Nanofluids, liquid suspensions of nanoparticles (Np), are an effective agent to alter the wettability of oil-wet reservoirs to water-wet thus promoting hydrocarbon recovery. It can also have an application to more efficient carbon storage. We present a series of contact angle (θ) investigations on initially oil-wet calcite surfaces to quantify the performance of hydrophilic silica nanoparticles for wettability alteration. These tests are conducted at typical in-situ high pressure (CO2), temperature and salinity conditions. A high pressure–temperature (P/T) optical cell with a regulated tilted surface was used to measure the advancing and receding contact angles at the desired conditions. The results showed that silica nanofluids can alter the wettability of oil-wet calcite to strongly water-wet at all operational conditions. Although limited desorption of silica nanoparticles occurred after exposure to high pressure (20 MPa), nanoparticle adsorption on the oil-wet calcite surface was mainly irreversible. The nanofluid concentration and immersion time played crucial roles in improving the efficiency of diluted nanofluids while salinity was less significant at high pressure and temperature. The findings provide new insights into the potential for nanofluids being applied for improved enhanced oil recovery and carbon sequestration and storage.
The 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 MoreThis paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
... Show MoreThe performance of asphalt pavements is crucial due to heavy traffic loads from civil and industrial developments. Various additives and modifiers are used in flexible roads to improve their resistance to deterioration caused by climatic changes. From this context, modifying the asphalt binder with polymers is popular in asphalt pavement construction. The present research investigates the effect of Polyethylene (PE) polymers in powder form on the characteristics of asphalt mixtures since these polymers are composed of hydrocarbons. It is similar to asphalt binders, making them very effective in enhancing the performance of neat asphalt produced from the oil refinery. To confirm this, two types of PE, High-Density PE (HDPE) and Low-Density P
... 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
... Show MoreTo verify the influence of magnetic flux on the characteristics of SAE 10W-30 gasoline engine oil when the engine oil is exposed to different magnetic fluxes 0, 6, 9, and 13 Volt. The following oil characteristics were measured: viscosity at 40 and 100 °C, and total acid number (TAN) mg KOH/g. The research was carried out in a completely randomized design with three replications for each treatment under the 5% probability level to compare the means of the treatments. The results of the experiment showed that there were significant differences in the studied properties when the engine oil was exposed to the above magnetic fluxes and, inversely, especially the magnetic flux of 13 Volt,
To verify the influence of magnetic flux on the characteristics of SAE 10W-30 gasoline engine oil when the engine oil is exposed to different magnetic fluxes 0, 6, 9, and 13 Volt. The following oil characteristics were measured: viscosity at 40 and 100 °C, and total acid number (TAN) mg KOH/g. The research was carried out in a completely randomized design with three replications for each treatment under the 5% probability level to compare the means of the treatments. The results of the experiment showed that there were significant differences in the studied properties when the engine oil was exposed to the above magnetic fluxes and, inversely, especially the magnetic flux of 13 Volt, which led to a decrease in the viscosity of the oils at
... Show MoreSamples of gasoline engine oil (SAE 5W20) that had been exposed to various oxidation times were inspected with a UV-Visible (UV-Vis) spectrophotometer to select the best wavelengths and wavelength ranges for distinguishing oxidation times. Engine oil samples were subjected to different thermal oxidation periods of 0, 24, 48, 72, 96, 120, and 144 hours, resulting in a range of total base number (TBN) levels. Each wavelength (190.5 – 849.5 nm) and selected wavelength ranges were evaluated to determine the wavelength or wavelength ranges that could best distinguish among all oxidation times. The best wavelengths and wavelength ranges were analyzed with linear regression to determine the best wavelength or range to predict oxidation t
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