Iranian Oil Fields Research Articles

Detection of stratigraphic traps in the Asmari Formation using seismic attributes, petrophysical logs, and geological data in an oil field in the Zagros basin, Iran

Asmari Formation is the youngest reservoir rock in the Zagros basin, and for this reason, extensive studies have been done on the chronostratigraphy of this formation. The main purpose of this research is to use seismic data, petrophysical logs, evaluated lithology, seismic cross-section, and check shot data to determine system tract and sedimentary channels in one of Iranian oil fields in the Zagros basin. In this study, we have detected stratigraphic traps in the Asmari Formation by determining the system tracts and conformity using available well information. Moreover, by using the seismic attributes, amplitude envelope, and instantaneous dip, we detected a series of sedimentary channels.

Casing Failure in Salt Rock: Numerical Investigation of its Causes

Numerous cases of casing failure have been reported worldwide. Depletion-induced compaction is one of the main factors that may cause casing failure. Stress perturbation in salt layers may accommodate rock flow which endangers the stability of cased wells. Besides, poor cementing jobs are recognized as one of the wellbore instability causes. These factors need to be considered to determine the mechanism behind the casing failure. In this study, the creep behavior of the caprock salt layer in the southwest Iranian oil fields is experimentally studied through a number of creep tests under conditions of elevated temperature and pressure. Then, a three-dimensional finite element analysis is utilized to examine the validity of various casing failure scenarios after calibrating the model with well logs and experimental data. The results confirmed that the combined effects of creep behavior of rock salt and cementing imperfection can be the main cause of failure in the wellbore under study, because the failure time and depth predicted by the numerical simulation were found to be in accordance with the real field data. By history matching, the geomechanical parameter of the salt layer has been modified for study of the casing failure in other wells in the same formation.

Superiority of neuro fuzzy simulation versus common methods for Detection of Abnormal Pressure Zones in a southern Iranian oil field

Due to the importance of formation pore pressure detection, different methods have been established for its estimation. One of these methods is the d-exponent method which is used widely in petroleum industry due to its rapidity and cheapness. In this study we firstly estimate formation pore pressure using the d-exp method by the traditional formula based procedure, then an adaptive network has been applied based on fuzzy interface system (ANFIS) to predict the d-exponent amounts and formation pore pressure in an Iranian oil field. Finally the reliability of resulted network values has been checked by comparing to the traditional methods values. In this network the variables include N (rpm), Average ROP and Bit diameter as the chosen inputs.

A new generalized equation for estimation of sandstone and carbonate permeability from mercury intrusion porosimetry data

The reservoir rock cuttings can be characterized using mercury intrusion porosimetry (MIP). MIP tests do not yield the permeability of the sample directly; however, MIP results could be used to estimate permeability using empirical equations. Such effort has been attempted in several researches. Most of them have been performed on sandstones or carbonates solely. Therefore, a comprehensive study accounting for both types of reservoir rocks is missing. In the current research, MIP data of 187 sandstone, limestone, and dolomite samples with a wide range of permeability (from 0.001 to 2000 mD), and porosity (from 1 to 32%) taken from 8 Iranian gas and oil fields were used to develop a new generalized equation for estimating uncorrected gas permeability. We have concluded that in addition to the porosity, pore throat radii corresponding to a mercury saturation of 35% (r35) has the highest correlation with the permeability of the samples. The proposed equation was validated by data from another 21 carbonate and 9 sandstone rock samples. A comparison between our equation and other commonly used similar empirical equations showed the proposed equation has the highest precision in the estimation of permeability of all rock types. The findings of this study can be used to predict reservoir rock permeability from easily accessible and inexpensive drill cutting with acceptable precision. Additionally, the proposed equation is applicable in well-log interpretations and reserve determinations.

Investigation of effective parameters on asphaltene deposition and production optimization in one of the Iranian oil fields

Investigation of effective parameters on asphaltene deposition and production optimization in one of the Iranian oil fields

Wellbore stability analysis using integrated geomechanical modeling: a case study from the Sarvak reservoir in one of the SW Iranian oil fields

In this study, an integrated geomechanical analysis was carried out for the Sarvak carbonate reservoir in three wells of one of the oil fields in Abadan Plain, SW Iran. The static Young’s modulus (ES), unconfined compressive strength (UCS), cohesion (C), and angle of internal friction (Φ) were determined directly, using rock mechanics tests. Subsequently, some correlations were introduced based on tests-to-logs relationships. The 1D geomechanical models were constructed for three wells in the north, center, and south of the studied field. The results show that the stress state is not uniform for the studied wells, as it is strike-slip normal in northern well, strike-slip in central well, and strike-slip reverse in southern well. Likewise, the stability of the wells was evaluated using Mohr-Coulomb and Mogi-Coulomb criteria, and it was observed that the Mogi-Coulomb criterion could more accurately estimate the breakout pressure. According to the recognized borehole breakouts in image logs, the SHmax direction is to NE-SW in all three wells. Based on the wellbore stability analysis, it was concluded that the more stable directions for drilling are NW-SE in the northern part, E-W and N-S in the central part, and NE-SW in the southern part of the studied oil field.

