Determination of capillary pressure is of great importance in reservoir calculations and determination of levels of water-oil contact, transition zone and residual fluids saturation, which is usually conducted in laboratories and in so many cases, it is an expensive, time consuming and difficult process. Capillary pressure data are important indicators to be considered in reservoir studies. In this study NMR log data of Asmari Formation, Well# CB-2, in the Chahar Bisheh oilfield used to estimate capillary pressure data. In this method, it is always assumed that there is a connection between the pore throat and the pore itself, the same connection can be assumed for T2 distribution curve. In order to predict desired parameter capillary pressure estimated from T2DIST using by techlog softword, and plotted versus Sw, in the next stage, we conduct Rescal using the formula of PC=C(〖T_2〗^(-1)) in order to find 1/T_2 and then PC curve is drawn and compared with the measured mercury injection curves of the plug samples of the drilled well.
Neutron – density vs PEF cross plot was used to determine porosity and lithology. To analyse the reservoir quality estimated porosity and permeability from NMR and core pro-perm data were also used. Results depicted that CMR log data can be used to estimate PC data with high accuracy. Categorizing formations based on their lithology is very effective in increasing petrophysical attribute prediction accuracy. High Correlation coefficient of 94 is obtained for porosity by comparing core derived porosity versus NMR porosity and excellent. Permeability correlation coefficients of core derived permeability, and NMR permeability (KSDR and KTIM) for Asmari Formation are of 92 and 95, respectively. NMR, SDR and TIM, permeability mean is 0.71 and 0.54 (md) respectively.According to well log evaluation and interpretation by software, total mean porosity is 9.2% and effective porosity mean is 3.74 % for the reservoir. Low shale volume, adequate porosity and high net zone thickness are demonstrated the high reservoir potential.

Determination of the reservoirs potential and production zones are particularly importance to achieve maximum production efficiency and reduce the cost of operation and extraction of hydrocarbons. In this work, the main aim was to determine Archie exponent (m) and its evaluation in the reservoir potential and production zones of the Ahwaz oilfield. This oilfield is located in Dezful embayment and between 6 oilfields, Ramin to the north, Marun to the east, Abteymour to the esast, and Shadegan-Mansouri to the south. The effect of parameters such as the type and amount of porosity, pore throat radius, type of fabric and the permeability in the cementation factor causes a heterogeneity and complexity in reservoir data. The general usage of the constant number of m in all reservoir parts will be also caused a mistake in the output data. As a result, 18 samples was selected from well number 355 (12 samples) and well number 360 (6 samples) and was sent to the MAPSA laboratory in Tehran, Iran. Then resistivity, FRF, porosity and permeability was calculated. The reservoir flow lines was determined using FUZI method. This is resulted to define 5 flow lines to characterize the reservoir potential. Pay zones were also determined in the pay summary software environment using different parameters: cut-off values taken from the three parameters effective porosity, water saturation and volume of shale, in a certain thickness of the hydrocarbon reservoir storage capacity those can be used to separate the reservoir and non-reservoir parts. Therefore, the cementation exponents using related cross plot with associating of Electrofacies data can be favored in the reservoir management and production zones evaluation. Then petrophysical evaluation has been done. The result is: the reservoir has very god permeability and porosity and carbonates are main lithology of reservoir.

 The determination of electrical facies (log facies) is one of the most common methods of reservoir zonation. The most accurate method for determination of facies is using the core. But coring is expensive and time-consuming and availabel in some wells. Therefore, in this study, using from logging data and its comparison with thin sections for determination of lithofacies. Cluster analysis as one of the best methods to determine these facies was used. Hence, within this study electrofacies of the Ilam Formation within the Ahvaz Oilfield has been determined by using the Self-Organizing Map (SOM) method. With regard to this primary model of electrical facies, 25 facies can be constructed using petrophysical logs of the Ilam Formation in well#360. These facie were corrected and reduced to 7 facies according to their similarity in main petrophysical parameters. In order to evaluate the electric facies identified, thin section data was used to determine porosity types for each facies, and to coordinate with the facies. Generally, the identified electric facies in this study showed good correlation with petrographic data. In this research, variation of reservoir characteristics shows a decreasing trend from number 1 to 4 for carbonate electrofacieses and from number 5 to 6 for dolomitic sandstone electrofacieses. Therefore, carbonate electrofacies no. 1 with the lowest water saturation and highest effective porosity is the best reservoir quality. Dolomitic sandstone electrofacies no. 5 compared to no. 6 with the highest effective porosity is considered as the best one of dolomitic sandstone facieses. Also, limestone shale facies (No. 7) compared to all facies is shown the worst reservoir quality. Petrographical study also confirms the variation of petrophysical properties for studied electrofacieses, in which from electrofacies no. 1 to 4, fabric and porosity change form packstone with intergranular and large vuggy porosities to mudstone with small intergranular and vuggy porosities. The electrofacies of the dolomitic sandstone also show major petrographic changes in dolomitic sands with weakly cement (No. 5) and lime sandstone with dolomitic cement (No. 6). Identification of facies and govern diagenetic processes represent sedimentological environment and diagenesis as two sensational agents in the course of reservoir quality control. The presence of moldic and vuggy pores as dominant porosity is indicating severe and positive effects of diagenesis in controlling of the reservoir quality in Ilam Formation.

 Determination of geomechanical parameters and pore pressure prediction are among the most important parameters for constructing geomechanical model. The purpose of computing these parameters is to construct a 1D geomechanical model and to analyze the wellbore stability. For calculating geomechanical parameters, those relationships have been used that can be suitable to calculate elastic modulus including Young's modulus, poisson ratio, bulk modulus and shear modulus, and rock strength parameters such as uni-axial compressive strength, internal friction angle and tensile strength of rock, based on the P and S wave velocity. These waves are measured by the Dipole Shear Sonic Imager (DSI). This parameters calculated with Tec log 2015. Since the calculated parameters are of a dynamic type, for their useing it must to be converted those to static elastic parameters by experimental relationships based on testing of core data. The pore pressures for the studied formations (Dalan and Kangan formations) were predicted by Eaton, Bowers and the method for determining of pore pressure in carbonates. According to the values of elastic modulus, rock strength parameters and amount of pore pressure, the safety window of drilling mud was determined by the Mohr-Columb criterion for the studied formations. Due to the unavailability of core data for comparing the calculated parameters with core data, the weight on bit was used to measure the accuracy of the calculated parameters. By comparing elastic modulus and rock strength parameters, it was found that among the elastic modulus of the bulk modulus and among the rock strength parameters, the uniaxial compressive strength are the most matching with the weight on bit. By comparing the predicted pore pressure with RFT data, it has been determined that the predicted pore pressure with the relationship provided for carbonates, has the best matching with RFT data. Considering the safe mud window designed by the Mohr-Colomb scale for this wells, it was found that the drilling mud weight used in the well was located in safe mud window and so the wellbore is stable.

