Intelligent 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 improve the robustness of forecasting production from smart wells using reservoir simulation. High-level details in the rock and fluid flow properties are required in the horizontal well region to capture the flow dynamics accurately. Thus, the study offers an enhanced method for predicting the performance of intelligent or smart wells in reservoir modeling. This model was history matched for a period of 20 years for three horizontal wells by using program Petrel (2017.4) and ECLIPS (2011). After successful validation of model on a field scale and well level, performance prediction was carried out to see the effect of (number of valves, number of nozzle and compartment length) using PICD/AFCV completion. Optimizing well performance entails lowering water-cut. From an economic viewpoint, the goal is to maximize NPV or profit, depending on the situation, from PICD wells, which compared to other wells.
A 3D Geological model was generated using an advanced geostatistical method for the Cretaceous reservoir in the Bai Hassan oil field. In this study, a 3D geological model was built based on data from four wells for the petrophysical property distribution of permeability, porosity, water saturation, and NTG by using Petrel 2021 software. The geological model was divided into a structural model and a property model. The geological structures of the cretaceous reservoir in the Bai Hassan oil field represent elongated anticline folds with two faults, which had been clarified in the 3D Structural model. Thirteen formations represent the Cretaceous reservoir which includes (Shiranish, Mashurah, U.kometan, Kometan Shale, L. Kometan, Gulnen
... Show MoreA geological model was built for the Sadi reservoir, located at the Halfaya oil field. It is regarded as one of the most significant oilfields in Iraq. The study includes several steps, the most essential of which was importing well logs from six oil wells to the Interactive Petrophysics software for conducting interpretation and analysis to calculate the petrophysical properties such as permeability, porosity, shale volume, water saturation, and NTG and then importing maps and the well tops to the Petrel software to build the 3D-Geological model and to calculate the value of the original oil in place. Three geological surfaces were produced for all Sadi units based on well-top data and the top Sadi structural map. The reservoir has
... Show MoreHorizontal wells are of great interest to the petroleum industry today because they provide an attractive means for improving both production rate and recovery efficiency. The great improvements in drilling technology make it possible to drill horizontal wells with complex trajectories and extended for significant depths.
The aim of this paper is to present the design aspects of horizontal well. Well design aspects include selection of bit and casing sizes, detection of setting depths and drilling fluid density, casing, hydraulics, well profile, and construction of drillstring simulator. An Iraqi oil field (Ajeel field) is selected for designing horizontal well to increase the productivity. Short radius horizontal well is suggested fo
The productivity of oil wells may be improved by determining the value of enhancing well productivity and the likely reasons or sources of formation damage after the well has been recognized as underperforming. Oil well productivity may be improved, but the economics of this gradual improvement may be compromised. It is important to analyze the influence of the skin effect on the recovery of the reserve. The acid treatment evaluated for the well AD-12, primarily for the zone Mi4; using a license of Stimpro Stimulation Software to validate the experimental work to the field scale, this software is considered the most comprehensive instrument for planning and monitoring matrix acid treatments and utilizing actual data to provide a far
... Show MoreThe productivity of oil wells may be improved by determining the value of enhancing well productivity and the likely reasons or sources of formation damage after the well has been recognized as underperforming. Oil well productivity may be improved, but the economics of this gradual improvement may be compromised. It is important to analyze the influence of the skin effect on the recovery of the reserve.
The acid treatment evaluated for the well AD-12, primarily for the zone Mi4; using a license of Stimpro Stimulation Software to validate the experimental work to the field scale, this software is considered the most comprehensive instrument for planning and monitoring matrix acid treatments and utilizing actual data to prov
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreRock type identification is very important task in Reservoir characterization in order to constrict robust reservoir models. There are several approaches have been introduced to define the rock type in reservoirs and each approach should relate the geological and petrophysical properties, such that each rock type is proportional to a unique hydraulic flow unit. A hydraulic flow unit is a reservoir zone that is laterally and vertically has similar flow and bedding characteristics. According to effect of rock type in reservoir performance, many empirical and statistical approaches introduced. In this paper Cluster Analysis technique is used to identify the rock groups in tertiary reservoir for Khabaz oil field by analyses variation o
... Show MorePorosity and permeability are the most difficult properties to determine in subsurface reservoir characterization. The difficulty of estimating them arising from the fact that porosity and permeability may vary significantly over the reservoir volume, and can only be sampled at well location. Secondly, the porosity values are commonly evaluated from the well log data, which are usually available from most wells in the reservoir, but permeability values, which are generally determined from core analysis, are not usually available. The aim of this study is: First, to develop correlations between the core and the well log data which can be used to estimate permeability in uncored wells, these correlations enable to estimate reservoir permeabil
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