Estimation of reservoir porosity using analysis of seismic attributes in an Iranian oil field

The most commonly used data for reservoir description are well and seismic data. Well data such as logs typically provide sufficient vertical resolution but leave a large space between the wells. Three-dimensional seismic data, on the other hand, can provide more detailed reservoir characterization between wells. However, the vertical resolution of seismic data is poor compared with that of well data. Conventionally, seismic data have been used to delineate reservoir structure; however, seismic data can be used for reservoir characterization such as porosity. Therefore, we can combine these two types of data to obtain reservoir parameters such as porosity and saturation. It is available the desired parameter (such as porosity) of the number of wells in the reservoir and seismic cube. And we are looking for the parameter estimation in the whole reservoir. To do this, there are several methods including multiple linear regression, neural networks, and geostatistical methods. Therefore, by determining the reservoir properties and correctly estimating these parameters, optimization can be performed with fewer wells, and the costs of exploration and production are reduced. In this paper, we apply these methods on the available data for an oil field in southwest Iran to obtain the porosity in a total reservoir cube, and these methods are then compared with one another. The results clearly show the superiority of neural networks compared with the other methods in estimating the reservoir parameter. The results also show that although estimation accuracy is increased significantly with the use of the geostatistical approach, this method requires that a sufficient number of well logs, representing all the fields under investigation, be provided in order to improve the geological model obtained by the multi-attribute and neural network methods.

Chemical study of asphaltene inhibitors effects on asphaltene precipitation of an Iranian oil field

The amount of precipitated asphaltene can be considerably reduced with pretreatment of asphaltene inhibitor, in the crude oil. Efficiency of asphaltene inhibitors mainly depends on some parameters such as pH of the oil and the chemical structure of asphaltene inhibitors. In this paper, the amounts of asphaltene precipitation have been experimentally measured using two n-paraffin precipitants; n-heptane and n-hexane. The performance of the studies on the asphaltene accumulation was studied using Fourier-Transform Infrared (FTIR) Spectroscopy analysis. The onset point has been determined by three different commercial asphaltene inhibitors. The results show that when an asphaltene inhibitor is not injected into the mixture of synthetic oil/n-heptane, AOP (Asphaltene Onset Point) occurs at 35 vol.% of n-heptane, while with addition of 3000 ppm of asphaltene B inhibitor, AOP occurs at 60 vol.% of n-heptane.

Wellbore Trajectory Optimization of an Iranian Oilfield Based on Mud Pressure and Failure Zone

Determination of the borehole and fracture initiation positions is the main aim of a borehole stability analysis. A wellbore trajectory optimization with the help of the mud pressure may be unreasonable since the mud pressure can only reflect the degree of difficulty for the initial damage to occur at the wellbore rather than the extent of the wellbore damage. In this work, we investigate the failure extension in different arbitrary inclination boreholes under different in-situ stress regimes. Assuming the plane strain condition, the Mohr-Coulomb, Mogi-Coulomb, and Modified Lade rock failure criteria are utilized. We present an analytical equation to determine the optimum drilling trajectory of an Iranian oilfield. In order to predict the degree of wellbore damage, the initial shear failure location, failure width, and failure depth of arbitrary wellbores are determined. Then a new model is derived to calculate the initial failure area of a directional wellbore because it is more efficient in a wellbore stability analysis. The results obtained show that in the target oilfield, the vertical and low-deviated direction is the optimum drilling path. According to the results of this work, optimization of the wellbore trajectory based on the estimated failure zone is a reasonable method if a considerable failure zone takes place around the borehole wall.