 The main goal of this research is estimation of geomechanical parameters using compressional and shear waves velocities of vertical seismic profile data processing in the one of wells of kangan - dalan reservior in south pars gas field. By using amounts of these wave velocities and empirical relations, dynamic modulus values were determined and then converted to the static modules which is more close to the actual amounts. Overburden pressure was calculated by log density (RHOB) and graphic well logs data. The amounts of overburden pressure, pore pressure, horizontal and inductively stresses (from drilling process), estimation are used to evaluate of wellbore stability and safe mud weight window. Data revealed that the average value of Young's, shear and bulk modulus in the Kangan Formation are 6.54, 2.50, 15.36 and in Dalan Formation equal 6.43, 2.48 and 15.52 Giga Pascal (Gpa), respectively. Also average value of Poisson's ratio in Kangan and Dalan formations is 0.2900 and 0.2929, respectively. To investigate the stability of wells, Young's, shear and bulk modulus divided into four classes, which class one has the highest values and class four has the lowest values of elastic modulus. Uniaxial strength value was also divided into 5 classes that classes I and V are representing the maximum and minimum amounts. Elastic modulus and uniaxial strength classification compared with bit size and caliper logs and it was found that at the location with the collapse in the wellbore, elastic modulus are often types three and four and uniaxial strength are type four and five. Safe mud weight window were determined by using values of pore pressure, minimum and maximum horizontal stress. The suitable weight of drilling mud for well over the Kangan-Dalan reservoir was determined. To drill well at the Kangan-Dalan reservoir, the minimum and maximum mud weights were 1.093 and 2.11 (gr/cc), respectively. The average weighted of critical mud 2.48 (gr/cc) was suggested. By using the values of PEF logs data and location of the wells with less stability, it was found that the depth of 2932, 2943 to 2945, 3080 to 3120 and 3170 to 3174 m in the Kangan-Dalan reservoir has sands produce potential. Based on the induction stresses (tangential, axial and radial) estimation, shear fractures is conventional type (SWBO). Elastic modulus, uniaxial strength, porosity, maximum and minimum horizontal stresses and difference of these stresses with adjacent layers verified that the best zone for hydraulic fracturing is located at depth of 2836 to 2900 m

Reservoir management needs to evaluate accurately the measurements related to geochemical and petrophysical characteristics. The present study tends to evaluate the Bangestan reservoir (Cenomanian-Campanian) quality of Ahvaz oil field, SW Iran using petrophysical logs, core and thin sections data and NMR log. Lithological logs and petrographic thin sections study revealed that the reservoir is mainly consisted of limestone, and a less quantity of shale and dolomitic limestone. To analysis oil geochemical characteristics of the Bangestan reservoir have been selected 12 oil samples to subject under SARA test and GC-MS analysis. The results of oil fractions are indicating the presence of high saturation fractions which are ascribed to paraffinic oils. The high saturation/aromatic ratio may be related to long migration distance or high relative maturity. In these samples high ratios of tricyclic C22/C21 terpane to low values of C24/C23, and low tricyclic C26/C25 vs high values of C31R/C30 Hopane are indicators of carbonate-marl source rocks for studied crude oils. The plot of C25/C26 to C25/C24 tet exhibits a marine environment to deposit of the source rocks. The variation plot of C32-22S/ (22S+22R) against C29-20S/(20S+20R) presents medium –high maturity for the oils understudy.
The calculated C28/C29 Strane ratios vary from 0.9 to 1 which resemble the age of early Cretaceous time of oil generation (Gadvan and Kazhdumi formations). Maturity pattern observed in the Bangestan oils of Ahvaz oil field can be related to a rising thermal gradient ascribed to basement fault effects passing through the field.
Nuclear Magnetic Resonance (NMR) T2 measurements can be used directly to estimate the properties of reservoir rocks such as porosity, irreducible water saturation and fluids types. The MRIL data quality was checked in view of mud based drilling fluid and echo time. The results indicated the heterogeneity in the reservoir. Effects of the presence of very light oil (condensate) or gas on the T2 distribution were observed through reservoir for multi times. The carbonate reservoir understudy is consisted of tight and permeable zones based on MRIL parameters. The permeability is showing a general decreasing trend and periodic peak pattern. In spite of clay bound water (CBW) distribution and permeability correlation, effective porosity (PHIE) is not indicated a regular pattern. The fracture may be involved to increase drastically permeability in upper part. All data indicated that pore throat is the main factor to control the reservoir fluid flow. Clay minerals effect as a negative parameter even in negligible quantity. It is proposed that the tight horizons (as a thin and resistance separator) play an important role in hydrocarbon fluid flow as the presence of abnormal pressure. Data indicated that the fluids are not uniformly distributed through the reservoir.
 

Shah Deniz field is the largest natural gas field of Azarbaijan which is located at south of Caspian sea. This elongated structure is formed in late Pliocene and grown in Quaternary. In the present study, attempt to estimate the reservoir quality parameters along seismic traces using attributes analysis and intelligent models. Methodologically, based model inversion was applied for seismic traces and seismic reflected data were then converted into acoustic impedance. Comparing to seismic amplitudes, the results of inversion has higher resolution and associated with accurate interpretation. In this study was used post – stack inversion which is a process involving to stack seismic data to convert into earth acoustic impedance. The basic model which is the basis of inversion is convolution inversion model which analysis passing effect of deformed wave process through the earth. The final results of inversion were considered as outer attributes. The reservoir quality parameters were estimated by probable neural network as a supervised net type which is learning process based on output data that is considered as a linear compound. The relationship between output and input data was determined in the learning stage and these relations involved in whole of seismic data to convert each seismic trace into goal parameter. Therefore concerned parameter was extended from the well into inter well spaces. For each of goal parameter including of porosity, water saturation and permeability a separate net was educated with at least error and attributes. Outer (acoustic impedance) and inner attributes taken from seismic and inverted sections are consisted of the best input data of each net. Estimated results led to determine high reservoir quality in Balla Khani Formation which is characterized by high porosity and permeability values and less quantity of water saturation.

Pore pressure is an important parameter in exploration and production of hydrocarbon resources. This pressure is sometimes encountered in the reservoir as abnormal pressure and therefore is a concern subject in a formation during all phases of oil field operations (exploration, drilling, casing, completion and reservoir evaluation). Accurate knowledge about distribution of pore pressure in a field, leads to reduce risks in drilling, improve well planning and mud weight calculations. The main aim of this study is to prediction of abnormal and pore pressure .The kupal oil field is located at 60 km east of Ahvaz, northern Dezful Embayment. During burial, normally pressured formations are able to maintain hydraulic communication with the surface. So, this pore fluid pressure equals the hydrostatic pressure of a column of formation water extending to the surface and is also commonly termed as normal pressure. Pore pressure prediction based on seismic velocity is a common method for pre-drill pore pressure prediction. In this method, pore pressure can be obtained from transformation of seismic velocity to pore pressure. In this study, the available seismic velocity was the stacking velocity. This seismic velocity was calibrated with the velocities derived from sonic logs. The Gardner equation coefficients was calculated using available density and velocity logs, then; density cube was constructed by Gardner equation. After calculating the density cube The overburden pressure cube was calculated with integrating of density cube. Afterward; The effective pressure cube was constructed using the Bowers equation and the calibrated velocity field. According to the principle of Terzaghi the pore pressure cube was constructed by computing the differences between the overburden pressure cube and the effective pressure cube. Finally the predicted pore pressure cube was calibrated with the measured pore pressure at the locations of some wells using geostatistical methods. In the area of study, the seismic velocity field was improved and calibrated; then the pore pressure cube was generated accordingly. The predicted pressure show good agreement with the measured pressures at the 6 well locations. The results revealed that the Bowers relationship can be used to predict pore pressure in carbonate reservoirs. Based on estimated cubes of pore pressure, three layers with abnormally high pressure were identified on this field including the Gachsaran Formation, particularly member 1 (cap rock), the Pabdeh-Gurpi formations and bottom of Bangestan reservoir. The results can be used in new drilling projects in view of well design, drilling program, the proper position of casing installation and pressure adjustment of drilling mud.

