, many simplifying assumptions have been made in order to find analytical solutions for diffusivity equation which is theoritical foundation for most of well test analysis techniques , but these assumptions cause a great deal of error in final results. In addition to this, the available methodologies for well testing in such reservoirs are sensitive to measurment errors and flactuation in test data, consequently, any inaccurate mesuarment can be really misleading. Therefore, we used EnKF technique to cover the deficiencies appear in previous analysis methods. Furthermore, extracting relative permeability curves is the unique advantage of this technique.
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Multitransform of Seismic Attributes to Petrophysical Properties Using Committee Fuzzy Inference System
Authors A. Kadkhodaie-Ilkhchi, M.R. Rezaee, P. Hatherly and A. ChehraziThis paper presents an intelligent model based on fuzzy systems for making a quantitative formulation between seismic attributes and petrophysical data. The methodology consists of two main steps. In the first step, petrophysical data including water saturation (Sw) and porosity are predicted from seismic attributes using fuzzy inference systems (FIS) including the Sugeno (SFIS), Mamdani (MFIS) and Larsen (LFIS) fuzzy inference systems. In the second step, a committee fuzzy inference system (CFIS) is constructed using a hybrid Genetic Algorithms-Pattern Search (GA-PS) technique. The inputs of the CFIS model are the outputs and average of the fuzzy inference systems. Each of them has a weighting factor showing its contribution to the overall prediction. For this paper, 3D seismic data and petrophysical data from 11 wells of the Iranian Offshore Oilfield in Persian Gulf Basin are used. The performance of the CFIS model is compared to that of a probabilistic neural network (PNN). The results show that the CFIS method performs better than a neural network, the best individual fuzzy model and a simple averaging method.
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Microfacies and Sedimentary Environment of the Asmari Formation in Lali Oil Field (NW Masjed-e-Soleyman)
By A. EynollahiThe Oligocene-Miocene Asmari Formation is a thick sequence of carbonate rocks in the Zagros basin. The Formation has been studied in Lali oilfield, which locates at 40 kilometers of south-west Masjed-e-Soleyman. It lacks the Lower Asmari but involves the Kalhur Member and Basal Anhydrite at that area. The study of the Asmari thin sections from available cores and cuttings at wells no. 20 and 22 of Lali oilfield, led to recognize 10 microfacies, related to six facies zone, including: supratidal, intertidal, shelf lagoon, barrier or shoal, shallow open marine and basin margin. The Asmari Formation represents sedimentation on a homoclinal carbonate ramp.
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Unsupervised Seismic Facies Analysis Using Singularity and Self-organizing Maps in Southern Pars Oil Field
Authors S. Hadiloo, H. Siahkoohi, A. Edalat and R. TaherkhaniUnsupervised seismic facies analysis provides an effective way to estimate reservoir properties by combining different seismic attributes through pattern recognition algorithms. In many cases important information is carried by singularities that are not necessarily associated to certain amplitude patterns. We use Hölder exponent (α) as a seismic attribute which captures the locations and strengths of irregularities in the data. It is demonstrated that α is a natural attribute for delineating stratigraphy boundaries due to its excellent abilities in detecting detailed geologic features from seismic data. We use wavelet transforms and Hölder exponent to identify seismic trace singularities in each geologically oriented segment, and then we build the seismic facies map using the clustering ability of the SOM. We tested method using real seismic data from Southern Pars oil Field. The results confirm that we can estimate the appropriate number of seismic facies through the clustering of the SOM. We also showed that we can improve the seismic facies analysis by using trace singularities detected by the wavelet transform and Hölder exponent technique. Key words Seismic Facies Analysis; Time-Frequency Analysis; Hölder exponent; SOM
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New Data on Sequence Stratigraphy of Dashtak and Khaneh Kat Formation and Re-evaluation as Effective Cap Rock in Zagros Basin
Authors M. Khoshnoodkia, H. Mohseni, M. Hajian, M. Fallah Kheirkhah, K. Khosro Tehrani and M. KhaleghiDashtak Formation composed of dolomite, anhydrite and limestone acts as an effective seal whereas Khaneh Kat Formation composed of dolomite, shale and limestone excluding evaporites has no cap rock characteristics. Both Formations deposited in a homocline carbonate ramp with depositional facies including supratidal, tidal flat, lagoon, shoal and mid ramp. However a relatively more deep setting wherein no more evaporites were deposited for Khaneh Kat Formation.These formations were evaluated in 8 subsurface and 3 outcrops. Data gathered from field observation, thin sections, geophysical data (GR, Sonic and Neutron logs) and strontium isotope. Dashtak Formation comprises 4 sequences and Khaneh Kat Formation has 5 sequences. Southeast ward part of uppermost sequence of Dashtak Formation has been removed due to post depositional erosion. Lowermost sequence extends in whole of basin with carbonate facies,is equivalent of Kangan Formation. Sequences 2 to 5 of Khaneh Kat Formation are equivalents of Dashtak Formation. These sequences show a distinct lateral facies changes from Sartal#1 borehole toward Kuh-E-Manghasht and OshtoranKuh from evaporite dominated facies to carbonates. An increase in thickness of Dashtak Formation has been revealed toward boreholes Dalan#1, Kuh Siah#1, Dashtak#1; however high anomalously thickness in Sartal#1.
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Applicability of New Production Logging Tools in Horizontal and Deviated Wells of One of Iranian Fields
Authors A. Qazvini Firouz, K. Shahhoseini and A. MortezapourWe found out gas is producing from the beginning section of open hole interval. We recognized this happened after increasing the wellhead choke size in order to increase oil production without bearing in mind that the field is natural fracture carbonate reservoir which has very large numbers of vertical and horizontal fractures in reservoir rock. Also in spite of starting gas injection project, pressure drop continued to increase as a result of increasing oil production rate which caused more oil loss. Consequently gas oil contact has gone down and we had additional gas production in our producing wells.
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Drilling Optimization in the World's Largest Offshore Gas Field by Optimizing the BHA Design
More LessDrilling is an expensive industry these days which consist of tools, services, rig and etc. so it's important for drilling engineers to optimum drilling parameters to reduce costs and avoid problems. In this paper an integrated drilling system with specific focus on BHA design which has been used to improve drilling performance in the world's largest offshore gas field will be discussed. The effect of this optimization was reduction of actual drilling time to more than half of the budget time.
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Casing Design Reevaluation in South Iran Oil Field
Authors M. Shaban, A. Pouladi and S. Behzadisize and type of the casing is chosen based on the geology and formation properties of the field. Cost of the casing design is more than 30% of overall drilling cost which make it an expensive operation for each well. Saving in this operation causes huge reduction in total expenditures of drilling. It seems that it is accessible to reach an optimum method by complete analyzing and reevaluating of the relevant factors in customary design programs which are done traditionally in the Iranian Oil fields. In this paper, by using minimum-cost casing design two methods are proposed for Iranian oil field. In the first proposed method, 30 in conductor casing is used and completed with 7 in liner which make it suitable for high producing field. This method save 17.31% cost of casing design compare to traditional method. The application of the second method is not restricted to special condition and it is compatible to the all cases. This method saves 17.4% cost and also providing sufficient stability and safety in casing program by using two liner and prevent unnecessary cost and time-consuming operations. Finally these two methods are applied to south and southwest Iranian oil field.
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