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The study of petrophysical parameters plays a major role in the evaluation of hydrocarbon reservoirs. In this study, using well data in Geolog software, the petrophysical parameters of the Arab Formation (equivalent to Surmeh) in one of the oil fields in southern Iran were studied in two ways. Based on the petrophysical evaluation and using conventional cross-plots (neutron-density) and histogram of porosity and water saturation, the lithology of the Arab Formation was determined. The lithology consists of a combination of calcite, dolomite, and anhydrite. Comparison of the results of porosity changes is more consistent with the values obtained from core analysis. According to the calculated petrophysical properties, the upper part of the Arab (Surmeh) Formation was divided into seven parts. Comparison of water saturation showed that in all zones, the range of changes is high. By comparing the zones quality, zones 5 and 6 are introduced as the best reservoir zones. [ABSTRACT FROM AUTHOR]

The characterization of carbonate rocks is not straightforward, as they often experience complex diagenetic processes causing them to expose wide variations in pore types. This research aims to characterize the properties of a carbonate reservoir with a complicated porous structure through rock physics principles and tools. Two representative wells from an oil field located in SW of Iran were selected, and two-dimensional (2D) and three-dimensional (3D) rock physics templates (RPTs) were constructed by employing the appropriate rock physics models. The porosity, water saturation, and pore type are considered reservoir parameters affecting carbonate rock's elastic properties and indicating the reservoir quality. The 2D RPTs described variations in two reservoir parameters in terms of elastic properties. However, they were not able to simultaneously characterize all three reservoir parameters. The proposed 3D RPTs revealed the underlying relationship of elastic properties with pore aspect ratio, water saturation, and porosity. To validate the constructed RPTs, well logging data, scanning electron microscope images, and thin section images were utilized. The RPTs were also employed to predict the reservoir properties quantitatively, and these predictions were compared with the petrophysical data. The average errors of the predicted porosity and water saturation by 3D RPT were, respectively, 1.22% and 6.66% for well A, and 2.65% and 8.18% for well B. The 2D RPTs provided three sets of predictions for porosity and water saturation (considering three specific pore aspect ratios of 0.03, 0.1, and 0.5), all with higher average errors compared to the predictions by 3D RPT for both wells. The obtained results proved that 3D RPT could predict reservoir properties more accurately. Finally, based on the estimated values of pore aspect ratio, water saturation, and porosity using 3D RPTs, the reservoir under study was divided into distinct depth intervals, and a quality level was assigned to each interval. The introduced rock physics-based procedure for a carbonate reservoir characterization could increase the reliability in predicting the reservoir properties, enhance the ability to detect the reservoir fluid, and thereby reduce the interpretation risk. [ABSTRACT FROM AUTHOR]

This study presents indirect methods of source rocks characterization by integrating geochemical data with well logs and seismic inversion results. Well logs and seismic data are commonly more available than scarce geochemical data in oil and gas fields. Combining high vertical resolution well logs with high lateral resolution seismic data generates some enhanced geochemical data on inter-well spaces where no well is drilled. Acoustic impedance was obtained and utilized for the TOC prediction and source rock detection because of its good correlation with geological parameters such as the lithology and fluid contents. A cross-plot of log-derived water saturation versus acoustic impedance successfully differentiates source from non-source rocks based on geological variations of lithology, porosity, formations density, and the TOC content. The impact of the TOC content on acoustic properties was elaborated in the next step. Acoustic impedance is obtained as the most important seismic attribute for the TOC prediction. Well logs and seismic data are integrated to predict the TOC logs from seismic data. First, seismic data were inverted to obtain the acoustic impedance. Then, the produced acoustic impedance was used as a seismic attribute for the TOC prediction. The outcome is used to illustrate and follow the TOC variation to distinguish source rocks in the oil and gas fields. The study is carried out in the Cretaceous succession in three hydrocarbon fields in the central part of the Persian Gulf to observe the TOC variations in the Albian-aged Kazhdumi Formation. • Fusion of geochemical, petrophysical and seismic data for source rock characterization • A rock physics template based on acoustic impedance versus water saturation cross-plot for source rock detection • Inversion of post-stack seismic data to acoustic impedance and total organic carbon • Taking the advantage of high vertical resolution of well logs and high horizontal resolution of seismic data for source rock mapping • A fast, cost-effective and robust method for source rock mapping [ABSTRACT FROM AUTHOR]