 Petrophysical evaluation reservoirs during production life, is a subject to which importance and re-examine the reservoirs allocations is done in direction of the reservoir management. The aim of this study was to evaluate petrophysical parameters such as total porosity, effective porosity, permeability, saturation, volume of shale, size and type of mineral clay and lithology to evaluate the reservoir oil potential of Ilam (Late Cretaceous) in Ahvaz oil field. In this study the petrophysical evaluation carried out by using petrophysical digital logs and analyzing core data in Geolog software environment (7.1) and also the study of petrographic thin sections. Ilam Formation consists lithologically of limestone, dolomitic limestone and also very less quantity of shales as sparse and lithofacies changes are also detected during the formation distribution. According to the petrophysical characteristies distribution, the reservoir was divided into four zones. The results of the present data showed that the volume of shale which was calculated using the corresponding gamma-ray logs (CGR) as shale index log, was less than 10% and so the Ilam Formation is considered as a clean formation. Zones 2 and 3 are showing less shale volume than zones 1 and 4. Although the volume of clay minerals is small but it has a severe impact on petro physical parameters, especially porosity and permeability. The reservoir has an average of water saturation about 26.8 and 51.98 percent different wells and of the irreducible water saturation is about 3.3 percent. The middle part of the reservoir is indicating less water saturation compared to other sectors. Well Test data showed that the main fluid is heavy oil (API ≤ 13) in bottom and lighter oil (API ≤ 24) in upper part of the reservoir. This distribution pattern could be generated by pore pressure (due to the degree of water saturation) and gravity (secondary migration). The average effective porosity varied in the range of 9.4 - 14.7 percent in different wells. The results showed that the middle section is the most useful parts in view of the effective porosity and hydrocarbon accumulation. The mean permeability values calculated in different wells are in the range of 8.3 and 5.3 which are indicating a direct relationship with the effective porosity. According to the results of the evaluated wells, the middle section of Ilam Formation (zones 2 and 3) difined as oil potential zone and having higher hydrocarbon reserve, compared to the other parts (zones 1 and 4)

 Study of porosity condition, as a reservoir parameter in oil reservoirs, has a special importance. This study is an attempt to estimate fracture, Vuggy and interparticle (matrix) porosity and find relationship between these types of porosity and investigation of the contribution of each one to the total porosity in Asmari Formation in Gachsaran oilfield. Fracture and Vuggy porosities have been calculated by using FMI, while interparticle porosity has been determined by conventional logs. Also porosity conditions detected by velocity deviation log were compared with FMI. Fractures distribution was determined by image logs (FMI) and petrophysical logs. Secondary porosity variation derived by conventional logs compared with resulted secondary porosity from FMI. In most intervals, secondary porosities resulted from FMI and conventional logs are compatible. According to type of porosities variation, 7 types were recognized in the reservoir and based of these criteria the reservoir divided into 15 zones. This pattern indicated that oil accumulation was controlled by matrix porosity. Fractures are mainly two types, longitudinal and oblique, and formed with high dip relative to the layering. Petrophysical data revealed that Dolomite, in some cases Limestone and Shale with some Anhydrite veins are dominant constituents of Asmari Formation. In order to follow the given goal; image logs in the well No.392 were processed and interpreted by CIFLOG software. The results of this interpretation were used to achieve fracture parameters. Velocity deviation log was plotted for the well, using GELOG software. It showed that the pore network of this reservoir is mainly consists of intergranular, fracture and vuggy porosity. Fractures in the Asmari reservoir have two sets with two directions: discontinuous fracture has dip within 8−49∘ with azimuth 10–20 and 330–360, continuous fracture has higher dip rather discontinuous and are between 53−82∘ with azimuth 200–230. Fracture aperture variations indicate that zones with dominant pure dolomite presented higher aperture. Fracture density is more affected by bed thickness than the mineralogy. According to high correlation between velocity deviation log data and the results of image logs in the fracture study and determination of pore network of the Asmari reservoir, it has been suggested to study fractures, especially in the fractured reservoirs, image logs can be a good substitute for core analysis.

 The reservoir heterogeneity is an interesting subject in oil-prolific areas. Bangestan reservoir is the second reservoir of Gachsaran oilfield in southern Dezful embayment. The purpose of this study is to determine the porosity type and also heterogeneity investigation of Bangestan reservoir in well#393 of Gachsaran oilfield by using petrophysical and image logs (XRMI). Petrophysical parameters such as hydrocarbon saturation and total porosity was calculated for this well using Geolog software. Secondary porosities like fracture and vuggy was determined based on the interpretation of image logs. 333 open fractures were detected in whole vertical section and categorized in three set: longitude fracture with average of strick S50E, transvers fractures with average of strick N50E and oblique fractures with average of strick N90E (originating from folding). Fracture and vuggy porosity and then primary porosity was calculated based on image log. Primary porosity also calculated using petrophysical logs and then compared with image logs and total porosity and showed a good correlation. Primary porosity is higher in top to middle interval of reservoir than other depths. Velocity deviation log plotted by differences between real sonic and virtual sonic velocities. The velocity deviation log data is in the range of -500 to +500 in whole well and indicates primary porosity. In whole section the presence of Fracture parameters such as aperture (VAH), length (VTL) and density (VDC) were determined using image log and was also compared with velocity deviation log data. In areas that fracture aperture is showing the highest value, velocity deviation log reading is low. To study the heterogeneity of the reservoir, on the basis of porosity variation, seven types were defined and compared with hydrocarbon saturation column and velocity deviation log data. In intervals with domination of primary porosity and fractures (type 2), the velocity deviation log shifted to zero while in intervals with high hydrocarbon saturation the velocity deviation log shifted to the negative values. In intervals containing type 7 (triple porosity) and type 2 (primary and fracture porosity), hydrocarbon saturation indicates highest value. In zones which are characterized by type 7, velocity deviation log is deviated toward positive values, representing the effect of vugs.

Reliable and effective reservoir modeling based upon geological models is one of the most important goals of the upstream sector of petroleum industries in recent years. Improved reservoir model-building techniques can help to estimate the in-situ hydrocarbon with a higher precision to make a better production optimization and development in an oil field. In the present research work reservoir characterization and evaluation of Ghar sandstone, clastic member of Asmari Formation, in Hendijan oil field was carried out using well drilling data, interpreted petrophysical data of seven drilled wells, associated core analyses data and 3D interpreted seismic data. Reservoir geological model was made based on stochastic and deterministic methods and reservoir quality modeling of zones understudy was done to improve efficiency and enhance estimation power in modeling. The results indicated that reservoir discrimination will decrease the estimation variance while modeling and increase the certainty of the reservoir model. Using effective porosity log as an indicator of electrofacies determination causes to improve the effective porosity model in the reservoir with respect to geological condition of the area.
The Chaos/Envelop/GLCM/Phase/Frequency attributes were selected related to seismic facies and utilized in 3D seismic facies modeling using supervised neural network. To do this, the facies log of the well was supervised. Probable trends of facies and estimation of porosity values in Facie modeling with the help of SIS algorithm revealed a good correlation to final porosity model based on SGS simulation algorithm. Final model of porosity based on facies model of each reservoir zone indicated that mean effective porosity is variable in the range of 10-20% in zone G1 and G3 with their reservoir quality as intermediate, higher than 20% in zone G2 and so the reservoir quality is higher than other zones. The provided models revealed that all sites of drilled wells in the Asmari Formation were selected with suitable risk coefficient.
 

