Porosity is important because it reflects the presence of oil reserves. Hence, the number of underground reserves and a direct influence on the essential petrophysical parameters, such as permeability and saturation, are related to connected pores. Also, the selection of perforation interval and recommended drilling additional infill wells. For the estimation two distinct methods are used to obtain the results: the first method is based on conventional equations that utilize porosity logs. In contrast, the second approach relies on statistical methods based on making matrices dependent on rock and fluid composition and solving the equations (matrices) instantaneously. In which records have entered as equations, and the matrix is solved in one step, the porosity, saturation, and volume of minerals embedded inside the rock formations were obtained. The results indicated that the porosity was determined using statistical and conventional approaches matched to the core porosity. In the end, statistical techniques afford a different path for calculation and provide outcomes that can be used in all situations, particularly when the rock has many types of components. Furthermore, it is not based on conventional equations and overcomes the problems coming from the unreliability of porosity logs in formations containing mixed minerals.
The reservoir characterization and rock typing is a significant tool in performance and prediction of the reservoirs and understanding reservoir architecture, the present work is reservoir characterization and quality Analysis of Carbonate Rock-Types, Yamama carbonate reservoir within southern Iraq has been chosen. Yamama Formation has been affected by different digenesis processes, which impacted on the reservoir quality, where high positively affected were: dissolution and fractures have been improving porosity and permeability, and destructive affected were cementation and compaction, destroyed the porosity and permeability. Depositional reservoir rock types characterization has been identified de
The current work is focused on the rock typing and flow unit classification for reservoir characterization in carbonate reservoir, a Yamama Reservoir in south of Iraq (Ratawi Field) has been selected, and the study is depending on the logs and cores data from five wells which penetrate Yamama formation. Yamama Reservoir was divided into twenty flow units and rock types, depending on the Microfacies and Electrofacies Character, the well logs pattern, Porosity–Water saturation relationship, flow zone indicator (FZI) method, capillary pressure analysis, and Porosity–Permeability relationship (R35) and cluster analysis method. Four rock types and groups have been identified in the Yamama formation de
The carbonate ramp facies of the Late Albian-Early Cenomanian Mauddud Formation were studied in the Ratawi Oilfield, Basra Governorate, south of Iraq using integrated borehole data set that included, core and cutting samples in three drilled wells to analyze the petrography of the Mauddud Formation, two hundred and eighty-one (281) thin sections were prepared and examined for the three selected wells. The results show that the formation is composed of light grey dolomitized limestone and pseudo-oolitic creamy limestone with green to bluish shale. The petrographic observations results show four facies’ associations in the Mauddud Formation. These include: Mid–Ramp environment which is represented by Argillaceous mudstone mi
... Show MorePermeability is an essential parameter in reservoir characterization because it is determined hydrocarbon flow patterns and volume, for this reason, the need for accurate and inexpensive methods for predicting permeability is important. Predictive models of permeability become more attractive as a result.
A Mishrif reservoir in Iraq's southeast has been chosen, and the study is based on data from four wells that penetrate the Mishrif formation. This study discusses some methods for predicting permeability. The conventional method of developing a link between permeability and porosity is one of the strategies. The second technique uses flow units and a flow zone indicator (FZI) to predict the permeability of a rock mass u
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The heterogeneity nature of carbonate reservoirs shows sever scattering of the data, therefore, one has to be cautious in using the permeability- porosity correlation for calculating permeability unless a good correlation coefficient is available. In addition, a permeability- porosity correlation technique is not enough by itself since simulation studies also require more accurate tools for reservoir description and diagnosis of flow and non-flow units.
Evaluation of reservoir characterization was conducted by this paper for Mishrif Formation in south Iraqi oil field (heterogeneous carbonate reservoir), namely the permeability-porosity correlation, the hydraulic units (HU’s) an
... Show MoreThe heterogeneity nature of carbonate reservoirs shows sever scattering of the data, therefore, one has to be cautious in using the permeability- porosity correlation for calculating permeability unless a good correlation coefficient is available. In addition, a permeability- porosity correlation technique is not enough by itself since simulation studies also require more accurate tools for reservoir description and diagnosis of flow and non-flow units. Evaluation of reservoir characterization was conducted by this paper for Mishrif Formation in south Iraqi oil field (heterogeneous carbonate reservoir), namely the permeability-porosity correlation, the hydraulic units (HU’s) and global hydraulic elements (GHE
... Show MoreOil recovery could be impacted by the relation between vertical permeability (Kv) and horizontal permeability (Kh) (Kv/Kh). 4816 plugs that have been getting hold of 18 wells of Mishrif formation in the West Qurna oilfield were used. Kv/Kh data provided some scatter, but the mean is ~1. Kv/Kh =1 was used for the Petrel model before upscaling according to the heterogeneity of each layer.
Kv/Kh values for Mishrif Formation in West Qurna Oilfield are 0.8 for relatively homogeneous, 0.4 for heterogeneous rock, and 0.1 for cap rocks (CRII).
Eclipse TM was used for reservoir simulation. PVT and SCAL data e
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