Carbonate rocks, along with sandstone, constitute the main reservoirs of oil and gas in the world. Examination of petrophysical properties includes parameters such as porosity, permeability and fluid saturation, lithological variations according to depth and hydrocarbon properties including effective and ineffective thickness and effective hydrocarbons column. Asmari reservoir of Bibi- Hakimeh oilfield is one of the tertiary carbonate reservoirs in Iran located 210 km southeast of Ahwaz. The reservoir is divided into 8 zones, each zone having its own petrological characteristics and lithology. Considering the fact that all three major lithologies of reservoirs (limestone, dolomite and Shale) exist in the Asmari reservoir of Bibi- Hakimeh oilfield, lithological study and its impact on petrophysical parameters of reservoirs are very important. Based on the assessments, zone 1 with more than 85% limestone has the most effective hydrocarbon column, the highest net thickness and the highest net to total thickness ratio, and due to its low water saturation (about 20% for effective zones), it has the best reservoir quality among the other zones. Following zone 1, zones 2 and 3 take the second and the third places, respectively. Zones 4 to 8 are below the water-oil interface, hence they are not included in productive zones and have lower reservoir quality. Zone 1 is considered as the best oil producing layer with respect to petrophysical parameters. [ABSTRACT FROM AUTHOR]

Porosity, shale volume, and fluid saturation are the most important parameters used to determine the characteristics of oil reservoirs. The kupal oil field has located in Dezful embayment. Illam formation introduced as a fractured reservoir at the southwest of Iran. In this study, wells No.48 and 54 investigated. Based on this study and using well logging diagrams, the main lithology determined Limestone. It is worth mentioning that substrates of shale, dolomite and in some cases anhydrite can see. As well as based on the performed study, this formation divided into three zones, including two permeable zones and one non-permeable zone. In the non-permeable section, main minerals have determined as clay, being types of Montmorillonite, Mix layers, and Illite. Base on Gr log, the average volume of shale in wells No. 48 and 54 was 8% to 17% respectively, that overall shows Low percent volume of shale. In this field, the amount of porosity increased from SE to NW. Accordingly, the well log plot, there are appropriate porosity and water saturation in this horizon. To enhance the accuracy of formation of water saturation calculations, we calculate it by software using Indonesian and Simandoux methods. Such that the average effective porosity and water saturation are 7.9 and 43.4 %, respectively. Finally, it can be stated this formation has poor to mean reservoir characteristic, but it can achieve reservoir capacity from some wells and adjacent fields. [ABSTRACT FROM AUTHOR]

Determining petrophysical parameters and reservoir evaluation has special importance in the oil industry. The precise knowledge of these parameters allows the petroleum engineers to have the tools they need in a given field to study precisely the production stages and, with their knowledge, will be more capable of developing oilfields. In this study, two wells in Asmari reservoir in Mansour Abad oil field has been investigated, and reservoir properties such as porosity, shale volume, and water saturation have been calculated, and the volume of water and oi l have been determined. All calculations, cross-plots, and logs diagrams are done via software Geolog version 6.7.1. Studies show that the Asmari Formation in this field has a low average shale volume. On the other hand, Asmari reservoir has good porosity, especially in the upper part (Zone 3), and porosity variations of the field are not high. Also, the use of the M-N plot indicates the prevalence of carbonate lithology. In addition, based on Thorium-Potassium cross-plots, the dominant clay minerals were identified as Illite and mixed layer. [ABSTRACT FROM AUTHOR]

