The Yamama Formation is a significant reservoir in the southern part of Iraq. This formation consists of limestone deposited throughout the Lower Cretaceous period within main retrogressive depositional series. This study aims to identify the impact of the diagenesis processes on the reservoir’s characteristics (porosity and permeability). Diagenesis processes’ analysis and the identification of Yamama Formation depended on the examination of more than 250 thin sections of the core samples from two wells that were used to determine different diagenetic environments and processes. The three identified diagenetic environments that affected Yamama reservoir were the marine, meteoric and burial environments. Eight diagenetic processes were recognized in Yamama Formation and showed positive and destructive effects on the reservoir quality; Dissolution and fracture had highly positive effects through creating and improving porosity and permeability that led to improving reservoir quality. Cementation and compaction had destructive effects, through reducing porosity and permeability, that led to reducing reservoir quality. Other processes such micritization, dolomitization, bioturbation and neomorphism did not have strong effects on reservoir quality. Based on genetic classification of porosity, most of porosity within Yamama Formation in this field was formed by diagenesis processes, implying that Yamama reservoir is a type of diagenetic reservoir.
The reservoir characterization of Lower Qamchuqa (Shu'aiba) Formation (Aptian) is studied at the well BH-86 of Bai- Hassan Oilfield in Kirkuk area, Northern Iraq. The lithological study (of 91 thin sections) revealed that the formation consists of shaly limestone, a thin bed of marl within the limestone, and dolomitic limestone. Four petrographic microfacies were noticed Lime mudstone microfacies, Dolomudstone microfacies, Lime wackestone microfacies, subdivided into benthonic foraminifera lime wackestone submicrofacies and bioclasts lime wackestone submicrofacies, and the last microfacies is the Lime packstone microfacies, which is subdivided into pelloidal lime packstone submicrofacies and Orbitolina lime packstone microfaci
... Show MoreIncreasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off perm
... Show MoreIncreasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off permeab
... Show MoreIncreasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off
... Show MoreThe Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there
... Show MoreThe main goal of this study is to evaluate Mishrif Reservoir in Abu Amood oil field, southern Iraq, using the available well logs. The sets of logs were acquired for wells AAm-1, AAm-2, AAm-3, AAm-4, and AAm-5. The evaluation included the identification of the reservoir units and the calculation of their petrophysical properties using the Techlog software. Total porosity was calculated using the neutron-density method and the values were corrected from the volume of shale in order to calculate the effective porosity. Computer processed interpretation (CPI) was accomplished for the five wells. The results show that Mishrif Formation in Abu Amood field consists of three reservoir units with various percentages of h
... Show MoreIntelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we
... Show MoreThe petrophysical characteristics of five wells drilled into the Sa'di Formation in the Halfaya oil field were evaluated using IP software to determine a reservoir and explore hydrocarbon reserve zones. The lithology was evaluated using the M-N cross-plot method. The diagram showed that the Sa'di Formation was mainly composed of calcite (represented by the limestone region) is the main mineral in the Sa′di Reservoir. Using a density-neutron cross plot to identify the lithology showed that the formation mainly consists of limestone with minor shale. Gamma-ray logs were employed to calculate the shale quantity in each well. The porosity at weak hole intervals was calculated using a sonic log and neutron-density log at the reservoir
... Show MoreThis study aims to set up a 3D static model to characterize and evaluate Mishrif Formation which represents the main reservoir in Buzurgan Oilfield, southern Iraq. Six wells have been selected to set up structural, facies and petrophysical models of Mishrif reservoir by using Petrel Software. The structural model has been built based on the structural contour map of the top of Mishrif Formation, which derived from seismic interpretation, and by using different static algorithms in Petrel Software. The structural model showed that the Buzurgan Oilfield represents an anticlinal fold with two domes north and south separated by a depression. The petrophysical model included the porosity model and water saturation model. Th
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