Coupled generative adversarial and auto-encoder neural networks to reconstruct three-dimensional multi-scale porous media

In this study, coupled Generative Adversarial and Auto-Encoder neural networks have been used to reconstruct realizations of three-dimensional porous media. The gradient-descent-based optimization method is used for training and stabilizing the neural networks. The multi-scale reconstruction has been conducted for both sandstone and carbonate samples from an Iranian oilfield. The sandstone contains inter and intra-grain porosity. The generative adversarial network predicts the inter-grain pores and the auto-encoder provides the generative adversarial network result with intra-grain pores (micro-porosity). Different matching criteria, including porosity, permeability, auto-correlation function, and visual interpretation have been used to investigate the performance of the models. This methodology provides researchers with a reliable method to reconstruct multi-scale realizations of porous media.

Antibacterial activity of the lipopeptide biosurfactant produced by Bacillus mojavensis PTCC 1696

Bacillus mojavensis PTCC 1696 (a member of Bacillus subtilis group) has been isolated from the Iranian oil field (Masjed-I Soleyman), to examine its ability to produce biosurfactant (lipopeptide type) [28]. The present study was designed to characterize the antibacterial activity of the isolated biosurfactant. The antibacterial activity towards several bacteria including clinical isolates and type strains species was examined. For detecting the extent of antibacterial activity, the agar disc diffusion method was used, where the measured diameter of the zone of inhibition was used as an index for determining the antibacterial activity. Among the test microorganisms, the antibacterial activity was highest in Pseudomonas aeruginosa ATCC 27853. At concentration as low as 16 μg/ml, the inhibitory effect of the lipopeptide biosurfactant was detectable. The stability of the test biosurfactant also was examined over a wide range of temperatures (40–100°C)and pH values (2-11). The stability was further tested using protease and lipase, where the substance showed clear sensitivity towards lipase. The potentiality of this antibacterial agent in clinical applications is of interest and needs to be further recognized.

INSAR TIME SERIES INVESTIGATION OF LAND SURFACE DEFORMATION IN AZAR OIL FIELD

Abstract. Time-series interferometric synthetic aperture radar (InSAR) has developed as an influential method to measure various surface deformations. One of the generations of time-series InSAR methodologies is Persistent Scatterer Interferometry (PSI) that focuses on targets with a high correlation over time. In this study, we have measured the surface deformation in Azar Oil Field utilizing time series analysis. Azar Oil Field is one of Iran's oil fields. This oil field is located in the east of the city of Mehran, Ilam province. The reservoir of this oil field is shared by Iraq oil field whose name is Badra where oil extraction started in 201409. While Iran started oil exploration in 201709, Iraq has maximized its oil exploration ever since. The subsidence is mainly observed in the vicinity of the oil field. The Stanford Method for Persistent Scatterers (StaMPS) package has been employed to process 20 descending ENVISAT-ASAR images collected between 2003 and 2009, as well as 50 descending Sentinel-1A satellite images collected between 2014 and 2019. Sentinel-1 images bring new improvements due to their wide coverage and high revisiting time, which allows us to make a wide area processing. Due to the high depth of oil wells (4,300 meters), as well as the stone type of the region’s bed in some areas, we needed to calculate the magnitude of subsidence. The results show the maximum displacement rate in this area is 18 mm between 2014 and 2019 in the radar line of sight direction, but no subsidence took place between 2003 and 2009 .The results of the study confirm typical patterns of subsidence induced by oil extraction. Also, since 2017, with the onset of Iran’s oil extraction and the intensification of Iraq's oil exploration, subsidence has taken place with a steeper slope. The displacement of the area before and after this date is modelled with two lines.

Simulation study of the Gachsaran asphaltene behavior within the interface of oil/water emulsion: a case study

Molecular dynamics (MD) simulation was utilized to study the role of asphaltene extracted from Gachsaran (an Iranian oilfield) at the synthetic oil-water interface. In agreement with experimental data, IFTs predicted by MD simulation for heptol/brine system showed a minima at around 50 vol.% n-heptane, reflecting the highest contribution of asphaltene into the interface. At greater n-heptane fractions, IFT was increased steadily. Simulation results suggest the asphaltene propensity for remaining in the bulk heptol phase rather related to the fraction of toluene in the mixture. Heptol ingredients, i.e., toluene and heptane, act differently with respect to asphaltene, where former tends to solvate heavy compounds by virtue of pi-pi interaction and keep them in bulk space; on the contrary, the unfavorable apolar interplay with heptane renders asphaltene to accumulate at the water interface to exploit the water capability for establishing favoring bonding with polar sites of asphaltenes.