Image logs of OBMI/UBI are powerful tools to analysis fractures by necessary data.
In the present study these logs were used to evaluate bedding, structural dips, fractural description, and well stability in studied intervals in the Asmari reservoir of Kupal oil field (well no. 30). According to the results, bedding structure can be observed. It is estimated 297 layers in general through the section with the sharp boundary and the mean structural dip is 17o towards S50-55W. There is observed a diagnostic differences of 10-30o in dips. The dips of stylolites are 20-18o with two directions of S35-40W and S55-60W as similar to the layering dip and so it can be classified as strata type. It is also determined irregular dips in compatible to layers dips which are related to sedimentary discontinuity or diagenetic processes in some horizons. In general, 117 features were detected in the vertical section (studied well). Dip statistical distribution indicated that the dip range varied from 0-32o. Their dips are comparable to the layering dips and showing a general trend of SW. It was determined two dominant open fractures group individually in 72-74o. One group is showing N-S strike with the dips towards E and the second group with the strike of S5-10E, N5-10W towards N80-85E. Closed fractured group are indicating strike of S30-50E and N40-60E with the dip of 30-32o. The major fractures are longitudinal to oblique types based on fractures patterns related to folding which are developed well in zones 1, 2, and subzone 5-1. The minimum stress of the well is located at NW-SE that is consistent of Zagros trend.
Fracturing feature of the well stress (breakout) in the UBI image is in the trend of minimum stress and indicating NW-SE trend. It is also 10 dissolution fractures are determined which are accumulated around fractures in 3429m-3430m. Induction fracturing of drilling process was also detected. The results of petrophysical interpretation indicated that zones 1 and 2 of the Asmari reservoir are in good hydrocarbon potential in comparing to other zones due to higher porosity and moveable petroleum reserve. These results are consisted to OBMI data. It is revealed that there is a very high correspondence between mud lost data and fracturing density. Therefore, by comparing all data it can be concluded that Zone 1 of the Asmari reservoir in Kupal oil field is presenting a good potential of production prospect due to fracturing density, porosity value and high mud lost.

<p style="text-align: left;">Hydrocarbon reservoir modelling is one of the most important steps in the planning production and field optimization. Ilam formation is one of the main reservoirs, as well as Asmari and Sarvak Formation, in the south-western part of the Iran. Ilam Formation was divided into five zones (A, B, C, D, E) which based on petrophysical properties two of this zones including B (Upper Ilam) and D (Main Ilam) are the main reservoir zones. The main aim of this study is to modelling the petrophysical parameters such as porosity, permeability and water saturation, especially in the zones B and D. For this aim hydraulic flow units (HFU) were used as a basement for modelling due to their ability to reducing reservoir heterogeneity. There are many methods for determination of HFU such as; histogram, normal probability plot, sum of square error (SSE), stratigraphic modified lorenz plot (SMLP), winland R35, reservoir quality index (RQI) and discrete rock type (DRT). Using of all these methods, HFU was classified in four groups in Ilam Formation. Artificial neural network (ANN) was used to predict the FZI parameter in the intervals without core data, which indicates a good correlation coefficient (0.7) with core data. Based on seismic studies, there is not faulting in this oil field and has simple structure as well as a layers cake model. So, Structural modelling was designed from underground couture maps (UGC) and well tops using Petrel software. Sequential Gaussian simulation (SGS) algorithm was used as best function for Petrophysical properties modelling by well log data and acoustic impedance (AI). Distribution of DRT and relation between K and &phi; in each DRT was utilized to permeability modeling. Water saturation and transitional area modelling are considered as important parameters for reservoir evaluation which they were calculated using well log data, water oil contact (OWC) and capillary pressure curve. This study indicates that, porosity and permeability show most rate in the eastern section, and they increasing from western section to east. Also our results confirmed that irreducible water saturation is distribute in the axial reliefs and southern part of studied field. Evaluation of model shows that the axial reliefs, east and southern parts have best quality and they can be considered for future drilling optimization. Finally, volume of fluid reservoir was estimated based on the reservoir volume, net to gross zone thickness, petrophysical characteristics and oil-water contact.</p>

Determination of the reservoirs potential and production zones are particularly importance to achieve maximum production efficiency and reduce the cost of operation and extraction of hydrocarbons. In this work, the main aim was to determine Archie exponent (m, a) and its evaluation in the reservoir potential and production zones of the Paranj oilfield. This oilfield is located in Dezful embayment and between two oilfields, Karanj and Parsi, with 5 wells in two culminations in West to East trend. According to the wire logs data, reservoir parameters were calculated using Archie petrophysical equation. The effect of parameters such as the type and amount of porosity, pore throat radius, type of fabric and the permeability in the cementation factor causes a heterogeneity and complexity in reservoir data. The general usage of the constant number of m in all reservoir parts will be also caused a mistake in the output data. As a result, to enhance the accuracy of the Archie exponent (m, a), clustering method was applied to make the reservoir uniformity. According to the high correlation between the porosity (Ø) and formation resistivity factor (F), it was selected the best method from clusters and used basic information to estimate the water saturation. The reservoir electrofacies were determined using concerned well logs such as PHIE, DT, NPHI, RHOB, SW and CGR in Geolog6.7.1 Facimage environment with clustering MRGC method. This is resulted to define 9 facies and by considering the similarity they decreased to 5 facies to characterize the reservoir potential, so condition prepare determine Electrofacies. Pay zones were also determined in the pay summary software environment using different parameters: cut-off values taken from the three parameters effective porosity, water saturation and volume of shale, in a certain thickness of the hydrocarbon reservoir storage capacity those can be used to separate the reservoir and non-reservoir parts. Therefore, the cementation exponents using related cross plot with associating of Electrofacies data can be favored in the reservoir management and production zones evaluation.

The main goal of this research is to predict and model the permeability and water saturation as well as determine production pay zones in a reservoir of the Abadan plain fields. The permeability and water saturation are complex subjects which are interested to geologists, petrophsicists and reservoir engineers. Understanding these parameters is an effective and important tool in reservoir modeling, production process and management reservoir. Data based on core analysis is however high accuracy, but due to its expensive and time-consuming and also may not be available for all boreholes, therefore it is preferred to use well log data which are available for all boreholes used as indirect methods.
In the present study flow zone indicator (FZI) was used to determine the number of hydraulic flow units. Then, a model constructed to estimate the permeability in un-cored intervals, through the porosity log data in these wells. The results show that the model approach was successful for prediction of permeability in this reservoir. In addition to modeling the permeability based on hydraulic flow unit (HFU) concept, artificial neural network (ANN) method was used. For this purpose, it was constructed a three-layered back-propagation network with Levenberg-Marquardt algorithm and 15 neurons in hidden layer. The constructed network predicts the permeability with acceptable accuracy values. The model revealed that the permeability of the main part of Ilam Formation is higher than upper Ilam and consequently it is expected to have high production rate.

The other petrophysic parameter, water saturation, decreases with height above a datum until it assumes to minimum or irreducible water saturation value in a continuously porous and permeable reservoir rock. This phenomenon is modeled by a mathematical equation based on a normalized or average capillary pressure curve. J-function was used to convert all capillary pressure data related to HFU to get single capillary pressure curve. Finally, to build a saturation-height model, J-Sw grouped data was fitted on the capillary pressure data for each unit through advanced exponential function to determine function coefficients, and then water saturation calculated by using saturation-height function obtained from Leverett function. Also, artificial neural network with Levenberg-Marquardt algorithm and 14 neurons in hidden layers was used to predict the water saturation. The constructed network showed acceptable results compared to core data.
 

