Petroleum Engineering
Hessam MansouriSiahgoli; Mohammad Ali Riahi; Bahare Heidari; Reza Mohebian
Abstract
It is difficult to identify the carbonate reservoirs by using conventional seismic reflection data, especially in cases where the reflection coefficient of the gas-bearing zone is close to that of the carbonate background. In such cases, the extended elastic impedance (EEI) as a seismic reconnaissance ...
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It is difficult to identify the carbonate reservoirs by using conventional seismic reflection data, especially in cases where the reflection coefficient of the gas-bearing zone is close to that of the carbonate background. In such cases, the extended elastic impedance (EEI) as a seismic reconnaissance attribute with the ability to predict fluids and lithology can be used. It allows for a better distinction between seismic anomaly caused by lithology and the one caused by the fluid content. The EEI attribute extends the available reflection angles and applies different weights to the intercept and gradient values so as to extract the petrophysical properties of the rock at a specific incident angle. Using the EEI attribute, we can estimate the elastic parameters such as shear impedance; the ratio of the compressional velocity to shear velocity; Poisson’s ratio; and bulk, Lame, and shear moduli, and petrophysical properties, including porosity, clay content, and water saturation. The known reservoirs in the study area are three oil-bearing formations namely, Surmeh (Arab), Gadvan (Buwaib), and Dariyan (Shuaiba), and three gas-bearing formations, including Kangan, Dalan, and Faraghan. The Dehram group is composed of Kangan (Triassic), Dalan, and Faraghan (Permian) formations. Permian carbonates of Kangan–Dalan and its equivalent Khuff have regionally been developed as a thick carbonate sequence in the southern Persian Gulf region. In this paper, parameters 𝜆𝑝 and 𝜇𝜌 extracted from the EEI method are used to characterize a carbonate reservoir. Our results show that the EEI can highlight the difference between the reservoir and non-reservoir formation to identify the gas-bearing areas.
Petroleum Engineering – Reservoir
Ali Kadkhodaie-Ilkhchi; Rahim Kadkhodaie-Ilkhchi
Abstract
Carbonate reservoirs rock typing plays a pivotal role in the construction of reservoir static models and volumetric calculations. The procedure for rock type determination starts with the determination of depositional and diagenetic rock types through petrographic studies of the thin sections prepared ...
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Carbonate reservoirs rock typing plays a pivotal role in the construction of reservoir static models and volumetric calculations. The procedure for rock type determination starts with the determination of depositional and diagenetic rock types through petrographic studies of the thin sections prepared from core plugs and cuttings. In the second step of rock typing study, electrofacies are determined based on the classification of well log responses using an appropriate clustering algorithm. The well logs used for electrofacies determination include porosity logs (NPHI, DT, and RHOB), lithodensity log (PEF), and gamma ray log. The third step deals with flow unit determination and pore size distribution analysis. To this end, flow zone indicator (FZI) is calculated from available core analysis data. Through the application of appropriate cutoffs to FZI values, reservoir rock types are classified for the studying interval. In the last step, representative capillary pressure and relative permeability curves are assigned to the reservoir rock types (RRT) based upon a detailed analysis of available laboratory data. Through the analysis of drill stem test (DST) and GDT (gas down to) and ODT (oil down to) data, necessary adjustments are made on the generated PC curves so that they are representative of reservoir conditions. Via the estimation of permeability by using a suitable method, RRT log is generated throughout the logged interval. Finally, by making a link between RRT’s and an appropriate set of seismic attributes, a cube of reservoir rock types is generated in time or depth domain. The current paper reviews different reservoir rock typing approaches from geology to seismic and dynamic and proposes an integrated rock typing workflow for worldwide carbonate reservoirs.
Petroleum Engineering
Abolfazl Hashemi; Seyed Reza Shadizadeh
Abstract
Hydrochloric acidizing is a routine operation in oil fields to reduce the mechanical skin. In this paper, practical acidizing in a typical carbonate oil reservoir located in the southwest of Iran is practiced, which shows an unexpected improvement after acidizing. To understand the acidizing effect on ...
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Hydrochloric acidizing is a routine operation in oil fields to reduce the mechanical skin. In this paper, practical acidizing in a typical carbonate oil reservoir located in the southwest of Iran is practiced, which shows an unexpected improvement after acidizing. To understand the acidizing effect on reservoir rock, the formation rock is analyzed on different scales. An acidizing laboratory test is also carried out on formation core samples to understand the acidizing performance. The results show that the main feature of this reservoir is its dominated secondary porosity and its special pattern of distribution. Practically, this porosity percolation has caused high mechanical skin during drilling and a large productivity improvement after acidizing. The acidizing increased the ultimate recovery of the reservoir with existing wells and prolonged the production plateau.
Morteza Azadpour; Navid Shad Manaman
Abstract
Pore pressureis defined as the pressure of the fluid inside the pore space of the formation, which is also known as the formation pressure. When the pore pressure is higher than hydrostatic pressure, it is referred to as overpressure. Knowledge of this pressure is essential for cost-effective drilling, ...
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Pore pressureis defined as the pressure of the fluid inside the pore space of the formation, which is also known as the formation pressure. When the pore pressure is higher than hydrostatic pressure, it is referred to as overpressure. Knowledge of this pressure is essential for cost-effective drilling, safe well planning, and efficient reservoir modeling. The main objective of this study is to estimate the formation pore pressure as a reliable mud weight pressure using well log data at one of oil fields in the south of Iran. To obtain this goal, the formation pore pressure is estimated from well logging data by applying Eaton’s prediction method with some modifications. In this way, sonic transient time trend line is separated by lithology changes and recalibrated by Weakley’s approach. The created sonic transient time is used to create an overlay pore pressure based on Eaton’s method and is led to pore pressure determination. The results are compared with the pore pressure estimated from commonly used methods such as Eaton’s and Bowers’s methods. The determined pore pressure from Weakley’s approach shows some improvements in comparison with Eaton’s method. However, the results of Bowers’s method, in comparison with the other two methods, show relatively better agreement with the mud weight pressure values.