Analysis of Occupational Hazards and Lateral Environmental Pollution in the Construction Phase of Yadavaran Oil Field

Occupational hazards in the petroleum industry have always been among the major problems in the various phases of construction and installation, which sometimes cause environmental damage. The present study aims to evaluate the risk of occupational accidents in the petroleum industry in the construction phase (2010-2015) in one of the largest oil fields in Iran, namely the Yadavaran Oil Field in Khuzestan Province, and also discuss the lateral environmental damage. The environmental damage such as air, soil, and water pollution caused by occupational accidents were identified, and the distribution and type of activity were analyzed. For this purpose, the Failure Mode and Effects Analysis (FMEA) model was applied to evaluate the risk of occupational accidents. A total of 47 occupational accidents were identified during the 6-year construction phase of this oil field. The data was collected and underwent statistical analysis and risk assessment based on the location and hazards clustering, which is the main novelty of the article. According to the results, the average number of risk priorities for the observed occupational accidents was 212. Also, the occupational accidents were categorized by the type of accidents, and several corrective measures suitable for each type of accident were suggested. Based on these suggestions, the corrective Risk Priority Number (RPN) was expected to be about 133.2. As a result of these corrections, the risk reduction was expected to be 37% of the initial value. The changes introduced were low-cost, continuous, and periodic measures with positive effects on this oil field.

Natural fracture characterization and wellbore stability analysis of a highly fractured southwestern Iranian oilfield

Wellbore stability analysis is an essential part of well planning where mechanical characteristics of rocks and the state of in-situ stresses are determined to evaluate the likelihood of borehole failure during drilling. In this study, natural and drilling induced fractures were characterized using image logs for a fractured reservoir located in Southern Iran. Mechanical Earth Modeling (MEM) and wellbore stability analysis were also carried out by the combination of wireline log data and in-situ measurements for a vertical well drilled in this field. The obtained results indicated the presence of several major/minor fractures in the studied interval but majority of them were found to be closed fractures. According to the MEM, formations would suffer from breakout (shear failure) in several intervals which might be linked to their low strengths, huge stress anisotropy and inappropriate selection of the mud weight. Give then fact that the break-out failure obtained from the Mogi-Coulomb criterion had a match with the borehole failure captured by the caliper log, the geomechanical parameters estimated through the methodology proposed should have sufficient accuracy and can be used for the stability analysis of other wells drilled in the same field.

Toward mechanistic understanding of Fast SAGD process in naturally fractured heavy oil reservoirs: Application of response surface methodology and genetic algorithm

Thermal recovery is one of the most common enhanced oil recovery (EOR) techniques in heavy oil reservoirs. Fast-SAGD method is a novel SAGD approach in which offset wells are drilled for periodic injection and production. This reduces the costs of SAGD pair injection-production wells and results in more production in a shorter time. Since production from heavy oil reservoirs is becoming more and more important, this study focused on thermal recovery of Mond field as one of the heavy oil fields in Iran. In this study, effective parameters of Fast-SAGD process including injection pressure and rate, injection, production, and offset well heights, offset well pressure and its injection and production periods were studied. The main purpose of this research was solving the problem of Fast-SAGD process optimization in terms of time and accuracy, as similar studies were not systematically studied on optimization of this process. In previous studies, effective parameters on the objective function were considered independently for obtaining the optimum conditions. Genetic algorithm was applied for optimization. The objective function was selected as a combination of recovery factor (RF) and cumulative steam to oil ratio (CSOR). To speed-up the optimization, effective variables were converted to discrete values. Optimization results using discrete and continuous variables were compared to each other. Moreover, results were compared to previously optimization technique applied in this field by Hemmati et al. (2013). Another point in this study was sensitivity analysis application. This showed that reservoir parameters are dependent on each other and traditional methods are inefficient for optimization of complex heavy oil reservoirs and thermal EOR processes. These points led to better results in terms of time and accuracy in this model. Results indicated 3% increase in RF and 4.7% decrease in CSOR for one injection cycle approach in comparison to two-cycle case. Response surface methodology (RSM) was introduced to setup a mathematical basis for effective variables and their interactions. Optimization results using analysis of variance (ANOVA) denoted that the injected steam and RF were 10% and 6% less in comparison to the results of genetic algorithm, respectively.