In the present research work, petrophysical parameters of Arab Formation (equal to Surmeh Formation) were evaluated using three methods: petrography, carbonate petrography and multimin. Wirelog data are input in GEOLOG software by probability method in one of oil fields of south of Iran. Arab Formation in this oil field divided into 7 zones. Limestone and anhydrite with a less value of shale are the main lithological components. Dolomite is appeared to be a dominant mineral than calcite. The estimated values of dolomite volume comparing to carbonate petrography are not uniform in all zones. However, the results of the other two methods are showing a positive correlation with a high correlation coefficient. Anhydrite distribution is not uniform and its value increases to depth. Multimin and petrography results are showing good correlation. To comparing all lithological results it is provided that the calcite variation are not follow the same trend and carbonate petrography method is showing weak correlation to the log in spite of high resolution of limestone presentation than multimin. Therefore, by analyzing petrophysical parameters in the studied borehole and uncertainty method it is revealed that the reservoir quality is prone in most depths.
GEOLOG petrophysical software by applying petrographic, carbonate petrographic and core data. After correction of well logs, all data uploaded in the software and construct the basic petrophysical model. To get the quality of improving the petrophysical evaluation data, the results were compared to core data and well tests. The porosity data variation in with and without petrographic processes, with and without carbonate petrographic and core data revealed that the correlation coefficients are 0.69, 0.71, and 0.91 respectively. This is concluded that the carbonate petrographic procedure is terminated to more suitable results than other methods. Water saturation study is also provided the same results. However, the results of the carbonate petrography are scattered than petrography method. Based on these results, reservoir zones 1 and 3 are indicating the best reservoir quality in view of porosity and water saturation values.
 

Shadegan petroleum oil field is located on Dezful Embayment and is a nearly symmetrical anticline with 23.5 Km length and 6.5 Km width on top of Asmari Formation. The field trend is similar the regional Zagros trend. The aim of the present study is fracture determination using FMI logs, drilling mud loss informations and construct 3D-modeling of the Asmari reservoir using RMS software. The computer program utilizes advanced mathematical and geostatical functions to provide 3D insight of different reservoir properties such as structure and geology, dynamic fluids and well planning. First of all, zonation was made in the reservoir as a basic reservoir study factor which defines oil and water horizons. Asmari Formation divided into 13 zones & subzones. Zones 1, 2, 5, and 6 are interest in terms of petroleum potential. Petrophysical and structural models have been made. Dominant fractures were in reservoirs zones with ENE-WSW trend and most of them were open, longitudinal-oblique and parallel-oblique to bedding plane. Mud losses in north flank special in central region were higher than south flank that indicates dominant open fractures &possibility of higher productions in this sector. Asmari formation composed of two upper & lower reservoirs with different oil properties indicates no connections between them & non transmission faults. Petroleum reservoir is undersaturate reservoir without original gas cap. Porosity & water saturation quantities increase with depth. Active drive mechanism is water drive mechanism.
To calculate in situ oil volume, fluid and reservoir data were input data for RMS software. This model was constructed by help of critical limit concerned porosity, water saturation.
Generally, bedding plane & fractures attitudes determination, fault effects and oil volume determination are the main output results.
 

The present study is an attempt to quality improvement of the petrophysical data evaluation in the reservoir using XRD data (in one of drilled well of Arab Formation in Persian Gulf). In this study different parameters such as lithology, porosity and water saturation were analysed using multimin and XRD methods. Neutron-density cross plot data revealed that the main lithology is dolostone. According to Th-K cross plot, illite is not determined which is verified by XRD data.
The porosity values in different zones except zone 1 are showing good correlation in different methods. The frequency histograms of the porosity shows differences which it is in the case of non XRD data, the variation range is low. Water saturation values in all zones are indicating high ranges. However, the frequency of water saturation except zone 1, are presenting high ranges by multimin method. Statistical parameters comparison in two methods is indicating a good correlation. This variation is also consistent with the core data. As regarding XRD data, the results is going to match well to the core data. Anhydrite scattering is about 30% wt by using XRD method but this value is increased toward depth.
The frequency comparison of anhydrite by two methods indicating a high correlation. However this discrepancy is not uniform in all zones. Dolomite scattering is higher than 40% (except some horizons at higher depths), however, the resulted data in two methods are indicating relative good correlation.
Lithological columns plotted using two methods and uncertainty revealed that the reservoir has good quality in relatively all depths. The comparison of the results appeared that the resolution value of the lithology is increased in the case of involving of XRD data. However, XRD method is suitable to estimate shale volume but it will be failed in differentiation of dolomite and anhydrite.
 

Hydrochemical characteristics in the oil field play important role in oil production. Water formation can be effected on all process such as production, initial migration, oil displacement in secondary migration, and as well in biodegradation. The present study tends to study water formation properties in Bangestan and Asmari reservoirs of Ahvaz oil field. The present data revealed that water formation increased relatively in permeable layers (fractured dolomitized and sandstone) to depth.
Chemical variation plots of water formation are indicating high correlation coefficient alkaline elements and calcium to Cl, Mg to sulfate, Ca and bicarbonate and can be related to different sources involvement. Alkaline ions to sulfate and bicarbonate are showing a good correlation and there are also different trends in Ca to Mg variation in the Bangestan (positive) and Asmari (negative) reservoirs. Water formation is classified as Cl-Ca type but due to higher correlation of Ca –sulfate in the Bangestan reservoir it is expected to be higher ratio of mixing of bicarbonate and sulfate waters.
Salinity, temperature and pressure data of water formation in two reservoirs indicated that density increased with salinity and decreased with temperature. Pressure increasing is also effected on increasing density value. According to variation plots, it is inferred that the variation is more irregular in the Bangestan reservoir. Oil density is also exhibits the same trend as water formation. The effect of higher temperatures is more than lower temperature in oil density that reflected in increasing of the line gradient. Oil density values of the Bangestan vary in a wide rage than the Asmari oils.
Interfacial tension study of the Asmari oil revealed that the density increased with the salinity but this effect is showing some inconsistent in 50000 ppm (salinity) than other values. It increased relatively to the pressure increasing. There is also observed a similar trend in the Bangestan oil but it is more cleared at 101°C and 100000 ppm (salinity) and 25°C and 130000 ppm (salinity). It is not observed a relative tangible variation in interfacial tension in high salinity and low temperature (less than 100°C ) condition. It is also recommended to prohibit the water resource of the country and environmental problems, the produced waters can be injected to drilled holes or refined to use for industrial purposes.
 

An important method in oil and gas exploration is Vertical Seismic Profile (VSP) to estimate rock properties in drilling well. During seismic project performance, elastic wave is sent to the enterior and the result data will be received to the surface by reflection waves. These data subjected to process to indicate subsurface layer position. This step in the main seismic data application in oil and gas industry. Quality factor is also crucial point of seismic attribute in VSP data. In the present study, this factor was used to evaluate hydrocarbon potential in Kangan Formation in one of Persian Gulf fields using VSP data. In porous layers, Vs/Vp ratio increases dramatically. Resistivity log can be used to determine fluid type since low values are indicating water or saline water and high values are related to oil and gas presence.in the present oil field this changes are inconsistence in some depths that is referred to reserve of hydrocarbon.
According to Vs/Vp plots and geological logs indicated that Vp/Vs is increased at 2900-3100m indicating hydrocarbon presence which is correlated to petrophysical logs. Therefore, VSP method can be used to infer Vp/Vs and Q-factor and it will be a good alternative method to find hydrocarbon reserves in those boreholes without petrophysical logs.
 