Determining the potential of reservoirs and production zones is very important to reach maximum product performance and decrease hydrocarbon recovery costs. The calculation of the Water Saturation (S W) significantly affects oil-in-place estimations. The Saturation-Height Function (SHF) is operated to predict the saturation in the reservoir for a given height above the free water level. Typical approaches for predicting water saturation as a function of rock properties and height above contact include two types, those based on capillary pressure curve averaging and log-based techniques. The goal of this study is to define an appropriate SHF and S W using the usual functions to delineate production zones using rock typing with an example from the Dorood oilfield in the Persian Gulf. In this study first, the reservoir has been divided into different rock types and water saturation is estimated by different methods in each rock type. The Reservoir Quality Index (RQI) along with Water Saturation profile for representative rock types were used for determining reservoir zones. Accordingly, a formulation was developed to model the behavior of Capillary Pressure (P C) as a characteristic of S W and to determine the Free Water Level (FWL) based on laboratory data. To achieve this goal, the appropriate saturation-height functions and their coefficients were chosen for representative reservoir rock types. The Pc curves are classified based on Discrete Rock Types (DRT) and a proper saturation-height function was assigned for individual rock types. Finally, some of the most common equations for calculating SHF were fitted to the representative Pc curve of each rock type and coefficients of the equation for any rock type were determined by using the MATLAB software in the studied carbonate reservoir. After investigating the results of fitting different SHF, water saturation was calculated using a modified lambda function and compared with the log-derived water saturation. The SHF applied, could be used to estimate saturations of unreachable zones of the field. • Classification of geological facies based on static characteristics and hydraulic flow units approach. • Including SMLP, DRT and K-means were implemented to categorize reservoir rocks based on FZI. • Results of the DRT method were used to determine saturation-height function for each individual rock type. • The generated SHF based on individual rock types generates S W in transition zone of uncored wells. • The SHF based calculated water saturation is comparable with well log-derived Sw. [ABSTRACT FROM AUTHOR]

An important application of the concept of capillary pressures pertains to the fluid distribution in a reservoir prior to its exploitation. The capillary pressure-saturation data can be converted into height-saturation data by using the capillary pressure equation and solving for the height (h) above the free water level. Estimation of the water saturation greatly impacts oil-in-place calculations. Saturation-height function is used to predict the saturation in the reservoir for a given height above the free water level. The authors investigate performance of eight saturation-height methods (i.e., Leverett, Cap-Log, Modified Cap-Log, Johnson, Cuddy, Modified Cuddy, Skelt-Harrison, and Sodena methods) employed in the oil industry. They collected measured capillary pressure data and core properties from a well in one of the Southern Iranian reservoirs. The authors review advantages and disadvantages of each method while comparing the output of each method with saturation obtained from the log data. The results indicate that the Skelt-Harrison and Leverett methods, with coefficients independent of core properties, would be the best and worst option, respectively. [ABSTRACT FROM PUBLISHER]

In this article, two approaches are presented to calculate three crucial petrophysical parameters (water saturation [Sw], cementation factor [m], and saturation exponent [n]). In the first approach, an artificial neural network (ANN) was implemented to calculate water saturation in Sarvak limestone formation in an Iranian oilfield (Azadegan). Core data from three wells (AZN01, AZN03, and AZN04) have been used to train and test the artificial neural network. Conventional wireline logs such as formation resistivity log, density log, sonic log, gamma ray, and porosity recorded from cores to be used as input to the ANN and water saturation measured in laboratory as target. Among four generated networks, network 3 showed the best correlation coefficient of 0.969 between ANN-predicted Sw and target Sw. Using this network, water saturation of the Sarvak formation in well AZN01 was predicted that showed good conformity with results of a dual water saturation model considering m = 2.0 and n = 2.0 in the upper parts of the formation, whereas in the lower parts of the formation the dual water saturation model calculated higher values, proving the variations of both m and n parameters along the formation. In the second approach, using Archie's equation's components (ANN-predicted water saturation, resistivity log, porosity log, and aRw), a system of two equations and two unknowns was developed to calculate the cementation factor (m) and saturation exponent (n) simultaneously for every two consecutive wireline tools measurements all over the formation. Then the variations of m and n, for the entire depth of the reservoir pay zone, versus depth were plotted. These plots prove that m and n should not be considered constant in petrophysical interpretations that conventionally assume constant in the water saturation models. [ABSTRACT FROM PUBLISHER]

