A modified water injection technique has organized by this study to improve oil recovery of the Mishrif reservoirs using polymerized alkaline surfactant water (PAS-Water) injection. It is planned to modify the existing water injection technology, first to control and balance the hazardous troublemaker reservoir facies of fifty-micron pore sizes with over 500 millidarcies permeability, along with the non-troublemaker types of less than twenty micron pore sizes with 45 to 100 millidarcies permeability. Second to control Mishrif reservoirs rock-wettability. Special core analysis under reservoir conditions of 2250 psi and 90 °C has carried out on tens of standard core plugs with heterogeneous buildup, using the proposed renewal water flooding mechanism. The technique assures early PAS-water injection to delay the water-breakthrough from 0.045 – 0.151 pore volumes water injected with 8 – 25% oil recovery, into 0.15 – 0.268 pore volumes water injected with 18 to 32% improved oil recovery. As well as, crude oil-in-water divertor injection after breakthrough, within 0.3 to oil0.65 – 0.85-pore volume of water injected to decrease water cut 1 four 0 to 15%. The overall progress of the PAS-water injection has achieved residual oil mobility of 65%, and upgraded the 35 – 50% oil recovery range by less than three pore volume water injected with 20 – 60% water cut, compared with the same oil recovery range by more than ten pore volume water injected with around 70% water cut. The ultimate oil recovery improved by this technique is from 70% via more than 20 pore volume water injected with over 95% water cut by usual water injection, to 85 – 90% via 6.4 pore volume water injected with over 90% water cut by the modified water injection. The technique succeeded to lower the end-point mobility ratio to 1.5 from above five by usual water injection. It is highly recommended to use ten micron mesh filter at the main injection site and four or five micron mesh filter at the injector sites; to avoid more than 80% of the suspended particles and save as much as possible the overall reservoir facies from permeability damage.
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 sol
... Show MoreThe reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese
... Show MoreDrag reduction (DR) techniques are used to improve the flow by spare the flow energy. The applications of DR are conduits in oil pipelines, oil well operations and flood water disposal, many techniques for drag reduction are used. One of these techniques is microbubbles. In this work, reduce of drag percent occurs by using a small bubbles of air pumped in the fluid transported. Gasoil is used as liquid transporting in the pipelines and air pumped as microbubbles. This study shows that the maximum value of drag reduction is 25.11%.
Constructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distribution along
... Show MoreConstructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distri
... Show MoreThe 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
Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
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