 Qaleh Nar oil-field is located at Dezful Embayment and is adjacent to Bala Roud and Gul Mahak fields. The main purpose of the present research is to determine the reservoir rock types and study their reservoir quality. At the first, flow units were specified using available porosity and permeability data using the flow zone indicator method. The primary reservoir electrofacies model was then developed with three DYNAMIS, MRGC, and SOM methods. By comparing the three aforementioned methods with specified flow units, SOM which is a self-organizing unsupervised network was selected as the premier method. Hence, using DT, PHIE, RHOB, CGR, and NPHI logs in four wells, the first six facies were developed and then ordered and numbered based on reservoir quality. To evaluate the determined facies, capillary pressure data were used to study porosity pore throats and their relations in all electrofacies used. Finally, to prove the validation of the research, thin sections of core samples were studied in two wells of the field. The capillary pressure and petrography data are also approved by determined electrofacies, and finally the developed model was extended to all the wells of the oil field.
The rock type properties indicate that the reservoir quality increased from the facies 1 to facies 6. The improvement of fabric and porosity from cemented packstone with intergranular porosity to packstone and wackestone with intergranular and vuggy porosities affirms the research work.

Abstract :

Cap rocks of Binak, Siah Makan, Kilor Karim and Gulkhari oil fields in the margin of southern Dezful embayment have been studied. In this research the parameters of lithology and cap rock thickness variations and the physical quality of the cap rock in the marginal part of the basin have been investigated. In these fields such as other oil fields in the Dezful embayment, member 1 of Gachsaran formation plays cap rock role for Asmari oil reservoir. In this research with application of gamma ray, sonic and graphic well logs of 33 wells and 250 microscopic thin sections, the characteristics of the cap rock have been analyzed. Petrographic and Petrophysic studies indicate 6 key beds in the mentioned fields with some minor differences. Main diagenetic processes are Anhydritization, Dolomitization and Compaction. Dominant textures in anhydrites are flowage, nodular, decussate, spherolithic and Lath textures. These Petrographical evidences reveal that cap rock has been deposited in a Sabkha-lagoonal system.With regard to drawn stratigraphical correlation charts and Isochore maps, in different parts of these four fields it can be sayed that overall thickness variations in the Binak and Golkhari oil fields have thinned to the Westward and in the Siah Makan and Kilur Karim oil fields have been thicken from South to the North.
 

Geochemical characteristics and analysis of effective factors play an important role in petroleum reservoir evaluation since the feasible period of petroleum production has been terminated. Today, geochemical studies are vital factors in exploration, production, field development, and new drilling process.
This study tends to analyze oil geochemically characteristics and their correlation in Ahvaz and Mansuri oil fields, composition and miscible of different oil sources, their composition effective factors, and oil maturity determination in different wells.
We have selected 4 oil samples from Ahvaz oil field (wells # 49, 368, 375, 455 ) and 6 samples from Mansuri oil field(wells # 45, 23, 19, 40, 77, 33) and subjected to SARA test and GCMS. The results of oil fractions indicate the presence of high % of saturation fractions that can be ascribed to paraffinic oils. The high saturation to aromatic ratio may be related to long migration distance or higher relative maturity. In these samples high ratios of tricyclic C22/C21 terpane to low values of C24/C23, and low tricyclic C26/C25 vs. high values of C31R/C30Hopane are indicators of carbonate-marl source rocks for studied crude oils. The plot of C25/C26 to C25/C24 tet. ratio exhibits a marine environment to deposit of the source rocks. The variation plot of C32-22S/(22S+22R) against C29-20S/(20S+20R) however presents medium –high maturity but MPI-1 to MPI-2 ratios are indicating higher maturity for the Bangestan oils in Ahvaz oil field.
The calculated C28/C29 Strane ratios vary from 0.9 to 1 which resemble the age of early Cretaceous time of oil generation. Gadvan and Kazhdumi formations are probable good candidate of source rocks according to biomarkers in the studied crude oils. Increasing maturity trend in Ahvaz oil field can be related to a rising thermal regime towards the east.
This matter can be facilitated by the fracture system which is useful to easy heat transfer as well as the variation trends of C22/C21, C22/C21, C24/C23, C26/C25, C31R/C30, C35R/C34R, and C29/C30 verified that the oil composition separation boundary is located at the center (site of well # 220) of Ahvaz oil field.
 

 Drilling fluid properties effects analyseson the process of cutting transfer to the surface is a main consideration topic in oil industrywhile drilling of the Gachsaran Formation. In the present research work, drilling fluid properties of different members of the formation in 52 drilled wells data compared with a new drilled well (Kupal #57) data, the reserve fluid tank and concerned cuttings compositions.
Rheological properties of drilling mud of Gachsaran Formation indicated that initial gel and pH are constant relatively. The range of pH value is 9.3 to 11 which plays a role in instability of drilled cuttings. Higher ranges of Ca. in no sampling horizons (1500-7000) compared to other cases (1500-5000) seems to be an effective factor in dispersion of marl samples.
Viscosity, gel strength, and yield points in no sample occurrence of individual depths show some variations, and YP variations are corresponding to cutting transferring volume.Cutting samples analyses present considerable diagnostic in compared to drilling muds. The presence of swelling clays in marl units helps to dispersethe samples.
There are also visible differentiations between fluids and reserve tank fluid. The cutting samples chemical compositions are comparing to drilling muds showing that CaO,SiO2,Al2O3, and Mg O % are higher than BaO and SO3%. Cl content of drilling fluids issame to higher normally than the formation except in member 6 (sample no. 16 and 17). All these differences cause to solve the salt and then disperse the samples.In addition, Pb content of drilling muds and reserve tank is different but they are showing trace elements. Gachsaran Formation exhibits differences in As, Zn, and etc comparing to drilling fluids.
Based on daily drilling reports, graphic well log and rheology properties (esp. mud weight) in members of the Gachsaran Formation revealed that no sampling occurred in members 5 and 6 in marl and salt layers. Generally, it can be concluded that technical problems, drilling mud composition, lithological characteristic and clay and salt association in marl layers are responsible in no sampling event that the role of rheological properties changes is more dominant than other factors. Chemical differences of the formation and mud facilitate dispersion of drilling cuttings.

The supergiant south pars gas field is the largest gas field in Middle East which is located in Persian Gulf and located between Iran and Qatar. This field’s study is a top priority because it’s a shared gas field. Porosity, permeability and pore throat are three most important parameters which their precise characterizations in oil fields are of special importance in these fields’ exploration and development. In this study changing trend of these parameters are studied in south pars field. Due to absence of porosity and permeability data in whole well depth, these parameters were estimated with a high accuracy using artificial neural network. Correlation coefficient (R2) of neural network estimated data with core data for porosity is more than 0.8 and for permeability is more than 0.7. Practical equation of Winlad and Pittman was used for pore throat values characterization. Then changing trend of these petrophysical parameters in whole field were modeled using geostatic methods and PETREL software. According to structural model, south pars field is a gentle fold and dip of east limb is higher than west limb. According to major and minor cross sections of this field, it’s concluded that there is no important fault and probably this can be discussed more using geophysical studies. Petrophysical modeling was performed using Sequential Gausian Simulation (SGS). According to porosity and permeability models, it’s concluded that there is no logical relationship between porosity and permeability distribution in this field, which it can be a result of carbonate lithology of Kangan reservoir. According to the permeability model, it is revealed that, increasing trend of permeability in this field is west to east which is consistent with trend of field. Moreover study of pore throat model of this field shows a good relationship with the trend of pore throat, permeability and Iso-depth maps. Moreover comparison of neural network estimated porosity and permeability with pore throat evaluated by Winland and Pitman equation shows a good relationship between permeability and pore throat and an unsatisfying relationship between permeability and pore throat with porosity. Overall it can be concluded that, KG4 reservoir zone is indicating the best quality and KG1 is the worst reservoir zone from the ptrophysical results.