Water saturation is defined as that fraction, or percentage, of the pore volume occupied by water. Estimation of the water saturation greatly impacts oil-in-place calculations. A saturation height function is used to predict the saturation in the reservoir for a given height above the free water level. Traditionally, methods for predicting water saturation as a function of rock properties and height above contact have fallen into two groups, those based on capillary pressure curve averaging and log-based methods. In this study, eight saturation height methods (i.e., Leverret [1941], cap-log, Cuddy et al. [1993], Johnson [1987], modified cap-log [2007], modified Cuddy [2007], Skelt-Harrison [1995], and Sodena methods) employed in the oil industry are investigated. In this article, a new artificial neural network (ANN) is developed to predict the water saturation. Two hundred sixty-three data sets were collected from a southern Iranian reservoir. Porosity (Φ), permeability (k), and height above the free water level (h) were used as the input data and water saturation was the target data. Seventy percent of these data points were used for training and the remainder for predicting the Sw (validation and test). An ANN was developed and a correlation coefficient (R2) of 0.985 and absolute average relative error (%) of 6.40% were obtained by comparing water saturation obtained from the ANN model and logging. [ABSTRACT FROM AUTHOR]

In this research, an integrated geological and petrophysical approach was applied to understanding the most critical factors affecting the water saturation exponent in the Permian–Triassic Kangan and Dalan carbonate formations in the central Persian Gulf in Iran. Economically, water saturation has a fundamental role in reservoir characterisation. A total of 8 sedimentary facies were recognised with multiple diagenetic phases. Diagenetic processes include marine cementation, moldic dissolution, early dolomitisation, recrystallisation, anhydrite cementation, compaction, and fracturing, which have influenced reservoir properties. Four third-order sequences were distinguished in the study area accompanied by nine fourth-order sequences. Petrographic analysis, scanning electron microscopy, petrophysical core analysis, wireline log data as well as mercury injection tests integrated through flow zone indicator, Lucia classes, and Lorenz plot approaches. Consequently, 4 integrated rock types (IRTs) were identified with particular depositional and diagenetic features. IRT1 with dominant interparticle pore type and strong porosity–permeability correlation (average 9.1% porosity and 27 mD permeability, R2 = 0.98), has a high saturation exponent (n = 2.2). IRT4 with grain-to mud-dominated facies, low porosities (average 1.4%), and a mean value of 4.54 mD permeability has the lowest saturation exponent (n = 1.07). Moldic dissolution with low pore connectivity is the dominant pore type in IRT2 and IRT3 which have a medium and relatively high saturation exponent, respectively (IRT2 n = 1.53 and IRT3 n = 1.78). Accordingly, a conceptual model was suggested for saturation exponent variations in a high-frequency sequence stratigraphic framework. In order to evaluate the heterogeneity of the studied formations and its impact on the reservoir properties, the characteristics of the determined rock units were studied. This study integrates microscopic to macroscopic geological and petrophysical factors to understand the saturation exponent distribution in a heterogeneous carbonate reservoir, leading to obtaining a more accurate water saturation estimation of such reservoirs. [Display omitted] • A total of 8 depositional facies were deposited in a ramp environment. • Moldic dissolution and early dolomitisation changed the reservoir properties. • By integration of FZI values and Lucia plot, four IRTs were identified. • Hydraulic flow units and Lorenz plots were correlated with depositional sequences. • A conceptual model has proposed to predict distribution of saturation exponent. [ABSTRACT FROM AUTHOR]