Thermodynamic analysis PVT equation of state definition and gas injection review along with case study in three wells of Iranian oil field

ABSTRACT The study aims to predict the physical properties of Iran crude oils using modified pressure-volume-temperature (PVT) equation of state. The modification was theoretically developed and then performed by using data of 30 black oil samples representing all active oil producing areas of Iran. The equation enables to predict the bubble-point pressure, oil formation volume factor, gas–oil ratio, oil density, crude oil gravity, gas gravity, and gas formation volume factor of black oils with average relative errors ranging from 0.01% to 10.713%. Calculation sensitivity of the proposed Peng-Robinson is determined by testing four oil samples collected from different locations in Iran and comparing the measured PVT properties with those calculated from Peng-Robinson. These evaluations show an excellent agreement between the measured properties and calculated ones. The estimation of reservoir liquid and gas properties from Peng-Robinson is often needed when detailed laboratory PVT data are not available.

Three-parameter normal moveout correction in layered anisotropic media: A stretch-free approach

In conventional normal moveout (NMO) correction, some parts of the recorded data at larger offsets are discarded because of NMO distortions. Deviation from the true traveltime of reflections due to the anisotropy and heterogeneity of the earth, and wavelet stretching are two reasons of these distortions. The magnitudes of both problems increase with increasing the offset to depth ratio. Therefore, to be able to keep larger offsets of shallower reflections, both problems should be obviated. Accordingly, first, we have studied different traveltime approximations being in use, alongside new parameterizations for two classical functional equations, to select suitable equations for NMO correction. We numerically quantify the fitting accuracy and uncertainty of known nonhyperbolic traveltime approximations for P-waves in transversely isotropic media with vertical symmetry axis (VTI). We select three suitable three-parameter approximations for NMO in layered VTI media as the VTI generalized moveout approximation, a double-square-root approximation, and a perturbation-based approximation. Second, we have developed an extension of the earlier proposed stretch-free NMO method, using the selected moveout approximations. This method involves an automatic modification of the input parameters in anisotropic NMO correction, for selected reflections. Our anisotropic stretch-free NMO method is tested on synthetic and three real data sets from Gulf of Mexico and Iranian oil fields. The results verify the success of the method in extending the usable offsets, by generating flat and stretch-free NMO corrected reflections.

Application of decision tree, artificial neural networks, and adaptive neuro-fuzzy inference system on predicting lost circulation: A case study from Marun oil field

Abstract One of the most prevalent problems in drilling industry is lost circulation which causes intense increase in drilling expenditure as well as operational obstacles such as well instability and blowout. The aim of this research is to develop smart systems for estimating amount of lost circulation making able to use appropriate prevention and remediation methods. To obtain this aim, a large data set were collected from 61 recently drilled wells in Marun oil field in Iran to be used for developing relevant models. After that, using the extracted data set consisting of 1900 data subset, intelligent prediction models including decision tree (DT), adaptive neuro-fuzzy inference systems (ANFIS), artificial neural networks (ANN) and also hybrid artificial neural network namely genetic algorithm-multi-layer perception (GA-MLP) were developed to make a quantitative prediction on lost circulation. The model outputs are then analyzed by various performance indices such as variance accounted for (VAF), root mean square error (RMSE), performance index (PI) and coefficient of determination (R2). Eventually, it is found that developed models are highly applicable in lost circulation prediction. Concluding remark is that DT model having determination coefficient of 0.9355 and RMSE of 0.091 is superior comparing to other developed models and hybrid ANN (GA-MLP) exhibits lowest prediction performance among other implemented models.

Computation of Porosity Using Sand and Carbonate Rock Physics Models in an Iranian Oilfield

In this case study, we have employed post stack inversion, guided by rock physics, to estimate reservoir porosity in an Iranian oil field. The reservoir, based on the lithology and porosity information can be divided into 8 zones and 19 subzones with lithologies comprised of shale, sand and carbonates. Among them, three zones above WOC are carbonate and sandstone. We use different rock physics model to estimate porosity from wire line and seismic data. The procedure uses stack and estimated wavelet to determine the elastic parameter: Pwave impedance. Different rock physics model were applied to relate acoustic impedance (AI) to porosity. This allowed performing rock physics analysis, not only on well log data, but also on seismic data (post stack inversion results). The poststack inversion of AI within the target zone was projected onto the template to generate porosity volume. One of the most important issues in carbonate rock physics is fracture distribution. Petrophysical analysis in carbonate sections of the reservoir shows that fracture distribution is limited and production is mostly from matrix porosity. Fractures in the carbonate zone are mostly joints with 0.5 mm opening and 15 cm in length, so the isotropic medium assumption can be made. The results show that Nur-Dvorkin (1996) model and Raymer-Greenberg-Castagna (1997) are appropriate for predicting porosity in sandstone and carbonate zone of the reservoir respectively and predict porosity up to 30% which shows good agreement with the porosity values measured from well log data.