Abstract:
In the present study it is tended to evaluate different views of Member 7 of Gachsaran Formation in Western part of Ahvaz oil Field. Characteristics study of Gachsaran Formation has special importance in petroleum systems and reducing the drilling risk. Gachsaran Formation has wide spread as well as the regional variation in facies and divided into seven members. Member 7 of Gachsaran Formation is acting as a separator between low-pressure (above) and high pressure zones (below). Therefore undiagnosed of suitable point for casing pipe and change of drilling mud type in this section may be caused a serious drilling problem. To study the petrography of the samples, 100 thin sections were used. Different logs such as gamma ray, sonic, graphic well logs were applied to plotting stratigraphic columns and correlation chart. Chemical analysis of 10 selected samples by XRF method and 3D modeling by RMS software were done.
Based on petrographic data it is cleared that this member has been made of the evaporite (mainly anhydrite and limestone) along with some clastic (marl) depositions. Accurate analysis of this section indicated that anhydrite is the main constituent. Also a wide variety of textures was observed by anhydrite study. Some of these are formed during deposition, such as: nodular, chicken wire, lath, spherulitic, fluidal, porphyroblast and other cases including of anhydritization, nodular growth, recrystalization, dissolution, pore filling, compaction, micritization and pyritization are formed under diagenetic processes. After anhydrite, the most abundant constituents of the Member 7 of the Gachsaran are marl and limestone. XRF analyses of the selected samples show that CaO, SO3 and SiO2 are most ingredients of the lithology of Mbr. 7. Therefore, these oxides form dominant lithologies such as anhydrite and marl (mostly with clay combination).
The results of the modeling showed that the maximum thickness is observed in northwestern part of the field. Zone 1 with maximum thickness and zone 4 with minimum thickness are highlighted.
Based on Dip-Map plot, maximum dip is observed in northwestern flank that confirm the increasing dip from southeastern to northwestern. According to lithological and chemical changes it can be suggested that dry weather conditions was dominated during the deposition of the base of mbr.7.

 Abstract:
Characterization of permeability in hydrocarbon reservoirs is an integral component of reservoir simulation, enhanced oil recovery, well completion design, and overall field exploitation and development strategies. Despite its vital importance, it is one of the most difficult and controversial petrophysical properties to calculate accurately. Recently, several different methods of artificial intelligence techniques have been used to predict this fundamental parameter by using well log data. However, predicting the characteristics of heterogeneous reservoirs always has been facing many problems and an appropriate response is rarely achieved. In this study efforts were made to estimate the permeability of Kangan and Dalan carbonate reservoir using Ant Colony Algorithm and Genetic Algorithm. Permeability estimation results in south pars field indicated that Ant Colony Algorithm performs relatively better than Genetic Algorithm. Performances of these methods were evaluated by comparing the results with the most common Neural Network and Nero-Fuzzy methods. Moreover a new methodology is presented for permeability estimation by integration of stochastic optimization in the structure of a fuzzy inference system. The proposed model, which is called Ant Colony-Fuzzy Inference System (ACOFIS), is based on integration of fuzzy reasoning and Ant Colony Optimization Algorithm. In this study conventional well logs data along with core data from two wells of the South-Pars field were used for permeability prediction. The well SP-A was used for models construction and test well (SP-B) set for investigating the efficiency of the intelligent models. A comparison between cross-plots of different logs data and core derived permeability in training well showed that NPHI, DT and GR show better correlations with permeability in comparison to other logs; therefore, these parameters were selected as inputs of the intelligent systems. Experimental results proved that ACOFIS outperforms all the other methods and it can be considered as a powerful tool for permeability estimation, especially in cases where a precise estimation criterion is crucial. Moreover results of this study show that the developed ACOFIS model can serve as an effective tool for estimation of other reservoir rock properties such as shear wave velocity, porosity and amount of total organic carbon.

 Characteristics and variation of the cap rock in a petroleum system plays an important role in oil industry. The cap rock sequence evaluation and thickness and depth estimation is necessary to predict the probable entrance depth of the reservoir, casing operation, and to prevent mud loss or blow out. In the present study the cap rocks of Milatun, Rudak, Chahar Bishe, and Chillingar fields which are located at Dezful Embayment edge have been investigated. The cap rock is member 1 of the Gachsaran Formation as a general case in Dezful Embayment region. Study of microscopic thin sections and petrophysical well logs of Cap rock in 11 well show that cap rock in this oilfield, consisted of anhydrite and marl and a layer of dolomitic limestone and bituminous shale. This lithology indicates textural wide variations that may be resulted during sedimentation or from diagenetic processes. Textural variations in anhydrites are important in analysis of.depositional environment and diagenetic process. Mosaic, lath, spherulitic, fluidal, porphyroblasic textures are more common than other textures.
Anhydritization, cementation, compact, recrystallization, replacement and dolomitization are the main diagenetic processes of sulphate sediments. These data presents that the cap rock was deposited in a sabkha-lagoonal system.
The cap rock of these fields classified as marginal type and have incomplete sedimentary sequence and in the basis of petrophysical well logs have 3 key beds: A, B and C. The Plotted stratigraphic columns and their comparison indicated that the cap rock thickness decreased from NW to SE. By considering the key beds position and petrographic studies, the first anhydrite layer located under the base of key bed C is favored for casing point.

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<p>Production performance in a heterogeneous reservoir without calculating the exact parameters canʼt realistically be expected. <br /> One of the parameters is permeability that the most important characteristics of formations containinghydrocarbon and in addition, it is most difficult to predict rock properties. Another parameter is the radius of the pore throat that very important role in determining the permeability, Porosity, enhanced recovery, the capability of thehydrocarbon column in cap rock and&hellip; . In direct methods because of time-consuming, expenses mercury injection operation on the samples, the toxicity of mercury and need to core presence different methods to estimate these parametershave been proposed.<br /> The oil industry has tried to date to accurate permeability values from laboratory measurements core or well testing interpretation. However, both of these methods are accurate, but not sufficient to completely characterize the reservoir. In each oil field because of time-consuming and high cost only a limited number of wells have been coring or only a limited number of well for testing in each oil field recommended.<br /> One of the objectives of petrophysical studies is accurate estimation of permeability in wells that is not possible measurement of permeability in them for any reason (lack of core, presence fracture in samples and ...).<br /> Achieving this goal is difficult, because any log canʼt directly measure permeability in a well-developed yet. Therefore, indirect methods for determining permeability by petrophysical data and different logs are used. Thus permeability wellslack of core obtained by calculation. In this study, the combination of mercury injection experimentsmethods with Pittman and Winland theory methods and compare these methods with the technique of artificial neural networks to determine the parameters of permeability and pore throat radius in carbonate rocks, were calculated using petrophysical evaluation results.<br /> Initial calculations indicated earlier theoretical approaches canʼt properly calculate the throat radius; So considering in this fact that artificial neural network is a new technique inspired by the structure of the nervous system of the human brain high capacity to solve and understand the very complex relationships between different variables and is widely used in the calculation of permeability is shown, therefore in this study we use both neural network MLP and LSSVM the best correlation coefficient of the permeability and pore throat radius to find that using algorithms designed the best correlation coefficient of permeability 0/99 and for pore throat radius 0/89 was calculated, which indicates a very good performance these two methods in the determination of these two parameters.<br /> &nbsp;</p>

 Petrophysical parameters have a significant and decisive role in reservoir characterization and therefore any type of data should be used to estimate these parameters. Continuance data must be prepared in order to examine and review reservoir quality and fortunately seismic data has this advantage. In this study in order to estimate petrophysical parameters such as porosity cube and water saturation cube, Model-based inversion is used successfully. Acoustic impedance is the result of seismic inversion and can be used with other geological information such as petrophysical logs and core data to determine and evaluate geological change in 3D dimension like facies change, petrophysical changes (Porosity, water saturation, density, fluid content)lithological changes (Faults, fractures, lateral changes). In this project porosity cube is estimated by Neural network RBF method and multiple attributes method. Multiple attributes method represents high correlation between porosity logs that are actual data and porosity cube which is predicted data. In addition, water saturation is predicted throughout the north limb of the reservoir using two methods. Neural network (PNN) shows a good correlation and in much better than multiple attributes method. Marun oilfield is one of the biggest oilfield in Iran and it is located south west of Iran which in known as Dezful Embayment. The Asmari Formation is the main oil-production reservoir unit in Iran, consisting of interbedded carbonate, and sandstone of Oligocene to Miocene age. Geological model of Asmari reservoir consists of four main layer which every layer contains two sandy and carbonate sublayer. Upper sublayer contains carbonate rocks and bottom sublayer is almost sand. First and second sandy sublayers are discontinuous which have interbedded thin carbonate sheets. Third and fourth sandy sublayers are continuous and traceable in porosity cube. Sand zones can be traced well by using seismic inversion method. The results showed that there is a good correlation between porosity values and sand zones in the Asmari reservoir of the Marun oil field. Furthermore, in this case best reservoir zones are recognized by means of time slices through the porosity and acoustic impedance cubes. In porosity slices, lithological changes are distinguished and reservoir variations are evaluated. All slices are extracted from Asmari Formation with a time window range from 5 to 20 milsec. In result, three reservoir zones are considered as best reservoir zones which have high reservoir quality. These continuous sandy layers include zone number 3-2, 4 and 5.&nbsp; Finally, it can be said that the acoustic impedance in this reservoir is maximized in edge of the crest and it minimized in the area of the crest which the most wells are located and radial fractures and crestal collapse could be main reasons for this changes of acoustic impedance.

Abstract:
Shaly formations generate a few drilling problems such as well instability, hole wider, well chock and leave the hole and a serious form in orientiation drilling wells. Well stability during mud drilling base water is possible to solve by clay minerals analysis. The presence of shaly formations of Pabdeh and Gurpi and scatter horizons found in the Asmari produce some drilling problems and so need to study these formations. The Marun oil field located at the Dezful Embayment is the main target of the present study. In the present work 17samples taken from well no. 291 analyzed chemically using XRF method. NGS well logs and XRD methods were also used to study 22 samples from selected wells.
The NGS results indicated that Illite, Mixed layer and Glauconite are the clay minerals in Pabdeh&Gurpi formations. It seems the NGS results are relatively (except Illite) and it needs to calibrate with other methods. The clay minerals determined by XRD plots are Illite, Mixed layer, Montmorillonite, Chlorite and Kaolinite.
According to the nature of NGS log, it can be used to determine the clay sources, drilling problematic sites, and reservoir quality.
Major and trace elements vs. Al2O3 indicated that these elements (except SO3, CaO, and P2O5) have the linear relations with high correlation coefficients (R2) that are related to genesis, noncontributing in clay structures and sea level conditions. Trace elements are presenting negative trends (except Sr, Cr, V, Ga, La, Pb, Y, and Rb) and low correlation coefficient due to sedimentation rate or organic matter changes.
Major and trace elements variations to depth indicate that there are three to five alternative stages of increasing peaks (except P2O5). It can be reflected the variation of the basin during sedimentation time of Gurpi, Pabdeh and Asmari formations. Therefore, chemical elemental changes can be used to study sedimentation condition and reservoir chemical zonation if there is no lithological disturbation. Chemical parameters are also verified the relative frequencies of Illite, Montmorillonite, Chlorite, and Mixed layers. Chemical changes attribute to sedimentation conditions as well. Fe, Mn, and V values are indicating reducing condition with low-intermediate pH (group 2 and 3) for the formations studied. Th/U ratio varies from 0.5 to 4 which is indicating marine-intermediate environments. Based on clay minerals determined in these formations, the sediments are classified in D type of drilling fluid and therefore it is proposed to drill these formations using fresh water fluid with suitable ingredients materials.
 

Abstract:
Determination of capillary pressure is of great significance in reservoir parameters calculations, determination of the levels of water-oil contact, transition zone and residual fluids saturation, which is usually conducted in laboratories and in so many cases, it is an expensive, time consuming and difficult process. Capillary pressure data are important indicators to be considered in reservoir studies. In this study NMR log data of Kangan and Dalan formations of SP-A well in the south pars gas field used to estimate capillary pressure data. In this method, it is generally assumed that there is a connection between the pore throat and the pore itself, the same connection can be assumed for T2 distribution curve. In order to predict desired parameter capillary pressure ,estimated from T2DIST, is plotted versus Sw, in the next stage, we substitute 1/T2 in the formula of PC=C(T2-1), then PC curve was drawn and compared with the measured mercury injection curves to the pertinent Well. Neutron – density vs. PEF cross plot were used in order to determine porosity and lithology.To recognize reservoir quality,estimated porosity and permeability from NMR vs. core pro-perm data were used. Results depict that CMR log data can be used to estimate PC data with high accuracy. Comparison of the area under the curve of CMR total porosity with resistivity curves revealed that major portion of the large and connected pores free fluid filler is gas. Categorizing formations based on their lithology is very effective in increasing petrophysical attribute prediction accuracy. High Correlation coefficient of 0.93 and 0.98 is obtained respectively for porosity and permeability by comparing core derived porosity versus NMR porosity and core derived permeability versus NMR Timur permeability (mean NMR Timur permeability 80 md) for the best reservoir zone (k4). According to well log and software evaluation mean total porosity is 15.5% and mean effective porosity is 11.9 % for the study area. Low shale volume, adequate porosity and high net zone thickness is demonstrator of high reservoir potential in the study region.
 

Maroun oil-field is adjacent to Kupal, Agahajari, Ramin, Shadegan and Ramshir oil-fields in Dezful embayment. The main aim of the present study is rock type determination of the Bangestan reservoir at Maroun oil-field. At first using porosity and permeability data in zonal flow unit indicator method flow unit was recognized. Then, reservoir electrofacies determined by clustering methods of SOM, MRGC and DYNAMIC. By comparing and correlating of different methods with flow units of clustering SOM method, as a self-organization competition non witness neural net, was selected. In the present study, the primary electrofacies model of 6 drilled wells of the Bangestan reservoir were divided into 9 set (facies) using petrophysical logs. The presence of similarity between basic reservoir parameters caused to reduce electrofacies to 4 facies. Capillary pressure data were used to evaluate determined electrofacies, in view of pore throats characteristics in each electrofacies. To correlate carbonate rock fabrics with pore distribution and petrophysical properties of electrofacies, petrographic studies were done as well. Due to the presence of a good correlation of electrofacies and capillary pressure, Lucia plot and petrographic data, the resulted model was extended to the whole field and then using Neural net method and core data, porosity and permeability volumes were estimated in other locations which are unavailable core data. Reservoir characteristics of each rock type indicated that those parameters (Reservoir quality) improved from 1 to 4. Fabric and porosity varied from packstone with cemented intergranular porosity to wackstone-packstone with intergranular porosity and micropores, and verifies as well by petrographic studies.